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Carpal tunnel syndrome (CTS) is a hand disease caused by the pressing of the median nerve present in the palmar side of the wrist. It causes severe pain in the wrist, triggering disturbance during sleep. Different products like splints, braces and gloves are available in the market to alleviate this disease but there was still a need to improve the wearability, comfort and cost of the product. This study was about designing a comfortable and cost-effective wearable system for mild-to-moderate CTS. Transcutaneous electrical nerve stimulation (TENS) therapy has been used to reduce the pain in the wrist.

After simulation by using Proteus software (which allowed the researchers to draw and simulate electrical circuits using ISIS, ARES and PCB design tools virtually), the circuit with optimum frequency, i.e. 33 Hz was selected, and the circuit was developed on a printed circuit board (PCB). The developed circuit was integrated successfully into the half glove structure.

The developed product had good thermophysiological comfort and hand properties as compared to the commercially available product of the same kind. In vivo testing (It involves the testing with living subjects like animals, plants or human beings) was performed which resulted in 85% confirmed viability of the product against CTS. A glove with an integrated circuit was developed successfully to accommodate various sizes without any sex specifications in a cost-effective way to mitigate the issue of CTS.

Industrial workers, individuals frequently using their hands or those diagnosed with CTS may wish to use this product as therapy. The attention could not be paid to the aesthetic or visual appeal of the developed product.

A very comfortable glove with integrated TENS electrodes was developed successfully to accommodate various sizes without any sex specifications in a cost-effective way to mitigate the issues of CTS.

This paper aims to evaluate the effect of plasma treatment on the performance and color strength of pigment printed polypropylene nonwovens fabrics.

Melt spun nonwoven fabrics have been treated with plasma discharge using oxygen as a reactive gas to activate their surfaces for better interfacial interactions. The untreated and plasma treated fabrics are printed using pigment print pastes to investigate the print properties of nonwoven fabrics that are correlated to surface characteristics. The printed fabrics are characterized through FTIR, color fastness to washing and rubbing, flexural rigidity and moisture management observations.

The fabrics treated with oxygen plasma exhibited higher wettability, higher overall moisture management capability, enhanced color strength and superior color fastness to washing. However, bending length and flexural rigidity have been increased.

This study offers promising findings regarding the surface activation of polypropylene nonwovens for enhanced performance, comfort and color fastness characteristics.

This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

This study investigates the impact of the COVID-19 pandemic on investors' sentiments, behavioral biases and investment decisions in the Pakistan Stock Exchange (PSX).

The authors have assessed investors' behaviors and sentiments and the stock market overreaction during COVID-19 using a questionnaire and collected data from 401 investors trading in the PSX.

Results of structural equation modeling revealed that the COVID-19 pandemic affected investors' behaviors, investment decisions and trade volume. It created feelings of fear and uncertainty among market participants. Evidence suggests that behavioral heuristics and biases, including representative heuristic, anchoring heuristic, overconfidence bias and disposition effect, negatively influenced investors' decisions at the PSX.

This study will contribute to behavioral finance literature in the context of developing countries as it has revealed the impact of COVID-19 on the emerging stock market, and its results are generalizable to other emerging stock markets.

The findings of this study will help academicians, researchers and policymakers of developing countries. Academicians can formulate new behavioral models that can depict the solutions of dealing with an uncertain situation like COVID-19. Policymakers like the Securities Exchange Commission and the PSX can formulate crisis management strategies based on behavioral finance concepts to cope with situations like COVID-19 in the future and help lessen investors' losses in the stock markets. The role of the Securities Exchange Commission is crucial as it regulates the financial markets. It can arrange workshops to educate investors to manage their decisions during crisis time and focus on the best use of irrational and rational decision-making at the same time using Lo (2004) adaptive market hypothesis.

The novelty of the paper is that the authors have introduced overconfidence and disposition effect as mediators that create a connection between representative and anchoring heuristics and investment decisions using primary data collected from investors (institutional and retail) to demonstrate the presence of psychological biases during COVID-19, and it has been done for the first time according to authors' knowledge. It is a contribution and addition to the behavioral finance literature in the context of developing countries' stock markets and their efficiency.

This research paper aims to analyze the stock exchanges of developed, emerging and developing countries to investigate the volatility in stock markets and to evaluate the rate of mean reversion.

The stock exchanges included in the research are NASDAQ, Tokyo stock exchange, Shanghai stock exchange, Bombay stock exchange, Karachi stock exchange and Jakarta stock exchange. Secondary daily data from Bloomberg are used to conduct the research for the period from January 2011 to December 2018. Generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model was applied to examine volatility and the half-life formula was used to calculate mean reversion in days.

The research concluded that all the stock exchanges included in the research satisfy the assumptions of mean reversion. Developing countries have the lowest volatility while emerging countries have the highest volatility which means that the rate of mean reversion is fastest in developing countries and slowest in emerging countries.

Future studies can determine the reasons for fastest rate of mean reversion in developing countries and slowest rate of mean reversion in emerging countries.

Developing countries show the lowest mean reversion in days while the emerging countries show the highest mean reversion in days indicating that developing countries take less time to revert to their mean position.

The majority of previous studies on univariate volatility models are mostly on applications of the models. Only a few researchers have taken the robustness of the models into account when applying them in emerging countries and not in developed, developing and emerging countries in one place. This makes the current study unique and more rigorous.

This research aims to examine how health consciousness, social identity, self-identity, trust and willingness to pay premium impact individuals’ intention to make green purchases, which in turn influences organic purchasing behavior. Additionally, the study tried to examine the moderating effect of willingness to pay premium.

Utilizing a purposive sampling approach, a questionnaire survey was used to gather information from 452 customers in India. The conceptual model was assessed, and the research hypotheses were examined using partial least squares structural equation modeling.

The results of this study showed that the intention to make green purchases is strongly influenced by consumers health consciousness, social identity and trust. However, self-identity did not influence consumers green purchase intention. Furthermore, the moderating effect of willingness to pay premium was significant, except for self-identity, in the relationship of health consciousness, willingness to pay premium social identity and trust with green purchase intention.

The research will help producers and marketers refine food and marketing tactics to promote a favorable perception of organic food products.

This study is pioneering in (1) investigating the moderating impact of willingness to pay premium (WLPP) in the relationship of health consciousness, social identity, self-identity and trust with green purchase intention and (2) investigating the influence of consumer identities on green purchase intention in the Indian context.