*3.3. Survival and 18F-FDG-PET:*

The median OS and PFS were 716 and 161 days, respectively, and the 2-year OS rate was 44.8%. Among all patients, those with a low TLG exhibited significantly better OS than those with a high TLG. Similarly, the survival analysis of MTV on 18F-FDG uptake demonstrated a significantly worse OS and PFS for patients with a high MTV (Figure 2). No statistically significant difference in the OS and PFS was observed between patients with a low and high SUVmax (Figure 2). However, in 70 patients without an EGFR mutation, a statistically significant difference in OS and PFS was recognized between patients with low and high TLG or low and high MTV, but not between those with low and high SUVmax and low and high TB (Figure 3). Survival analysis results are listed in Table 2. Univariate analysis in all patients identified performance status (PS), TLG, and MTV as significant prognostic markers for OS; the significant predictors for PFS were PS and MTV. Subsequently, we performed a multivariate analysis according to TLG and MTV and confirmed that PS, TLG, and MTV were independent prognostic factors for poor OS and PFS; the significant prognostic marker for PFS was PS (Table 3). In patients without EGFR mutation, a multivariate analysis identified TLG and MTV as independent prognostic factors for predicting poor OS. Histological typing confirmed TLG and MTV as significant prognostic factors in patients with adenocarcinoma, but not in those with non-adenocarcinoma.

**Figure 2.** Discriminative value by log-rank test according to various TLG (**A**), MTV (**C**) and SUVmax (**E**) cutoff for OS and TLG (**B**), MTV (**D**) and SUVmax (**F**) cutoff for PFS in 18F-FDG-PET.

**Figure 3.** Kaplan–Meier curves according to various TLG (**A**), MTV (**B**), SUVmax (**C**) and TB (**D**) for OS and PFS. (**A**); OS (upper left) and PFS (lower left) in all patients and OS (upper right) and PFS (lower right) in those without EGFR mutation according to TLG. (**B**); OS (upper left) and PFS (lower left) in all patients and OS (upper right) and PFS (lower right) in those without EGFR mutation according to MTV. (**C**); OS (upper left) and PFS (lower left) in all patients and OS (upper right) and PFS (lower right) in those without EGFR mutation according to SUVmax. (**D**); OS (upper left) and PFS (lower left) in all patients and OS (upper right) and PFS (lower right) in those without EGFR mutation according to TB. (**E**); OS (upper left) and PFS (lower left) in patients with AC patients and OS (upper right) and PFS (lower right) in those with non-AC according to TLG. (**F**); OS (upper left) and PFS (lower left) in patients with non-AC patients and OS (upper right) and PFS (lower right) in those with non-AC according to MTV. Abbreviation: TLG, total lesion glycolysis; MTV, metabolic tumor volume; SUVmax: maximal standardized under value; TB, tumor burden; OS, overall survival; PFS, progression-free survival; AC, adenocarcinoma; non-AC, non-adenocarcinoma.

**Table 2.** Univariate analysis in overall survival and progression-free survival.

Abbreviations: TLG, total lesion glycolysis; MTV, metabolic tumor volume; SUVmax, the maximum of standardized uptake value; AC, adenocarcinoma; Non-AC, non-adenocarcinoma; PS, performance status; HR, hazard ratio; 95% CI, 95% confidence interval; NR, not reached; EGFR, epidermal growth factor receptor; TB, tumor burden; Bold character shows statistically significance.

**Table 3.** Multivariate analysis of overall survival and progression-free survival.

Abbreviations: TLG, total lesion glycolysis; MTV, metabolic tumor volume; PS, performance status; HR, hazard ratio; 95% CI, 95% confidence interval; EGFR, epidermal growth factor receptor.

#### **4. Discussion**

To the best of our knowledge, this is the first study to evaluate the prognostic significance of metabolic parameters measured by 18F-FDG-PET for predicting outcomes after the initiation of anti-PD-1 antibodies in patients with previously treated NSCLC. We found that the tumor metabolic volume assessed by TLG and MTV was an independent prognostic factor, but not SUVmax and TB. The roles of TLG and MTV as significant predictive markers after anti-PD-1 antibody therapy may be closely associated with patients with a histology of adenocarcinoma and without EGFR mutation. Although the value of SUVmax on 18F-FDG uptake within tumor cells was closely correlated with that of TLG and MTV, SUVmax on 18F-FDG uptake before anti-PD-1 antibody could not accurately predict the outcome after the initiation of treatment. Furthermore, we found that low uptake of 18F-FDG was closely associated with the occurrence of irAEs and the incidence of grade 3 or 4 irAEs exhibited no close correlation with the degree of 18F-FDG uptake on PET. In addition, there was no significant correlation between the response to the anti-PD-1 antibody and the degree of 18F-FDG uptake. However, we discovered that MTV of pretreatment 18F-FDG-PET plays a crucial role in the prognostic significance of anti-PD-1 antibody treatment. Unlike previous studies [12,13], our study indicated that TB determined by baseline tumor size was not a significant predictor of ICI or irAEs. Further studies are warranted to investigate whether pretreatment of MTV can predict the outcome of ICI plus ICI or the combination of ICI plus cytotoxic chemotherapy as first-line treatment.

A recent study reported that the metabolic response to 18F-FDG uptake measured by TLG or MTV was a stronger biomarker for the prediction of efficacy and survival at one month after the initiation of nivolumab than SUVmax [10]. The predictive probability of partial response (100% versus 29%, *p* = 0.021) and progressive disease (100% versus 22.2%, *p* = 0.002) at one month after nivolumab treatment was significantly higher in 18F-FDG-PET than in CT. Moreover, multivariate analysis confirmed the 18F-FDG uptake measurement by TLG or MTV as an independent prognostic factor. Thus, 18F-FDG-PET may be a useful radiographic modality for immune monitoring to predict the efficacy of ICI. However, a large-scale prospective study is required to confirm these results [10,18]. A recent meta-analysis suggested that in lung cancer, metabolic parameters such as TLG and MTV are better prognostic predictors after any treatment when compared with SUVmax [11].

Recently, Jreige et al. described that the metabolic-to-morphological volume ratio (MMVR)—calculated by dividing MTV by morphological tumor volume (MoTV)—was able to predict the radiological response to anti-PD-1/PD-L1 blockade and was negatively correlated with tumor PD-L1 expression and tumor necrosis [18]. Although their study analyzed only 17 patients who received anti-PD-1 therapy, they suggested that anti-PD-1 therapy is effective for tumor tissues with a low ratio of MTV, and the presence of a low MTV contributes to the upregulation of PD-L1 expression by the hypoxic environment in the tumor arising from necrosis and inflammation. However, it remained unclear whether MMVR could predict the outcome after anti-PD-1 therapy. Our study, however, indicated that patients with a low MTV exhibited a favorable prognosis after anti-PD-1 therapy. Several studies have demonstrated that tumor necrosis triggers inflammation, which facilitates the influx of lymphocytes and the upregulation of PD-L1, related to tumor necrosis factor-α, and that necrosis or inflammation was closely linked to tumor recurrence and worse survival [19,20]. Our study could not investigate the relationship between necrosis or inflammation and tumor metabolic volume; therefore, it remains unclear whether low MTV and TLG are associated with necrosis, inflammation, and hypoxic environment in the tumor. Further investigation is warranted to elucidate the prognostic significance of MTV and TLG as predictive markers of anti-PD-1 therapy based on the biological aspect.

The mechanism by which tumor cells uptake 18F-FDG requires glucose metabolism, hypoxia, and angiogenesis, and 18F-FDG is closely associated with the expression of these markers [6]. The expression of PD-L1 is significantly related to Glut1, HIF-1α and SUVmax on 18F-FDG uptake in lung cancer [7–9]. However, it is reported that TLG and MTV on 18F-FDG uptake were not closely correlated with PD-L1 expression levels [18], but Foxp3-Tregs are described to be positively associated with TLG and MTV [21]. Considering these evidences, the active environment with high MTV may form an immunosuppressive state, contributing to the resistant situation to ant-PD-1 blockage.

Our study has several limitations. First, we employed a retrospective approach and a small cohort, which may have introduced bias in our results. More than half of the patients with previously treated NSCLC had not undergone 18F-FDG-PET just before the initiation of anti-PD-1 antibody treatment. Therefore, we think that the number of eligible patients was slightly limited. However, the current study is meaningful for the prediction of anti-PD-1 therapy. Second, our study suggests that MTV could be a predictive marker for ICI treatment compared to the morphological tumor volume. However, the

appropriateness of morphological assessment used for calculating the optimal tumor volume of all metastatic lesions using CT scan is debatable. Thus, it may be difficult to perform a concise comparison between metabolic and morphological tumor volumes. Moreover, we had no information about the calculation of MMVR in our study, thus, there were some limitations in discussing the prognostic significance of metabolic tumor volume compared to MMVR. Lastly, an the immunohistochemical analysis of PD-L1, expression within tumor cells using tumor specimens was not performed before anti-PD1 antibody treatment. At our institution, re-biopsy was not done routinely before ICI treatment except for the initial diagnosis. Further study is warranted to investigate the relationship between MTV and the immune environment.

In conclusion, TLG and MTV on 18F-FDG uptake may predict the prognosis after anti-PD-1 antibodies in patients with previously treated NSCLC, but not SUVmax on 18F-FDG uptake. Although MTV may indirectly reflect the presence of morphological tumor volume with active tumor cells, the assessment of TLG and MTV on 18F-FDG uptake is easily executable in daily practice. A prospective study is needed to confirm these results.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/3/725/s1.

**Author Contributions:** K.H., A.S., K.K. (Kunihiko Kobayashi) and H.K.: conception and preparation of the manuscript. A.M., A.S., O.Y., K.H., Y.M. (Yu Miura), and Y.M. (Yoshitake Murayama): management of the patient. O.Y.: statistical analysis and patient's data collection. A.S., A.M., O.Y., K.K. (Kyoichi Kaira), I.K. and H.K.: revising the manuscript. All authors contributed and agreed with the content of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

**Conflicts of Interest:** A.M., K.K., O.Y. and H.K. have received research grants and a speaker honorarium from Ono Pharmaceutical Company and Bristol-Myers Company. All remaining authors have declared no conflicts of interest.


*4.2.2 Stilbene-based polyphenolic compounds*

Stilbene-based polyphenolic compounds, i.e. resveratrol, pterostilbene, and piceatannol, are of particular interest from a medicinal chemistry standpoint, having multiple pharmacological activities (**Figure 4**).

In particular, *trans*-resveratrol (3, 5, 4′-trihydroxystilbene) became popular as a result of an attempt to explain the "French paradox" [47]. Resveratrol and other polyphenolic-stilbene derivatives showed a wide range of beneficial physiological properties. They possess antibacterial, anti-inflammatory, hypolipidemic, cardiovascular-hepatoprotective, and anticancer activities [48–50]. In particular, the hypolipidemic and cardiovascular protective activity derived from the agonistic activity against PPARα and PPARγ receptors [51, 52] For all this benefit, resveratrol has attracted the attention of the scientific community and pharmaceutical and nutraceutical industries. Indeed, several drugs and dietary supplements containing resveratrol are commercially available.

Even though resveratrol is produced naturally in plants, the extraction of resveratrol in commercial quantities is a problem, because of its low concentration, multiple steps of isolation and purification, unfriendly environmental issues, and seasonal occurrence [53]. Moreover, the preparation of resveratrol by synthesis is difficult owing to the formation of many unwanted side products [54, 55]. Only recently, the production of resveratrol in heterologous engineered microorganisms

**45**

*4.2.3 Terpenoids*

*<IP_ADDRESS> Artemisinin and paclitaxel*

*Microwave-Assisted Solid Extraction from Natural Matrices*

has been proposed [56]. Thus, resveratrol is still being extracted from wild *Polygonum cuspidatum*'s root (Japanese knotweed), grape skins and seed, and the domestic giant knotweed of China, which is the world's largest producer [53, 56–58]. Garcia-Ayuso *et al.,* in late 1998, found that by applying the MW irradiation to SE, the last of the extraction was drastically reduced from 8 hours to 60 minutes with comparable results to SE in yield. MASE was further optimized by testing solvents and times on bark extraction and compared to SE on the same tree sample. The results suggested that microwave extraction may be more efficient than SE. The extraction of resveratrol by MASE from different plant materials (i.e. *Arachis repens* and grape seeds) has also been investigated. To exhaustively extract resveratrol from *A. repens*, commonly known as peanut grass, three different methodologies (conventional maceration, ultrasound-assisted extractions, and MASE) have been compared. Although sonication resulted more effectively in the extraction of resveratrol compared to MASE and maceration, MASE showed to be

an excellent choice since it extracted high yields in a reduced time [59].

In another study, Dang et al. combined the aqueous two-phase extraction technique (ATPE) with MASE for the extraction of the total polyphenol content, including resveratrol, from grape seeds [60]. Microwave-assisted ATPE (MAATPE) required lower solvent concentration and less time compared with other methods such as refluxing solvent or SE. A higher level of resveratrol was obtained with MAATPE, in contrast to ATPE. The Authors also compared the effectiveness of three solvents (water, water: ethanol (1:1) and ethanol) and three extraction methods, including MASE and ultrasound-assisted extraction (UAE) and the conventional SE. MASE provided a better extraction with water and ethanol (1:1) obtaining extracts very rich in polyphenolic substances, including stilbenes.

Lastly, MASE has successfully applied also for the extraction of other polyphenolic-stilbene based compounds such as pterostilbene, mainly found in blueberries and in *Pterocarpus marsupium* heartwood, and ε-viniferin, found in *Vitis coignetiae*, a wild grapevine (**Figure 4**). Kim et al. reported the MASE of pterostilbene, and other derivatives, from *Vitis coignetiae*, using 80% ethanol at 90 W for 15 min, resulting in a stilbenoids overall yield of 0.13%, with pterostilbene the most representative compound in the extract [61]. An optimized protocol (70–150 W for 8–18 min, using 30–50% ethanol) was further developed for the extraction of viniferin from the same drug [48]. Recently, Pinero et al. disclosed a new process for recovering stilbenes from woody vine by-products such as grape stem and cane samples. MASE was carried out under different extraction conditions. The best results were achieved from grape stems, using 80% ethanol in water as an extraction solvent, a temperature of 125°C, an irradiation power of 750 W for 5 min [49].

Terpenes and isoprenoids, in general, gained much attention for their physiological functions (i.e., hormones, aliphatic membrane anchors, maintaining membrane structure), ecological roles (i.e., defense compounds, insect/animal attractants), and extensive pharmaceutical applications such as flavors, fragrances, and medicines. In particular, artemisinin and paclitaxel represented two milestones in the fight against malaria and cancer, respectively. Artemisinin (**Figure 5**) is a sesquiterpene lactone isolated from *Artemisia annua* and it is a first-class drug for the treatment of drug-resistant malaria. The conventional artemisinin extraction procedure requires room temperature, heat-reflux, or SE. Hao et al., in 2002 reported a first attempt to extract artemisinin from *Artemisia annua* by MASE. Several solvents were explored,

*DOI: http://dx.doi.org/10.5772/intechopen.95440*

**Figure 4.** *Chemical structure of polyphenolic-stilbene based secondary metabolites.*

#### *Microwave-Assisted Solid Extraction from Natural Matrices DOI: http://dx.doi.org/10.5772/intechopen.95440*

*Microwave Heating - Electromagnetic Fields Causing Thermal and Non-Thermal Effects*

the cleanup steps, and allows a quantitative recovery of the drugs.

*4.2.2 Stilbene-based polyphenolic compounds*

resveratrol are commercially available.

ing multiple pharmacological activities (**Figure 4**).

*Chemical structure of polyphenolic-stilbene based secondary metabolites.*

the leaves of *Erythroxylum coca* by MASE. Different solvents, particle size, time, and power were evaluated. Since MeOH is a high absorbing microwave solvent, and cocaine is highly soluble in it, it was found to be the best extraction solvent [36]. Interestingly, MASE found application in the forensic field as a rapid and cleanup-free method for the extraction and quantification of drugs of abuse and the respective metabolites from human fluids and tissues. Fernandez et al. reported the simultaneous extraction of cocaine, benzoylecgonine, cocaethylene, morphine, 6-monoacethylmorphine, and codeine from human urine [44], hair [45], and vitreous humor samples [46]. The MASE procedure reduces the extraction time, avoids

Stilbene-based polyphenolic compounds, i.e. resveratrol, pterostilbene, and piceatannol, are of particular interest from a medicinal chemistry standpoint, hav-

In particular, *trans*-resveratrol (3, 5, 4′-trihydroxystilbene) became popular as a result of an attempt to explain the "French paradox" [47]. Resveratrol and other polyphenolic-stilbene derivatives showed a wide range of beneficial physiological properties. They possess antibacterial, anti-inflammatory, hypolipidemic, cardiovascular-hepatoprotective, and anticancer activities [48–50]. In particular, the hypolipidemic and cardiovascular protective activity derived from the agonistic activity against PPARα and PPARγ receptors [51, 52] For all this benefit, resveratrol has attracted the attention of the scientific community and pharmaceutical and nutraceutical industries. Indeed, several drugs and dietary supplements containing

Even though resveratrol is produced naturally in plants, the extraction of resveratrol in commercial quantities is a problem, because of its low concentration, multiple steps of isolation and purification, unfriendly environmental issues, and seasonal occurrence [53]. Moreover, the preparation of resveratrol by synthesis is difficult owing to the formation of many unwanted side products [54, 55]. Only recently, the production of resveratrol in heterologous engineered microorganisms

**44**

**Figure 4.**

has been proposed [56]. Thus, resveratrol is still being extracted from wild *Polygonum cuspidatum*'s root (Japanese knotweed), grape skins and seed, and the domestic giant knotweed of China, which is the world's largest producer [53, 56–58]. Garcia-Ayuso *et al.,* in late 1998, found that by applying the MW irradiation to SE, the last of the extraction was drastically reduced from 8 hours to 60 minutes with comparable results to SE in yield. MASE was further optimized by testing solvents and times on bark extraction and compared to SE on the same tree sample. The results suggested that microwave extraction may be more efficient than SE.

The extraction of resveratrol by MASE from different plant materials (i.e. *Arachis repens* and grape seeds) has also been investigated. To exhaustively extract resveratrol from *A. repens*, commonly known as peanut grass, three different methodologies (conventional maceration, ultrasound-assisted extractions, and MASE) have been compared. Although sonication resulted more effectively in the extraction of resveratrol compared to MASE and maceration, MASE showed to be an excellent choice since it extracted high yields in a reduced time [59].

In another study, Dang et al. combined the aqueous two-phase extraction technique (ATPE) with MASE for the extraction of the total polyphenol content, including resveratrol, from grape seeds [60]. Microwave-assisted ATPE (MAATPE) required lower solvent concentration and less time compared with other methods such as refluxing solvent or SE. A higher level of resveratrol was obtained with MAATPE, in contrast to ATPE. The Authors also compared the effectiveness of three solvents (water, water: ethanol (1:1) and ethanol) and three extraction methods, including MASE and ultrasound-assisted extraction (UAE) and the conventional SE. MASE provided a better extraction with water and ethanol (1:1) obtaining extracts very rich in polyphenolic substances, including stilbenes.

Lastly, MASE has successfully applied also for the extraction of other polyphenolic-stilbene based compounds such as pterostilbene, mainly found in blueberries and in *Pterocarpus marsupium* heartwood, and ε-viniferin, found in *Vitis coignetiae*, a wild grapevine (**Figure 4**). Kim et al. reported the MASE of pterostilbene, and other derivatives, from *Vitis coignetiae*, using 80% ethanol at 90 W for 15 min, resulting in a stilbenoids overall yield of 0.13%, with pterostilbene the most representative compound in the extract [61]. An optimized protocol (70–150 W for 8–18 min, using 30–50% ethanol) was further developed for the extraction of viniferin from the same drug [48]. Recently, Pinero et al. disclosed a new process for recovering stilbenes from woody vine by-products such as grape stem and cane samples. MASE was carried out under different extraction conditions. The best results were achieved from grape stems, using 80% ethanol in water as an extraction solvent, a temperature of 125°C, an irradiation power of 750 W for 5 min [49].

#### *4.2.3 Terpenoids*

### *<IP_ADDRESS> Artemisinin and paclitaxel*

Terpenes and isoprenoids, in general, gained much attention for their physiological functions (i.e., hormones, aliphatic membrane anchors, maintaining membrane structure), ecological roles (i.e., defense compounds, insect/animal attractants), and extensive pharmaceutical applications such as flavors, fragrances, and medicines.

In particular, artemisinin and paclitaxel represented two milestones in the fight against malaria and cancer, respectively. Artemisinin (**Figure 5**) is a sesquiterpene lactone isolated from *Artemisia annua* and it is a first-class drug for the treatment of drug-resistant malaria. The conventional artemisinin extraction procedure requires room temperature, heat-reflux, or SE. Hao et al., in 2002 reported a first attempt to extract artemisinin from *Artemisia annua* by MASE. Several solvents were explored,

**Figure 5.**

*Chemical structures of artemisinin and paclitaxel.*

such as ethanol, trichloromethane, cyclohexane, n-hexane, petroleum ether, and two in-house oils. Compared with SE, supercritical CO2 extraction, and normal stirring extraction, MASE of artemisinin from *Artemisia annua* considerably reduced the processing time to 12 minutes and resulted in a 92.1% extraction rate (compared to several hours and 60% extraction yield obtained with Soxhlet) [50]. Later, Liu et al. applied the MASE for the isolation and quantification of artemisinin in comparison with the traditional protocols. MASE confirmed shorter extraction time necessity, reduced solvent consumption, and higher recovery of artemisinin than conventional procedures. The best extraction solvent was petroleum ether–acetone (4:1 v/v), because of the high solubility of artemisinin and adequate microwave energy absorption, at 50°C. The highest yield of artemisinin achieved was 0.55% in 30 minutes among all the extractive methods used [62].

Recently, Misra et al. developed a rapid and reliable MASE and HPTLC protocol for the analysis of artemisinin. The optimized MASE conditions required 100 mg of dried and grinded drug with a size of 14 mesh dispersed into 10 mL of toluene. The irradiation of the sample at 160 W for 120 seconds led to the extraction of 0.816% of the content of artemisinin.

Paclitaxel (**Figure 5**) is a member of the taxane class, and it is one of the most important anticancer drugs approved for human use against ovarian, breast, and pulmonary cancer.

Although the total synthesis of paclitaxel has been reported, its application for the commercial production of this drug is impracticable. Thus, paclitaxel is still produced by extraction from taxol biomass*.* The most commonly used methods for the extraction of paclitaxel require the use of methanol at ambient temperature, although other protocols requiring refluxing methanol, 1:1 methanol-chloroform at ambient temperature, and percolation using ethanol or 95% ethanol-water at ambient temperature have been reported. However, these methods require a long time (12–24 h) for a complete extraction. Incorvia-Mattina et al. reported for the first time in 1997 the use of MASE to optimize the efficiency of the extraction of paclitaxel. The effects of the biomass, solvent ratio and water content on taxane recovery were also determined. Under appropriate MASE conditions an extract equivalent to the one obtained by conventional extraction methods was produced [63].

Talebi et al. investigated the use of MASE to extract paclitaxel from the needles of *Taxus baccata L.* The extraction parameters were investigated resulting in 90% aq. MeOH as a solvent, a temperature of 95°C, 7 min of extraction time, and a closed-vessel system as the best performing extractive conditions [64].

Recently, another study for the extraction of paclitaxel from biomass through MASE and based on kinetic and thermodynamic analysis has been carried out. The

**47**

**Figure 6.**

*Microwave-Assisted Solid Extraction from Natural Matrices*

[65, 66] and the tetrahydrocannabinol derivatives (i.e. Δ9

tuberous sclerosis complex (TSC) in patients 1 year of age and older.

majority of paclitaxel was recovered from the biomass (∼99%) within 6min in a single cycle of microwave-assisted extraction at microwave powers of 50–150W and

*Cannabis sativa* L. has always been considered a controversial plant due to its use as both medicine and illicit drug. Nevertheless, Cannabis is a good source of nutrients, fibers, and natural compounds thus, its industrial and pharmaceutical use is undoubtful. Cannabis produces a peculiar class of natural compounds, namely phytocannabinoids. The two most important and renowned phytocannabinoids are the cannabidiol derivatives (i.e. CBD, CBDV, CBDB, and CBDP)

recreational use of hemp and therefore its use is banished or tightly regulated by

CBD-like derivatives are non-psychotropic compounds but with other recognized pharmacological properties such as anti-inflammatory, antioxidant, and anticonvulsant. As an example, Epidiolex, a CBD-based anticonvulsant drug, has been approved in 2018 by Food and Drug Administration for the treatment of seizures associated with Lennox–Gastaut syndrome (LGS), Dravet syndrome, or

The discovery of a plethora of pharmacological activities ascribed to CBD and other minor phytocannabinoids has increased attention from both scientists and industries for medical, nutraceutical, and cosmetic applications of these cannabinoids. Several synthetic procedures have been developed and optimized for the industrial preparations of phytocannabinoids and in particular of CBD. However, this process suffers from several drawbacks such as the cost of the starting materials, reagents and solvents, the formation of by-products with consequent cumbersome purification procedures, and the difficulty to control the stereochemistry, the isomerism of the terpenic double bond, and the easy interconversion of CDB into

Thus, the extraction and purification of phytocannabinoids from *C. sativa* remain the preferred procedure for its cost-effectiveness. Besides, tight monitoring of the chemical consistency of the extracts results therefore mandatory in producing consistent and reliable medical cannabis preparations for human uses. Recently, Nahar et al. reviewed all the procedures adopted at the present for the extraction of

*Chemical structures of CBD-like and THC-like major phytocannabinoids present in* C. sativa*.*

*DOI: http://dx.doi.org/10.5772/intechopen.95440*

temperatures of 30–45°C [64].

*4.2.4 Phytocannabinoids*

THCB, and Δ9

national governments.

THCs in the synthetic conditions.

naturally occurring phytocannabinoids [68].

majority of paclitaxel was recovered from the biomass (∼99%) within 6min in a single cycle of microwave-assisted extraction at microwave powers of 50–150W and temperatures of 30–45°C [64].


*2.8. Selective Pressure on UGlcAE Proteins in the Tomato*

**Figure 6.** Assignment of Gene Ontology categories to *UGlcAE* genes in tomato. The lengths of the rectangular columns indicate the number of genes that participated in the corresponding classification. The purple rectangular columns mean gene functions of *UGlcAE* in *Arabidopsis*, the red rectangular columns represent gene functions of *UGlcAE* in tomato. All of the gene functions were classified into three categories, which were further divided into eight minor terms. To examine the evolutionary conservation of the UGlcAE proteins, the selective pressure on the UGlcAE was analyzed with SELECTON. We found that the domain of SlUGlcAE3-like1 protein was undergoing strong purifying selection (Figure 7). Selective pressure analyses of the other SlUGlcAE proteins were also analyzed and the results are shown in Supplementary Material Figure S2. These results confirm that the *SlUGlcAE* genes are undergoing strong purifying selection. The amino acids *2.8. Selective Pressure on UGlcAE Proteins in the Tomato*

that are emphasized in yellow are under positive selection; however, no positive selection site was found in this selection analysis. These results confirm that these gene family members were very conservative in evolution, which imply them playing a pivotal function in pectin biosynthesis. Selection pressure in the promoter regions of *SlUGlcAE* genes indicated that they are also undergoing negative selection (Figure S3). that are emphasized in yellow are under positive selection; however, no positive selection site was found in this selection analysis. These results confirm that these gene family members were very conservative in evolution, which imply them playing a pivotal function in pectin biosynthesis. Selection pressure in the promoter regions of *SlUGlcAE* genes indicated that they are also undergoing negative selection (Figure S3).

results confirm that the *SlUGlcAE* genes are undergoing strong purifying selection. The amino acids

*Int. J. Mol. Sci.* **2018**, *19*, x FOR PEER REVIEW 9 of 21

To examine the evolutionary conservation of the UGlcAE proteins, the selective pressure on the UGlcAE was analyzed with SELECTON. We found that the domain of SlUGlcAE3-like1 protein was undergoing strong purifying selection (Figure 7). Selective pressure analyses of the other SlUGlcAE

**Figure 7.** Selection pressure analysis of the UGlcAE proteins in tomato. The red shades represent ω < 1 (purifying selection). Amino acid sequence of SlUGlcAE3-like1 is shown, and the sequences of other SlUGlcAE proteins are presented in the Supplementary Materials Figure S2. **Figure 7.** Selection pressure analysis of the UGlcAE proteins in tomato. The red shades represent ω < 1 (purifying selection). Amino acid sequence of SlUGlcAE3-like1 is shown, and the sequences of other SlUGlcAE proteins are presented in the Supplementary Materials Figure S2.

#### *2.9. Cis-Acting Elements Analysis of the UGlcAE Genes in the Tomato 2.9. Cis-Acting Elements Analysis of the UGlcAE Genes in the Tomato*

To explore the *cis*-acting elements of *SlUGlcAE* genes, we analyzed the 0.5 kb upstream sequences of nine *SlUGlcAE* genes using online software Plant CARE and the result was shown in Figure 8 and Supplementary Materials Table S1. The analysis result of 1.5 kb upstream genomic sequences of genes was shown in Supplementary Materials Table S2. To explore the *cis*-acting elements of *SlUGlcAE* genes, we analyzed the 0.5 kb upstream sequences of nine *SlUGlcAE* genes using online software Plant CARE and the result was shown in Figure 8 and Supplementary Materials Table S1. The analysis result of 1.5 kb upstream genomic sequences of genes was shown in Supplementary Materials Table S2.

Kinds, numbers, and locations of *cis*-elements in the upstream of *SlUGlcAE* genes were shown in Figure 8A, and the functional descriptions of these stress-related, hormone-related, and development-related *cis*-elements were exhibited in Figure 8B. As shown in Figure 8A, there are three *cis*-acting elements that are related to hormone, including TGA-element, TATC-box and TCA-element, and 5 stress-related elements including HSE (heat stress-related element), TC-rich repeats (*cis*-acting element involved in defense and stress responsiveness), LTR (*cis*-acting element involved in low-temperature responsiveness), WUN-motif (wound-responsive element), and MBS (MYB Binding Site), and seven elements that are involved in development (Skn-1\_motif, HD-Zip 1, HD-Zip 2, circadian, CAT-box, W box, and ELI-box3). Among them, the 0.5 kb upstream regions of four *SlUGlcAE* genes were found to be the presence of heat stress-related element (HSE), of which had two HSE elements in the 0.5 kb upstream region of *SlUGlcAE6* and 1 HSE elements in the 0.5 kb upstream regions of *SlUGlcAE1*, *SlUGlcAE3,* and *SlUGlcAE5*. Furthermore, defense- and stress-response

element (TC-rich repeats) was identified in the 0.5 kb upstream regions of four *SlUGlcAE* genes (*SlUGlcAE1-like*, *SlUGlcAE3-like1*, *SlUGlcAE3-like2*, and *SlUGlcAE5*), and circadian element (circadian) was found in the 0.5 kb upstream regions of three *SlUGlcAE* genes (*SlUGlcAE1-like*, *SlUGlcAE3-like1,* and *SlUGlcAE3-like2*), and endosperm expression-related element (Skn-1\_motif) was discovered in the 0.5 kb upstream regions of two *SlUGlcAE* genes (*SlUGlcAE1* and *SlUGlcAE6*), and other 11 elements are all present in the 0.5 kb upstream regions of only one *SlUGlcAE* gene. Four elements are located in 0.5 kb upstream region of *SlUGlcAE1*, and element numbers are diversified in the 0.5 kb upstream region of other genes, respectively (four in *SlUGlcAE1-like*, three in *SlUGlcAE2-like*, one in *SlUGlcAE3*, two in *SlUGlcAE3-like1*, four in *SlUGlcAE3-like2*, five in *SlUGlcAE5*, four in *SlUGlcAE6*, and zero in *SlUGlcAE6-like*). *Int. J. Mol. Sci.* **2018**, *19*, x FOR PEER REVIEW 10 of 21

**Figure 8.** Kinds and numbers of stress-related, hormone-related, and development-related *cis*-elements in the upstream of *SlUGlcAE* genes. (**A**) Various symbols indicate different *cis*-acting elements; and (**B**) Element names and their functional descriptions. **Figure 8.** Kinds and numbers of stress-related, hormone-related, and development-related *cis*-elements in the upstream of *SlUGlcAE* genes. (**A**) Various symbols indicate different *cis*-acting elements; and (**B**) Element names and their functional descriptions.

Kinds, numbers, and locations of *cis*-elements in the upstream of *SlUGlcAE* genes were shown in Figure 8A, and the functional descriptions of these stress-related, hormone-related, and development-related *cis*-elements were exhibited in Figure 8B. As shown in Figure 8A, there are three *cis*-acting elements that are related to hormone, including TGA-element, TATC-box and TCA-element, and 5 stress-related elements including HSE (heat stress-related element), TC-rich repeats (*cis*-acting element involved in defense and stress responsiveness), LTR (*cis*-acting element involved in low-temperature responsiveness), WUN-motif (wound-responsive element), and MBS (MYB Binding Site), and seven elements that are involved in development (Skn-1\_motif, HD-Zip 1, HD-Zip 2, circadian, CAT-box, W box, and ELI-box3). Among them, the 0.5 kb upstream regions of four *SlUGlcAE* genes were found to be the presence of heat stress-related element (HSE), of which had two HSE elements in the 0.5 kb upstream region of *SlUGlcAE6* and 1 HSE elements in the 0.5 kb No of stress-, hormone-, and development-related element was found in the 0.5 kb upstream region of *SlUGlcAE6-like* gene, and the previous spatial expression patterns showed *SlUGlcAE6-like* was lowly expressed at every stages, which are highly consistent. Thus, we infer that *SlUGlcAE6-like* may not be involved in the process of growth and development. In addition, HD-Zip 1 and HD-Zip 2 are located in the same position of *SlUGlcAE1* and *SlUGlcAE1-like*, implying that the two elements might be closely related and complementary to each other. Furthermore, other stress-, hormone-, and development-unrelated *cis*-acting elements have also been identified. For example, core promoter element (TATA-box) and common *cis*-acting element (CAAT-box) are present in the 0.5 kb upstream regions of all nine *UGlcAE* genes. Light responsive *cis*-acting regulatory elements (GATA-motif, chs-CMA1a, G-box) and enhancer (TA-rich region) could also be found.

#### upstream regions of *SlUGlcAE1*, *SlUGlcAE3,* and *SlUGlcAE5*. Furthermore, defense- and *2.10. Expression Patterns of SlUGlcAE Family Genes in Response to IAA, GA and SA*

*SlUGlcAE3-like2*, five in *SlUGlcAE5*, four in *SlUGlcAE6*, and zero in *SlUGlcAE6-like*).

(GATA-motif, chs-CMA1a, G-box) and enhancer (TA-rich region) could also be found.

*2.10. Expression Patterns of SlUGlcAE Family Genes in Response to IAA, GA and SA*

stress-response element (TC-rich repeats) was identified in the 0.5 kb upstream regions of four *SlUGlcAE* genes (*SlUGlcAE1-like*, *SlUGlcAE3-like1*, *SlUGlcAE3-like2*, and *SlUGlcAE5*), and circadian element (circadian) was found in the 0.5 kb upstream regions of three *SlUGlcAE* genes (*SlUGlcAE1-like*, *SlUGlcAE3-like1,* and *SlUGlcAE3-like2*), and endosperm expression-related element (Skn-1\_motif) was discovered in the 0.5 kb upstream regions of two *SlUGlcAE* genes (*SlUGlcAE1* and *SlUGlcAE6*), and other 11 elements are all present in the 0.5 kb upstream regions of only one *SlUGlcAE* gene. Four elements are located in 0.5 kb upstream region of *SlUGlcAE1*, and element numbers are diversified in the 0.5 kb upstream region of other genes, respectively (four in *SlUGlcAE1-like*, three in *SlUGlcAE2-like*, one in *SlUGlcAE3*, two in *SlUGlcAE3-like1*, four in Plant hormones, such as IAA, GA, and SA are used as endogenous messengers in response to biotic and abiotic stresses in plants [33]. It has been reported that the treatments of plants by exogenous hormones often lead to transient and rapid transcriptional changes in the whole genome [34]. According to *cis*-acting elements analysis of the *SlUGlcAE* genes upstream, three *cis*-acting elements that are related to plant hormones (IAA, GA, and SA) are located in 0.5 kb upstream genomic sequences of *SlUGlcAE1*, *SlUGlcAE2-like*, and *SlUGlcAE5*, respectively (Figure 9A). Thus, we investigated the expression profiles of *SlUGlcAE1*, *SlUGlcAE2-like,* and *SlUGlcAE5* with IAA, GA, and SA treatments (Figure 9B–D).

and development-unrelated *cis*-acting elements have also been identified. For example, core promoter element (TATA-box) and common *cis*-acting element (CAAT-box) are present in the 0.5 kb upstream regions of all nine *UGlcAE* genes. Light responsive *cis*-acting regulatory elements

Plant hormones, such as IAA, GA, and SA are used as endogenous messengers in response to biotic and abiotic stresses in plants [33]. It has been reported that the treatments of plants by

No of stress-, hormone-, and development-related element was found in the 0.5 kb upstream region of *SlUGlcAE6-like* gene, and the previous spatial expression patterns showed *SlUGlcAE6-like* was lowly expressed at every stages, which are highly consistent. Thus, we infer that *SlUGlcAE6-like*

exogenous hormones often lead to transient and rapid transcriptional changes in the whole genome [34]. According to *cis*-acting elements analysis of the *SlUGlcAE* genes upstream, three *cis*-acting elements that are related to plant hormones (IAA, GA, and SA) are located in 0.5 kb upstream genomic sequences of *SlUGlcAE1*, *SlUGlcAE2-like*, and *SlUGlcAE5*, respectively (Figure 9A). Thus,

**Figure 9.** The detection of expressional level of *SlUGlcAE* genes after plant hormone treatments. (**A**) Hormone-related *cis*-elements prediction in the upstream of three *SlUGlcAE* genes (TGA-element: auxin-responsive element, TATC-box: gibberellin-responsive element, TCA-element: salicylic acid-responsive element); (**B**) The qPCR expression analysis of *SlUGlcAE1* response to plant hormone treatments; (**C**) Responses of *SlUGlcAE2-like* to plant hormones; (**D**) Expression profile analysis of *SlUGlcAE5* under plant hormone treatments; (**E**) Expression of *SlUGlcAE1-like* after hormone treatments; (**F**) Expression level of *SlUGlcAE3* after three hormones treatments; (G) Responses of *SlUGlcAE3-like1* under hormone treatments; (**H**) Expression profile analysis of *SlUGlcAE3-like2* to plant hormones; (**I**) The expression analysis of *SlUGlcAE6* under three hormones treatments; and, (**J**) Expression pattern of *SlUGlcAE6-like* response to plant hormone treatments. The error bars represent the SEM. \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001, Ns: No significant. **Figure 9.** The detection of expressional level of *SlUGlcAE* genes after plant hormone treatments. (**A**) Hormone-related *cis*-elements prediction in the upstream of three *SlUGlcAE* genes (TGA-element: auxin-responsive element, TATC-box: gibberellin-responsive element, TCA-element: salicylic acid-responsive element); (**B**) The qPCR expression analysis of *SlUGlcAE1* response to plant hormone treatments; (**C**) Responses of *SlUGlcAE2-like* to plant hormones; (**D**) Expression profile analysis of *SlUGlcAE5* under plant hormone treatments; (**E**) Expression of *SlUGlcAE1-like* after hormone treatments; (**F**) Expression level of *SlUGlcAE3* after three hormones treatments; (G) Responses of *SlUGlcAE3-like1* under hormone treatments; (**H**) Expression profile analysis of *SlUGlcAE3-like2* to plant hormones; (**I**) The expression analysis of *SlUGlcAE6* under three hormones treatments; and, (**J**) Expression pattern of *SlUGlcAE6-like* response to plant hormone treatments. The error bars represent the SEM. \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001, Ns: No significant.

The expression of *SlUGlcAE1* in response to IAA was increased at 1 h, decreased at 3 h, and increased thereafter, including 6 and 12 h, and returned to background level until 24 h (Figure 9B). On the whole, the expressional level of *SlUGlcAE1* gene was up-regulated after IAA treatment, although accompanying an unclear reason of being down-regulated only at 3 h. The expressional level of *SlUGlcAE1* gene was not significant different when comparing to the control in response to GA and SA throughout the treated process (Figure 9B). Combining to the result analysis of *cis*-acting elements in *SlUGlcAE1* gene upstream, we found that *SlUGlcAE1* expressional regulation was consistent with TGA *cis*-acting elements existing in the upstream of this gene, which is an auxin-responsive element, while GA or SA responsive element is non-existent (Figure 9A). This indicated that the expression of *SlUGlcAE1* gene could be regulated by IAA, but it could not be regulated by GA and SA (Figure 9B). The *SlUGlcAE2-like* gene under IAA treatment was down-regulated at 6 and 24 h, and no obvious difference was found at other time points (Figure 9C). The change of *SlUGlcAE2-like* expression pattern was unobvious under SA treatment. *SlUGlcAE2-like* showed increasingly strong down-regulation in expression at 6, 12 and 24 h, while similar expression level to the control within the first 3 h under GA treatment (Figure 9C). These results indicated that the expression of *SlUGlcAE2-like* gene could be regulated by GA, and be regulated by IAA irregularly, but not be regulated by SA (Figure 9C). This is aligned with the previous *cis*-acting elements analysis result. That is the fact that there are a gibberellin-responsive element (TATC-box) within 0.5 kb genomic sequences of *SlUGlcAE2-like* gene upstream (Figure 9A) and another gibberellin-responsive element (GARE-motif) within 1.5 kb genomic sequences outside 0.5 kb genomic sequences of *SlUGlcAE2-like* gene upstream (Table S2). There is an auxin-responsive element (AuxRR-core) within 1.5 kb genomic sequences outside 0.5 kb genomic sequences of *SlUGlcAE2-like* gene upstream (Table S2). *SlUGlcAE5* after IAA treatment showed a similar expression level to the control at different time points (Figure 9D). The expression level of *SlUGlcAE5* after GA treatment was no significant change in the first 12 h, but it reduced at 24 h with unknown reasons). *SlUGlcAE5* was up-regulated at 1 h, not affected at 3 h, and up-regulated continuously at later time points, including 6, 12, and 24 h after SA treatment (Figure 9D). The results suggested the expression of *SlUGlcAE5* gene could indeed be regulated by SA. It keeps consistent with the result of *cis*-acting elements analysis, which has a salicylic acid-responsive element (TCA element) in 0.5 kb genomic sequences of *SlUGlcAE5* gene upstream (Figure 9A). Taken together, these data suggest that although the result of *cis*-acting elements analysis may contain a few false positives, the prediction of these three hormone response sites in our study is still relatively reliable.

In addition, we also examined the expression level of the other six *UGlcAE* genes after three hormones treatments. The results were shown in Figure 9E–J. Both *SlUGlcAE1-like* and *SlUGlcAE3* were down-regulated by SA (Figure 9E,F). *SlUGlcAE3-like2* was up-regulated by the three hormones within 12 h of hormone treatment. However, it was down-regulated by three hormones at 24 h (Figure 9H). *SlUGlcAE3-like1*, *SlUGlcAE6*, and *SlUGlcAE6-like* were affected by different hormones at different times after hormones treatments (Figure 9G,I,J).


*4.7. General Remarks*

As for any distributed system, the engineering of robot teamwork raises questions about concerns such as scalability, fault tolerance, performance, software evolution, and the like. It is important that developers of teamwork applications respond to these concerns. We do not discuss these concerns here because they do not create specific questions for the engineering of robot teamwork.


**2. The Improved Method of Calculating Direct Rebound E**ff**ect**

Improving energy efficiency will decrease energy consumption with the same level of energy service. For instance, if the rate of electricity use and cooling area decrease, residents will use less electricity cooling the same area. However, improving efficiency means a decrease in real power price, which will incentivize residents to use more electricity in turn. Calculating the direct rebound effect is to calculate the gap between the expected savings and the actual savings. Direct rebound effect is then defined as: Direct rebound = (expected savings − actual savings)/expected savings. The traditional calculation method of the direct rebound effect controls no other variables, so some studies recommend that the price elasticity could be an ideal proxy indicator of direct rebound effect with other variables controlled [39]. The definition and identification of direct rebound effect can be found in Appendix A.

The calculation method above only analyzes the energy consumed by the same consumers (consumers in the local region) and does not consider other consumers (consumers in the adjacent region). It implies the assumption that energy consumption in different regions is independent. However, if there is a spatial "convergence effect" in energy consumption, whereby the increased energy efficiency in a local region will have an influence on the energy consumption not only in the local region, but also in the adjacent regions, leading to a "spatial feedback effect". For the same reason, the improvement of energy efficiency in the adjacent region also induces a direct rebound effect in the local region. This paper views this as the spatial spillover effect of the direct rebound effect. It is

impossible to distinguish whether the additional energy consumption in the local region is caused by the energy efficiency improvement in the local region or in the adjacent region without considering spatial spillover effect.

Based on spatial spillover effect, this paper improves the calculating model of direct rebound effect. The spatial lag of electricity consumption is introduced into the model, and the spatial lag model (SLM) controlling other variables is:

$$y\_t = \lambda N y\_t + X\_t \beta + c + u\_t \tag{1}$$

where both the explained variable and the explanatory variable are logarithmized. *yt* is the urban residents' electricity consumption of *n* regions in year *t*. *W* is the space weight matrix, and *Wyt* is the spatial lag of *yt*. λ measures the effect of spatial lag *Wyt* on *yt*, reflecting spatial dependence. *Xt* is the explanatory variables matrix of *n* regions in year *t*. β is the coefficient of the explanatory variable. *c* is the individual effect of *n* regions. According to the individual effect, the model can be divided into fixed effect model and random effect model.

If the spatial correlation of urban residents' electricity consumption is not considered, Equation (1) is reduced to a standard static panel model.

Rewrite Equation (1) as a reduced form:

$$\mathbf{y}\_{l} = \left(I - \lambda \mathbf{W}\right)^{-1} \left(X\_{l}\boldsymbol{\beta} + \mathbf{c} + \mathbf{u}\_{l}\right) \tag{2}$$

$$E(y\_t | \mathbf{X}\_t, \mathcal{W}) = \left(I - \lambda \mathcal{W}\right)^{-1} (\mathbf{X}\_t \boldsymbol{\beta})\tag{3}$$

Equation (3) shows that measuring the direct rebound effect should consider the spatial feedback effect. According to the research on direct and indirect effects in spatial econometric models by LeSage and Pace [40], the calculation of the direct rebound effect in the space lag fixed effect model is:

$$\text{RE} = -\frac{1}{nT} \sum\_{t=1}^{T} \sum\_{i=1}^{n} \frac{\partial E(\hat{\mathcal{G}}\_{it} | \mathbf{X}\_{t\prime} \mathcal{W})}{\partial \ln P\_i} \tag{4}$$

where *y*ˆ*t* = *yt* − (*I* − λ*W*) −1 *c*. The direct rebound effect calculated here is the average value of the direct rebound effect of *n* regions, so it can be called the average direct rebound effect (abbreviated as RE).

The calculation of the space spillover effect of direct rebound effect is defined as:

$$\text{SRE} = -\frac{1}{nT(n-1)}\sum\_{t=1}^{T}\sum\_{i=1}^{n}\sum\_{j=1, j\neq i}^{n}\frac{\partial E(\hat{\rho}\_{it}|\mathbf{X}\_{t\prime}\mathcal{W})}{\partial \ln P\_{j}}\tag{5}$$

Equation (5) also calculates the average spatial spillover effects of *n* regions, so it can be called the average spatial spillover effect (abbreviated as SRE).

The spatial lag model only considers the endogenous interaction effects, ignoring the spatial correlation of unobservable random impacts. In the case of multiple spatial interactions, a more appropriate method is to use the spatial autoregressive model with spatial autoregressive disturbances (SARAR) model. Since urban residents' electricity consumption may have both the interaction of endogenous interaction and error terms, the SARAR model is introduced to measure the direct rebound effect and its spatial spillover effect:

$$y\_t = \lambda Wy\_t + X\_t\beta + \varepsilon + \varepsilon\_t, \varepsilon\_t = \rho W\varepsilon\_t + q\_t \tag{6}$$

where ρ is the coefficient of spatial lag *W*ε*t*. The calculation of the average direct rebound effect and the average spatial spillover effect of the SARAR model is consistent with the SLM model.

The process of using spatial econometric models is as follows: before establishing a spatial econometric model, it is necessary to test the spatial autocorrelation and heterogeneity in the data, using two types of spatial autocorrelation test: local autocorrelation and global autocorrelation. Then multiple models are set up. For nested models, a likelihood ratio (LR) test can be used to choose the best model. Due to endogeneity problems, the ordinary least squares (OLS) estimators are inconsistent. This paper uses the maximum likelihood estimator method (MLE) to get the consistent estimator. For panel data, individual effects need to be tested, so the Hausman test is used to select the appropriate model between the fixed effect and random effect models. And we use the method proposed by Lee and Yu [41] to estimate the panel spatial econometric model. Firstly, the individual effects are eliminated, then the maximum likelihood estimator method is performed.


**6. Landforms and vegetation**

Much of the natural vegetation has been removed and replaced with agricultural enterprises. Depressional areas consisting of backswamp deposits typically supported bald cypress (*Taxodium distichum* L.), water tupelo (*Nyssa sylvatica*), sweetgum (*Liquidambar styraciflua* L.), and multiple species of canes, rushes, and grasses, whereas recent meander belt deposits have willows (Salicaceae sp.), eastern cottonwoods (*Populus deltoides* Marsh.), American elm (*Ulmus americana* L.), yellow poplar (*Liriodendron tulipifera* L.), and boxelder (*Acer negundo* L.). Mixed forest species existed on well-drained to moderately well drained soils residing on variably textured alluvium and natural levees. Mixed forest species included: southern red oak (*Quercus falcata* L.), willow oak (*Quercus phellos*), white oak (*Quercus alba* L.), swamp white oak (*Quercus bicolor* Willd.), and shagbark hickory (*Carya ovata* Mill.).

The Southeast Lowlands Groundwater Province (SLGP) is bounded on the north and west by the Ozark Plateau, with the transition from the SLGP to the Ozark Plateau called the Ozark escarpment. The eastern boundary is the modern Mississippi River and the southern boundary is the Missouri-Arkansas state border. The western boundary of Dunklin Co. is the St. Francois River (**Figure 1**).

A prominent ridge within the SLGP is called Crowley's Ridge and the Benton Hills. These elevated land masses consist on Paleozoic rocks, largely Ordovician, and are covered by Tertiary gravels and loess [6]. Crowley's Ridge and the Benton Hills bisect the SLGP, with the land mass between Ozark Escarpment and west of Crowley's Ridge and the Benton Hills called the Advance Lowlands (also called Western Morehouse Lowlands). The Advance Lowlands represent the ancestral channel of the Mississippi River and are generally composed of loamy to silty terraces and back-swamp deposits overlying glacial outwash and valley train. Conversely, the Morehouse Lowlands extend from Crowley's Ridge eastward to the Mississippi River. The Morehouse lowlands consist of terraces of varying textures, back-swamp deposits, and other alluvial environments overlying braided glacial outwash. The modern Mississippi River and its flood plain is the youngest and easternmost feature with meandering channel deposits, natural levees, silty terraces, back-swamp environments, and crevasse splay deposits that characterize the Mississippi River floodplain [7]. Sikeston Ridge and Barnes Ridge (east of Portageville, MO) are low-elevation ridges, composed of coarse-textured materials and both are in the Morehouse Lowlands. Just east of Crowley's Ridge and extending into Dunkin Co. is a terrace system of coarse-texture materials called the Kennett-Malden Prairie. The Charleston Lowland is located primarily in Mississippi Co. and consists of fine to coarse textured materials, composed to recent terrace and back-swamp environments. Between the Benton Hills and the Charleston Lowlands is the Blodgett terrace composed of coarse-textured materials and the Charleston Fan, also composed of coarse-textured materials.


*4.7. Double Mutant Cycle Analysis*

Double mutant cycle analysis [44] was performed to determine the interaction free energy (∆Gint) between charged residues Xaa4 and Zbb9 in the HPTXaaZbb peptides using Equation (7) [44,45]. This analysis accounted for the effect of each charged residue (individually) on strand stability using data from the corresponding Ala-containing peptides HPTXaaAla [3] and HPTAlaZbb [3] to determine the Xaa4-Zbb9 ion-pairing interaction exclusively (Table 3). The peptide with Ala incorporated at positions 4 and 9, HPTAlaAla [22], was used as the reference peptide.

$$
\Delta \mathbf{G}\_{\text{int}} = (\Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{Z}\mathbf{b}} - \Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{A}\mathbf{A}}) - (\Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{A}\mathbf{A}} - \Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{Z}\mathbf{b}}) - (\Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{Z}\mathbf{b}} - \Delta \mathbf{G}\_{\text{HFT}\mathbf{\hat{a}a}\mathbf{A}\mathbf{A}}) \tag{7}
$$


*Article* **Industry 4.0 as a Challenge for the Skills and Competencies of the Labor Force: A Bibliometric Review and a Survey**

**Abdelkarim Alhloul 1 and Eva Kiss 2,\***

**Abstract:** The latest technological development called Industry 4.0, like the previous industrial revolutions, has also brought a new challenge for people as a labor force because new technologies require new skills and competencies. By 2030 the existing generation in the labor market will have a skill gap threatening human replacement by machines. Based on bibliometric analysis and systematic literature review the main aims of this study are, on the one hand, to reveal the most related articles concerning skills, competencies, and Industry 4.0, and on the other hand, to identify the newset of skills and competencies which are essential for the future labor force. Determining the model of new skills and competencies in connection with Industry 4.0 technologies is the main novelty of the study. A survey carried out among the workers of mostly multinational organisations in Hungary has also been used to explore the level of awareness about those skills and Industry 4.0 related technologies, and this can be considered the significance of the empirical research.

**Keywords:** Industry 4.0; skills; competencies; bibliometric analysis; survey; Hungary

**Citation:** Alhloul, A.; Kiss, E. Industry 4.0 as a Challenge for the Skills and Competencies of the Labor Force: A Bibliometric Review and a Survey. *Sci* **2022**, *4*, 34. https:// doi.org/10.3390/sci4030034

Academic Editor: Johannes Winter

Received: 23 June 2022 Accepted: 31 August 2022 Published: 5 September 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

### **1. Introduction**

The economic structure has changed over time because of technological development. This development started with the dawn of the first industrial revolution (1760–1840). After that, the world witnessed two more revolutions at the end of the 19th century and between the 1970s and 1990s [1,2]. The Fourth Industrial Revolution (4IR), which started at the turn of the millennium, is also called Industry 4.0 (I4.0), and it has been accelerated in the last decade. The term Industry 4.0 was originally mentioned as Industrie 4.0 at the Hannover Fair in 2011 and indicated a programme for the digitisation and strategic development of the German industry [3,4]. Since then, it has been widespread, although it has several definitions. For example, "Industry 4.0 is nothing more than a digital transformation" or "The next phase in the digitalisation of the processing industry". According to a different view, "Industry 4.0 is a vision sponsored by the German government for a more advanced processing industry". In a narrower sense and most often, as can be seen from the above definitions to some extent, it is related to industry and includes the new technologies that will result in a radical transformation of industrial production [5]. According to Reischauer [6], Industry 4.0 represents a major technological revolution, which takes place primarily in industry, factories, and production. This is why Industry 4.0 and thus the Fourth Industrial Revolution are often referred to as "smart factory", "intelligent industry" or "advanced manufacturing".

The use of Industry 4.0 emerging technologies to fulfill the requirements of production has caused a rapid change in the labor market which has been defined as a digital influence on the labor market. Industry 4.0 has affected many jobs, replacing humans with machines, as we can see e.g., during the check-in process at the airport and many other routine jobs.

Previous studies have confirmed that only highly skilled and qualified human resources will be able to control Industry 4.0 technologies [7–11].

Industry 4.0 emerging technologies require more than just performing a task or resolving a problem in each field, which is exactly the definition of the skill. Rather, the capability to meet complex demands, including interpersonal attributes to be self-driven for lifelong learning in each field as the competency definition states [12,13] and to be able to understand what the required skills and job profiles are, as well as having an understanding of the emerging technologies of Industry 4.0 is important. Therefore, Industry 4.0 has ten main technologies which are the driving forces of this revolution as follows:

In the operation of these, Industry 4.0 technology operators play an important role. The concept Operator 4.0 became popular among studies referring to the qualified persons for those technologies. Operator 4.0 is also known as a smart operator, and it defines this as "a smart and skilled operator who performs not only 'cooperative work' with robots, but also 'work aided' by machines and if needs employing of human cyber-physical systems, advanced human-machine interaction technologies, and adaptive automation towards human-automation symbiosis work systems" [11,25,26]. In order to achieve the concept of Operator 4.0, which represents the future of workplaces, a set of skills is needed to integrate the workforce into I4.0. This integration can be called human-cyber-physical systems (H-CPS). Those systems are created to enhance the human-machine relationship [27].

Operator 4.0 knowledge transfer methodologies are aimed to create an environment to reach the concept (CPS) to improve the abilities of the workforce by allocation of tasks to machines and operators overseeing the ructions to the machine, which can be programmed into a machine, as an aid to handle uncertain events [11,28]. That can sum up the abilities of the human and machine in optimised manufacturing. To infer the cognitive states and emotions associated with the decision-making and operator behavior, the Operator 4.0 concept requires precise chronological time-harmonisation of the operator actions, sensory data and psychophysiological signals [29]. Moreover, the study aims to upskill and

train the existing labour to be able to use the Industry 4.0 technologies in an innovative way. In the future, the number and composition of employees will also transform [30,31].

The most visible consequences of the use of new technologies can most likely be expected in industrial employment. On the one hand, the increase in automation, digitalisation and robotisation will reduce the demand for living labour in industrial production; thus, a smaller number of people will work in the manufacturing industry. On the other hand, thanks to new technologies, the quality of the workforce is also changing. Among the few industrial employees, there will be fewer low-skilled, physically employed and more qualified, intellectually skilled employees. According to a survey conducted in 37 countries, as the use of industrial robots increases, the proportion of people doing routine work among the employees, who are usually less educated, decreases [32]. Some 80 million low-skilled workers in the EU could lose their jobs as a result of automation and robotisation, while in the US, it is estimated that 47% of jobs could disappear [33,34]. Not only are old jobs and occupations transformed or eliminated, but new ones (e.g., data scientists) appear. Some of the new jobs will have different requirements on the workforce than the current ones. That is why new or different knowledge, abilities and skills will be needed more than before, and this will also place a heavy burden on education at all levels. It is likely that there will be high demand in the labour market for those who have adequate competencies in software development and information technology, as well as in info-communications, because the use of software, connectivity and analysis will increase [35]. In addition, many other skills and capabilities (e.g., flexibility, creativity, problem solving, decision-making, etc.) are needed to meet the labour market challenges of the coming decades. This also shakes the world of work to its foundations and may lead to serious problems [36]. Consequently, it is very important to identify the new skills and competencies, which can be relevant in the future. That is the research gap that this study intends to fill by replying to the following study questions:

RQ1: What are the top-cited articles concerning Industry 4.0 jobs related to needed skills and competencies?

RQ2: What are the trends of required skills and competencies in Industry 4.0 jobs among the different sectors of the economy according to the top-cited articles in relation to the topic?

RQ3: What is the level of awareness about Industry 4.0 emerging technologies among the employees of mostly multinational companies in Hungary?

The replies to these questions contribute to set up a new model for Industry 4.0 skills and competencies, and this can be considered the main novelty of the study. The empirical research is significant because it makes an attempt from a practical viewpoint to reveal the level of current awareness of skills and competencies related to Industry 4.0 technologies.

The study has five major parts. After the "Introduction", the "Materials and Methods" are presented with particular regard to the major steps of the research process. Section 3 demonstrates the results of the bibliometric analysis, which describes the database of the study and the results of the survey concerning the level of skills and the awareness level concerning Industry 4.0 technologies and needed competencies. Section 4 is the discussion of the results, and, finally, the conclusions follow.

#### **2. Materials and Methods**

#### *2.1. The Process of the Research*

Reaching the study aim requires going through study goals. Thus, reaching the best profile fit for the human workforce to meet the requirement of Industry 4.0 needs to explore the most related scientific studies on the given topic. Therefore, a hybrid method of a bibliometric analysis on the Scopus database and systematic literature review (SLR) was applied on the most cited articles. After reaching the results of the conducted search, a survey was carried out mostly among employees of multinational organisations in Hungary to reveal the awareness level concerning Industry 4.0 technologies and the new required skills. The major phases of the research work were the following:

The first step was to formulate the study questions, which allowed us to screen the data sets and include and/or exclude the desired documents.

The second step was data collection. Study data were collected from the Scopus database using the following query in the advanced search: TITLE-ABS-KEY (("human factor") OR ("operator") OR ("smart operator") OR ("workforce") OR (operator 4.0)) AND (("Industry 4.0") OR ("4th industrial revolution") OR ("smart factories") AND ("training") OR ("education")) AND (("skill\*") OR ("Competenc\*")) AND (EXCLUDE(PUBYEAR,2022)) AND (LIMIT-TO(LANGUAGE, "English") OR LIMIT-TO (LANGUAGE, "German")) to create illustrative maps. Then, other searches were also conducted to reveal data more related to the topic to avoid excluding important research from the discussion and conclusion. Those search queries were made concerning the job advertisements of Industry 4.0-related technologies. Also, a search query took place in the normal search instead of the advanced to compare the results with the study search. The last search was made to ensure the information novelty. Only one study was found in a peer reviewed journal which adopted a similar concept and method in terms of Industry 4.0 skills and competencies as well as using a bibliometric review. That research, however, used a different software together with different inclusion and exclusion approaches.

The third step was to apply the above-mentioned search query in the Scopus database and download the data sets for further analysis.

As a fourth step, exclusion and inclusion criteria were defined. Exclusion criteria were: (1) not English and/or German; (2) not related to Industry 4.0 related skills and competencies; (3) articles related to chemistry, biology, hydrology, medical and psychology aspects; (4) no full text available. Inclusion criteria were the following:

It is also necessary to note that the information for the documents that meet the requirements were the year of publication, language, journal, title, author, affiliation, keywords, document type, abstract and counts of citation which were exported into (CSV) format for the Scopus data set (This data set is compatible with VOS-viewer software.).

The fifth step was reporting the results using descriptive analysis. The software VOS viewer and Excel was used for bibliometric analysis.

As a sixth step, a small survey was carried out in 2022 among expats working in national and multinational organisations in Hungary to reveal the level of awareness concerning Industry 4.0 requirements for the new labor market using Google forms and Microsoft excel. Testing the awareness level in practice is also a new kind of approach in this topic.

The time span of the search was 2015–2021. The search was conducted from the middle of January with continuous updates until the beginning of April 2022.

#### *2.2. Justification for the Methodology Used*

VOS viewer (version 1.6.18) was used to analyse the co-authorship, co-occurrence, citation, bibliographic coupling, co-citation and themes. The research questions have been set up to make a bibliometric investigation of the needed skills and competencies in the Industry 4.0 paradigm. Using these methods and software such as VOS viewer helps to explore the relationships through visualising and mapping that can help in reaching the answers to the study questions in a logical way [13,19]. VOS viewer and equivalent software can supply a clustering mapping that can be a powerful tool for reaching the most important studies by knowing the citation strength, which explains the document's importance. Why have the top cited articles been used for the analysis? Studies have proved that concrete answers are more likely to be found in the top cited articles [37,38]. The stronger the citation position is the more valuable information the document holds in regard to the chosen topic.

The study objective is to find the most related set of skills and competencies that must exist in the workforce of the existing generation to cope with Industry 4.0. For those reasons, many keywords concerning the topic have been reviewed to reach the most related keywords. The explanation for choosing them is that the concept of Industry 4.0 is known in a decent number of studies as the Fourth Industrial Revolution. The other variable of the study is the human factor, which is known in most of the studies as the Operator or Operator 4.0. Sustainability was chosen as a keyword combined with the rest of the keywords because the studies which are concerned with the replacement of humans by machines (human-centered studies) have the keywords of training and education. The last variable is the skills and competencies combined. The reason for choosing, for example (Competenc\*) is to relate all the studies that have competence or competencies all at once. Those areas of research will help in revealing the most related skills and competencies that are needed for Operator 4.0 in the era of Industry 4.0 [39]. They will form the skills and competencies model of the study.

#### **3. Results**

#### *3.1. Bibliometric Analysis Results*

In this section, first, the results will refer to the first RQ1. Running the search on the Scopus database, 588 documents were found, covering the years of 2015–2021 in all the fields, except for those mentioned in the exclusion criteria. Then, their number was decreased to 266 using the condition of exclusion (three citations at least per document). Dates of the search were in January 2022.

After that, using VOS viewer software, the citation analysis of the documents was conducted to determine the top cited articles in the given topic and to create a map depicting how much they are connected by the citation links of the documents and authors. Then, the articles were examined to help to create an image of what are the most suitable skills that can be built through training to reach the efficiency of the competencies in the workplace to cooperate with Industry 4.0. The final result of the top 20 cited articles in concern of Industry 4.0 skills and competencies is given in Table 1.

Source: based on Scopus database edited by authors.

According to the Scopus database, the most cited article had 378 citations, while the least cited one had only 44. However, the article published in the journal International Journal of Information Management with the highest impact factor had only 68 citations. At the same time, the second most cited article had the lowest IF. Thus, it seems that there is no close correlation between the number of citations and the value of impact factor. Figure 1 of the database shows the connectivity among the documents using the document citations as the unit of analysis because the software has excluded some documents and shows only the connected ones. Bigger dots or circles represent more cited documents (Figure 1).

The following results refer to RQ2: What are the required trends of the skills and competencies concerning Industry 4.0 that can fit different professions among the different economic sectors?

VOS viewer was used for mapping the data extracted from Scopus and the top twenty cited articles to help to create the most adaptable skills and competency attributes model. A competency model is a descriptive tool that identifies what are the required competencies to perform a job effectively [1,8,9,37,43,49–54]. Therefore, these four sets of competencies are the most used and accepted in the related studies of the study database (Table 2).

According to the Scopus database, the most cited article had 378 citations, while the least cited one had only 44. However, the article published in the journal International Journal of Information Management with the highest impact factor had only 68 citations. At the same time, the second most cited article had the lowest IF. Thus, it seems that there is no close correlation between the number of citations and the value of impact factor. Figure 1 of the database shows the connectivity among the documents using the document citations as the unit of analysis because the software has excluded some documents and shows only the connected ones. Bigger dots or circles represent more cited documents

**Figure 1.** The most connected documents of the database by citations. Source: based on Scopus database edited by authors. **Figure 1.** The most connected documents of the database by citations. Source: based on Scopus database edited by authors.

(Figure 1).

Source: based on Scopus database edited by authors.

Personal learn, ability to work under pressure, sustainable mindset) Social/Inter-personal (Intercultural skills, language skills, communication skills, networking skills, teamwork, ability to transfer knowledge, The competencies mentioned in Table 2 are required by many companies for the new jobs, which are related to Industry 4.0, for example, supply chain analyst, supply chain engineer, CPS and IoT for a robotised production engineer. More results on the new jobs which have been created by Industry 4.0 can be found in only four studies [37,58–60]. The bibliometric analysis has revealed the top twenty countries in this field of the research using citation as the basis of comparison. It is presumable that the majority of these countries are advanced in the application of Industry 4.0 technologies and/or in their research (Table 3).

(Flexibility, ambiguity tolerance, motivation to

leadership skills)

[1,8,52,54,55]

[1,8,51,54,55]

**Table 3.** Top twenty contributed countries in the given field.

Source: based on Scopus database edited by authors.

Most of the publications were published in Italy, the US and Germany, and the number of citations was also the highest in these countries. The total link strength means the connection between one document and another by a different author/s in Industry 4.0 topic. The stronger it is, the more citations it has from more than three authors in more than three documents.

A special spatial pattern of countries can be created by the database using the citation links between the documents as the unit of the analysis as well as the authorship analysis concerning Industry 4.0 skills and competencies (Figure 2). *Sci* **2022**, *4*, x FOR PEER REVIEW 9 of 17

**Figure 2.** The most connected countries of the database by citations. Source: based on Scopus database edited by authors. The most important keywords which were mentioned in each document at least 3 **Figure 3.** Database by keywords. Source: based on Scopus database edited by authors. **Figure 2.** The most connected countries of the database by citations. Source: based on Scopus database edited by authors.

times and the connectivity among them also have a special pattern (Figures 3 and 4).

base edited by authors.

*Sci* **2022**, *4*, x FOR PEER REVIEW 9 of 17

The most important keywords which were mentioned in each document at least 3 times and the connectivity among them also have a special pattern (Figures 3 and 4). The most important keywords which were mentioned in each document at least 3 times and the connectivity among them also have a special pattern (Figures 3 and 4).

**Figure 2.** The most connected countries of the database by citations. Source: based on Scopus data-

**Figure 3.** Database by keywords. Source: based on Scopus database edited by authors. **Figure 3.** Database by keywords. Source: based on Scopus database edited by authors.

**Figure 4.** Database by keywords and the connectivity among them. Source: based on Scopus database edited by authors. **Figure 4.** Database by keywords and the connectivity among them. Source: based on Scopus database edited by authors.

All keywords are connected to a big dot, which is Industry 4.0. This is probably because of the popularity of the word itself. Augmented reality is the other, most common All keywords are connected to a big dot, which is Industry 4.0. This is probably because of the popularity of the word itself. Augmented reality is the other, most common

*3.2. Industry 4.0 Awareness and Its Impacts on the Labor Force Based on a Survey*

The major characteristics of the respondents are the followings:

− Age: 75%, 25–34 years old; 20%, 35–44 years old; 5%, 45 years and older. − Education level: 50%, postgraduate; 35%, graduate; 15%, non-graduate

keyword, which takes the second place in the intensity of connections and the third is the Operator 4.0, and the reason for this is that most of the studies were related to skills and

To answer RQ3 (What is the level of awareness about Industry 4.0 emerging technologies?), a survey was conducted in March 2022 among expatriates working primarily at multinational organisations in Hungary. The survey was shared using Google forms, which is a popular method as it makes it possible to create and share the questionnaire as

The questionnaire consists of four major parts: respondents' personal data, Industry 4.0 concept, impacts of Industry 4.0 and skills and competencies. The survey had open and close questions and Likert scale questions to reveal the awareness level and the skills and competencies level among the sample. Also, the sample was asked about the relation-

Only twenty expatriates took part in the survey. Their number or this sample is too small to generalise any of the results, but they are sufficient to indicate the level of awareness concerning I4.0. The participants of the study were selected because they were occupying positions related to I4.0 technologies in different sectors of the economy, and the reason that the employees of multinational companies were asked is that those companies attract talent from all countries. They are also known for their innovation, research and development, which makes them the best place for such technologies and have already

ship between technology and the COVID-19 crisis.

started using these new technologies.

− Gender: 25% female, 75% male.

competencies.

the study requires.

keyword, which takes the second place in the intensity of connections and the third is the Operator 4.0, and the reason for this is that most of the studies were related to skills and competencies.

#### *3.2. Industry 4.0 Awareness and Its Impacts on the Labor Force Based on a Survey*

To answer RQ3 (What is the level of awareness about Industry 4.0 emerging technologies?), a survey was conducted in March 2022 among expatriates working primarily at multinational organisations in Hungary. The survey was shared using Google forms, which is a popular method as it makes it possible to create and share the questionnaire as the study requires.

The questionnaire consists of four major parts: respondents' personal data, Industry 4.0 concept, impacts of Industry 4.0 and skills and competencies. The survey had open and close questions and Likert scale questions to reveal the awareness level and the skills and competencies level among the sample. Also, the sample was asked about the relationship between technology and the COVID-19 crisis.

Only twenty expatriates took part in the survey. Their number or this sample is too small to generalise any of the results, but they are sufficient to indicate the level of awareness concerning I4.0. The participants of the study were selected because they were occupying positions related to I4.0 technologies in different sectors of the economy, and the reason that the employees of multinational companies were asked is that those companies attract talent from all countries. They are also known for their innovation, research and development, which makes them the best place for such technologies and have already started using these new technologies.

The major characteristics of the respondents are the followings:

Responses to the different questions are the following:

"I work in a multinational company in technology business as a Service Desk Analyst, some parts of the system are already automated, I can imagine that my work will be less and less important". This reply also calls attention to the fact that in the future, not only will new skills and competences be required, but several jobs may also disappear. At the same time, new jobs, although in smaller numbers, will also emerge [34]. Some employees may also not be able to work because they cannot meet the requirements or because there will not be enough jobs as machines take over more work.

#### **4. Discussion**

This study has made an attempt to determine what kind of new skills and competencies will be required by Industry 4.0. Based on the bibliometric analysis and the questionnaire survey, it has become obvious from theoretical and practical viewpoints that the labour force has to be trained in order to be able to use the new technologies. For that reason, previous studies have focused on putting humans at the center of Industry 4.0 [9].

There is no doubt that having humans at its center is the key to the success of Industry 4.0. Thus, Operator 4.0 has a minimum requirement of the skills that those studies discussed [8,9,11,13,24,25,49,60–62], and they all agreed on a similar model described clearly in [9], which divided the skills into four main categories. They are the following:

Different studies have discussed more than the four categories of skills considering scenario-based learning (SBL), Education 4.0 and vocational training [1,52,63]. In connection with these, the main question is: Which of them is believed to be the most suitable way of training the new workforce to meet the requirements of the labour market? Another study besides the ones which used the text mining techniques [37,43] compared most of the models resulting in "Five dimensions of worker readiness competencies model" [8] discussing most of the studies which have proposed other models of competencies to meet the requirements of Industry 4.0 [1,8,9,37,43,49–54], and all those studies agreed on the model used in this study. At the same time, other studies' models have focused on the skills needed to enhance the machine-human relationship [46]. The need for new behaviours in the machine-human relationship is important, and at the same time, the trust in the machine, the system and their connectivity can be challenging for the communication infrastructure in the era of cybersecurity.

Finally, we also have to mention that many studies highlighted how important it is to have the skill of decision-making as it appears in most of the studies as a soft skill, while other studies find it more related to AI systems. The question remains on what is the most important skill to have: programming or decision-making. As this study can conclude that both are indeed needed, decision-making can be more accurate and effective with the use of machine learning (ML) as one of the AI applications, as well as the use of the ML, which needs the ability to work with the cloud systems and big data that both require programming languages. This study has not mentioned anything related to programming so far; the needed programming languages for use in I4.0 applications, based on a study made on the LinkedIn database, were C, C++, assembly and JavaScript [37,64]. The results of the survey also highlighted the importance of using programming and coding skills in the age of Industry 4.0.

Parallel to the spread of Industry 4.0 technologies, a marked transformation will occur in all areas of life. New technologies first appeared in the manufacturing industry and continue to spread throughout the economy and society as a whole. The use of new machines and IT tools will require many new skills and competencies. This will most likely be a challenge for the workforce. Those who will have these new skills and competencies, which the study also revealed, will be in a more advantageous position in the labour market. There may be more to these in the future, as Industry 4.0 is constantly developing and making demands on the workforce. However, it is not only the workers and subordinates who have to constantly adapt to the new expectations through the development of their various skills and knowledge, but also the managers of the enterprises. In the age of the Fourth Industrial Revolution, a particularly large responsibility falls on managers, who are responsible not only for the training of the workers, but also for the development of their own expertise and skills. A great variety of knowledge, skills, abilities and competencies are necessary for them in order to be successful and for their business to function effectively. It is likely that, thanks to new technologies, certain skills (e.g., digital skills, communication skills, quick adaptation, system-level thinking, problem solving) will become more valuable, the absence or modest level of which may have unfavourable consequences for the development and future of the enterprise.

The empirical research also confirmed that the new skills and competencies will not be needed to the same extent in different sectors of the economy. Those interviewed considered technical and methodological skills to be the most important. The COVID-19 epidemic probably also contributed to the former, because the use of ICT increased, which required the development of technical skills. In the following years, in line with new technologies and the transformation of education, not only the number of the workforce, but also its quality (training, skills, competences, knowledge, etc.), will change. The labour market, the operation of enterprises and the management of human resources, as well as the economy as a whole, are being transformed.

The result of the study was narrow because of the inclusion criteria of the research, which resulted in excluding many of the most important documents on the topic of Industry 4.0. These articles were mostly in German and discussed the technologies rather than the skills and competencies. Examining [9] in relation to the most crucial citations for the definitions of Industry 4.0 as well as [14], which led this study to elaborate the definitions of Industry 4.0, another finding is that the citation score could be related to the name of the author and the connections between the authors rather than the in-depth information of the document. A further result is that most of the highly cited documents are not necessarily in high impact factor journals. It is probably because non-IF journals are used in a larger circle than the journals with impact factor.

The theory of the study that claims the COVID-19 crisis accelerated and increased the dependency on IT-related systems and Industry 4.0 emerging technologies is supported by the fact this crisis has opened our eyes to the ability of those technologies as crisis response and contingency plans as those studies have discussed before [65]. However, the remaining important issues and questions are related to the education of the coming generation: Is Education 4.0 in developed countries enough? Will the Operator 4.0 be able to control Industry 4.0 technologies according to the risk assessment of volatility, uncertainty, complexity and ambiguity? Answering the questions and applying Industry 4.0 necessitates the development of education and training. In the era of the Fourth Industrial Revolution, a significant transformation of the structure of education will be necessary at all levels (e.g., new subjects must be introduced, new methods must be used, the role of the teacher will change). This is a huge challenge for the current education system everywhere because

it is necessary to provide trainings that provides marketable and competitive knowledge and professions, while it is impossible to know exactly what occupations there will be and what knowledge, skills and competencies will be required in the next years and decades.

#### **5. Conclusions**

Since the First Industrial Revolution, the labour force has had to adjust to the requirements of the labor market. In each industrial revolution, a new set of skills and competencies had to be developed. Since the Fourth Industrial Revolution has already begun, it is important to explore what the new expectations of the labour market are and what new human resource capabilities are necessary for the workforce to meet them. Based on bibliometric analysis and systematic literature review, this study determined the most related articles concerning skills, competencies, and Industry 4.0, and identified the new set of skills and competencies which are important for the future labour force. It has also evaluated several skill and competency models referring to the top-cited articles in the topic and more models referring to more recent articles published in 2020 that did not have enough time to reach a high citation score.

According to the models which have focused on interpersonal and technological skills, the most important skills and competencies are interpersonal skills, as many studies have confirmed that these are necessary in the workforce on all levels [23,31,38]. Interpersonal skills are important because they are the crucial area where human can surpass the machine. This study also focuses on the innovation competencies. These kinds of competencies can enhance the ability of the human to use the machine relationship to create and invent using the AI and ML at the maximum application, which will make a place for the human workforce in the workplace [62].

Fewer studies have focused on the technical and domain skills, which are more important in regard to the programming language, which is the way to communicate with the computer. It is presumable that in the upcoming ten years, these competencies will be categorized as communication skills and considered as a language, not a technical skill. Moreover, interpersonal skills and programming competencies will be necessary in all job profiles in the future, and the technical and domain skills to be developed based on the job profile. The question here is: What are the most important interpersonal skills? It can be found in the model of [52,66,67]. The experiences of the survey also confirmed that technical and methodological skills are the most important, the significance of which will probably continue to increase in parallel with the spread of Industry 4.0. For the latter, however, significant infrastructural, especially info-communication technology, developments are also necessary. In the future, what we cannot ignore is that the real application of this industry on all levels would need the glue of communication, which cannot be provided without the fifth generation of communication. Although humans will play the key role in the success of this transition, ensuring the material availability that helps in producing, for example, the chipsets of the computers theyalso have to face several other challenges (e.g., shortage of energy and water, climate change, different epidemics, economic crisis, digitalised world), the effects of which affect all fields of life and people's skills and competencies to varying degrees, encouraging them to continuously develop and adapt. In order for humans to cope with and adjust to them, it is extremely important to see clearly what kind of new skills and competencies will be important in the future, and this study has made an attempt at this.

The results of this research, on the one hand, draw attention to the new skills and competencies, which should be emphasized more at different levels of education. On the other hand, they can contribute to the development of human resources of enterprises and the elaboration of new training programs of educational institutions. Based on the lessons learned from the research, the study recommends that more attention be paid to the development of analytical skills in education and vocational training, which may be important in the adaptation of Industry 4.0, as well as to the teaching of subjects related to information and communication technologies.

There are several options for continuing the research. One of these could be to use another database (e.g., WOS) and make a comparison to confirm and refine the current results. Another possibility to continue the research is to widen the scope of the participants in the survey and to examine how much the various sectors and enterprises of the economy are prepared for the new challenges posed by Industry 4.0 technologies to the skills and competencies of the workforce. These studies can also contribute to defining the necessary structural changes in the economy, labour market and education in the age of the Fourth Industrial Revolution.

**Author Contributions:** Conceptualization: A.A. and E.K.; making bibliometric analysis and survey: A.A.; writing original draft: A.A.; rewriting, reviewing and editing: E.K.; supervising and project administration: E.K. editing figures and tables: A.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the National Research, Development and Innovation Office (project number K125 091).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The questionnaire and replies are available for request.

**Acknowledgments:** The authors of the study would like to thank the three anonymous reviewers and editors for their valuable comments and suggestions, which contributed to the final form of the study.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**