Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting website audience demographics based on browsing history

Objectives of the Study The objective of the study was to explore the possibility to predict demographics from browsing behavior of web users. To achieve this objective, the issue of predicting online audience demographics was addressed from three different perspectives. Firstly, the study addressed quality of input data for models and its impact on the accuracy of predictions. Then, it was analyzed how demographics of web users influences their online behavior and, finally, the focus laid on defining factors useful for predictions. Academic background and methodology Scientific literature has a record of several previous attempts to predict online audience demographics. Also, some studies examine demographic differences in online behavior. However, the issue of quality of input data for predictive models is almost entirely ignored. Two theoretical frameworks for the study were formed on the basis of the literature review. Other research method used in this study is statistical analysis including t-tests, z-tests, ANOVA, linear regression and logistic regression models. Findings and conclusions The study showed existence of several factors greatly deteriorating quality of input data for models predicting online audience demographics. This results in a decrease in accuracy of predictions in several ways such as smaller datasets, overestimation of the size of some demographic groups and incorrect models. Also, the study indicated that demographic groups show differences in online behavior including preferred website content, website visiting patterns over time and likelihood to click online ads. Thus, information on these aspects of online behavior can be used for predicting demographics of web users.
On the development and extensions of some classes of optimal three-point iterations for solving nonlinear equations

We develop a new families of optimal eight--order methods for solving nonlinear equations. We also extend some classes of optimal methods for any suitable choice of iteration parameter. Such development and extension was made using sufficient convergence conditions given in [14]. Numerical examples are considered to check the convergence order of new families and extensions of some well-known methods.
Are We Ready for New Technologies? The Relation Between Human Values and Technology Readiness Applied to M-Commerce in Brazil

Abstract This study describes the relation between human values and technology readiness in Brazilian mobile commerce (m-commerce). This study consisted of an online survey including the Portrait Values Questionnaire-Revised (PVQ-R), the Technology Readiness Index 2.0, and SES items in all Brazilian states (N=2,171). Our structural equation modeling showed that human values predicted technology readiness; and attitude, intention to purchase online via mobiles. Self-enhancement and openness to change positively influenced the technology readiness contributor factor, whereas self-transcendence negatively influenced the technology inhibitor factor, and conservation positively influenced it. Theoretical and managerial contributions developed a conceptual model involving human values, technology readiness, and intention to purchase online via mobiles. This study can help develop public policies related to information security, aiming to increase consumer confidence in using new technologies in m-commerce.
Effectiveness of blended learning in the first year of fashion education

ABSTRACT Fashion programmes have increased the use of e-learning and blended learning to enhance the levels of understanding of students on complex issues. The first year in higher education is important because it significantly affects future academic success and the completion rate of students. The effectiveness of blended learning for undergraduate students in their first year of study is explored by comparing the actual grades of students in a blended learning and in a traditional face-to-face classroom. Two first-year subjects, goal-setting and sewing, with blended learning activities are introduced. No significant difference exists in the actual grades of students who used the blended learning modules compared to the control group students. First-year fashion students are interested in blended learning with a positive uptake rate to enhance self-regulated learning. The diverse educational backgrounds of students and their prior learning experiences and needs must be considered to increase their engagement in online modules.
Designing a Model to Explicate Factors Influence the Process of IT User Adoption: (A Research about Iranian Offshore Engineering and Construction Company)

Technology acceptance model is a widely accepted model for explaining user behavior in technology adaptation. The coping model of user adaptation defines user adaptation as the cognitive and behavioral efforts performed by users to cope with significant IT events that occur in their work environment. This paper based on the combination of the mentioned models proposes a model for explicating factors influencing the process of IT user adaptation. A study of the research model in the Iranian Offshore Engineering and Construction Company (IOEC) provides preliminary support for our model. The data gathered from 350 users of project management information system (SAP) analyzed by structural equation model. The findings indicate significant impact of individual factors and also important role of usefulness in user believes forming. Our model offers predictive power while evaluating a new system most users perceived threats of the technology and consider its negative aspects. In the result, they choose strategies that unlikely has few impact on improving user effectiveness and efficiency, lead to reduce negative impacts of IT event and will enhance user assessment.
A tale about vipers’ tails: phylogeography of black-tailed rattlesnakes

The phylogenetic relationships among black-tailed rattlesnakes remain poorly understood and some authors indicated that the diversity of this group has been underestimated and additional analyses are required to clarify the biogeographic patterns throughout its distribution in Mexico. Therefore, the aim of this study was to elucidate the phylogenetic relationships among black-tailed rattlesnakes across their range, identifying relative divergence times among the main clades and reconstructing the biogeographical history of the group. Three partial mitochondrial genes (ND4, cytb and ATPase6) and one nuclear gene (RAG1) were sequenced to infer the phylogenetic relationships, through the maximum likelihood and Bayesian inference-based methods; demographic history reconstruction was investigated through Bayesian Skyline plot analysis and the ancestral area reconstruction was carried out considering a Bayesian framework. We found strong evidence that the black-tailed rattlesnakes’ group is composed of six clades, which is in agreement with subspecies previously reported. Divergence time estimation indicated that the origin of the C. molossus group could be traced to the middle of the Miocene (~7.71 Mya). Ancestral area reconstruction indicated that early divergence events occurred in Central Mexico, probably related to the geological dynamics of the Trans-Mexican Volcanic Belt. The lineage C. m. oaxacus is the basal member of the C. molossus group. Furthermore, the combination of geological events and changes in Quaternary vegetation may have contributed to the divergence of C. molossus clades. Our results suggest several clades within C. molossus complex could be potentially recognized as separate species.
Human Head Yaw Estimation Based on Two 3-Axis Accelerometers

The estimation of the orientation of an object, and a human head in particular, can be defined by the Euler angles: the yaw, pitch and roll. The robust and drift-free estimation of those angles is usually achieved with the data from several sensors such as accelerometers, gyroscopes and magnetometers, processed with sensor fusion algorithms. However, wearable devices such as hearing instruments are rarely equipped with all those sensors, and might usually only have a single accelerometer embedded per device. While it is possible to retrieve a correct estimation of the roll and pitch using only a single accelerometer, estimating the yaw is a more challenging task as accelerations around the gravity vector cannot be detected by an accelerometer. In the context of binaural communication devices and spatial hearing, the yaw of the head is a key information that helps achieving dynamic binaural synthesis. This work proposes an algorithm that aims at estimating the yaw of a human head by using only two 3-axis accelerometers that are placed at each side of the head. The algorithm is evaluated with acceleration measurements of human subjects achieving a realistic task. The results suggest that the strategy used is promising as a good performance can be achieved for a majority of the measures as long as an individualized set of parameters can be selected. The results also suggest that the performance of the current implementation is sensitive to sensor displacement after calibration or a wrong estimation during initialization.
An evaluation of partially nonergodic PGA ground-motion models for Japanese megathrust earthquakes

We used a ground-motion database of Japanese subduction interface (megathrust) earthquakes from the NGA-Subduction project to develop a series of ground-motion models (GMMs) for peak ground acceleration (PGA) that explore the effects of including random-effect event and station terms and differences in attenuation between forearc and backarc tectonic regions. The GMMs with the lowest standard deviations and the best goodness-of-fit metrics are those that include event and station terms and that differentiate between forearc and backarc attenuation using fractional travel paths within each region as distance metrics. In the best models, anelastic attenuation is found to be much greater in the backarc than in the forearc. The inclusion of station terms does not result in a geographic bias in anelastic attenuation as has been found in past studies. Inclusion of a rake-angle term is found to be marginally significant, whereas the addition of a volcanic-arc-crossing term is most important when station terms are excluded. We provide model coefficients, statistical significance of coefficients, standard deviations, and goodness-of-fit metrics for all of the GMMs explored in this study to show the impact of model assumptions as well as allow users the ability to select a model consistent with their application.
Convergent functional changes of the episodic memory impairment in mild cognitive impairment: An ALE meta-analysis

Background Mild cognitive impairment (MCI) is considered to be an intermediate stage between normal aging and Alzheimer's disease (AD). The earliest and most common symptom of MCI is impaired episodic memory. When episodic memory is impaired in MCI patients, specific functional changes occur in related brain areas. However, there is currently a lack of a unified conclusion on this change. Therefore, the purpose of this meta-analysis is to find MRI-specific functional changes in episodic memory in MCI patients. Methods Based on three commonly used indicators of brain function: functional connectivity (FC), the amplitude of low-frequency fluctuation /fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo), we systematically searched PubMed, Web of Science and Ovid related literature and conducted the strict screening. Then we use the activation likelihood estimation (ALE) algorithm to perform the coordinate-based meta-analysis. Results Through strict screening, this meta-analysis finally included 21 related functional neuroimaging research articles. The final result displays that functional changes of episodic memory in MCI patients are mainly located in the parahippocampal gyrus, precuneus, posterior cingulate gyrus, cuneus, middle temporal gyrus, middle frontal gyrus, lingual gyrus, and thalamus. Conclusions There are specific functional changes in episodic memory brain regions in MCI patients, and the brain functional network can regulate episodic memory through these brain regions. And these specific changes can assist in the early diagnosis of MCI, providing new ideas and directions for early identification and intervention in the process of MCI.
The Evolving Role of Radioembolization in the Treatment of Neuroendocrine Liver Metastases

Simple Summary This review provides basic insights into radioembolization, also known as selective internal radiation therapy, in patients suffering from neuroendocrine liver metastases. Radioembolization is a treatment that uses radioactive beads that are implanted intra-arterially to locally irradiate liver tumors. The available literature on radioembolization in neuroendocrine liver metastases show promising results in terms of efficacy and toxicity and will be discussed in more detail. However, data in the field of NELM need clarification, and this review also discusses the caveats, challenges and new insights when considering radioembolization in neuroendocrine liver metastases. Abstract At diagnosis, 21–50% of neuroendocrine tumors already have distant metastases, of which the liver is most commonly affected. Unfortunately, the presence of neuroendocrine liver metastases (NELM) is the most incriminating factor for survival. At NELM diagnosis, 60–70% of patients suffer from bilobar multifocal disease, making them ineligible for surgical resection. With limited systemic options, a clinical need for liver-directed treatments exists. Trans-arterial (bland) embolization, chemoembolization and radioembolization have been increasingly used in the treatment of NELM. In recent years, radioembolization (also known as selective internal radiation therapy) has gained attention due to promising tumor reductive results, limited toxicities and increasing scientific evidence. This review provides basic insights into radioembolization as a technique, a summary of available literature on radioembolization in NELM, and discusses caveats, challenges and new insights when considering radioembolization in NELM.
Localized Muscle Fatigue: Theoretical and Practical Aspects in Occupational Environments

Localized muscle fatigue (LMF) is a complex, multifactorial phenomenon that involves exercise-induced decrements in the ability to generate force or power. LMF can adversely affect performance and may increase the risk of work-related musculoskeletal disorders (WMSDs), and is thus of contemporary occupational relevance. Despite considerable progress in understanding and predicting muscle fatigue, there are many uncertainties and unresolved issues that are principally associated with the physiological complexity of LMF and the diverse mechanisms that underlie LMF development. This research thus aimed to address some of the theoretical and practical issues related to muscle fatigue and recovery. Regarding the theoretical aspects, two specific muscle fatigue models (MFMs) were directly compared and some important differences in their predictions were identified. These differences were used, in part, as a basis for developing testable hypotheses and designing associated experiments. Further theoretical evaluations were conducted to explore the sensitivity of these models to the model parameters and their ability to predict endurance time in both prolonged and intermittent exertions. Sensitivity to inherent model parameters was quantified, which was relatively high in conditions involving lower to moderate levels of effort. Further assessments indicated substantial variability related to model recovery parameters, which might be related to the inability of these MFMs in simulating the recovery process. From a
Identifying characteristics of non-completers in fear conditioning paradigms with children and adolescents

The number of studies on fear conditioning in children and adolescents has increased in recent years. Most of these studies exclusively focus on data of completers while dropout rates, reasons for dropout, and specific characteristics of non-completers are underreported. This study systematically investigated data of 283 children and adolescents between 8 and 17 years (M = 11.10, SD = 2.14) undergoing a differential fear conditioning paradigm using a female scream as unconditioned stimulus (US). The sample included 230 children and adolescents with a current primary anxiety disorder (separation anxiety disorder, social anxiety disorder, and specific phobia) and 53 non-anxious controls. The dropout rate was 24.1%. The most common reason to discontinue was being afraid of the US (59.1%) followed by the startle probe being too loud (15.2%). Logistic regressions revealed that younger age and a present anxiety disorder predicted dropout. There seem to be distinct characteristics potentially predicting dropout from fear conditioning paradigms. Thus, interpretability and generalizability of those paradigms are limited when non-completers are not considered. Future research should conscientiously look at these data more closely and investigate paradigms that work independent of age and diagnostic status.
Effective and practical recommendations to dental team when providing dental services in the era of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) is the coronavirus that causes COVID-19 (coronavirus disease 2019). It is an airborne virus and can spread through small droplets of saliva.Dental professionals work very close to the patient’s mouth, putting them at high risk of contracting SARS-CoV-2. This is because aerosols and splatter are generated when performing some dental procedures, which are known to be the possible potential sources of some other serious diseases to the dental team and patients in the dental settings. During the COVID-19 pandemic, dental professionals continued to provide dental services to patients; however, dental professionals are more likely to become contaminated due to the nature of their work. Hence a cautious emergency implementation of extra-protective measures is paramount to limit viral contamination between patients and the dental team. This research review was performed to summarize essential practical recommendations to be adopted by the dental team when providing dental services to the patient during the COVID-19 period, to minimize the risks of COVID-19.
Between fear of and desire for the digitalization of retailing: An initial conceptualization to understand the ambivalent reactions of shoppers

Digitalization has resulted in deep changes to the retail landscape, which have been the subject of extensive research. Most studies have only seen this growing phenomenon as a source of benefits for shoppers. However, this technological optimism runs into problems when the technologies offered by retailers are ignored or abandoned by shoppers. To address this gap, our research investigates how shoppers react to the digitalization of retailing through the prism of ambivalence. A systematic literature review identified a dataset of 108 papers in major journals published between 2005 and 2020. Our critical analysis revealed positive and negative reactions to digitalization among shoppers. Grouping these into pairs of two opposites, we propose an initial conceptualization of shopper ambivalence divided into eight distinct components. We also highlight the components of shopper ambivalence that merit further attention and offer a research agenda accordingly. Finally, our conceptualization may help managers to make sense of the heterogeneous reactions of shoppers to the technologies they offer.
Amino Acids, B Vitamins, and Choline May Independently and Collaboratively Influence the Incidence and Core Symptoms of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a developmental disorder of variable severity, characterized by difficulties in social interaction, communication, and restricted or repetitive patterns of thought and behavior. In 2018, the incidence of ASD was 2.4 times higher than estimated in 2000. Behavior and brain development abnormalities are present in the complex disorder of ASD. Nutritional status plays a key role in the incidence and severity of the core symptoms of ASD. The aim of this study was to review the available peer-reviewed studies that evaluated the relationship between amino acids, choline, B vitamins, and ASD incidence and/or severity of symptoms. Through examining plasma profiles, urine samples, and dietary intake, researchers found that low choline, abnormal amino acid, and low B vitamin levels were present in children with ASD compared to those without ASD. The evidence supports the need for future research that implements simultaneous supplementation of all essential nutrients in individuals with ASD and among prenatal mothers. Future evidence could lead to scientific breakthroughs, ultimately reducing the rates of ASD incidence and severity of symptoms by applying nutritional interventions in at-risk populations.
Service Delivery and Branding Management in Digital Platforms: Innovation through Brand Extension

Purpose. Resources and experiences may give platform owners an advantage to expand their business to new areas of possible growth. However, can the winner take it all? Or is the spandex rule—“just because you can, does not mean you should”—valid for platforms, as well? The present study is aimed at narrowing this research gap by focusing on the innovation through brand extension impact on customer satisfaction and brand loyalty in an ever-greater area of the service sector. Design/Methodology/Approach. The partial least-squares structural equation modelling (PLS-SEM) is applied to analyse the questionnaires and explore the relationships between the proposed research model’s constructs. Findings. The results reveal that service innovation through brand extension impacts customer satisfaction and loyalty favourably. Customer satisfaction mediates the relation between innovation through brand extension and brand loyalty. Parent brand reputation intensifies service innovation through the impact of brand extension on customer satisfaction and loyalty, while perceived risk deters its effects. Customer innovativeness enhances customer satisfaction. Finally, perceived category similarity (fit) augments customer satisfaction while impacting loyalty negatively. Practical Implications. The findings provide a deeper understanding of innovation and brand management in digital platforms and forge a promising path forward for marketing researchers investigating the platform economy. Originality/Value. Little remains acknowledged regarding the theoretical interface of innovation through brand extension in the digital platform sphere and its consequences on customer behaviour. Building on this lacuna, the authors adopt an underexplored object that focuses on digital platform innovation through brand extension, customer satisfaction, and brand loyalty.