**8. Prognostic factors**

Unfortunately, regardless of the treatment regimen, survival of patients afflicted with osteosarcomas of the head and neck remains poor.

While there are several single and multicenter studies reported, population data are scarce and controversial. On a literature review by Mendehall et al. [6] in 2011, overall survival shows a very wide range among the different series, going from 24 to 86% at 5 years. In Smith et al. [8] NCDB study with 496 patients, the 5-year diseasespecific survival was reported to be 59.7%, for patients who were diagnosed with HNOS between 1985 and 1991. Similarly, in Lee et al. [9] cohort of the SEER tumor registry, with 541 patients, the 5-year overall and disease-specific survival were 52% and 62%, respectively, and the 10-year overall and disease-specific survival were 35% and 54%, respectively, with a median overall survival of 8 years.

Both of this large series report multiple patient, tumor, and treatment factors that were associated independently with a significantly worse survival. These risk factors included: skull or facial bone sites (vs. mandible); age older than 60 years; tumor size >6 cm; osteoblastic/NOS histology; high histological grade; advanced stage at presentation; nonsurgical initial therapy; and the presence of residual disease after surgical resection [8, 9].

Different series confirm the finding that mandibular tumors appear to have a better prognosis than maxillary tumors, showing significant difference in the metastatic rate and local recurrence [8, 9, 16]. The median overall survival for osteosarcoma of the mandible has been reported to be 10.4 years vs. 6.3 years for osteosarcoma of the skull/facial bones, including the maxilla [9]. This may be due to a greater metastatic potential in more vascularized sites such as the maxilla and skull base and/or to a more economical resection in these areas, compared with the mandible, with smaller oncologic safety margins, given the greater anatomic complexity and proximity to vital structures. Maxillary tumors show greater rate of positive margins [16]. In any case, this observation emphasizes the need for greater therapeutic consideration.

Age is another factor named repeatedly by different authors to impact survival, generally 60 years and older. Advanced age could affect by an age-dependent T-lymphocyte depletion, an intolerance to the cytotoxic effects of chemotherapy, a higher propensity to development of metastatic disease, or differences in management based on age [9].

In addition, a tumor size, histology, and grade have also shown to impact survival. Of note, osteoblastic OS has evidenced worse overall survival [8], and fibroblastic and chondroblastic osteosarcoma had the best prognosis of histological subtypes,

### *Perspective Chapter: Osteosarcomas of the Head and Neck DOI: http://dx.doi.org/10.5772/intechopen.107456*

while osteosarcoma in Paget disease had a particularly poor outcome with an overall survival not longer than 6 months [9].

Histological Grade has been proved to impact severely on survival, thus is now taken into account for staging [8, 9, 16, 39]. Within the NCDB [8], patients with low-grade HNOS tumors showed a 74% 5-year survival rate, compared with 42% for patients with high-grade tumors. Ha et al. [21] also noted a marked discrepancy in survival for patients with high-grade versus low-grade HNOS tumors, with a difference at 5 years of nearly 60%. However, on the SEER tumor registry [9], the multivariate analysis found that grade was not considered to be and independent significant determinant of survival, which could perhaps be explained by the high percentage of cases defined to be unknown.

On another hand, treatment has shown to impact dramatically patients' outcome, and surgical resection has been found to improve 5-year overall and disease-specific survival [8, 9, 16]. Complete surgical resection with wide margins has been reported as the most significant prognostic factor in HNOS [6, 13, 15]. It is reasonable to state that patients with HNOS who are not candidates for surgical resection because of advanced disease or notable comorbidities at presentation may bias the survival advantage seen in the different cohorts. However, according to Smith et al. [8], patients who did not undergo surgical therapy had a markedly worse survival with a 5-year overall survival of 21.7% compared with 74.7% for patients treated with surgery alone and 71.3% surgery plus chemotherapy.

Finally, prognosis follows a dynamic course that has been and will continue to change as the best treatment approach for these patients becomes clearer. In a study by Granowski-LeCornu et al. [16], where patients with OS of the jaw were treated from 1967 to 1991 where compared with patients treated from 1992 to 2009, this second group had better prognosis than patients in the earlier treatment group (overall 5-yeral survival rate of 77% vs. 52%). They discuss that this could be explained by several factors favoring the latter group, such as better imaging, both CT and MRI, allowing for earlier diagnosis, thus, smaller tumors at diagnosis and better treatment planning. Also, more sophisticated reconstructive techniques allow wider ablative procedures and better chance of achieving clear margins.

For more recent HNOS patients, we now offer improved diagnostic tools, more aggressive treatment, and better surveillance. The role of neoadjuvant chemotherapy remains to be elucidated and may perhaps, added to all this other factors, continue to improve prognosis.


*Article* **Application of Room Cooling and Thermal Insulation Materials to Maintain Quality of Okra during Storage and Transportation**

**Jutarat Rattanakaran 1, Rattapon Saengrayap 1,2, Chureerat Prahsarn 3, Hiroaki Kitazawa 4 and Saowapa Chaiwong 1,2,\***

**Abstract:** A combination of room cooling and the use of thermal insulation materials to maintain okra quality under simulated storage and transportation was evaluated. Okra pods were packed in plastic baskets and either cooled at 18 ◦C or not cooled in a room for 2 h. After either room cooling or no cooling, the okra pods were covered with three different materials: (1) perforated linear low-density polyethylene (P-LLDPE), (2) two layers of heat-reflective sheet with thin nonwoven (HRS+TNNW), and (3) metalized foam sheet (MFS). Typical handling (TP) without cooling and covering with P-LLDPE was used as the control. The six treatments were conducted during simulated storage (18 ◦C for 48 h) and transportation (30 ◦C for 15 h). Results showed that MFS gave the best insulation properties (Qx and R-values), followed by HRS and TNNW. After room cooling, both HRS+TNNW and MFS materials delayed the time for pulp temperature to reach 18 ◦C (10 h), compared to P-LLDPE (2 h). TP presented the highest mass loss (17.8%) throughout simulated conditions, followed by cooling plus P-LLDPE (15.2%) and either of the thermal insulation materials with or without room cooling (3.6% to 5.2%), respectively. TP, cooling plus P-LLDPE, and no cooling plus MFS (44% to 56%) showed the highest percentage of decay, while cooling combined with both HRS+TNNW and MFS gave the lowest decay incidence (11–21%). Findings demonstrated that room cooling combined with HRS+TNNW had the highest efficiency for preserving cool temperature and reducing decay, compared to TP and room cooling plus MFS.

**Keywords:** decay; covering; nonwoven; mass loss; metalized foam sheet

#### **1. Introduction**

Okra (*Abelmoschus esculentus* L.) is an economic vegetable crop widely grown in tropical and sub-tropical global regions. Okra pods are harvested when immature and eaten as vegetables [1]. Okra is an export vegetable crop of Thailand, with the Japanese market accounting for 83.3% of the total exported okra volume. The main growing areas are the central and northern areas of Thailand [2]. A decline in the quality of okra is attributable to various issues, including techniques for determining okra fruit quality, poor harvesting methods, okra harvester training levels, lack of good vehicles, terrible roads, and insufficient pre-cooling facilities [3]. High respiration rate and rapid deterioration causes heat build-up and leads to pod blackening as well as a rapid increase in okra water loss after harvesting [4,5].

Temperature and relative humidity are the most important factors affecting the shelf life of okra [6]. The optimal storage temperature of okra ranged from 7 to 10 ◦C, and the pods can be stored satisfactorily for 7–10 days [7]. Fresh okra pods exhibited extremely

**Citation:** Rattanakaran, J.; Saengrayap, R.; Prahsarn, C.; Kitazawa, H.; Chaiwong, S. Application of Room Cooling and Thermal Insulation Materials to Maintain Quality of Okra during Storage and Transportation. *Horticulturae* **2021**, *7*, 188. https:// doi.org/10.3390/horticulturae7070188

Academic Editors: Maria Dulce Carlos Antunes, Custódia Maria Luís Gago and Adriana Guerreiro

Received: 11 June 2021 Accepted: 5 July 2021 Published: 8 July 2021

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

**Copyright:** © 2021 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/).

short shelf life due to high water loss or transpiration rates. Storage of okra at 25 ◦C resulted in a higher mass loss (14%) compared to a lower temperature of 4 ◦C after 5 days due to wilting, yellowing, and decay [8]. Storage at low temperatures led to a reduction of respiration rate, transpiration, and ethylene production [9]. At high temperatures, okra is highly susceptible to water loss, color fading, and decay, becoming squashy with a loss of commercial value and not easy to consume when fresh [10].

Heat generation, specifically known as 'Vital heat' in fresh produce, is produced as a by-product, primarily through the respiration process. Okra is classified at a very high respiration level, with a respiration rate of 40–60 mg CO2 kg−1 h−1 and vital heat ranging from 427 to 640 J kg−1 h−1 at 5 ◦C [9]. Consequently, a cooling process should be taken into consideration when the storage room is designed as well as during transportation [11]. Cooling as quickly as possible after harvesting is critical to remove heat from the fresh produce and is a very important requirement for maintaining optimal product quality, especially for merchandise with naturally high respiration rates [12]. Forced-air cooling has been used for the export of okra received directly from the field [13]. In India, room cooling at 15 ◦C before storage at 8 ◦C is used for the export of okra [14]. The procedure of no cooling resulted in decreased fruit quality and increased fruit decay. Post-harvest loss of commercial fruits and vegetables increased by 25–30% when no cooling was employed through the whole storing and transporting chain, while it was only 5–10% when a cooling step at 8 ◦C was practiced [15]. Wang et al. [16] showed that room cooling at 2 ◦C reduced changes in the physiological quality of button mushroom (*Agaricus bisporus*). However, scant research has reported on cooling conditions and the efficiency of cooling processes to reduce heat generation in okra to extend storage or shelf life.

Thermal insulation materials are defined as materials or combinations of materials that retard the flow of heat to prevent or minimize temperature changes in the system or space [17]. Thermal insulation materials are normally used as pallet covering, combined with other materials, to protect fresh produce during transportation [18]. Thermal insulation material testing evaluates whether a packaging design succeeds in maintaining a temperature-sensitive product within its appropriate temperature range when exposed to ambient conditions [19]. The main thermal insulation properties are measured as thermal heat transfer and R-value. Heat transfer is the mechanism of energy movement due to temperature differences between two sources [20]. A low rate of heat transfer implies better insulation of the materials via reduction of conductive heat loss [21]. The resistance to heat flow through an insulation material, known as the R-value, is determined by ice-melt processing [22]. A higher R-value presents a better performance of thermal insulation materials [19].

Pallet cover is an alternative method used as packaging technology to reduce waste from food spoilage by minimizing temperature and humidity change during the transportation of fresh produce [18,23,24]. Research on packaging for vegetables revealed that covering the pallet side and bottom with insulated pallet cover (Reflectix™) resulted in a reduction of mass loss and wilting in amaranth and preserved a desirable dark green color. Use of pallet cover for amaranth gave a high score in overall quality, with improvement on no cover [18]. Liu [25] reported the use of an insulated cover to keep pre-chilled lettuce at low temperatures. The insulated cover was also suitable for low-temperature phosphine fumigation to control western flower thrips on harvested lettuce. Chaiwong and Bishop [23] reported on lightweight insulation bags. Results showed that insulated bags provided cool temperature management and reduced the cool chain breakdown of strawberries from the supermarket to domestic refrigerators. The insulated pallet covers also gave better temperature preservation compared to no cover, and temperature changes occurred more slowly in chard, cucumber, and carrot [18,23,24]. However, very few studies exist about the use of thermal insulation cover to prevent post-harvest losses of okra under different temperature conditions.

The main post-harvest problems of okra during domestic transportation are temperature and relative humidity fluctuation. These lead to physiological damages such as

wilting and fruit rot before the freeze-drying process. Cooling treatment could delay the deterioration of okra quality, whereas thermal insulation covering could improve controlling temperature and humidity fluctuations under typical truck transportation. In this study, the efficiency of room cooling and thermal insulation materials in controlling cool temperature and okra quality under simulated storage and transportation were evaluated.

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

*2.1. Materials Properties*

Thermal heat energy was determined according to the procedure of Harvey [21], using an expanded polystyrene box with dimensions (75 × 38 × 38.5 cm3) with two sections (Figure 1). The material sample was taped on a hole (C) 10 cm × 10 cm to allow heat from the heated copper coil (E) at temperature 45 ◦C in section 1 (A) to pass through the material sample and enter section 2 (B). Temperature data loggers (Tinytag Talk 2: TK-4014-PK, Gemini Data Loggers, West Sussex, UK) were used to monitor the temperature change between the two sections (section 1 (I) and section 2 (J)) of the box for 3 h until a constant temperature was recorded. The rate of transfer of thermal heat energy (Qx) in J s−1 was calculated.

**Figure 1.** Schematic diagram for heat transfer test through material covers at the laboratory.

The water vapor permeability (WVP) through different materials was determined using the desiccant in cup method. Following ASTM E96 [26], the specimen or cover material was sealed on the open mouth of a test dish containing a desiccant, and the test dish was placed in a constant climate chamber (KBF-115, Binder, Tuttlingen, Germany) at 25 ◦C and 50% relative humidity (RH). Water vapor permeability was then calculated as rate of water vapor transmission in g h−1 m−2.

Air permeability was determined using an air permeability tester (FX 3300 LabAir IV, Textest Instruments, Schwerzenbach, Switzerland) according to ASTM D737-04 [27]. Thermal insulation materials were cut into square pieces of 20 × 20 cm and measured for air permeability (l m−2 s−1). The R-value was determined as resistance to heat flow through the thermal insulation material using the ice-melt test, following Singh et al. [19]. In this method, 2000 g of ice were placed in a non-metallic bucket, which was then positioned in the center of a basket inside thermal insulation bags and wrapped tightly with tape. The package was stored on a shelf at ambient temperature (25 ◦C) for 12 h. At the end of the test, the thermally insulated containers were opened, and water was collected from the buckets. The weight of water was recorded to calculate the melt rate (m2 ◦C W−1). Five samples (replications) in each material were tested.

#### *2.2. Plant Materials*

'Lady Finger' okra pods from Green Global Seeds Company Limited, Thailand, were planted with the spacing between plant and row of 50 and 100 cm, respectively, with sprinkler irrigation. The okra pods were harvested 45 days after planting, or 6 days after flowering from an okra plantation (20◦13 27.2 N 99◦50 05.2 E), in Mae Chan district, Chiang Rai Province. The pods were transported from the farm to the Postharvest Laboratory at Mae Fah Luang University within 30 min. After arrival at the laboratory, the okra pods

were graded to uniform size of pod length 7–11 cm (the specific size for okra processing), with minimum requirements being green in color, free of distinct signs of bruising and disease, and a clean-cut peduncle.

#### *2.3. Experimental Treatments and Heat from Respiration Rate (RR)*

The research study was divided into two experiments.

#### 2.3.1. Handling Procedures

Six treatments were studied. The control, as typical handling (TP) of the Phayao community enterprise (without room cooling and covered with perforated linear low-density polyethylene (P-LLDPE)) was compared with developing handling (DH), comprising room cooling, covered by two thermal insulation materials (heat-reflective sheet (HRS) + thin nonwoven (TNNW)), which were polypropylene (PP)-based spunbond nonwoven, and metalized foam sheet (MFS)), as shown in Table 1. It is noted that the HRS material was evenly perforated and distributed with a pin of diameter 0.55 mm for a total perforation area of 0.09 cm2.

**Table 1.** Six treatments (with or without room cooling) using different material covers.

For each treatment, 1500 g of okra pods were packed in a plastic basket (five replications). Initial temperature at the core of the okra pods was approximately 30 ◦C. Room cooling treatments (DH1, DH4 and DH5) were performed by setting the cooling medium at 0 ◦C for 2 h, compared with a cool room at 18 ◦C (no room cooling) (TP, DH2, and DH3) for 2 h as the 7/8 cooling time. Pulp temperature of the okra was monitored by a multichannel data logger (Hioki, LR8431, Nagano, Japan) connected with a type-K thermocouple for 10 channels. Five baskets each room cooling at 0 ◦C or at 18 ◦C were allocated for temperature monitor. After room cooling, the okra pods were covered with different thermal insulation materials, except for TP and DH1. Storage and transportation conditions of okra to simulate commercial practice before processing comprised storage at 18 ◦C for 48 h and transfer at 30 ◦C for 15 h.

#### 2.3.2. Determination of Respiration Rate

Respiration rate of okra was determined under three storage conditions (10, 20, 30 ◦C) for 2 and 3 days. Okra pods (150 g) were packed in a plastic food container (8400 mL) (Figure 2). Respiration rate testing was conducted in a closed system for 2 h. A gas sample of 5000 μL was drawn from each container at daily intervals for gas chromatography (GC) analysis. A gas chromatograph (7890A, Agilent Technologies, California, USA) equipped with a thermal conductivity detector (TCD) and HayeSep Q column (80/100 mesh, 3.05-m long) was used to analyze the gas samples. Nitrogen was used as the carrier gas at a flow rate of 52.2 mL min−1 with split mode. Injector, oven, and detector temperature conditions were 150, 60, and 275 ◦C, respectively. The respiration rate (RCO2) was determined on days 2 and 3 for the three storage conditions and calculated by the following Formula (1) [11];

> RCO2 (mg CO2 kg−1 h−1) = (CO2 (%) × volume of container (mL)) 100 × (fruit weight (kg)) × (closing time (h)) (1)

**Figure 2.** Okra pods packed in a plastic food container for respiration rate measurement by a closed system.

The respiration rate (RCO2) of okra pods in each closed system storage condition was calculated as the temperature coefficient (Q10) value by Formula (2):

$$\mathbf{Q}\_{10} = (\mathbf{R}\_2 \mathbf{R}\_1)^{10/(T\_2 - T\_1)} \tag{2}$$

where R2 and R1 are the respiration rate at temperature T2 and T1, respectively [28].

The Q10 values on day 2 (48 h) and day 3 (72 h) were used to estimate the respiration rate of okra pods (RC) in different air temperature levels using a temperature data logger (Tinytag Talk 2: TK-4014-PK, Gemini Data Loggers, West Sussex, UK). This depended on the thermal insulation cover treatments under simulated storage (18 ◦C for 48 h) and transportation (30 ◦C for 15 h), respectively. The air temperature for estimation of okra respiration rate (RC) in each cover treatment was determined from the final air temperature level before simulated storage (RC1) and transportation conditions (RC2). Respiration rates of okra pods in each cover material were converted into vital heat by Formula (3) [29]:

$$\text{Vital heat (J kg}^{-1}\text{ h}^{-1}) = \text{R}\_{\text{C}} \times 10.7 \tag{3}$$

where RC = respiration rate of okra pods in each cover treatment.

#### *2.4. Temperature and Relative Humidity Monitoring*

Air temperatures inside the covering and pulp temperatures at the core of the okra pods were measured using a temperature data logger for air temperature (Tinytag Talk 2: TK-4014-PK, Gemini Data Loggers, West Sussex, UK) with three replications and pulp temperature (Tinytag Talk 2: TK-4023-PK, Gemini Data Loggers, West Sussex, UK) with four replications. Relative humidity inside the covering was recorded using a temperature and relative humidity data logger (Tinytag Ultra 2: TGU-4500, Gemini Data Loggers, West Sussex, UK) at 30 s intervals. Pulp temperature was analyzed using temperature profile and boxplot at 12 h after simulated storage with stable temperature level. After simulated transportation at 30 ◦C for 15 h, air and pulp temperature levels were analyzed using a boxplot at 1 h 30 min (air temperature of TP at 25 ◦C) and 15 h after simulation, and the rate of change during temperature rise after simulated transportation was calculated. Data analysis of both air and pulp temperature focused on the data point at 25 ◦C and temperature range from 25 ◦C to 30 ◦C. Furthermore, heatmap analysis represented pulp temperature levels after simulated storage and transportation for 12 h. Python 3.6.9 was used to create the heatmap chart. The packages Seaborn version 0.11.1, Pandas version 1.1.5, and Matplotlib version 3.2.2 were all required by heatmap. The profile of relative humidity throughout the experiment was also investigated.

#### *2.5. Mass Loss Determination*

Mass loss of the okra pods was determined using an electric weighing balance (PioneerTM, Ohaus, NJ, USA). Percentage mass loss (%) was calculated on the basis of initial weight (IW) before cooling and final weight (FW) at the end of simulated storage and transportation, using WL (%) = [(IW − FW/IW] × 100 [30].

#### *2.6. Determination of Decay Incidence*

The first sign of okra deterioration was observed as a small wet lesion on pod, and then the entire pod coated with a grayish-white mass of mold. The okra pods were evaluated when incidence of decay occurred, calculated based on weight of pods showing symptoms of decay (D), and classified into four categories, including <10% of decay occurrence, 10–25% of decay occurrence, 25–50% of decay occurrence, and >50% of decay occurrence. Percentage decay (%) was calculated on the basis of total weight of pods per plastic basket (TW), using D (%) = [(D/TW) ×100] [30]. Incidence of decay was determined at the end of simulated storage and transportation.

#### *2.7. Statistical Analysis*

SPSS for Windows version 20 (SPSS Inc., Chicago, IL, USA) was used for the statistical analysis. Data analysis for the estimated respiration rate with three replicates, averaged pulp temperature in heatmap chart with four replicates as well as material properties, mass loss, and incidence of decay with five replicates compared by mean at a significant level of 0.05 using Tukey's HSD post hoc test.

#### **3. Results and Discussion**

#### *3.1. Materials Properties*

The properties of the thermal insulation materials, including thickness, thermal heat energy, WVP, air permeability, and R-value, are shown in Table 2. Temperature transfer through the material was studied in terms of the heat transfer processes. Heat transfer is the process of energy movement caused by temperature differences [20]. Lower thermal heat energy (Qx) value shows a lower heat transfer rate (good insulator) through the substance layer, while higher Qx shows a higher heat transfer rate (poor insulator) through the layer [21]. In this study, results indicated that MFS with a thickness of 3.1 mm gave the lowest heat transfer property (Qx = 1.53 J s−1), compared to the other three materials, while P-LLDPE (0.120 mm) had the highest Qx value (3.85 J s−1). A combination of HRS (1.450 mm) (2.57 J s−1) and TNNW (0.270 mm) (3.23 J s−1) showed improved insulation property and potential for prototype development for covering material in the future. The high insulation properties of MFS and HRS materials may be partly due to greater thickness. Material with lower thermal heat energy (Qx) also tends to have a higher R-value. MFS had the highest R-value (0.225 m2 ◦C W−1), followed by HRS (0.211 m2 ◦C W−1), TNNW (0.187 m2 ◦C W−1), and P-LLDPE (0.153 m2 ◦C W−1), respectively (Table 2). Results showed that MFS and HRS preserved cool temperatures better than the other materials (Figure 3).

**Table 2.** Covering material properties (thickness, thermal heat energy, WVP, R-value and air permeability).

Note: Different letters for different mean levels in each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from five replicates. Four materials were perforated linear low-density polyethylene (P-LLDPE), heat-reflective sheet (HRS), thin nonwoven (TNNW), and metalized foam sheet (MFS).

**Figure 3.** Pulp temperature profiles during simulated storage at 18 ◦C for 12 h (**A**) and boxplot of pulp temperature profiles during simulated storage at 18 ◦C for 12 h (**B**). Boxes indicate the lower and upper quartile. The horizontal line in each box represents the median temperature. Mean temperature for each treatment is indicated by -. Vertical lines extending above and below each box represent minimum and maximum temperature recorded. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

For water vapor permeability (WVP), a partial pressure difference between the inside and outside of the test material affects the gain or loss of moisture in the product [31]. In this study, TNNW and P-LLDPE showed higher WVP than MFS and HRS, and would be suitable for highly breathable fruits (Table 2). High WVP material had the potential to eliminate vapor condensation, thus inhibiting microbial activity [31]. On the other hand, both MFS and HRS materials had lower WVP values and air permeability, which may cause vapor condensation inside the covering (Table 2). Interestingly, a combination of HRS and TNNW showed good performance in terms of insulation and water and air permeability properties, with the potential to maintain cool temperatures and protect condensation inside the package or cover.

#### *3.2. Respiration Rate, Q10 Value, and Heat from Respiration Rate*

An increase in storage temperature and time resulted in a rise in okra respiration rate. Respiration rate at three storage conditions (10, 20, 30 ◦C) for 2 days increased gradually from 186.39 (10 ◦C) to 355.44 (30 ◦C) mg CO2 kg−1 h−1 as well as on day 3 (Table 3). Similarly, Hardenburg et al. [7] reported that higher storage temperature at 25–27 ◦C (328–362 mg CO2 kg−1 h−1) increased respiration rate compared to lower temperatures at 5 ◦C (59 mg CO2 kg−1 h−1) and 10 ◦C (86 to 95 mg CO2 kg−1 h−1). Furthermore, the widely used Q10 value represents an improvement in the rate of a process with a 10 ◦C increase in temperature [32]. In this study, the Q10 value of temperature range (10–20 ◦C) on days 2 and 3 increased from 1.17 to 1.87, while the Q10 value of temperature range (20–30 ◦C) decreased from 1.50 to 1.37 (Table 3). In lower temperature storage, Q10 value is typically less than 2.00 levels, whereas Q10 value gradually decreased in higher temperature conditions [33]. However, Q10 values of okra during different storage temperatures have never been reported. Yasunaga et al. [34] reported that Q10 value of cucumber at 10 to 20 ◦C was 4.37 and dramatically decreased to 1.89 with higher temperature storage at 20–30 ◦C. In this study, to estimate okra respiration rate under simulated storage (RC1) and transportation (RC2), the Q10 value was calculated for respiration rate in each cover treatment and converted to vital heat as shown in Tables 4 and 5, respectively.

**Table 3.** Rate of respiration of okra pods at different storage conditions (10, 20, 30 ◦C) for 2 and 3 days in a closed system.

**Table 4.** Estimated respiration rate (RC1) and vital heat among the six treatments under simulated storage at 18 ◦C for 48 h.

Note: Different letters for different mean levels in each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from three replicates. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

**Table 5.** Estimated respiration rate (RC2) and vital heat among the six treatments under simulated transportation at 30 ◦C for 1 h (air temperature of TP at 25 ◦C) and 15 h (the end of simulated transportation).

Note: Different letters for different mean levels in each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from three replicates. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

The efficiency of room cooling and thermal insulation materials under simulated storage and transportation conditions for respiration rate and heat from respiration (vital heat) was studied. Table 4 shows that respiration rates and vital heat levels in DH4 and DH5 were lower than in the other three treatments under simulated storage at 18 ◦C for 48 h. After room cooling at 0 ◦C for 2 h, the field heat and vital heat of okra were removed and reduced to around 20% of no room cooling before the cool storage condition. However, no difference was shown between no room cooling plus either P-LLDPE or insulated materials (HRS + TNNW, MFS), as well as room cooling with P-LLDPE. A decrease in vital heat in okra suggested that room cooling combined with insulated material cover should be employed. During simulated transportation at 30 ◦C for 1 h, the vital heat of DH2, DH3, and DH5 (5148–5202 J kg−1 h−1) was lowest compared with TP and DH1, and DH4 treatments (5791–5873 J kg−1 h−1). However, at a longer period of simulated transportation

for 15 h, vital heat levels in all DH treatments were similar to TP. The efficiency of thermal insulation materials reduced the vital heat loss for a short period of around an hour. Either room cooling or no room cooling with thermal insulation material covering reduced heat from respiration under heat stress conditions over a short period (Table 5).

#### *3.3. Air and Pulp Temperature Levels of Okra*

Room cooling and thermal insulation materials showed efficient cooling under simulated storage and transportation. After simulated storage at 18 ◦C for 12 h, okra pulp temperature profiles of room cooling treatments (DH1, DH4, and DH5) maintained cool temperature for around 10 h, better than no room cooling treatments (TP, DH2, and DH3). The use of two thermal insulation materials (HRS and MFS) combined with room cooling (DH4 and DH5) maintained cool temperatures, compared to no cover. In addition, the combination of room cooling and thermal insulation as a covering material effectively maintained cool temperature (Figure 3A). Temperature control of cover treatments was presented as a boxplot (Figure 3B) which showed the mean (rhombuses), lowest (lower error bars), and highest temperature (upper error bars) levels. Okra pulp temperature in DH4 and DH5 had the lowest mean temperature (17 ◦C) compared to the other four treatments (19 ◦C for TP and DH1; 20 ◦C for DH2 and DH3). The use of thermal insulation materials without room cooling (DH2 and DH3) gave the significantly highest pulp temperature (highest upper error bars) as well as the warmest level (highest lower error bars) after simulated storage at 18 ◦C for 48 h. This was presented as a narrow range of cool temperature levels (a smaller boxplot) compared with room cooling (DH4 and DH5) (a larger boxplot).

To simulate actual transportation for 15 h, we designed an experiment to analyze when the air temperature of TP reached a constant level at 25 ◦C. Thermal insulation materials maintained a cool temperature (average and minimum temperature levels) better, compared to either no covering or covering with P-LLDPE (TP and DH1). However, thermal insulation materials tended to build up pulp temperature (Figure 4C,D). The minimum air and pulp temperatures inside thermal insulation materials were the lowest. (Figure 4A,B). As no published reports were available concerning the effect of room cooling combined with thermal insulation covering under storage and transportation conditions on the quality of okra, the results of this study were compared to published data for other fresh fruits and vegetables. Bollen et al. [35] used low-temperature cooling in combination with pallet covers for asparagus. They found that the use of covering with insulation materials reduced heat generated by fresh produce with high respiratory rates inside the covering. Long-term covering was recognized as a problem due to heat accumulation, leading to a higher temperature than no cover. Other studies reported that thermal insulation covers showed better temperature preservation than no cover, and temperature changes occurred more slowly than with no cover in amaranth [18], strawberries [23], and chard, cucumber, and carrot [24]. However, in this study, both temperature profiles increased to 30 ◦C within 15 h (Figure 4B,D). Covering with thermal insulation materials maintained cool temperature (<25 ◦C) under a high-temperature environment for less than 6 h. Additionally, the pulp temperature levels after simulated storage and transportation are presented in the heatmap chart (Figure 5) as a matrix of red–blue color tones with average temperature in each hour for 12 h. At the simulated storage (Figure 5A), DH4 and DH5 had a significantly low average of pulp temperature (blue color tone), while DH2 and DH3 had a significantly high average of pulp temperature (light orange color tone) that related to the highest pulp temperature profiles (Figure 3A) and the smallest boxplot size with the lowest pulp temperature profiles when compared among the five treatments (Figure 3B). Moreover, the heatmap chart during simulated transportation (Figure 5B) showed that the use of thermal insulation materials (DH2, DH3, DH4, and DH5) caused a heat accumulation (light orange color tone) within an hour, then there was no significant difference among all treatments after an hour. The combination of room cooling and thermal insulation materials (DH4 and

DH5) increased the efficiency of maintaining cool temperature more than using thermal insulation materials without room cooling (DH2 and DH3).

**Figure 4.** Air temperature profile after 1 h 30 min (**A**) and 15 h (**B**), pulp temperature profile after 1 h 30 min (**C**) and 15 h (**D**) during simulated transportation at 30 ◦C. An interpretation of the box plot graph is presented as a caption in Figure 3. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

**Figure 5.** Heatmap chart of pulp temperature profiles during simulated storage at 18 ◦C for 12 h (**A**) and simulated transportation at 30 ◦C for 12 h (**B**). Different letters in each row indicate significant differences of mean temperature from four replicates for pulp temperature in each hour at *p* < 0.05. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

Table 6 compares the air temperature change rate inside the covering under simulated transportation testing. TP and DH1 showed the lowest rates of temperature change, whereas no cover in TP and DH1 treatments showed reduced control of cool temperature due to either high air ventilation through the plastic basket or no thermal insulation covering, respectively, indicating the highest thermal heat energy (Qx) and lowest R-value of

P-LLPPE (Table 2). P-LLDPE gave poor preservation of cool temperature during simulation compared with the other materials. By contrast, low pulp temperature change rate showed high effectiveness of thermal insulation materials (TNNW, HRS, and MFS) for DH2 to DH5 by maintaining cool pulp temperature (Table 6). In previous studies, cardboard in combination with plastic foil of bottle beer gave control cold temperature than hard plastic crate under air temperature condition at 30 ◦C due to a reduction of the air movement and transferring contribution of the beer bottle as well as a reduction of vibration damping during transportation [36]. The efficiency of a base material nonwoven fabric on temperature-controlled deliveries was studied by Dieckmann et al. [37]. Nonwoven feather fiber composite isolation gave greater material performance aspects than EPS in terms of thermal insulation, and inexpensive, sustainable, and lightweight material. In this study, HRS and MFS-based aluminum foil material and nonwoven performed good thermal insulation. However, the browning incidence of okra pods also caused vibration damage during handling and transportation. Interestingly, further research should be conducted to investigate the combined effects of thermal insulation materials on cold temperature control and vibration damage reduction during transportation.

**Table 6.** Rate of changes in air and pulp temperature under simulated transportation at 30 ◦C for 15 h.

Note: T1 is the temperature at the end of the simulated storage. Different letters in different mean levels of each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from five replicates. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

#### *3.4. Relative Humidity inside Covering Materials*

Relative humidity was monitored during simulated storage and transportation. Relative humidity of TP and DH1 as no covering (75%) (Figure 6A) was lower than all the other thermal insulation materials (100% RH) (Figure 6B,C) after storage for 48 h. This showed that the use of thermal insulation materials for covering preserved relative humidity fluctuation inside the covering was better than without covering (Figure 6B,C). Low relative humidity in TP and DH1 increased mass loss (>15%), while thermal insulation covers with 100%RH reduced mass loss (5%) throughout this simulation (Figure 7). The effect of relative humidity (RH) on the quality of 'Niitaka' pears was studied by Lim et al. [38] using two types of pallet covers made of polyethylene film to maintain high RH in commercial low-temperature storage rooms. Use of pallet covers increased RH from 83 to 87% or 93 to 95% for open and closed pallet covers, respectively. Moreover, using insulated material for covering preserved the relative humidity inside the covering and was better than no covering during shipping delays in amaranth [18]. Covering with thermal insulation materials maintained the highest RH level (100% RH) after 12 h, particularly HRS and MFS (Figure 6). This result related to the lowest WVP level of HRS and MFS materials, which preserved the relative humidity inside the covering (Table 2). On the other hand, low WVP of MFS caused condensation inside the covering and accelerated the activity of microorganisms with an increase of decay incidence (Figure 8).

**Figure 6.** Relative humidity profiles among treatments, including TP and DH1 (**A**), DH2 and DH3 (**B**), DH4 and DH5 (**C**), after simulated storage at 18 ◦C for 48 h and simulated transportation at 30 ◦C for 15 h. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

**Figure 7.** Mass loss (%) among the six treatments after simulated storage at 18 ◦C for 48 h and simulated transportation at 30 ◦C for 15 h. Different letters in different mean levels of each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from five replicates. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

**Figure 8.** Incidence of decay (%) among the six okra treatments after simulated storage at 18 ◦C for 48 h and simulated transportation at 30 ◦C for 15 h. Different letters in different mean levels of each parameter for Tukey's HSD post hoc test indicate significant differences at *p* < 0.05. Values are mean ± S.E. from five replicates. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

#### *3.5. Mass Loss of Okra*

Okra pods in TP and DH1 (no cover and P-LLDPE covering) lost a significant amount of fresh weight (around 15%) compared to thermal insulation material treatments (5%) (Figure 7). This corresponded to better performance in maintaining lower temperature and higher relative humidity by thermal insulation materials (Figures 3 and 6). There was no significant difference between room cooling or no cooling combined with thermal insulation materials (Figure 7). However, limited data exist comparing the efficiency of thermal insulation covering on mass loss of fresh produce. Wheeler et al. [18] reported that amaranth contained in uncovered pallets had more weight (11.0%) than in pellets covered with ReflectixTM insulation material (2.0%) (bubble pack insulation consisted of reflective aluminum foil and heavy gauge polyethylene) overa6h storage cycle. ReflectixTM cover effectively minimized the amount of moisture loss during amaranth storage. Macnish et al. [39] compared the performance of four propriety pallet cover systems (CO2 West, PEAKfresh, PrimePro, and Tectrol) in maintaining the quality of strawberry fruit during transportation with a temperature at 20 ◦C. Results showed that pallet cover systems significantly reduced transport-related mass loss by less than 0.5%, compared to those with control or no cover material (0.8%). Similarly, Lim et al. [38] found that the use of pallet cover in pear storage for 7 days reduced mass loss compared to no pallet cover. The application of pallet cover is an alternative technique for controlling temperature and humidity fluctuation during transportation [40] as well as reducing the rate of mass loss [41]. In this study, low mass loss of okra in thermal insulation covers after simulation (Figure 7) was related to low levels of WVP (Table 2).

#### *3.6. Incidence of Decay (ID)*

Highly significant decay of okra at 50–80% was presented in no room cooling plus covering with either thermal insulation material or P-LLDPE. The okra pods turned black with mold infection. The DH4 and DH5 treatments had the lowest percentage of ID (<20%) compared to the other four treatments (Figures 8 and 9). Thermal insulation materials maintained cool temperature and relative humidity (Figures 3 and 6). This was related

to a lower incidence of decay (Figure 8) and mass loss (Figure 7). Increasing efficiency of thermal insulation covers suggested application with room cooling to maintain a cool temperature under heat stress conditions. However, the application of MFS covering should be considered in case of a high-temperature condition (30 ◦C) over 15 h, which may lead to heat accumulation (Figure 4). Vapor condensation resulted in an increase of okra decay (Figure 8) due to low WVP (Table 2). Thermal insulation covers may be applied for a short journey (<6 h) for domestic transportation under ambient temperature (no refrigerated vehicle) to maintain cool temperature with less decay. HRS+TNNW covering with cooling technique showed high potential application for fresh produce with high respiration rates, such as asparagus, broccoli, mushroom, and sweet corn [29]. The overall post-harvest loss from mass loss and incidence of decay showed that TP was the highest post-harvest loss (65%), followed by DH1 (59%), DH3 (52%), DH5 (27%), DH2 (26%), and DH4 (15%), respectively (Figures 7 and 8).

**Figure 9.** Okra pictures from the six treatments including TP (**A**), DH1 (**B**), DH2 (**C**), DH3 (**D**), DH4 (**E**), and DH5 (**F**) after simulated storage at 18 ◦C for 48 h and simulated transportation at 30 ◦C for 15 h. Six treatments were no room cooling with P-LLDPE covering (TP as control), room cooling with P-LLDPE covering (DH1), no room cooling with HRS+TNNW covering (DH2), no room cooling with MFS covering (DH3), room cooling with HRS+TNNW covering (DH4), room cooling with MFS covering (DH5).

#### **4. Conclusions**

Room cooling with TNNW provided greater efficiency to preserve a cool temperature (2 ◦C) and reduce the decay of okra (10%), compared to TP (42%) and no room cooling plus MFS (48%) after simulated cool storage and high-temperature transportation conditions. Application of thermal insulation materials for covering reduced mass loss (5%), compared to either no cover or P-LLDPE throughout the simulation test (15–17%). Thus, the room cooling combined with HRS+TNNW (DH4) gave the lowest post-harvest loss (15%) as compared to TP, cooling plus P-LLDPE (DH1), and no cooling plus MFS (DH3) in a range of post-harvest loss (52% to 65%). Results showed that cooling was a very important step to apply in the post-harvest handling of okra before covering to remove both field heat and respiratory heat. Material properties, including low thermal heat energy (Qx) level and high R-value and WVP value, should be considered for developing thermal insulation material for fresh produce. Future research should be conducted to assess the effect of room cooling and thermal insulation material for other fresh fruits and vegetables, particularly the high respiration rate group.

**Author Contributions:** J.R. conducted experiments, analyzed data, interpretated results, and assisted manuscript writing. R.S. co-investigated, interpretated results, and assisteddata analysis. C.P. coinvestigated, supported cover materials, interpretated results in material analysis, and assisted manuscript writing. H.K. provided comments and suggestions for the final draft of the manuscript. S.C. was the principal investigator of the research, responsible for the overall research management, interpretation of results, and manuscript writing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Thailand Graduate Institute of Science and Technology (TGIST), Grant (SCA-CO-2561-6988TH), Thailand.

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

**Informed Consent Statement:** Not applicable.

**Acknowledgments:** The authors appreciate Sujitra Arwatchananukul for teaching the Python program and are grateful to the Thailand Graduate Institute of Science and Technology (TGIST), the National Science and Technology Development Agency (NSTDA), and Mae Fah Luang University (MFU) for financial support and the provision of experimental sites for this research study, respectively.

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

#### **References**


**2.1 What is an extracellular vesicle?**

For the past decade the classification of EVs has been based on size, ranging from exosomes that are 30–100 nm, microvesicles (MVs) that are 100–1000 nm, and apoptotic bodies that are 0.1–5 μm [1]. Exosomes are the smallest EV and appear to originate within the lumen of multivesicular bodies [1]. Oncosomes, a subtype of MVs, are released by budding from malignant cells [1]. As cells undergo apoptosis, they release apoptotic bodies [1]. One factor that limits this classification system is that some EVs that function as oncosomes are larger than the typical 100–1000 nm and can be as large as 1–10 μm [1]. When trying to isolate and study EVs, it became apparent that size did not adequately capture the breadth of heterogeneity among EVs with their varied functions and content. In 2019 the International Society of Extracellular Vesicles published a recommendation for the use of the term *extracellular vesicle* to encompass all types of EVs while still including a subclassification system that incorporated size [11]. Therefore, in this chapter the term *extracellular vesicle* will be used. Eventually, the optimal method of classification for EVs will be based on the specific phenotype and content of an EV that would better describe its origin and function. However, current testing methods and understanding of this topic need to be further studied.


**6. Conclusion**

This chapter shows how satellite data, going through all levels of processing, become useful products for both science and applied environmental prediction problems. Assessment, and later predicting the dynamics of various environmental parameters, will help reduce damage to nature and identify the degree of influence of anthropogenic factors on the future of the Earth. Based on our analysis results, it seems that the existence of global warming phenomenon has already been proven, but its influence on different parts of the planet is heterogeneous and is not traced in all seasons in the same way. In the spring, there is a tendency to a decrease in the temperature of the surface layer of the Sea of Okhotsk, this tendency continues until August, where it changes to warming condition.

Periodic fluctuations of physical parameters are also not homogeneous in space. It is possible to identify areas where the main oscillation period is 3, 5, 6, 8 and 11 years. Using the sequential spectra method gives a relatively good estimate for the next year's ocean surface temperature. However, to improve the quality of the forecast, it is necessary to improve the quality of the initial data, comparing data from various sources and filling in the gaps associated with the presence of clouds and ice cover, as well as improve the interpolation algorithms to avoid losing sight of mesoscale phenomena.


**9.2 Residential: middle density and the intermediate housing**

There seems to be a conflict between epidemiologic studies that suggest a lower people density and the environmental approach that recommends the increasing of the built density. The urban sprawl is considered to increase pollution, to cause the loss of a sense of community [73], global warming [74], higher transportation costs and create health effects due to the dependence on automobiles [75]. It is addressed by professional organizations such as Architects' Council of Europe, the American Institute of Architects and the American Planning Association, by agencies such as European Environment Agency or by national legislation, such as the French law for Solidarity and Urban Renewal.

On the other hand, lowering the people density is not only implied by studies carried over time that correlate population density and pandemics but also the public preference. Pre-pandemic surveys showed that 76% of French [76] and 80% of US Americans [77] would choose to live in single-family houses. The COVID-19 pandemic increased this desire. Teleworking and the reduced access to shops, "led to a reduced demand for housing in neighborhoods with high population density", trend which strengthen after the market recovery in June 2020 [78].

**The solution to reconcile the dense city environmental paradigm with the low density of population suggested by epidemiologic studies can only find the answer in architecture and urbanism**. For most epidemiological approaches, people density is a figure in a quantitative approach while for architecture and urbanism there is also a shape-related morphological and typological building approach. Urban approach also considers different densities, such as population density (related to inhabitants' number), residential density (related to number of housings) or built density (related to gross floor area). Moreover, the same people density can be achieved with different urban typologies, such as parallel buildings, courtyard or scattered. Architectural approach also takes into account building morphology. The same people density can be achieved under different morphologies, such as detached houses, row houses or blocks. Therefore, addressing population density as a figure is not enough for analyzing the complexity of the built environment.

A more detailed approach should also be based on studies carried over the virus transmission in the interior spaces. Small, confined and poorly ventilated spaces, such as stairs or elevators, must be carefully planned as they are the most susceptible for aerosol contamination [79].

Medium density environments are the mostly supposed to reach this goal. Both New Urbanism and Urban village movements promote medium density housing. There are urban and architectural approaches that stay in between the single family detached house and the block paradigm. The French Intermediate Housing concept addresses buildings with more than one superposed apartments and with private access to each apartments. The definition appears in a French 1973 decree: the social intermediate housing (*habitat social intermédiaire*) is supposed to have a private access, a private exterior space of one quarter of the apartment surface and a height of no more than three floors. The organization led to densities of 80 to 100 dwellings per hectare for intermediate housing compared to the 10–50 dwellings per hectare for dense single-family houses [80].

#### **9.3 Public spaces: the key for the social interaction**

One of the problems the COVID-19 pandemic created was the social disruption. The public space was put under scrutiny [81]. In this matter, exterior public spaces

could play a key role. The COVID-19 droplets transmission occurs up to 6 feet (2 meters). According to Edward T. Hall's proxemics theories, the social distance far phase is in between 7 and 12 ft. (2.1–3.7 m) and the public distance is in between 12 and 25 ft. (3.7–7.6 m) for the close phase and more than 25 ft. (7.6 m) for the far phase. Therefore, far social and public contacts could be achieved in exterior spaces without transmission risks.

According to Jan Gehl's theories, social contacts in public spaces are among the most important. They have the characteristic of being spontaneous because people interact as a result of necessary or optional activities. The space in between the buildings is ideal for conversation, greetings, children playing: "life between buildings as dimension of architecture, urban design and city planning to be carefully treated [82]".

#### **9.4 Green areas: a perennial goal**

As recent scientific studies show, green areas can improve the response to pandemics. They were already present in the 1900s urban theories and they maintain their permanent importance.

#### **9.5 Working: downsizing and dispersion**

Architectural measures can be taken in the case of office buildings. Some approaches concern general building measures, such as air control by ventilation filtration and humidification. Other methods should lean on morphologic changes that consider access separation and office space distribution.

There is also question of the offices size and their urban distribution. During the COVID-19 pandemic, an Italian multicriterial research concluded that firm density, based on an over 250 employees firm index for each region, was positively associated with higher fatality rates [36].

The COVID-19 pandemic also accelerated the use of telecommuting (teleworking or working from home). In 2019, 5.5% of workers in the US already worked from home [83] and, in April 2020, already 20% of Americans were able to work from home and doing so [84]. Estimations from 2020 are that "37 percent of U.S. jobs that can plausibly be performed at home account for 46 percent of all wages [85]". Telecommuting has an indirect environment impact by reducing the greenhouse emissions, fuel and energy usage and network congestion [86, 87].

#### **9.6 Shopping: proximity and downscaling**

Apart air quality methods, different measures can be taken for shops. Reducing the size cold lead to a better ventilation and less potential contacts. Proximity shopping is also an environmental desideratum as it allows for less automobile transportation, lead to pedestrian cities, reduced pollution, less energy consumption and less environmental impacts. Recent study shows that "to achieve a balance between energy consumption, GHG [Greenhouse Gas] emissions and energy generation potential, a neighborhood should contain an optimal ratio of commercial to residential buildings of about 0.25 [88]."

The proximity and downscaling decision have long term social and environment motivations more than short term economic reasons. An example are hypermarkets, huge stores combing supermarkets to department stores. It is symptomatic how France, the country that first implemented hypermarkets with Carrefour, in 1963, prevented their implantation in cities ten years later, by the Royer law which regulated the creation of shops over 1500 m2 inside towns.

## **9.7 Transportation: walking, bicycling, shared mobility and robo-taxis**

Before the pandemic there was already very strong evidence of aerosol transmission over long distances [89]. Studies during 2020 showed substantial transmission in closed vehicles and suggest "future efforts at prevention and control must consider the potential for airborne spread of SARS-CoV-2, which is a highly transmissible pathogen in closed environments with air recirculation [90]". At the beginning of 2020, studies drew a warning about public transportation showing that, for New York City, the subway system was the major disseminator of COVID-19 [91].

To keep the present transportation system there could be applied methods that reduce the viral transmission. Airborne virus spread in public transport can be reduced by installing HEPA filters and surface disinfection can be done by UV disinfection.

There is also question of changing the current transportation paradigm. Changes that may reduce the virus transmission in the transportation system already begun before the COVID-19 pandemic. Cities designed at the scale of walking or bicycle distances were proposed by the 1900s Garden City movement, the 1970s Intermediate Housing or 1980s New Urbanism and Urban Village movements.

Mobility sharing with bicycles can increase the efficiency of an urban public transport network [92] and has health benefits [93]. Starting with the white bicycle and white path proposed by the Provo movement in Amsterdam, in 1965, the Vélib' in Paris, launched in 2007 and reached the Chinese bike sharing system where the two largest operators, Ofo, launched in 2014, and Mobilke 2015, totalize over 50 million orders per day [94]. Electric car sharing, on which UV disinfection could be applied, could be a pandemic and environmental solution too. It has a positive environmental approach by "reducing 29% of CO2 emissions and increasing 36% electric vehicle adoption, when compared to the business-as-usual scenario [95]". Along with UV disinfection, robo-taxis (robocabs, self-driving taxis or driverless taxis) could be used. Experiment in Beijing with electric robo-taxis showed a good impact in lower energy consumption, zero tailpipe emissions, traffic decongestion and reduced health risks [96] while simulation in Milan "propose that introducing a robo-taxi fleet of 9500 vehicles, centered around mid-size 6 seaters, can solve traffic congestion and emission problems in Milan [97]".

From the larger urban point of view, transportation is influenced not only by the means of transport but also by the overall cities' organization.


*Edited by Lulu Wang*

This book highlights original research and high-quality technical briefs on electromagnetic wave propagation, radiation, and scattering, and their applications in industry and biomedical engineering. It also presents recent research achievements in the theoretical, computational, and experimental aspects of electromagnetic wave propagation, radiation, and scattering. The book is divided into three sections. Section 1 consists of chapters with general mathematical methods and approaches to the forward and inverse problems of wave propagation. Section 2 presents the problems of wave propagation in superconducting materials and porous media. Finally, Section 3 discusses various industry and biomedical applications of electromagnetic wave propagation, radiation, and scattering.

ISBN 978-1-83968-581-1

Electromagnetic Wave Propagation for Industry and Biomedical Applications

Published in London, UK © 2022 IntechOpen © wacomka / iStock


**5. Conclusions**

In this study, we investigated the obesogenic properties of blood Hg using lipid profiles and hepatic enzymes. Higher blood Hg levels were observed in the hyperlipidemia group than in the non-hyperlipidemia group, and the elevated liver enzymes group had higher mean blood Hg levels than the normal group. Blood Hg was associated with higher odds of hyperlipidemia and elevated liver enzymes, even after adjusting for personal medications. These results indicate that Hg exposure is associated with obesity-related outcomes and that other health effects due to low-level Hg exposure should be investigated.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2305-6304/8/3/47/s1, Table S1: Blood Hg distributions by influential variables.

**Author Contributions:** Conceptualization, S.L. and S.-R.C.; Methodology, I.J. and J.B.P.; Formal analysis, S.L.; Writing—Original Draft, S.L.; Writing—Review and Editing, M.-Y.S., S.-R.C., S.K., J.H.K.; Supervision, S.K. and J.H.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

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


**Meet the editor**

Dr. Rita Rezzani is Full Professor of Human Anatomy and Chair of Anatomy and Physiopathology Section at University of Brescia (Italy). Her scientific fields include the immunosuppressive effects of cyclosporine A, the oxidative stress and the morphological alterations induced by cardiovascular diseases. Recently her interest involves the beneficial effect of natural antioxidants, in

particular of melatonin, in several diseases. She is interested in studying both the therapeutic and protective melatonin effects. For this purpose, she is working with important scientists around the world. She is an author of 165 full-length publications and she participated in writing of several books regarding cardiovascular diseases and atherogenesis.

Contents

**Preface VII**

and José Milei

**Clinical Trials 105**

**Stenosis 125**

**Protection Device 149**

Kougialis

Chapter 1 **Evaluation and Treatment of Carotid Artery Stenosis 1**

Chapter 3 **Carotid Artery – Pathology, Plaque Structure – Relationship between Histological Assessment, Color Doppler Ultrasonography and Magnetic Resonance Imaging –**

Chapter 4 **Carotid Plaque Morphology: Plaque Instability and Correlation with Development of Ischaemic Neurological Events 85**

Chapter 5 **Update on Carotid Revascularization: Evidence from Large**

Chapter 6 **Oxidised Low Density Lipoprotein (LDL) Modification with**

Chapter 7 **Cerebral Protection in Carotid Angioplasty – Is There a Need? Advantages and Disadvantages of Each Type of**

Antenor Tavares and José Guilherme Caldas

**Statin Therapy is Associated with Reduction in Carotid**

**Dolichoarteriopathies – Barorreceptors 31**

Reza Mofidi and Barnabas Rigden Green

Masanori Kawasaki, Shinichi Yoshimura and Kiyofumi Yamada

Ricardo Luis Beigelman, Andrés María Izaguirre, Francisco Azzato

Hussien Heshmat Kassem, Foad Abd-Allah and Mohammad Wasay

Elias Skopelitis, Dimitrios Levisianou, Helen Lydataki and Sofoklis

Lindsay Gates and Jeffrey Indes

Chapter 2 **Tissue Characterization of Carotid Plaques 19**


*Edited by Xianli Lv*

Clinical trials are research studies performed in people that are aimed at evaluating a medical device, drug, or surgical or behavioral intervention. They are the primary way that researchers find out if a new treatment, like a new drug or medical device (e. g., a neuroendovascular device) is safe and effective for patients. A clinical trial is used to confirm if a new treatment is more effective and/or has less harmful side effects than the standard treatment. Other clinical trials test methods of early disease detection, sometimes before there are any symptoms. Still, others test methods to prevent health problems. A clinical trial may also look at how to improve the quality of life in those individuals with a life-threatening disease or chronic health problem. Clinical trials sometimes even study the role of caregivers or support groups. Therefore, clinical trials are very important in the development of medicine. A good clinical trial can influence therapeutic modality and even transform our healthcare work. This book provides a comprehensive review of clinical trials.

ISBN 978-1-83768-068-9

Frontiers in Clinical Trials

Published in London, UK © 2023 IntechOpen © gopixa / iStock


**5. Examination and diagnosis**

Up to 90% of infants born with CLP suffer from OME before their first birthday [2]; therefore, it is recommended that otologic tests be conducted as soon as possible after birth to ascertain whether fluid has collected in the middle ear [21, 32]. The use of a pneumatic otoscope is the fastest and most direct method used for the inspection of the eardrum for color and contour and determining whether fluid has collected in the middle ear. It should be noted that the effectiveness of a pneumatic otoscope to test for OME depends on the experience and skill of the clinicians, the patient's full cooperation, and the anatomical structure of the ear canal [2].

Another method for inspecting the eardrum is videotelescopy. A telescope is placed against the eardrum through the external ear canal, and a charge‐coupled device (CCD) camera cap‐ tures images of the eardrum. The resulting magnified images can be presented on a mon‐ itor, thereby allowing clinicians to accurately diagnose middle ear effusion [33]. Guo and Shiao conducted a prospective study on the diagnostic efficacy of videotelescopy, pneumatic otoscopy, and tympanometry for the detection of pediatric OME. Their results demonstrate that the sensitivity, specificity, and accuracy of the videotelescopy were 97.8, 100, and 98.0%, respectively. These values significantly exceed the accuracy of conventional tests using pneu‐ matic otoscope and tympanometry [33]. Videotelescopy provides clinicians with visual infor‐ mation with which to validate the accuracy of the pneumatic otoscopy.

Pneumatic otoscopy and even videotelescopy are difficult to administer on newborns and small infants with CLP. Thus, objective acoustic immittance testing plays an important role in the diagnosis of OME in CLP patients [34]. Tympanometry is the most commonly used acoustic immittance test to measure pressure changes in the middle ear and the compliance of the eardrum [27]. Chen et al. found that the specificity of tympanometry, when used to test for OME in infants with CLP, was relatively low (only 59.6%). When used to test infants within 9 months of age, specificity dropped to only 37.5% [28]. Furthermore, when infants are crying or unable to cooperate during testing, it can be difficult to maintain airtight conditions in the ear, thereby preventing successful completion of the examination.

Pure tone audiometry can also be used to facilitate the diagnosis of OME; the results may reveal conductive or mixed hearing loss. The cooperation of children is required for this procedure, which means that it may be unsuitable for children under 3 years of age [35]. For patients in this age group, spectral gradient acoustic reflectometry (SGAR) may be an effective alternative to pure tone audiometry in the diagnosis of OME. SGAR transmits ultrasound waves to the eardrum, whereupon a microcomputer is used to filter, record, and analyze the ultrasound waves reflected back. SGAR is an efficient diagnostic tool for the detection of OME, requiring less than one second to complete the procedure. Although the sensitivity and specificity are somewhat low, SGAR is a noninvasive test that is unaffected by crying, cerumen, client cooperation, or the quality of the air seal in the ear, thereby making it useful for testing difficult infants [28, 36–38].