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Dysarthria is a neuromotor speech disorder caused by neuromuscular disturbances that affect one or more articulators resulting in unintelligible speech. Though inter-phoneme articulatory variations are well captured by formant frequency-based acoustic features, these variations are expected to be much higher for dysarthric speakers than normal. These substantial variations can be well captured by placing sensors in appropriate articulatory position. This study focuses to determine a set of articulatory sensors and parameters in order to assess articulatory dysfunctions in dysarthric speech.

The current work aims to determine significant sensors and parameters associated using motion path and correlation analyzes on the TORGO database of dysarthric speech. Among eight informative sensor channels and six parameters per channel in positional data, the sensors such as tongue middle, back and tip, lower and upper lips and parameters (y, z, φ) are found to contribute significantly toward capturing the articulatory information. Acoustic and positional data analyzes are performed to validate these identified significant sensors. Furthermore, a convolutional neural network-based classifier is developed for both phone-and word-level classification of dysarthric speech using acoustic and positional data.

The average phone error rate is observed to be lower, up to 15.54% for positional data when compared with acoustic-only data. Further, word-level classification using a combination of both acoustic and positional information is performed to study that the positional data acquired using significant sensors will boost the performance of classification even for severe dysarthric speakers.

The proposed work shows that the significant sensors and parameters can be used to assess dysfunctions in dysarthric speech effectively. The articulatory sensor data helps in better assessment than the acoustic data even for severe dysarthric speakers.

The analysis of fluid flow and thermal transport performance inside the cavity has found numerous applications in various engineering fields, such as nuclear reactors and solar collectors. Nowadays, researchers are concentrating on improving heat transfer by using ternary nanofluids. With this motivation, the present study analyzes the natural convective flow and heat transfer efficiency of ternary nanofluids in different types of porous square cavities.

The cavity inclination angle is fixed ω = 0 in case (I) and ω=π4 in case (II). The traditional fluid is water, and Fe3O4+MWCNT+Cu/H2O is treated as a working fluid. Ternary nanofluid's thermophysical properties are considered, according to the Tiwari–Das model. The marker-and-cell numerical scheme is adopted to solve the transformed dimensionless mathematical model with associated initial–boundary conditions.

The average heat transfer rate is computed for four combinations of ternary nanofluids: Fe3O4(25%)+MWCNT(25%)+Cu(50%),Fe3O4(50%)+MWCNT(25%)+Cu(25%),Fe3O4(33.3%)+MWCNT(33.3%)+Cu(33.3%) and Fe3O4(25%)+MWCNT(50%)+Cu(25%) under the influence of various physical factors such as volume fraction of nanoparticles, inclined magnetic field, cavity inclination angle, porous medium, internal heat generation/absorption and thermal radiation. The transport phenomena within the square cavity are graphically displayed via streamlines, isotherms, local and average Nusselt number profiles with adequate physical interpretations.

The purpose of this study is to determine whether the ternary nanofluids may be used to achieve the high thermal transmission in nuclear power systems, generators and electronic device applications.

The current analysis is useful to improve the thermal features of nuclear reactors, solar collectors, energy storage and hybrid fuel cells.

To the best of the authors’ knowledge, no research has been carried out related to the magneto-hydrodynamic natural convective Fe3O4+MWCNT+Cu/H2O ternary nanofluid flow and heat transmission filled in porous square cavities with an inclined cavity angle. The computational outcomes revealed that the average heat transfer depends not only on the nanoparticle’s volume concentration but also on the existence of heat source and sink.

The purpose of this paper is to synthesise new fatty dicarboxylic acid half ester (NFAHE) C25, which can be used as substitute to dimer/trimer acids commonly used (C36, 54) as basic raw materials for manufacture of polyamides for printing inks or as curing agents for epoxy paints and adhesives. This could be an economically viable synthesis by which the user could manufacture the finished products from relatively low cost raw materials.

Vegetable oils have several double bonds that undergo large number of reactions. Diels‐Alder addition is one of them. Dimer acids have been produced by using these double bonds by reaction of two fatty acid molecules. Maleic acid, acrylic acid has also been used for this purpose. Sorbic acid is a derivative of alcohol and hence a renewable raw material. It is relatively less used by the coating chemists due to its relatively limited availability due to restricted uses.

It was found that sorbic acid reacts easily with unsaturated fatty acids. Its solubility in fatty acids and esters is limited. A common solvent that can be removed easily after the reaction was necessary. Cyclohexanone was found to meet this requirement. The resultant half ester of dicarboxylic acid could be easily converted to polyamides for curing epoxies.

The user can manufacture his own dibasic/tribasic acid as a first step. As a source of methyl esters of fatty acids with iodine value about 110 to 130, vegetable oils such as soyabean oil can be used. Low value acid oils obtained from vegetable oil refining are also suitable. Bio diesel could be used directly. To account for large saturated fatty acids in bio diesel, corresponding trimer may be produced by appropriate addition of sorbic acid to fatty acid.

The process allows a manufacturer to develop low cost formulations for bulk products using simple chemistry that can be integrated in the existing process.

The purpose of this paper was to assess and compare beliefs about mental illness among pharmacy and non-pharmacy students and to explore its associated factors.

This research was a cross-sectional survey conducted among undergraduate pharmacy and non-pharmacy students of a Nigerian university. The selected participants completed the Belief toward Mental Illness questionnaires after usual class lectures. Descriptive statistics, χ² test, and t-test were used for data analysis. The level of significance was set at p<0.05.

Overall, pharmacy and non-pharmacy undergraduate students demonstrated negative beliefs about mental illness. There were no substantial differences in beliefs about mental illness among both groups of students. Students’ class, age, visit to a mental hospital and personal experience of mental disorder were significantly associated with beliefs about mental illness.

The generalization of the study findings to other schools of pharmacy in Nigeria is uncertain because this study used convenience sampling technique and was conducted in a single public university. However, the study provides relevant educational opportunities to guide policy makers and university administrators on mental health literacy. Therefore, educational interventions addressing observed gaps in students’ opinions regarding mental illness are recommended.

There appears to be little or no data on the beliefs of undergraduate pharmacy trainees about mental disorders in Nigeria and Sub-Saharan Africa.

This paper tests whether Bayesian A/B testing yields better decisions that traditional Neyman-Pearson hypothesis testing. It proposes a model and tests it using a large, multiyear Google Analytics (GA) dataset.

This paper is an empirical study. Competing A/B testing models were used to analyze a large, multiyear dataset of GA dataset for a firm that relies entirely on their website and online transactions for customer engagement and sales.

Bayesian A/B tests of the data not only yielded a clear delineation of the timing and impact of the intellectual property fraud, but calculated the loss of sales dollars, traffic and time on the firm’s website, with precise confidence limits. Frequentist A/B testing identified fraud in bounce rate at 5% significance, and bounces at 10% significance, but was unable to ascertain fraud at the standard significance cutoffs for scientific studies.

None within the scope of the research plan.

Bayesian A/B tests of the data not only yielded a clear delineation of the timing and impact of the IP fraud, but calculated the loss of sales dollars, traffic and time on the firm’s website, with precise confidence limits.

Bayesian A/B testing can derive economically meaningful statistics, whereas frequentist A/B testing only provide p-value’s whose meaning may be hard to grasp, and where misuse is widespread and has been a major topic in metascience. While misuse of p-values in scholarly articles may simply be grist for academic debate, the uncertainty surrounding the meaning of p-values in business analytics actually can cost firms money.

There is very little empirical research in e-commerce that uses Bayesian A/B testing. Almost all corporate testing is done via frequentist Neyman-Pearson methods.

The purpose of this study was to examine the relationship between online banking fraud experience and fear of cybercrime and distrust of online banking services, and to understand how perceived usefulness of online banking moderates the relationship.

The number of respondents involved in this study was 271 people from the Central Java region, Indonesia. Statistical analysis was performed using Jeffreys’s Amazing Statistics Program software to examine the relationships and interactions between the variables studied.

Experience of online banking fraud is positively related to fear of cybercrime and distrust of online banking services. Perceived usefulness of online banking moderates the relationship between online banking fraud experience and fear of cybercrime and distrust of digital payments. Perceived usefulness is negatively related to the level of distrust of online banking services.

Overall, the implications of this study underscore the importance of dealing with the risks of cybercrime in online banking services. By focusing on security, user awareness and the role of perceived usefulness, banking service providers can create a safer and more trusting environment for users of online banking services. This also contributes to the development of more innovative services and can increase customer satisfaction and trust.

The practical application of these findings is important for financial institutions and online banking service providers. Companies must improve cybersecurity with the latest technology and provide education about online security practices. Transparent communication and better customer service will help overcome customer fears. Compliance with security regulations and technological innovation is also important to protect online banking services. With these steps, customer security and trust can be improved, and the adoption of online banking services will increase widely.

The social implications of this research are increasing public awareness about cybersecurity, consumer protection and strengthening trust in online banking services. With joint efforts, a safer and more trusting environment in using online banking services can be realized.

The originality of this research lies in the use of perceived usefulness of online banking as a moderating variable to reduce the negative impact of online banking fraud experience. With a focus on the psychological effects of customers experiencing fraud, this research seeks to rebuild trust and improve the security of online banking services.

The purpose of this paper is to minimize corrosion-related pollution in the environment. From the lemongrass extract (LGE), the authors selected one of the best green inhibitors.

The corrosion and inhibition of mild steel in traditional acidification solutions were estimated by electrochemical measurements. The corrosion appearance was observed with scanning electron microscopy, atomic force microscopy micrographs and attenuated total reflectance infrared spectroscopy spectrum. The correlation was formed between the gained inhibition efficiency (IE)% from electrochemical measurements and certain quantum chemical parameters.

The results displayed that the IE was up to 90% when the LGE concentration was 300 ppm. The results confirmed that the theoretical experiments are very similar to the experimental observations.

For the first time, LGE was used as a cheap and safe corrosion inhibitor for mild steel corrosion in the acidification process. The mechanism of mild steel corrosion and anti-corrosion in acid solution has been suggested.

The purpose of this study is to explore the impact of social media use on both empathy and well-being through using a five-factor model (FFM) of personality in the context of Saudi Arabia.

Data were collected from the 13 regions in Saudi Arabia. Confirmatory factor analysis was used to measure the reliability and validity of the study’s constructs and a structural equation modeling technique was applied to test the study hypotheses.

With a sample of 450 users, the regression results indicate a less significant relationship between personality and social media use, as well as between personality and affective empathy, while a more significant relationship between personality and cognitive empathy. Also, individuals’ well-being are influenced directly by the heavy use of social media.

The cross-sectional design used in this research may not be able to provide the true essence of the hypothesized relationships compared to the cause-effect design. This study furthers the understanding of the role of personality on empathy and well-being in social media among Saudis from one side and provides insights to professionals for better improvement of social media and so better individuals’ well-being from the other side.

This paper fills an untapped gap in a developing country context by exploring the relationship between the usage of social media and the two dimensions of empathy, which, in turn, influence well-being under the theoretical lens of an FFM personality.

The purpose of this paper is to produce a comprehensive and tabulated review of the many and scattered papers on public mental health literacy, with particular focus on people's ability to recognise mental illness and beliefs about the treatment.

This was a review and tabula study. Comprehensive tables describe studies: the first looks at the beliefs of three different groups (the general public, students and young people) within developed English-speaking countries, and the second on studies from non-English-speaking countries.

Some illnesses like depression and schizophrenia are well researched and others like anxiety or personality disorders largely ignored. The conclusion considers terminological (the loose use of different terms), theoretical (little or no theoretical models) and methodological (heavy reliance on printed, culture-bound vignettes) issues in the developing area of research.

No such review exists and this therefore should be of considerable value to people working in the area.

This review deals with the pros and cons of ultraviolet (UV) radiation on human beings and the role of textile clothing and the chemicals used for textiles to protect from their harmful effects.

UV radiation (UVR) which has further divided into UVA, UVB, and UVC. Almost 100% of UVC and major portion of UVB are bounced back to stratosphere by ozone layer while UVA enters the earth atmosphere. Excessive exposure of solar or artificial UVR exhibit potential risks to human health. UVR is a major carcinogen and excessive exposure of solar radiation in sunlight can cause cancer in the lip, skin squamous cell, basal cell and cutaneous melanoma, particularly in people with the fair skin.

This article aims to provide a comprehensive overview of the harmful effects of UVR on human skin, factors affecting UV irradiance and factors affecting UV protection offered by textile clothing.

Effect of fiber properties, yarn properties, fabric construction, fabric treatments and laundering has been reviewed along with the identification of gaps in the reported research. A comparison of inorganic and organic UV absorbers has also been given along with different testing and evaluation methods for UV protective clothing.