Miracle-dz/UniFAR-FTUs huggingface dataset:
Antecedents of mobile marketing adoption by SMEs:Does industry variance matter?

ABSTRACT Although innovations such as mobile marketing offer targeting and a cost-effective approach to marketing that could be leveraged by small and medium-sized enterprises (SMEs), most SMEs have shown a noticeable skepticism toward adopting the innovation. To overcome this adoption inertia, more research is necessary. This study draws on an integrated framework with theoretical considerations from the technology–organization–environment (TOE) framework to examine how factors in the technology context (relative advantage, complexity, and compatibility), the organizational context (top management support, financial resource slack, and employee mobile marketing capability) and the environmental context (mobile marketing vendor support, competitive pressure, and customer pressure) predict marketing adoption behavior by South African SMEs. Using a comparative analysis, the study further ascertains whether industry variance moderates the factors predicting mobile marketing adoption behavior between manufacturing and tourism-sector SMEs. Data for the empirical testing of the integrated framework were randomly sourced from 201 SMEs in the manufacturing and tourism sectors. The results show that relative advantage, complexity, top management support, competitive pressure, and vendor support are key drivers of mobile marketing adoption in the overall sample of manufacturing and tourism sector SMEs in South Africa. However, the results not only show different set predictors of mobile marketing adoption between the manufacturing and tourism sector SMEs: they also emphasize that the relative importance of the salient determinants of the innovation’s adoption varies across the industries, suggesting that industry variance plays a significant moderating role in mobile marketing adoption decisions across the two SME sectors that are examined. The implications of the findings for researchers and practitioners interested in promoting a more favorably disposed adoption of mobile marketing at the SME interface are discussed.
RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases

Profiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. We characterised time-series of primary human naïve CD4+ T cells during early T helper type 1 differentiation with RNA-sequencing and mass-spectrometry proteomics. We performed computational time-series analysis in this system and in two other key human and murine immune cell types. Linear mathematical mixed time delayed splice variant models were used to predict protein abundances, and the models were validated using out-of-sample predictions. Lastly, we re-analysed RNA-seq datasets to evaluate biomarker discovery in five T-cell associated diseases, further validating the findings for multiple sclerosis (MS) and asthma. The new models significantly out-performing models not including the usage of multiple splice variants and time delays, as shown in cross-validation tests. Our mathematical models provided more differentially expressed proteins between patients and controls in all five diseases. Moreover, analysis of these proteins in asthma and MS supported their relevance. One marker, sCD27, was validated in MS using two independent cohorts for evaluating response to treatment and disease prognosis. In summary, our splice variant and time delay models substantially improved the prediction of protein abundance from mRNA expression in three different immune cell types. The models provided valuable biomarker candidates, which were further validated in MS and asthma.
Conclusions

Abstract This chapter draws conclusions and makes future recommendations on the management of parthenium weed (Parthenium hysterophorus), based on extensive information reviewed in different chapters of the book. There are some research gaps, particularly in quantification of economic losses and health effects of parthenium weed. The chapter also examines integrated management options and the way forward in the management of the weed under changing environmental conditions. Finally, this chapter looks at the gaps in our knowledge and how we might close these with collaborative programmes of research around the globe.
Disturbed Lipid Metabolism in Diabetic Patients with Manifest Coronary Artery Disease Is Associated with Enhanced Inflammation

Background: Diabetic vasculopathy plays an important role in the pathophysiology of coronary artery disease (CAD) with oxidative stress as a strong mediator. This study aims to elucidate the underlying pathomechanisms of diabetic cardiac vasculopathy leading to coronary disease with an emphasis on the role of oxidative stress. Therefore, novel insights into antioxidant pathways might contribute to new strategies in the treatment and prevention of diabetic CAD. Methods: In 20 patients with insulin-dependent or non-insulin dependent diabetes mellitus (IDDM/NIDDM) and 39 non-diabetic (CTR) patients, myocardial markers of oxidative stress, vasoactive proteins, endothelial nitric oxide synthase (eNOS), activated phosphorylated eNOS (p-eNOS), and antioxidant enzymes, e.g., tetrahydrobiopterin generating dihydrofolate reductase (DHFR), heme oxygenase (HO-1), as well as serum markers of inflammation, e.g., E-selectin, interleukin-6 (IL-6), and lipid metabolism, e.g., high- and low-density lipoptrotein (HDL- and LDL-cholesterol) were determined in specimens of right atrial tissue and in blood samples from type 2 diabetic and non-diabetic patients undergoing coronary artery bypass graft (CABG) surgery. Results: IDDM/NIDDM increased markers of inflammation (e.g., E-selectin, p = 0.005 and IL-6, p = 0.051), decreased the phosphorylated myocardial p-eNOS (p = 0.032), upregulated the myocardial stress response protein HO-1 (p = 0.018), and enhanced the serum LDL-/HDL-cholesterol ratio (p = 0.019). However, the oxidative stress markers in the myocardium and the expression of vasoactive proteins (eNOS, DHFR) showed only marginal adverse changes in patients with IDDM/NIDDM. Conclusion: Dyslipidemia and myocardial inflammation seem to be the major determinants of diabetic CAD complications. Dysregulation in pro-oxidative enzymes might be attributable to the severity of CAD and oxidative stress levels in all included patients undergoing CABG.
The Effects of Accounting and Market Indicators towards Stock Return of Amman Stock Exchange Index Constituents

The returns of ASE companies and share trading have significantly weakened. Numerous companies have been liquidated due to bankruptcy. Investors appear to be less able to find desired investments under these critical conditions. In addition, the investors in Amman Stock Exchange face challenges in determining the accounting and market indicators that affect the stock return. Therefore, this study investigates the effect of twelve accounting and market indicators on the stock return. A yearly data of indicators and company stock price are collected from the ASE website. Panel generalised least squares regression analysis (GLS) has been conducted to accomplish the research objective. Out of twelve accounting and market indicators, the study revealed the TOA had the highest significantly positive effect on stock return. ROA, EPS, STR, and PBV also had a significant positive influence on stock return. In addition, DR had a significantly negative impact on stock return, while the effect of BPS was marginally negative. Besides, MC, ROE, NPM, CR, and PER did not affect the stock return. This study could help investors and portfolio managers to identify the indicators that affect stock returns of ASE Index companies. Further studies in other emerging markets will support the results that came out in this study.
Genetic Hybrid Optimization of a Real Bike Sharing System

In recent years there has been a growing interest in resource sharing systems as one of the possible ways to support sustainability. The use of resource pools, where people can drop a resource to be used by others in a local context, is highly dependent on the distribution of those resources on a map or graph. The optimization of these systems is an NP-Hard problem given its combinatorial nature and the inherent computational load required to simulate the use of a system. Furthermore, it is difficult to determine system overhead or unused resources without building the real system and test it in real conditions. Nevertheless, algorithms based on a candidate solution allow measuring hypothetical situations without the inconvenience of a physical implementation. In particular, this work focuses on obtaining the past usage of bike loan network infrastructures to optimize the station’s capacity distribution. Bike sharing systems are a good model for resource sharing systems since they contain common characteristics, such as capacity, distance, and temporary restrictions, which are present in most geographically distributed resources systems. To achieve this target, we propose a new approach based on evolutionary algorithms whose evaluation function will consider the cost of non-used bike places as well as the additional kilometers users would have to travel in the new distribution. To estimate its value, we will consider the geographical proximity and the trend in the areas to infer the behavior of users. This approach, which improves user satisfaction considering the past usage of the former infrastructure, as far as we know, has not been applied to this type of problem and can be generalized to other resource sharing problems with usage data.
Efficient Steganography in JPEG Images by Minimizing Performance of Optimal Detector

Since the introduction of adaptive steganography, most of the recent research works seek at designing cost functions that are evaluated against steganalysis methods. While those approaches have been successful, they rely on intuitive principles and ad-hoc costs associated with each pixel or Discrete Cosine Transform (DCT) coefficient. Beyond the empirical assessments, the insights one can get from such approaches are very limited. On the opposite, this paper presents an original method for steganography in JPEG images that exploits a statistical model of the DCT coefficients. Within the framework of hypothesis testing theory, we use a statistical model of covers to derive the analytical expression of the most powerful detector. The objective of the steganographer is to minimize the statistical performance of this “omniscient detector” which represents a “worst-case” scenario for security. This paper shows how this method allows designing effective steganography, in terms of both security and computational complexity, in the two main use cases: when having only one single JPEG image and when the uncompressed image is available, case also known as Side-Informed (SI). A wide range of numerical comparisons shows that the proposed method outperforms the current state-of-the-art especially against the latest and most accurate steganalysis approaches based on Deep Learning.
Semantic‐aware automatic image colorization via unpaired cycle‐consistent self‐supervised network

Automatic image colorization without manual interventions is an ill‐conditioned and inherently ambiguous problem. Most of existing methods focus on formulating colorization as a regression problem and learn parametric mappings from grayscale to color through deep neural networks. Due to the multimodalities of color‐grayscale space, in many applications, it is not required to recover exact ground‐truth color. Pair‐wise pixel‐to‐pixel learning‐based algorithms lack rationality. Techniques such as color space conversion techniques are then proposed to avoid such direct pixel learning. However, the coloring results after color space conversion are blunt and unnatural. In this paper, we hold viewpoints that a reasonable solution is to generate some colorized result that looks natural. No matter what color a region is to be assigned, the colorized region should be semantically and spatially consistent. In this paper, we propose an effective semantic‐aware automatic colorization model via unpaired cycle‐consistent self‐supervised network. Low‐level monochrome loss, perceptual identity loss and high‐level semantic‐consistence loss, together with adversarial loss, are introduced to guide network self‐training. We train and test our model on randomly selected subsets from PASCAL VOC 2012. The experimental results including human subjective studies demonstrate that, compared with state‐of‐the‐art methods, our proposed model can achieve more convincing and superior results. Relevant source code is available at https://github.com/YuSuen/ACCycleGAN.
Three-dimensional hollow graphene–metallic nanocomposite foam manufactured by polymer-templated electrochemical co-deposition

Due to its outstanding electrical, thermal, and mechanical properties, graphene (Gr) has been extensively studied in recent years as nanofiller for metallic nanocomposites. However, the manufacture of metallic nanocomposites with Gr as a nanofiller is still challenging especially for three-dimensional (3D) architectures. This study explores an electrochemical co-deposition process to manufacture Gr–metal nanocomposites at ambient conditions. Utilizing a polymer foam as the template, a 3D graphene–nickel (Gr–Ni) foam is fabricated by this simple, cost effective and scalable technique. The Gr–Ni nanocomposite foam is characterized by electron microscopy, Raman spectroscopy and mechanical testing. It is revealed that both the elastic modulus and the strength of the foam can be improved after incorporation of Gr. Measurement showed that with only 10 μm coating thickness, the mechanical properties of hollow Gr–Ni foam will be improved about 35% more than the pure hollow Ni foam. The polymer-templated co-deposition method is a potential process to fabricate Gr nanocomposites into more architectures.
APTA Cross Sections and Academies Recommendations for COVID-19 Core Outcome Measures

Purpose: The novel coronavirus (COVID-19) emerged as a major health concern within the United States in early 2020. Because this is a novel virus, little guidance exists for best practice to evaluate this population within the field of physical therapy. Methods: An expert task force appointed by the leadership of 9 different academies or sections of the American Physical Therapy Association was formed to develop recommendations for a set of core outcome measures for individuals with or recovering from COVID-19. Results: This perspective provides guidance on a best practice recommendation to physical therapists and researchers regarding the use of core outcome measures for individuals with or recovering from COVID-19. The process for the selection of core measures for this population is presented and discussed. Conclusions: Core outcome measures improve the ability to track progress and change across the continuum of care at both the patient and population levels.
Features of the Development of the Cognitive Sphere in Children with Different Online Activities: Is There a Golden Mean?

The paper presents the results of a comparative study of cognitive functions in preschoolers (5—7 years old, n=50), elementary school students (7—11 years old, n=50), younger adolescents (12—13 years old, n=53), and older adolescents (14—16 years old, n=47) with different intensity of daily use of digital devices: low, medium, controlled high, and uncontrollably high. A battery of neuropsychological methods was used to study the state of cognitive functions. The main differences in accordance with online activity were found in groups of elementary school students and younger adolescents: results were obtained confirming that children using the Internet at medium frequency (1—3 hours per day) are effective in performing a number of cognitive tasks (regulation, control, dynamical praxis, verbal and visual-spatial functions, and neurodynamics). In this study, a certain optimum of online activity time was outlined for different age groups, in the presence of which higher levels of development of certain cognitive functions are recorded.
ONLINE FEEDBACK IMPACT ONLINE SHOPPERS' IMPULSE PURCHASES IN MALAYSIA

Online shopping has risen to the third position among Malaysians who use the Internet. Typically, past customer online reviews are deciding factors for an online business's success or failure because online consumers encounter online reviews while visiting a website, and it has a direct effect on their ability to purchase impulsively and online impulse buying conduct. The majority of previous research on market-generated context as a factor in online impulse buying behaviour has concentrated on the market-generated background. As a result, this research identified two types of online reviews as independent variables: hedonic and utilitarian value online reviews, browsing, and willingness to buy impulsively as mediating and moderating variables. While online impulse buying behaviour a dependent variable. This study only involves online shoppers who have made at least one purchase on both Lazada Malaysia and Shopee Malaysia websites. This study took a quantitative approach, with 100 responses collected from online shoppers who had made at least one purchase on Shopee Malaysia and Lazada Malaysia through an online questionnaire. Due to the deletion of one straight-lining response, 99 responses were subjected to data analysis using SmartPLS software. According to the results, hedonic value online reviews influence browsing, and browsing influences the urge to buy impulsively and directly to online impulse purchasing.
HABITS OF HIGHLY PRODUCTIVE INFORMATION SYSTEMS USERS: A LOOK AT ONE UNIVERSITY'S FACULTY, STAFF, AND STUDENTS

The adoption and use of information systems can help system users realize higher levels of productivity, but are people using systems in ways to help them achieve this aim? This paper explores the use of information systems and examines how stakeholders rank their productive use of technology. Four research questions were explored in order to delve deeper into the productivity of system users across a university campus, drilling down to the productivity of three underlying stakeholder groups: students, staff, and faculty. Furthermore, the study explores the breakdown of these three groups based on age and gender. The study found that, as a whole, West Liberty University is only 28% productive when using information systems. The study concludes with recommendations to educate the stakeholders on highly productive information systems habits. Finally, Steven Covey’s Seven Habits of Highly Effective People is presented as a resource to help stakeholder groups become more productive information systems users.
The demand for life insurance in a developing country and the mediating role of persuasion

This study examines the demand for life insurance in a rapidly developing economic environment in South East Asia, focusing on Malaysia. The study extends the Elaboration Likelihood Model (ELM) by introducing a mediating variable ‘Persuasion’ in examining the demand for life insurance among policy buyers. Fuelled by the recent COVID-19 pandemic, the life insurance market is expected to grow significantly and the role of the state and regulatory body to regulate this process would be pivotal. Given the increasing significance of this industry both before and after the epidemic, this study identifies seven research variables from previous literature sources related to finance and international insurance, including financial literacy, saving motives, religiosity, risk aversion, agent, persuasion and purchase intention of life insurance. A causal research design is used to formulate research framework and testable hypotheses for this study. Data collection encompasses face to face interviews with 385 life insurance policy holders between May 2019 and March 2020 by using a survey questionnaire. Data analysis is mainly based on PLS-SEM method by using SPSS and Smart PLS statistical software packages. Results reveal persuasion as an important construct that explains the demand for life insurance, while agent is found to have the highest impact towards persuasion. The study also finds a full mediation effect of persuasion in the demand for life insurance for risk aversion and agent. These findings add new insights to the body of knowledge in life insurance literatures. Furthermore, research is useful for policy makers including government, finance, and insurance agencies;and recommends relevant strategies to further improve life insurance penetration in the population.
On the monoid of monic binary quadratic forms

We consider the quadratic form x 2 C mxy C ny 2 , where j m 2 (cid:0) 4n j is a prime number. Under the assumption that a particular, small, ﬁnite set of integers is representable, we determine all integers representable by this quadratic form.
Propaganda in Contemporary Public Relations

: The contemporary theories in public relations—the excellence theory (Grunig & Hunt) and the dialogic theory (Kent & Taylor)—claim two-way dialog communication as the tenet of the theories. Propaganda, as the original root of public relations, is refused by both theories. This paper aims to analyze whether any propaganda elements have survived in both theories and practices nowadays. Investigating propaganda and public relations concepts propaganda theorist Edward Bernays, three elements are found in public relations' practices today: ‘manipulation,' ‘goals oriented,' and ‘one-way communication flow. ' Despite the ubiquity of interactive media in public relations practices, propaganda elements are still commonly found, and two-way dialogic communication in social media is overrated.
Abrasive Wear of High-Carbon Low-Alloyed Austenite Steel: Microhardness, Microstructure and X-ray Characteristics of Worn Surface

A high-carbon, high-silicon steel (1.21 wt% C, 2.56 wt% Mn, 1.59 wt% Si) was subjected to quenching from 900 and 1000 °C, resulting in microstructures containing 60 and 94% of retained austenite, respectively. Subsequent abrasive wear tests of quenched samples were performed using two-body abrasion and three-body abrasion testing machines. Investigations on worn surface and subsurface were carried out using SEM, XRD, and microhardness measurement. It was found that the highest microhardness of worn surface (about 1400 HV0.05) was achieved on samples quenched from 900 °C after three-body abrasion. Microhardness of samples after two-body abrasion was noticeably smaller. with a maximum of about 1200 HV0.05. This difference correlates with microstructure investigations along with XRD results. Three-body abrasion has produced a significantly deeper deformed layer; corresponding diffractograms show bigger values of the full width at half maximum parameter (FWHM) for both α and γ alone standing peaks. The obtained results are discussed in the light of possible differences in abrasive wear conditions and differing stability of retained austenite after quenching from different temperatures. It is shown that a structure of metastable austenite may be used as a detector for wear conditions, as the sensitivity of such austenite to phase transformation strongly depends on wear conditions, and even small changes in the latter lead to significant differences in the properties of the worn surface.