**7. Conclusions**

Worldwide, NAFLD and NASH as well as NAFLD-related diseases (OSAS, PCOS, non-obese NAFLD), have emerged as leading causes of chronic liver disease in the last decades. The pathogenesis of respective diseases is complex and influenced by genetic factors, patients' characteristics, and a variety of risk factors. Although the factors and involved pathways triggering initiating and progression of NAFLD and NASH are reasonably well known, there is an urgent clinical need to establish reliable, noninvasive biomarkers, tests or algorithms that avoid the need of liver biopsy and allow to differentiate between disease stages. During the last decades, a great variety of multiparametric panels and parameter combinations (NFLS, HIS, FLI, LAP index, FLIP, CHeK, NFS, APRI, BARD, ELF, Hepascore) taking into account serum markers (e.g., ALT, AST, bilirubin, Hb1Ac, HDL, α2M, platelet counts), patient characteristics (sex, gender, BMI), or comorbidities (diabetes) were established. However, all these diagnostic panels have limitations and alone are not suitable to replace liver biopsy. Nowadays, high-resolution imaging modalities such as ultrasound, MRI, elastography, and CAP have been established. Several of these techniques, such as MRI-PDFF, which can specifically detect the presence of hepatic steatosis and assess liver fat over the entire liver, might be useful to substitute biopsies and greatly assist the objective follow-up of therapeutic trials. Finally, liver-derived exosomes released into the systemic circulation and toxic lipids are in focus as targets for biomarkers development in liquid liver biopsies.

**Author Contributions:** Conceptualization, H.K.D. and R.W.; writing—original draft preparation, H.K.D. and R.W.; writing—review and editing, H.K.D., R.W. and S.W.; visualization, S.W.; funding acquisition, R.W.

**Funding:** This research was funded by the German Research Foundation (SFB/TRR57).

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

### **References**

© 2019 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 (http://creativecommons.org/licenses/by/4.0/).


*2.5.1 Aging mechanism of natural rubber*

The aging process is: under the action of ultraviolet rays, the oxidation reaction of natural rubber starts from α-H, first is attacked by oxygen to generate hydroperoxide, and then further reacts to generate aldehydes and ketones, and at the same time the main chain is broken [50, 51]. The free radicals generated by chain scission may combine with double-free radicals, or they may be further attacked by oxygen to continue oxidation; in this process, double bonds addition reaction occurs, and the attack of free radicals on double bonds reduces the content of olefinic hydrogen. The early stage of the reaction is dominated by oxidative degradation, which is manifested as the surface of the aged sample is sticky, and cross-linking occurs in the later stage, the surface of the sample is dried and hardened, and cracks appear.

Ling Ding et al. [52]'s 1H-NMR and FT-IR absorption spectroscopy experimental results proved that the products obtained in the aging process of natural rubber in artificial ultraviolet light aging and natural aging are roughly the same. They found that natural rubber has poor resistance to ultraviolet light aging, and its molecular structure changes significantly when exposed to ultraviolet light for 2 h. Under

natural aging conditions, the structure of natural rubber changes significantly after 30 days. Artificial UV aging for 7 days is equivalent to the effect of natural aging for 3 months.


*2.7. DLS Characterization of Retentate*

Liquid phase was monitored by the dynamic light scattering technique. DLS experiments were performed at 25 ◦C with Malvern Nano ZS instrument (λ = 633 nm, operating power 4 mW) at θ = 173◦. Gypsum was always taken as a light scattering material even for the pure PAA-F1 solutions.


**Accurate Deep Model for Electricity Consumption Forecasting Using Multi-Channel and Multi-Scale Feature Fusion CNN–LSTM**

### **Xiaorui Shao, Chang-Soo Kim \* and Palash Sontakke**

Department of Information Systems, Pukyong National University, Busan 608737, Korea<EMAIL_ADDRESS>(X.S<EMAIL_ADDRESS>(P.S.)

**\*** Correspondence<EMAIL_ADDRESS>
Received: 13 March 2020; Accepted: 10 April 2020; Published: 12 April 2020

**Abstract:** Electricity consumption forecasting is a vital task for smart grid building regarding the supply and demand of electric power. Many pieces of research focused on the factors of weather, holidays, and temperatures for electricity forecasting that requires to collect those data by using kinds of sensors, which raises the cost of time and resources. Besides, most of the existing methods only focused on one or two types of forecasts, which cannot satisfy the actual needs of decision-making. This paper proposes a novel hybrid deep model for multiple forecasts by combining Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) algorithm without additional sensor data, and also considers the corresponding statistics. Di fferent from the conventional stacked CNN–LSTM, in the proposed hybrid model, CNN and LSTM extracted features in parallel, which can obtain more robust features with less loss of original information. Chiefly, CNN extracts multi-scale robust features by various filters at three levels and wide convolution technology. LSTM extracts the features which think about the impact of di fferent time-steps. The features extracted by CNN and LSTM are combined with six statistical components as comprehensive features. Therefore, comprehensive features are the fusion of multi-scale, multi-domain (time and statistic domain) and robust due to the utilization of wide convolution technology. We validate the e ffectiveness of the proposed method on three natural subsets associated with electricity consumption. The comparative study shows the state-of-the-art performance of the proposed hybrid deep model with good robustness for very short-term, short-term, medium-term, and long-term electricity consumption forecasting.

**Keywords:** smart grid; electricity forecasting; CNN–LSTM; very short-term forecasting (VSTF); short-term forecasting (STF); medium-term forecasting (MTF); long-term forecasting (LTF)


*2.3. Tensile Test*

Tensile tests of the starting materials and the drawn tubes were performed using a universal testing machine (Autograph AG 25 TB, Shimadzu Co., Kyoto, Japan), as shown in Figure 2. Tensile tests were performed to evaluate the followings: (1) the stress-strain curves of the starting materials and the drawn tubes, (2) the Lankford value of the starting materials at a maximum stroke, and (3) the unloading behavior of the drawn tube after reaching a drawing tension.

*ε σ*

{ ൫ ൗ ൯ା ቀ ൗ ቁ} ൫ tensileൗ ൯

*β*

**Figure 2.** Schematic illustration of the method of tensile test used in this study.

The tube was grasped using a 5 kN grips set for fine wire (343-07529-01, Shimadzu Co., Kyoto, Japan). The distance between the chuck C and D was 100 mm before the test. The test speed was 5.0 mm/s. The test load was measured with a 5 kN load cell (SLBL-5kN, Shimadzu Co., Kyoto, Japan) affixed to the cross-head. The tensile test ended at a fracture point to obtain the stress-strain curves of the starting materials and the drawn tubes. The tensile tests of each material were conducted in triplicate. The nominal stress *s* was calculated by dividing the load by the initial cross-sectional area of the tube. The nominal strain *e* was calculated by dividing the stroke by the initial chuck distance. The true strain εtrue was calculated by converting the nominal strain to ln(*e* + 1). The true stress σtrue was calculated by converting the nominal stress to *s*(*e* + 1).

The Lankford value during each maximum stroke was evaluated by conducting tensile tests at maximum strokes of 10, 20, 30, 40, and 50 mm. The Lankford value *r* was calculated using Equation (2). The average values were calculated, and the standard deviations were obtained.

$$\tau = \frac{\{\ln(D\_{\text{busike}}/D\_0) + \ln(d\_{\text{busike}}/d\_0)\}/2}{\ln(t\_{\text{busike}}/t\_0)}\tag{2}$$

The parameters *D*tensile and *d*tensile are the outer diameter and inner diameter at each maximum stroke, respectively, as shown in Figure 3a. The method of measuring *D*tensile and *d*tensile is described in Section 2.4.

The loading-unloading tensile test was conducted to evaluate specimen unloading behavior. The drawn copper tube was loaded until reaching a load that corresponded to the drawing tension at a die reduction *R*e of 0.17 and drawing speed ratio β of 1.10. The cross-head was moved until the load reached 2 N during unloading. The test speed during loading and unloading was 1.0 mm/s. An equivalent strain was obtained by evaluating the change in chuck distance during loading and unloading using a digital image correlate (DIC) software GOM CorrelateTM (2019, Gesellschaft für Optische Messtechnik GmbH, Braunschweig, Germany).

− π −

**Figure 3.** Measurement method of sample dimensions. (**a**) Dimension definition of the tube before and after the tensile test and (**b**) ellipse approximation of the outer circumference pixel.

Tensile test of the copper tube was also conducted using the draw-bench machine without the die to investigate the load measurement accuracy of the load cell affixed to the chuck of the draw-bench machine. The copper tube was chucked without setting the die. The initial chuck distance was 465 mm. The tube was stretched by moving the two chucks. The moving speeds of the chuck A and B were 3.3 mm/s and 5.0 mm/s, respectively. The stroke was calculated as the difference in the distance between the two chucks. The nominal stress was calculated by dividing the load by the initial cross-sectional area of the tube. The nominal strain was calculated by dividing the stroke by the initial chuck distance.


*Article* **Short-Term Load Forecasting Model of Electric Vehicle Charging Load Based on MCCNN-TCN**

**Jiaan Zhang 1 , Chenyu Liu 2,\* and Leijiao Ge 3,\***

**Abstract:** The large fluctuations in charging loads of electric vehicles (EVs) make short-term forecasting challenging. In order to improve the short-term load forecasting performance of EV charging load, a corresponding model-based multi-channel convolutional neural network and temporal convolutional network (MCCNN-TCN) are proposed. The multi-channel convolutional neural network (MCCNN) can extract the fluctuation characteristics of EV charging load at various time scales, while the temporal convolutional network (TCN) can build a time-series dependence between the fluctuation characteristics and the forecasted load. In addition, an additional BP network maps the selected meteorological and date features into a high-dimensional feature vector, which is spliced with the output of the TCN. According to experimental results employing urban charging station load data from a city in northern China, the proposed model is more accurate than artificial neural network (ANN), long short-term memory (LSTM), convolutional neural networks and long shortterm memory (CNN-LSTM), and TCN models. The MCCNN-TCN model outperforms the ANN, LSTM, CNN-LSTM, and TCN by 14.09%, 25.13%, 27.32%, and 4.48%, respectively, in terms of the mean absolute percentage error.

**Keywords:** electric vehicle; short-term load forecasting; convolutional neural network; temporal convolutional network; climate factors; correlation analysis


*Proceedings* **The Importance of Corporate Social Responsibility among Students in EUROPE** †

## **Mihaela Bucur**

Department of Industrial Engineering and Management, "George Emil Palade" University of Medicine, Pharmacy, Science and Technology of Târgu Mure¸s, 540142 Târgu Mures, , Romania<EMAIL_ADDRESS>Tel.: +40-074-239-4396

† Earlier versions of this paper have been presented at the research workshops "Islamist Armed Conflicts and the Prospects for Conflict Resolution," 28–30 September 2018, Schwarzenberg, Switzerland, and "Sunni–Shia Relations in Europe: How to Study Them?", 13–14 December 2018, Turku, Finland.

Published: 26 January 2021

**Abstract:** This document addresses the issue of awareness and involvement in Corporate Social Responsibility (CSR) by students from all over Europe. The purpose of the document is to investigate the involvement and the knowledge of students in Social Responsibility and to obtain results that can confirm or invalidate the proposed hypotheses, presenting a real situation regarding their involvement. Social responsibility has a major impact on communities, and awareness of this concept is needed for involvement in CSR actions. The aim of the research is to study the knowledge and development of Corporate Social Responsibility (CSR) in Europe.

**Keywords:** CSR; students; initiatives; knowledge; CSR benefits

## **1. Introduction**

The concept of CSR has been debated in several contexts [1,2]. The following definitions are to be retained:

Most studies in this field have identified a relationship between CSR activities and the benefits to their organization [4,5]. Whether we are talking about reducing direct costs, increasing labor productivity, applying risk management, image enhancement, or improving environmental management [6], the importance and application of the concept of CSR in the strategy and activities of any type of organization are indisputable.

The quest of this subject in Romania started shyly but in the course of time attracted some followers. Lungu et al. (2009) [7] integrated the studies on social and environmental reporting in Europe and worldwide and the financial reporting experience in this area, ¸Sendroiu et al. referred to EMA principles in Romanian entities, Crisan-Mitra analyzes the context in which companies in Romania should use CSR practices [3]. There are also more concrete pieces of research regarding the involvement of CSR in the profession of accountants [6], Kork M. studies whether the concept of CSR is transposed from theory to practice [2,8] and even aspects related to public relations as a component of public [6].

The results of the Romanian research show that an integrated approach of corporate reports is needed as the CSR trends are set by the big companies. In this context, we believe that in order to change things for the better, little initiatives, organizational awareness, insistence from the stakeholders are needed. This study considers that it was an awareness first and then an empirical analysis, its results have a number of conclusions and recommendations about that society is becoming more involved in more branches and fields. In 2007, a survey was carried out by the Forum for International Communications through its CSR Romania program on a sample of 250 corporations active in the Romanian business environment [7], followed by research in the field of CSR communication, [8] conducted a survey between 2006 and 2008 focused on the evolution and the quality of the environmental reports from the Romanian companies listed on the Bucharest Stock Exchange. The research was resumed to cover 46 companies with an environmental impact.

Corporate Social Responsibility (CSR) is a useful tool for any organization that wants to be renowned. Even if it is not a mandatory mechanism, ignorance of this concept and its neglect may have effects on the image and implementation of future strategies of any type of organization. Through this article, the authors emphasize the Romanian context in which companies need to implement and develop CSR practices, with empirical qualitative research based on questionnaires. The research tool used is a questionnaire drafted by the authors and the respondents were the representatives of the most important companies in the technical and industrial field present at the face-to-face event with the employers organized by the Association of ESTIEM Mures and the Faculty of Engineering of "George Emil Palade" University of Medicine, Pharmacy, Science and Technology of Târgu Mure¸s, Romania. The ongoing research provides a detailed picture not only of the perception of CSR but also of the reasons that have led companies to invest in CSR.

## **2. Materials and Methods**

The parameters of the study consisted of:

The objectives of this study are closely related to the importance of the concept of CSR. Social responsibility has a major impact on communities, hence the awareness of the need to get involved in CSR actions. The aim of the research is to study the knowledge and development of Corporate Social Responsibility (CSR) in Europe. Among the objectives set by the research, we highlight four that are directly related to this paper: determining the level of knowledge on the concept of CSR, identifying ways to involve and organize CSR activities, implementation of CSR strategy, and implementation of CSR initiatives within organizations in the area of each respondent.

The questionnaire is based on the knowledge of the concept of Social Responsibility, which aims to identify the involvement of respondents in activities carried out by companies across Europe, the initiatives most often encountered in the communities they belong to, and the identification of reasons why participants were not involved in such activities. Depending on the purpose of the research and the literature, the structure of the CSR questionnaire was developed to verify the following hypotheses:

## **Hypothesis 1.** *People with university studies know the concept of CSR, they have contact with this concept through non-governmental organizations present in universities.*

Figure 1a,b refer to questions 3 and 4, show that 49 of the participants completing this questionnaire have university degrees, they are aware of the existence of this concept in a proportion of 62.7%. A fairly large number, 37.3%, are not familiar with this concept, which demonstrates that society needs to be more involved in such activities. Thus, Hypothesis 1 is confirmed.

**Figure 1.** (**a**) Level of education of respondents; (**b**) Did you hear about CSR?

**Hypothesis 2.** *The concept of CSR is often encountered in companies.*

Figure 2 is representative of question number 5, which refers to where this concept of CSR is often encountered. As we can see from the chart above, the participants in this study consider that this concept is often found in companies, in a percentage of over 50%, and less common in NGOs, a percentage of 20%. Hypothesis 2 is confirmed.

**Figure 2.** Where you can find this topic applied?

**Hypothesis 3.** *The field of involvement of companies in CSR projects is mainly for activities that cover initiatives towards the local community, environment, and business ethics.*

Figure 3 refers to question number 6, a question related to the initiatives that are most often applied/encountered in the country of which the respondents are part. The average of the answers is quite balanced, the first three positions being environmental protection, business ethics, and initiatives towards the local community. The hypothesis is confirmed.

**Figure 3.** Which of these initiatives are usually applied in your country?

**Hypothesis 4.** *Universities and organizations support the involvement of students in CSR programs; therefore they are familiar with the concept of CSR.*

Figure 4, refers to question number 8, a question related to the involvement and participation of respondents in CSR actions. It can be seen that a very large number of them did not participate in such activities at 71%. Only 29% were involved in CSR actions. The hypothesis is not confirmed.

**Figure 4.** Have you ever participated in social responsibility actions?

**Hypothesis 5.** *The reason for students' non-involvement is related to the fact that they were not given the opportunity to be part of such projects.*

Figure 5 shows the reasons why the participants were not part of CSR projects (question number 10). The most common reason is related to the fact that they were not offered this opportunity, which shows the lack of presentation and introduction of several CSR projects. The hypothesis is confirmed.

**Figure 5.** Specify your reasons for not being involved in CSR actions.

## **Hypothesis 6.** *Social responsibility is practiced following the emergence of legal provisions.*

A relevant question in this study is to find out the reason for the involvement of companies in such actions. Why do participants believe organizations participate in such actions? The results highlight an interesting situation, following the data in Figure 6—most respondents believe that this involvement is due to the company's need to protect its reputation, followed by the option legal provisions. These two reasons are followed to a lesser extent by reasons such as investor relations, pressure from NGOs. It can be seen that these implications are due to the desire to increase the image by remedying certain problems. Pressure from local communities, customers and suppliers ranks last in this survey. The hypothesis is confirmed.

**Figure 6.** Which are the main actions in case your organization is using CSR practices?

**Hypothesis 7.** *The type of program*/*cause supported by most companies should be related to the predominant problem in each country.*

One last question refers to a more sensitive point, the situations in which these projects offer a chance and hope to only certain categories of people (Figure 7). The chart above reflects the need to involve people in CSR projects, in situations where people suffer from certain incurable diseases, or in situations where people are victims of sexual exploitation, homeless people, and people subjected to domestic violence. The hypothesis is confirmed.

**Figure 7.** Which causes should be supported by companies from your country?

## **3. Conclusions**

Following the interpretation of the study, it can be seen that the field of corporate social responsibility in Europe is an area that is taking shape and is constantly evolving. The respondents included in the study have general/minimal knowledge and notions on what this field entails and are eager to be involved in CSR activities.

The study shows that society is becoming more and more involved in more branches and fields, which is a very positive thing, and we tend to believe in continuous growth in the coming years.

Respondents believe that lately, companies are trying to create and maintain a pleasant image among society through CSR actions. The main purpose of the private sector is to generate profit and value. Through such activities, the private sector contributes to economic growth and social development. In the long run, it is in the interest of both society and companies to have a private sector that works responsibly and develops products and services that help solve social and environmental problems. Practicing the concept of Social Responsibility brings added value to organizations due to the easier implementation of legal provisions and the betterment of the company's image in the community, NGOs, and other stakeholders.

**Funding:** This research was funded by the University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mures, Research Grant number 293/1/2020.

## **References**

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

© 2021 by the author. 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 (http://creativecommons.org/licenses/by/4.0/).


3.2.2. Structural Model

Drawing on earlier correlational results, the hypothesized mediation model including direct and indirect paths between two independent variables (risk perception of COVID-19 and meaning-based resources), three mediating variables (coping strategies), and the dependent variable (psychological well-being) was tested (Figure 1). Gender and age were also controlled in our structural analysis. In addition, each mediator was estimated independently, which generated more accurate mediating effects.

**Figure 1.** The theoretical model of the relations among risk perception of COVID-19, meaning-based resources, coping, and psychological well-being.

Structured equation modelling analysis revealed that model 1, which included three mediators and direct paths from risk perception of COVID-19 and meaning-based resources to psychological well-being had rather an unsatisfactory fit with the data: χ2 (20, *n* = 226) = 59.84, *p* < 0.001; GFI = 0.88; CFI = 0.83; NFI = 0.78; RMSEA = 0.09. Furthermore, some path coefficients were nonsignificant.

The model was thus modified to improve fit in accordance with the modification procedures (the order in which variables and paths were removed is included in a supplement). Emotion-focused coping and nonsignificant paths from risk perception of COVID-19 and meaning-based resources to psychological well-being were deleted. As a consequence, the final model turned out to have significant improvements and a satisfactory fit: χ2 (15, *n* = 226) = 38.36, *p* < 0.001; GFI = 0.95; CFI = 0.93; NFI = 0.92; RMSEA = 0.04 (model 2, Figure 2).

The final model contained one statistically significant direct effect (β = −0.43) from risk perception of COVID-19 to psychological well-being, which indicates that higher risk perception was related to a lower level of psychological well-being. In addition, problem-focused and meaning-focused coping accounted for indirect effects. Risk perception of COVID-19 had indirect relationships with psychological well-being through the two aforementioned coping strategies. The positive directions of those paths suggested that higher risk perception was related to more frequent use of problemand meaning-focused coping, which again was related to a higher level of psychological well-being. Analogously, there was an indirect relationship between meaning-based resources and psychological well-being through significant positive paths comprising problem-focused coping and meaning-focused coping. More meaning-based resources were associated with more frequent use of problem- and meaning-focused coping, which was then associated with greater psychological well-being.

**Figure 2.** The final mediating model of the relations among risk perception of COVID-19, meaning-based resources, coping, and psychological well-being (standardized coefficients). \*\* *p* < 0.01; \*\*\* *p* < 0.001.

The bootstrapping procedure was applied to examine the mediating effects of problem- and meaning-focused coping on the association between risk perception of COVID-19 and psychological well-being as well as the association between meaning-based resources and psychological well-being (samples = 5000; 95% bias-corrected confidence intervals [47]) (Table 4).

**Table 4.** Standardized indirect and total effects, standard errors (SE), and 95% confidence intervals (CI).

PWB—psychological well-being; a—empirical 95% confidence interval does not overlap with zero.

The results of mediation analysis revealed that problem- and meaning-focused coping mediated the relationship between risk perception of COVID-19 and psychological well-being as well as the relationship between meaning-based resources and psychological well-being. Interestingly, despite conceptual differences between risk perception and meaning-based resources, the mediating effects showed a similar pattern for both paths. Risk perception and meaning-based resources exerted significant indirect effects on the sphere of well-being via problem-focused and meaning-focused coping strategies. The total effects, which denote the sum of the direct and indirect effects, were significant for both paths, which implies therefore that problem-focused coping and meaning-focused coping function in the form of simultaneous mediators.

In addition, we decided to test whether those two indirect effects are significantly different (i.e., whether one or the other of the mediating effects is stronger). The result demonstrates that the mediation for the meaning-based resources–coping–psychological well-being path was significantly stronger than for the risk perception–coping–psychological well-being path (effect = 0.33; SE = 0.06; 95% CI = 0.05 to 0.41).

#### **4. Discussion**

The purpose of this study was to examine risk perception of COVID-19 infection and meaning-based resources in relation to coping strategies and psychological well-being amongst healthcare personnel in southern Poland during the COVID-19 outbreak between March and June 2020. We found that risk perception of COVID-19 infection—risk of contracting, fear, and perceived threat of COVID-19—negatively correlated with psychological well-being, whereas meaning-based resources (i.e., MIL and existential mattering) correlated positively with well-being. Moreover, both risk perception of COVID-19 infection and meaning-based resources were related to psychological well-being through the mediating effect of coping strategies.

As was hypothesized, risk perception, which reflects how healthcare personnel assess the probability of COVID-19 infection negatively correlated with psychological well-being. These findings are in line with previous studies that demonstrated perceived risk as a predictor of emotional distress amongst SARS survivors during the SARs epidemic in Hong Kong [10], as well as negative emotions amongst the Chinese population during the COVID-19 pandemic [49]. Our findings complement previous research in two important ways. First, both Cheng et al. [10] and Li et al. [49] studies were carried out amongst the Chinese general population, yet the health workers in Europe are exposed to a greater risk of infection, because of the rapid spread of COVID-19 and the sudden huge influx of patients. Second, SEM analysis revealed that the direct relationship between risk perception and healthcare personnel's well-being remained significant, even after controlling for the mediating effect of coping strategies. This implies the relatively strong character of the relationship between the way in which healthcare personnel interpret risk of contracting, fear, and perceived threat of COVID-19 infection and their psychological well-being.

In contrast, meaning-based resources positively correlated with psychological well-being. Thus, having more meaning-based resources was associated with higher well-being amongst healthcare personnel, which, in turn, can be used to deal with the negative psychological consequences of COVID-19. Healthcare workers who have a strong sense of purpose and value can more efficiently interpret and reorganize daily experiences, identify significant aspects of their life, and constructively pursue their aims. This finding corresponds with previous studies that indicated the predictive role of MIL on people's well-being [16–18] as well as the predictive role of MIL on the construction of individual identity amongst medical staff [19]. However, the direct relationship between meaning-based resources with psychological well-being was not obtained in the SEM analysis, after controlling for coping strategies. Given that SEM is considered to deliver more accurate results than correlations [50], these findings support an indirect rather than a direct relationship between meaning-based resources and well-being amongst healthcare personnel. Therefore, the availability of meaning-based resources can strengthen psychological well-being because they successfully trigger an effective use of coping strategies that can be applied to manage stress during the COVID-19 pandemic. The first hypothesis was only partially confirmed.

The main finding in this study was the mediating role played by coping strategies in the relationships between risk perception of the COVID-19 infection and meaning-based resources with healthcare personnel's psychological well-being. Two coping strategies—problem-focused and meaning-focused—were significant mediators in these relationships. The second and third hypotheses that assumed such relationships were thus confirmed. These results support previous studies that showed how coping strategies played a crucial role when people were facing an adverse situation [34,35,39,40]. They also suggest that perception and resource factors do not operate in "a vacuum" while influencing Polish healthcare personnel's psychological well-being; they are strongly interconnected with coping processes. It highlights the interplay of cognition (risk perception) and motivation (meaning-based resources) in managing stressful events and contributing to successful adaptation to stressors [51]. Problem-focused and meaning-focused coping is thus a dynamic process that varies according to one's cognitive appraisal and personal resources, and, consequently, regulates psychological well-being.

The present study builds on existing findings by revealing the cognitive and motivational mechanisms that underlie the effect of risk perception on psychological well-being in Polish healthcare personnel as they combat COVID-19. The two mediating strategies are predominately based on cognitive (problem-focused coping) and motivational (meaning-focused coping) processes. In contrast, emotional coping proved to be a less significant way of coping with stress during the pandemic. The utility of cognitive coping strategies in dealing with COVID-19 pandemic was confirmed by Gerhold's research [39], which showed that Germans tend to use problem-focused strategies in coping with COVID-19 (e.g., following expert advice and guidelines and thinking carefully about what to do). The current study extends Gerhold's [39] observations, by demonstrating that both problem-focused and meaning-focused coping operate simultaneously as mediators between risk perception and psychological well-being as well as between meaning-based resources and psychological well-being. There is, therefore, a noticeable interplay of cognitive and motivational processes underlying coping mechanisms in dealing with the dangers posed by COVID-19.

These findings suggest that although risk perception of the COVID-19 infection is related to lower psychological well-being, it paradoxically increases coping strategies, particularly problem-focused and meaning-focused coping (i.e., actions that help control the epidemics). In this sense, as noted by Li, Yang, Dou, Wang and colleagues [49], perceived severity can be regarded as a double-edged sword, being both risk and asset, in the encounter of pandemic.

These results can be interpreted within PMT, which posits that people confronted with threats resort to coping strategies that allow them to manage the threat. The decision to employ coping strategies is a consequence of severity, because people must believe that there is some potential harm (e.g., a high probability of infection with COVID-19 for healthcare personnel), and that they are vulnerable to this harm. The perception of threat from COVID-19 enhances the motivation to initiate the coping process [7]. The ability to adopt the recommended coping response may in turn enhance psychological well-being. This is in line with the meta-analysis of PMT findings by Milne et al. [52], which indicated that threat perception made it more likely that people would adopt some coping response because it provided motivational energy.

Our study shows that higher meaning-based resources predicted a more frequent use of problem-focused and meaning-focused coping, which was then related to a higher level of psychological well-being. Thus, personal resources that reflect the individual's convictions about having a significant, meaningful, and valuable life tend to play an important role in shaping coping behavior and, consequently, in predicting the well-being of healthcare personnel. These results can be interpreted within resource-based stress theories, which suggest that individual resources influence people's abilities to manage stress successfully and, consequently, to improve their well-being [12]. Meaning-based resources may be conducive to a constructive use of coping strategies, since a relatively stable pattern of commitment influences the way events are perceived and managed [25]. The predictive role of meaning-based resources in shaping the coping behavior of healthcare personnel is consistent with previous reports regarding the role of meaning in life in strengthening people's coping behavior and influencing their psychological well-being [19,20].

The present study also provides new empirical evidence by demonstrating that risk perception and meaning-based resources can operate together in predicting psychological well-being in healthcare personnel combating COVID-19. Problem-focused and meaning-focused coping mediated both the relationship between risk perception of COVID-19 infection and psychological well-being as well as the relationship between meaning-based resources and psychological well-being. However, the effect test showed that the mediating path for meaning-based resources was significantly stronger than for risk perception. This implies a more important role for coping strategies based on cognitive and motivational processes for healthcare personnel well-being in the case of personal meaning-based resources than the perceived risk of COVID-19 [20,38]. However, the mere availability of meaning-based resources does not contribute automatically to well-being, these resources must rely on coping strategies based on cognitive and motivational processes.

The present study has shortcomings. It should be emphasized that the cross-sectional design limits our ability to make a causal interpretation of the findings. The relationship between risk perception and well-being as well as the relationship between personal resources and well-being can be bilateral; risk perception and personal resources can affect healthcare personnel's well-being, but well-being may also contribute to more positive appraisals and higher meaning-based resources. Second, our explanation of the results of mediation analysis must be treated with caution. The model we tested, (which was confirmed), was based on theories and previous empirical research, but it should also be tested using a longitudinal design. Third, although respondents completed the measures anonymously, response bias could not be controlled, because the study was based on self-report. Therefore, future researchers need to attempt replication of the results with samples where this weakness is minimized.


*3.2. Pixel Compensation Module*

In this work, we compensate luminance according to the optimal backlight described as **BLop** and the luminance of the input image. Before the compensation, we use Improved Blur Mask Approach (IBMA) [10] to smooth optimal backlight to removes the block artifacts. Specifically, Zhang, T.; Wang, Y.F. [10] divided the points of **BLop** into three categories. The first category includes the corner points, the second category includes the peripheral points except for the cornet points, and the third category includes the internal points of **BLop**. Different Low Pass Filter (LPF) templates are used to smooth points of **BLop** in different categories. IBMA uses the smoothing process to simulate the light diffusion, and **BLop** is resized after each smoothing operation. By several smoothing operations, the smoothed backlight has the same size as the input image. The process is expressed in Equation (13).

$$\mathbf{BL\_{sm}} = IBMA\left(\mathbf{BL\_{op}}\right) \tag{13}$$

where **BLsm** represents the backlight after IBMA and **BLop** is the optimal backlight. The comparison results of using or not using IBMA are shown in Figure 6.

**Figure 6.** (**a**) Backlight without Improved Blur Mask Approach; and (**b**) backlight with Improved Blur Mask Approach.

Compared with Figure 6a, artifacts are removed obviously in Figure 6b by applying IBMA.

We use a compensation coefficient *k* to control the compensation degree, which is determined by the smoothed backlight and the luminance of the input image. The process is formulated as Equations (14) and (15).

$$\mathbf{k}\left(\mathbf{x},\mathbf{y}\right) = \left(\mathbf{BL\_{sm}}\left(\mathbf{x},\mathbf{y}\right) \div \mathbf{I}\left(\mathbf{x},\mathbf{y}\right)\right)^{\gamma} \tag{14}$$

$$\mathbf{I}\_{\mathbf{p}}\left(\mathbf{x},\boldsymbol{y}\right) = \mathbf{k}\left(\mathbf{x},\boldsymbol{y}\right) \times \mathbf{I}\left(\mathbf{x},\boldsymbol{y}\right) + \left(1 - \mathbf{k}\left(\mathbf{x},\boldsymbol{y}\right)\right) \times \mathbf{B}\mathbf{L}\_{\mathbf{sm}}\left(\mathbf{x},\boldsymbol{y}\right) \tag{15}$$

where *γ* = 0.125 is selected from multiple experimental results to prevent overcompensation problem and enhance the overall luminance of the image effectively. **IP** is the compensated luminance.

Next, IBHE is used to further enhance the compensated luminance. In BHE, an image is decomposed into two sub-images based on its mean, and then the sub-images are equalized independently to improve CR while maintaining the luminance of the image. Different from this, we rely on the Otsu method and the histogram of **r** in Equation (6) to obtain two sub-images. Algorithm 1 is devised to acquire the breakpoint for the image segmentation.

**Algorithm 1** Proposed algorithm for breakpoint acquisition.

```
Input: r, IP;
Output: the breakpoint T;
 1: [z1, z2] = size (r);
 2: num = 0;
 3: Im = IP;
 4: for i = 1 to z1 do
 5: for j = 1 to z2 do
 6: if r (i, j) == 0 then
 7: num+ = 1;
 8: else
 9: Im (i, j) = 0;
10: end if
11: end for
12: end for
13: T1 = (sum (sum (Im))) ÷ num;
14: T2 = Otsu ((Im)); the breakpoint obtained by Otsu method
15: T = floor ((T1 + T2) ÷ 2); the average value of T1 and T2
16: return T;
```
By the breakpoint *T*, the CDF curves of the two sub-images are obtained to perform BHE [17]. The process is expressed as Equation (16).

$$\mathbf{I\_{out}}(k) = \begin{cases} \left(T - I\_{p\text{min}}\right) \times \mathbb{C}DF\_1\left(k\right) + I\_{p\text{min}} & 0 < k < T\\ \left(I\_{p\text{max}} - T\right) \times \mathbb{C}DF\_2\left(k\right) + T & T + 1 < k < 255 \end{cases} \tag{16}$$

where *Ipmin* and *Ipmax* are the minimum and the maximum of compensated luminance **Ip**, respectively. *CDF*1 and *CDF*2 are respective CDF curves of the two sub-images.

Finally, **Iout** and **r** in Equation (6) are combined to reconstruct final luminance image by Equation (17), and color transformation from *YCbCr* to *RGB* [25] is employed to generate the final image.

$$\mathbf{Y\_{out}}\left(\mathbf{x},\boldsymbol{y}\right) = \mathbf{I\_{out}}\left(\mathbf{x},\boldsymbol{y}\right) \times \boldsymbol{e}^{\mathbf{r}\left(\mathbf{x},\boldsymbol{y}\right)}\tag{17}$$


*4.2. Effects of Meteorological Conditions and Environmental Management on Atmospheric Pollution*

Affecting the formation, diffusion, dilution, transformation, transportation, and accumulation of airborne pollutants, meteorological conditions are crucial for establishing air quality levels [11,12]. In this study, the meteorological factors significantly influenced the seasonal variations of particulate matter concentrations. This is partly because of the stable interaction between particulate matter and meteorological factors. Precipitation, for example, can remove particulate matter in the atmosphere and reducing the concentrations across seasons [27,28]. However, there are also some unstable interactions. Within a certain range, the wind can dilute the concentrations of particulate matter, otherwise the effect could be the opposite. In spring, for instance, strong winds from the northwest can easily bring sandstorms from Loess Plateau and increase the concentrations of particulate matter. The increased relative humidity caused by precipitation can reduce the concentrations of particulate matter, whereas high relative humidity can accumulate water-soluble ions, such as NH4 +, NO3 −, and SO4 2−, which are major aerosol components during haze episodes [29,30]. In addition, there may be a combination of other factors, such as vegetation cover, which can adsorb the particulate matter. Vegetation cover is regulated by phenology, such as atmospheric temperature [14]. This may result in the different relationships between particulate matter and atmospheric temperature across seasons.

The environmental management could determine the pollution intensity and the types of pollutants. In this study, we found that the environmental regulation intensity could significantly alleviate the emissions of SO2, smoke and dust, neither the particulate matter (Table 5). Compared with SO2, smoke and dust, the composition, chemical process, and the influence factors of particulate matter are more complicated [30,31]. It may be ineffective by simply increasing the environmental regulation intensity in a short period. Therefore, further exploration and verification are needed in terms of environmental management.

**Table 5.** Correlation coefficients between the environmental regulation intensity and the concentration and emission of atmospheric pollutants.

\*: *p* < 0.05.

Considering the difficulty of artificial control of meteorological conditions, more attention has been paid to the environmental management, which has been confirmed as the effective way to the improvement of atmospheric pollution. A one-size-fits-all management model may also have side effects on the development of socio-economics in a developing region. To reduce atmospheric pollution, effective environmental management should factor in the seasonal meteorological conditions. For instance, increasing relative humidity is an effective measure to reduce airborne pollution in spring and autumn. In winter, it is quite clear that improving ventilation and reducing relative humidity may ameliorate some of the effects of atmospheric pollution [25,32]. It is necessary to implement the intensity of targeted atmospheric governance under specific meteorological conditions to achieve the sustainability of socio-economic development and environmental protection.


**Author details**

Abdul Razak Mohamed Department of Planning, School of Planning and Architecture, Vijayawada, Andhra Pradesh, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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