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Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

The purpose of this paper is to study elastic properties of III-V nitride nanotubes (NNTs) using second generation (REBO) potential.

In the present research paper elastic properties of BN, AlN and GaN nanotubes have been investigated, using the second generation REBO potential by Brenner and co-workers, which is a bond order potential earlier used for carbon nanostructures successfully. In the present calculation, the same form of potential is used with adjusted parameters for h-BN, h-AlN and h-GaN. In all these cases the authors have considered graphite like network and strongly polar nature of these atoms so electrostatic forces are expected to play an important role in determining elastic properties of these nanotubes. The authors generate the coordinates of nanotubes of different chirality’s and size. Each and every structure thus generated is allowed to relax till the authors obtain minima of energy. The authors then apply the requisite compressions, elongations and twists to the structures and compute the elastic moduli. Young’s Modulus, Shear Modulus and Poisson’s ratio for single-walled armchair and zigzag tubes of different chirality’s and size have been calculated. The computational results show the variation of Young’s Modulus, Poisson’s ratio and Shear Modulus for these NNTs with nanotube diameter. The results have been compared with available data, experimental as well as theoretical.

The authors have calculated bond length, cohesive energy/bond, Strain energy, Young’s Modulus, Shear Modulus and Poisson’s ratio.

To the best of the knowledge this work is the first attempt to study elastic properties of III-V NNTs using second generation REBO potential

The purpose of this study was to determine the rate of concordance and discordance between clinical diagnosis and post‐mortem findings in patients admitted to the hospitals of the Saskatoon Health Region.

A retrospective record review of the medical and autopsy charts was carried out for all the deceased adult in‐patients admitted during calendar years 2002, 2003 and 2004. A total of 3416 in‐patient deaths were registered during the study period. Autopsies were performed on 206 of the deceased resulting in an autopsy rate of 6 percent. In accordance with selection criteria, 158 cases were included for this study. The mean age of subjects was 66.6±15.3 years with a range of 16‐94 years. The study group consisted of 92 males (58.2 percent) and 66 females (41.8 percent) with an average length of stay at the hospital of 12.9±10.9 days.

The concordance rate between clinical and autopsy diagnosis was found to be 75.3 percent. The discordance rate was 20.9 percent and in 3.8 percent of the study population a conclusive clinical or autopsy diagnosis was not finalized.

These results suggest that despite of the technical advances in medical and diagnostic modalities, diagnostic discrepancies in the present day health care system remain prevalent.

The authors encourage residents and physicians to continue using autopsy as an important tool to extend understanding of disease processes.

Phishing is one of the major threats affecting businesses worldwide in current times. Organizations and customers face the hazards arising out of phishing attacks because of anonymous access to vulnerable details. Such attacks often result in substantial financial losses. Thus, there is a need for effective intrusion detection techniques to identify and possibly nullify the effects of phishing. Classifying phishing and non-phishing web content is a critical task in information security protocols, and full-proof mechanisms have yet to be implemented in practice. The purpose of the current study is to present an ensemble machine learning model for classifying phishing websites.

A publicly available data set comprising 10,068 instances of phishing and legitimate websites was used to build the classifier model. Feature extraction was performed by deploying a group of methods, and relevant features extracted were used for building the model. A twofold ensemble learner was developed by integrating results from random forest (RF) classifier, fed into a feedforward neural network (NN). Performance of the ensemble classifier was validated using k-fold cross-validation. The twofold ensemble learner was implemented as a user-friendly, interactive decision support system for classifying websites as phishing or legitimate ones.

Experimental simulations were performed to access and compare the performance of the ensemble classifiers. The statistical tests estimated that RF_NN model gave superior performance with an accuracy of 93.41 per cent and minimal mean squared error of 0.000026.

The research data set used in this study is publically available and easy to analyze. Comparative analysis with other real-time data sets of recent origin must be performed to ensure generalization of the model against various security breaches. Different variants of phishing threats must be detected rather than focusing particularly toward phishing website detection.

The twofold ensemble model is not applied for classification of phishing websites in any previous studies as per the knowledge of authors.

The complications caused by metallic orthopaedic bone screws like stress-shielding effect, screw loosening, screw migration, higher density difference, painful reoperation and revision surgery for screw extraction can be overcome with the bioabsorbable bone screws. This study aims to use additive manufacturing (AM) technology to fabricate orthopaedic biodegradable cortical screws to reduce the bone-screw-related-complications.

The fused filament fabrication technology (FFFT)-based AM technique is used to fabricate orthopaedic cortical screws. The influence of various process parameters like infill pattern, infill percentage, layer height, wall thickness and different biological solutions were observed on the compressive strength and degradation behaviour of cortical screws.

The porous lattice structures in cortical screws using the rapid prototyping technique were found to be better as porous screws can enhance bone growth and accelerate the osseointegration process with sufficient mechanical strength. The compressive strength and degradation rate of the screw is highly dependent on process parameters used during the fabrication of the screw. The compressive strength of screw is inversely proportional to the degradation rate of the cortical screw.

The present study is focused on cortical screws. Further different orthopaedic screws can be modified with the use of different rapid prototyping techniques.

The use of rapid prototyping techniques for patient-specific bone screw designs is scantly reported. This study uses FFFT-based AM technique to fabricate various infill patterns and porosity of cortical screws to enhance the design of orthopaedic cortical screws.

The coronavirus disease 2019 (COVID-19) pandemic has been reported to have a major impact on the mental health of an individual. Healing the mental stress, anxiety, depression and insomnia of an individual's immediate surroundings play a major role. Therefore, this study reviews how the built environment impacts the healing of an individual's state of mind.

Various works of literature on healing environments were analysed to create frameworks that can facilitate psychological healing through architectural elements. Articles were selected from various journals like SAGE, PubMed, Journal of Applied and Computational Mechanics (JACM), Routledge Taylor and Francis, Journal of Contemporary Urban Affairs (JCUA), ScienceDirect, and Emerald databases, news articles, official web pages, and magazines that have been referred.

Indicators (spatial, sensory comfort, safety, security, privacy and social comfort) are linked to sub-indicators (access, distractions and views) and design characteristics (indoor climate, interior view, outside view, privacy, communication, noise, daylighting, temperature) which help in better connection of the built environment with individual's mental health. From the above indicators, sub-indicators and design characteristics, the authors have come to a conclusion that a view to the outside with better social interaction has an in-depth effect on an individual's mental health.

This study predominantly talks about healing in hospitals but quarantining of COVID-19 patients happens in residences too. So, it is important to find the healing characteristics in residences and in which typology the recovery process is high.

This paper has been written completely by the author and the co-authors and has not been copied from any other sources.

The economic crisis triggered by the COVID-19 pandemic seriously jeopardized small businesses. To survive, many small businesses turned to their networks by launching crowdfunding “rescue” campaigns, which were very successful in eliciting both funding and community support. This study aims to explain this success from the backers' perspective by addressing support intentions in uncertain times. The authors examine backers' paradoxical behavior by investigating the influence of ambiguity aversion (individual uncertainty), business-level uncertainty and environmental uncertainty on backers' intentions to support small businesses and the interaction of uncertainty with backers' well-being.

Survey data from 230 backers of small business rescue campaigns were analyzed using structural equation modeling.

The findings indicate that ambiguity aversion negatively dominates backers' support intentions. However, under the mediating effect of well-being, business-level and environmental uncertainties positively impact backers' intentions, whereas ambiguity aversion becomes non-significant.

Uncertainties are supposed to have a negative influence on individual well-being. By contrast, this study shows that backers' well-being is influenced by the context of the crowdfunding campaign. Uncertain conditions can provide value in addition to the benefits gained by backers from supporting crowdfunding campaigns.

Besides with a large amount of Na⁺ and Cl⁻ ions in seawater, the presence of Mg⁺² and SO₄⁻² ions builds more complex corrosion mechanism. This paper aims to investigate the corrosion of embedded reinforcement in concrete with the environment of both Cl⁻ and SO₄⁻² anions associated Mg⁺² cation.

The concrete specimens were prepared by using ordinary Portland cement (OPC), and OPC blended with metakaolin (MK) for water to cementitious material ratio (w/cm) 0.48 and 0.51. The concrete mixes were contaminated with the addition of MgCl₂ alone and combined MgCl₂ and MgSO₄ in mix water. Reinforcement corrosion was evaluated by half-cell potential and corrosion current densities (I_corr) at regular intervals. Moreover, the influence of cementitious material type, salt type and w/cm ratio on electrical resistivity of concrete was also investigated. The statistical models were developed for electrical resistivity as a function of calcium to aluminium content ratio, compressive strength, w/cm ratio and age of concrete.

Although the corrosion initiation time increases in the concomitant presence of MgSO₄ and MgCl₂ as internal source compared to MgCl₂, I_corr values are higher in both OPC and MK blended concrete. However, electrical resistivity decreased with addition of MgSO₄. MK blended concrete performed better with increased resistivity, corrosion initiation time and decreased I_corr values.

This study reports statistical distributions for scattered I_corr of rebar in different concrete mixtures. Stepwise regression models were developed for resistivity by considering the interactions among different variables, which would help to estimate the resistivity through basic information.

This work seeks to present a systematic study that aimed to provide quantitative understanding of the fundamental factors that influence the chloride threshold of pitting corrosion of steel in concrete, by conducting a set of laboratory tests to assess the corrosion potential (E_corr) and pitting potential (E_pit) of steel coupons in simulated concrete pore solutions.

With the aid of artificial neural network, the laboratory data were used to establish a phenomenological model correlating the influential factors (total chloride concentration, chloride binding, solution pH, and dissolved oxygen (DO) concentration) with the pitting risk (characterized by E_corr−E_pit). Three‐dimensional response surfaces were then constructed to illustrate such predicted correlations and to shed light on the complex interactions between various influential factors.

The results indicate that the threshold [Cl⁻]/[OH⁻] of steel rebar in simulated concrete pore solutions is a function of DO concentration, pH and chloride binding, instead of a unique value.

The limitations and implications of the research findings were also discussed.

This research could have significant practical implications in predicting the service life of new or existing reinforced concrete in chloride‐laden environments.

This study further advances the knowledge base relevant to the chloride‐induced corrosion of steel rebar in concrete.

This paper aims to describe the characteristics and modeling of the variable pitch quadrotor. In a variable pitch quadrotor, unlike ordinary quadrotors that the force is generated by the rotors, the speed of the rotors is constant, and the force is generated by varying the pitch angle of blades.

In this paper, a sliding mode controller and an adaptive sliding mode controller are used to control the variable pitch quadrotor to have better performance.

The variable pitch mechanism has a wider control bandwidth, and it is able to produce a negative thrust that facilitates trajectory tracking and aggressive maneuvers. The simulation results indicate high performance of the proposed control scheme in presence of disturbance and changes in mass of the quadrotor.

The performance of the controllers for the variable pitch quadrotor is investigated through computer simulation with MATLAB software.