Search results

Playing video gaming is one of the most popular forms of leisure activities. This study looks into a specific video game genre, under the category of Multiplayer Online Battle Arena (MOBA) games. The purpose of this research is to investigate the factors that lead to the consumption of MOBA games. Three factors, imaginal, emotional and sensory experiences, are investigated through an integration of the hedonic consumption model, Technology Acceptance Model (TAM) and Uses and Gratification Theory (UGT).

The study analyses a sample of 292 MOBA game players using the PLS-SEM model. The study comprises two stages; in the first stage, an estimation model was used to test the constructs' quality and legitimacy. In the second stage, we assessed the theoretical model to test the relationship between the principle constructs.

The study found that factors related to emotional experiences, namely enjoyment, emotional involvement, and arousal, led to greater intention to play MOBA games. Similarly, two factors related to imaginal experiences, escapism and role projection, also positively impacted while fantasy carried a negative impact. The study also found that sensory experiences had a significant positive impact on the intention to play MOBA games. Lastly, a positive correlation was also found between the intention to use and usage behavior in MOBA games.

This study contributes to the theoretical understanding of the playful-consumption experiences of pleasure-oriented information systems (I.S.) that is MOBA games that derive behavioral intention to play MOBA games, which in turn determines the usage behavior of MOBA players. The study also incorporates the uses and gratification theory to uncover the needs and experiences that trigger MOBA games' behavioral intention and its further impact on gamers' usage behavior. The study also presents useful insights for game developers and other relevant stakeholders in game development.

This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

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.

The purpose of this paper is to investigate an alternative simplified analytical approach for the design of electric machines. Numerical-based finite element method (FEM) is a powerful tool for accurate modelling and electromagnetic performance analysis of electric machines. However, computational complexity, magnetic saturation, complex stator structure and time consumption compel researchers to adopt alternate analytical model for initial design of electric machine especially flux switching machines (FSMs).

In this paper, simplified lumped parameter magnetic equivalent circuit (LPMEC) model is presented for newly developed segmented PM consequent pole flux switching machine (SPMCPFSM). LPMEC model accounts influence of all machine parts for quarter of machine which helps to reduce computational complexity, computational time and drive storage without affecting overall accuracy. Furthermore, inductance calculation is performed in the rotor and stator frame of reference for accurate estimation of the self-inductance, mutual inductance and dq-axis inductance profile using park transformation.

The developed LPMEC model is validated with corresponding FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy of ∼98.23%, and park transformation precisely estimates the inductance profile in rotor and stator frame of reference.

The model is developed for high-speed brushless AC applications.

The proposed SPMCPFSM enhance electromagnetic performance owing to partitioned PMs configuration which make it different than conventional designs. Moreover, the developed LPMEC model reduces computational time by solving quarter of machine.

This paper aims to reviewed analytical methodologies, i.e. lumped parameter magnetic equivalent circuit (LPMEC), magnetic co-energy (MCE), Laplace equations (LE), Maxwell stress tensor (MST) method and sub-domain modelling for design of segmented PM(SPM) consequent pole flux switching machine (SPMCPFSM). Electric machines, especially flux switching machines (FSMs), are accurately modeled using numerical-based finite element analysis (FEA) tools; however, despite of expensive hardware setup, repeated iterative process, complex stator design and permanent magnet (PM) non-linear behavior increases computational time and complexity.

This paper reviews various alternate analytical methodologies for electromagnetic performance calculation. In above-mentioned analytical methodologies, no-load phase flux linkage is performed using LPMEC, magnetic co-energy for cogging torque, LE for magnetic flux density (MFD) components, i.e. radial and tangential and MST for instantaneous torque. Sub-domain model solves electromagnetic performance, i.e. MFD and torque behaviour.

The reviewed analytical methodologies are validated with globally accepted FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy. In comparison of analytical methodologies, analysis reveals that sub-domain model not only get rid of multiples techniques for validation purpose but also provide better results by accounting influence of all machine parts which helps to reduce computational complexity, computational time and drive storage with overall accuracy of ∼99%. Furthermore, authors are confident to recommend sub-domain model for initial design stage of SPMCPFSM when higher accuracy and low computational cost are primal requirements.

The model is developed for high-speed brushless AC applications.

The SPMCPFSM enhances electromagnetic performance owing to segmented PMs configuration which makes it different than conventional designs. Moreover, developed analytical methodologies for SPMCPFSM reduce computational time compared with that of FEA.

The study aims to examine the relationship between personality traits and investor risk behavior of the individuals trading in stock markets. Furthermore, this study establishes the association of financial literacy on the relationship between personality traits and investor risk behavior.

The authors analyze cross-sectional survey method data by using moderated multiple regression analysis, a standard method of determining the moderation effect. PROCESS Model method has been used in this study to check the robustness of the results.

The findings reveal that personality traits significantly influence investor risk behavior and financial literacy modifies the fundamental relationships between personality traits and investor risk behavior. The findings also conclude that behavioral impact was predetermined by individuals' genetic traits and is influenced by financial literacy.

The current study provides valuable insights for investors and adamant grounds for future research. The two-fold role of individuals' personalities in case of gains and losses can be of interest to the researchers in future.

Investors currently facing the complex financial choices which are far beyond the day-to-day financial advice. This study guides rational investment behavior for portfolio managers and investors for advanced investment options.

Most of the prior literature is based on developed markets, whereas the current study focuses on less literate society (i.e. Pakistan) to protect the investors from scams and fraud. The current study supports the vital role of investors in the socio-economic development of emerging markets.

The authors believe this study expands the boundaries of personality theories, especially in the context of risk behavior and financial literacy. The study also contributes to advancing the personality theory trimmed with financial literacy and investor behavior while making important theoretical inroads for future research.

The purpose of this paper is to investigate the effect of materials, three dimensional (3D) structure and number of fabric layers on ultraviolet protection factor (UPF), air permeability and thickness of fabrics.

Total 24 fabrics samples were developed using two 3D structures and two weft materials. In warp direction cotton (CT) yarn and in weft direction polypropylene (PP) and polyester (PET) were used. Air permeability, thickness and UPF testings were performed and relationship among fabric layers, air permeability, thickness and UPF was developed.

UPF and thickness of fabrics increases with number of fabric layers, whereas air permeability decreases with the increase in number of fabric layers. Furthermore, change of multilayer structure from angle interlock to orthogonal interlock having same base weave does not give significant effect on UPF. However, change of material from polyester (PET) to polypropylene (PP) has a dominant effect on UPF. Minimum of three layers of cotton/polyester fabric, without any aid of ultraviolet radiation (UV) resistant coating, are required to achieve good. Cotton/polyester fabrics are more appropriate for outdoor application due to their long-term resistance with sunlight exposure.

Long-term exposure to UV is detrimental. So, there is need of proper selection of material and fabric to achieve ultraviolet protection. 3D fabrics have yarns in X, Y as well as in Z directions which provide better ultraviolet protection as compared to two dimensional (2D) fabrics. In literature, mostly work was done on ultraviolet protection of 2D fabrics and surface coating of fabrics. There is limited work found on UPF of 3D woven fabrics.

The coronavirus disease 2019 (COVID-19) epidemic has given an upsurge to online retailing in Pakistan. This shift has escalated the issues about privacy concerns among consumers. Keeping in view the growing concerns, the objective of this study is to investigate customer patronage in online shopping and the role of privacy concerns in this relationship.

To generalize the relationship between antecedents and outcomes of privacy concerns, a cross-disciplinary macro model was used. Data were collected through a survey method from the consumers who used credit and debit cards during online shopping.

Results show that government regulations have a significant positive relationship with privacy concerns and customer patronage. Privacy concerns are found to have a significant negative relationship with organizational ethical care while customer patronage was found to have a significant positive relationship with organizational ethical care. Customer patronage was also found to have a significant negative relationship with privacy concerns. Privacy concerns mediated the relationship between government regulations and customer patronage, whereas privacy concerns does not mediate the relationship between organizational ethical care and customer patronage.

The research adds to the existing literature and highlights the customer behavior toward online shopping/e-commerce in developing economies. The research gives a direction to stakeholders to counter privacy concerns and ensure safer e-commerce practices.

This paper aims to evaluate the therapeutic potential of apple extracts against thrombocytopenia, i.e. decrease in platelet count.

Male Sprague Dawley rats were used to evaluate therapeutic potential of apple extracts. Diets enriched with apple fruit and seed’s ethanolic extract were provided to normal and KBrO₃-induced thrombocytopenic rats for 60 days. KBrO₃ was administered at level of 85 mg/Kg of body weight of rats to intentionally decrease the platelet count. Platelet count and other hematological parameters were monitored at monthly intervals to evaluate therapeutic effect of apple extracts against thrombocytopenia.

The results of current research portrayed that both apple seed and fruit extracts enriched diets increased the platelet count significantly (p < 0.05) in thrombocytopenic rats. It was observed that apple fruit extract-enriched diet (AFE) raised the platelet count to 14.72 and 33.07 per cent in normal and thrombocytopenic rats, respectively. Apple seed extract-enriched diet (ASE) raised the platelet count to 11.08 and 32.90 per cent in normal and thrombocytopenic rats, respectively. Other hematological parameters including white blood cells, red blood cells and hemoglobin were also significantly increased.

Thrombocytopenia is uprising problem in developing world including India and Pakistan accompanied by different diseases especially dengue and related complications. Because of questioning on therapies against thrombocytopenia, research on diet-based therapies, as a substitute to synthetic one, is increasing. Diet rich in antioxidant compounds including apple fruit and seeds are the limelight of manuscript.