Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Privacy Concerns and Its Influence on Consumer Purchasing Intention in Bangladesh and India

The research studies the factors of customers’ awareness of their online behavior. This paper aims to highlight the gaps in customer awareness and views regarding data privacy, marketing research, and factors that impact the purchasing intentions in developing nations like India and Bangladesh. Previously it can be seen that there has been much research done in this area, but mostly those were for developed nations. However, in developing nations, like Bangladesh and India, which are outstanding and growing markets for online marketers, the concept of data privacy is not observed meticulously. Descriptive, relational, and quantitative research methodologies were applied for the study. Inferential statistics via SPSS were used to accomplish the purpose of the research. The target population was infinite, and the sampling frame was focused on Bangladesh and India’s internet users. 440 respondents were approached, and the received response rate was close to 81%, 354 responses. Unlike this study, commonly explorative and qualitative research methodologies were considered for similar research before. The research outcomes demonstrate that consumers in Bangladesh and India are mindful of data privacy, and the result of this research supports the current literature. The outcomes showed a significant positive relationship between the consumers’ view of how online platforms of companies handle their data with their buying intentions. Nevertheless, in these recommended relationships from the framework, customer commitment’s moderating influence plays a significant role in forming buying intention. The research is particularly important for marketing professionals to understand customers’ expectations from the companies regarding customize marketing. This research envisioned to cause some influence the literature and executive implications with development of a new research framework, adjusting new variables, and hypotheses, which were solely based on keeping in mind, the customers of Bangladesh and India.
Fast Molecular-Based Detection of SARS-CoV-2 Virus from Saliva by Direct RT-PCR

Since the COVID-19 occurs in Wuhan, because of the novel coronavirus nCov-2019, that was soon named SARS-Cov-2 due to closed genomic homology and clinical symptoms with SARS-Cov, authorities and the scientific community have emphasized the necessity of a mass screening campaign in order to control and prevent clusters and the epidemic from progressing. Indeed, the SARS-Cov-2 virus has a higher reproductive rate (R0) than SARS-CoV and MERS-CoV. This infection may mobilize many health professionals, and may present high short and/or long-term health risk. It is obvious that any reliable, simple, painless and sensitive diagnostic systems are needed to control the pandemic. Yet, very few sample and analytic methods are recognized as reference points, i.e., nasopharyngeal swabs (NPS) and detection of viral RNA by real-time reverse transcription polymerase chain reaction (rRT-PCR). To avoid painful sampling, testing hesitancy, healthcare professional contamination, and to access fast and reliable analytic methods, existing adjustments to testing methods are needed to be evaluated. Posterior oropharyngeal saliva is a sensitive source for SARS-CoV-2 detection. Stability of SARS-CoV-2 detection in simple saliva tube sampling without supplementation has been demonstrated, following RNA extraction and purification, or by direct rRT-PCR. The aim of this study is to investigate the feasibility of saliva direct rRT-PCR molecular diagnosis, comparing to NPS direct rRT-PCR, and a limited limit of detection determination to evaluate performance. It provides a much-needed alternative at exactly the right time.
Mean-Min task scheduling algorithm for cloud environment

Cloud computing is a form of distributed computing which provides various services to the users. Because it of its dynamic and distributed services it has attracted the users and it is a fast growing technology in the ﬁeld of distributed computing. It is highly scalable and it allows on-demand services. Millions of user are using the cloud environment because of its pay-as-you-go service. The cloud environment must be able to meet the user requirements and provide quality of service with high performance. The performance of cloud computing will be better if an efﬁcient task scheduling algorithm is used for mapping the tasks to the available resources. An efﬁcient scheduling algorithm increases the resource utilization thereby minimizing the execution time and cost. This paper proposes a Mean-Min Task Scheduling algorithm for Cloud environment based on the minimum execution time of the tasks submitted.
Basics of automated plant identification

Historically, image-based dichotomous plant identification keys precede text-based ones by nearly one hundred years. Having lain in conceptual torpor for over 300 years, the notion of image-based identification has experienced a revival as a result of the development of modern applications which depend upon recent technological advances in electronic hardware (e.g. image sensors, network bandwidth, computer storage capacity) and software (especially image recognition systems and efficient large file browsing). There are essentially two different approaches to automated image-based recognition of plant species: Leafsnap and Pl@ntNet. A brief discussion of the two approaches is here presented. Regardless of the approach, for successful automated plant identification, there are several dataset requirements and these are laid out in the following paper.
Employee-Organization Relationship and Organizational Citizenship Behaviour: The Roles of Organizational Identification and Leader-Member Exchange

Based on the social exchange theory and organizational identification theory, this study constructs a theoretical framework to explore the mediating mechanism and boundary conditions between employee-organization relationship and employees’ organizational citizenship behaviour. Firstly, this paper proposes that organizational identification as a mediator variable affects the relationship between employee-organization relationship and organizational citizenship behaviour, and then points out that the leader-member exchange can positively moderate the relationship between employee-organization relationship and organizational identification. Based on the survey data of 405 employees, those above hypotheses are tested, and the results support the theoretical expectation of this study. The conclusion reveals the influence mechanism of employee-organization relationship on organizational citizenship behaviour, which has important theoretical significance. At the same time, it has practical guiding significance to effectively carry out employment relationship management and enhance organizational citizenship behaviour.
Optimization of process variables for hyper-production of lovastatin from wild type Aspergillus terreus and its efficacy studies Optimización de variables de proceso para la hiperproducción de lovastatina a partir de Aspergillus terreus silvestre y estudios de su eficacia

The objective of this study was the investigation of optimum conditions for lovastatin production from Aspergillus terreus through response surface methodology (RSM) with central composite design (CCD). The efficacy of produced and purified statin was then evaluated by using induced hypercholesterolemic rats. A. terreus was used to synthesize statin by using solid state fermentation on lignocellulose substrate, wheat straw. Total 30 experiments were conducted in triplicate for four physical parameters, each at five levels and response (statin production) from A. terreus was measured. Maximum statin formation (60 mg/g) obtained from A. terreus at temperature 30 oC, pH 7.37, inoculum size 4.5 mL and fermentation time 192 h. Hypercholesterolemia was induced in rats by feeding a high cholesterol diet in group I, II and group III from 0 to 30 days. From days 15-30, Group III (treatment group) was given statin extracted from A. terreus. Significant reduction in serum cholesterol level in group III rats treated with purified statin were observed at 30th day with significant increase in ser HDL levels along w th significant reduction of serum LDL levels.
Brain Perturbation and Neuroimaging in NHPs Combining Brain Perturbation and Neuroimaging in Non-human Primates

Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.
Running head: EGOCENTRIC FOUNDATIONS OF TRUST 1 Egocentric Foundations of Trust

Trusting the trustworthy brings benefits whereas trusting the untrustworthy brings harm. Discriminating between the two is key to every social encounter. We propose that humans turn to internal information, namely the self, when judging the trustworthiness of others. Simulating how oneself would behave in situations that involve trust helps to predict how a counterpart may behave. Importantly, using the same self as a basis for judgments about others may result in diverging outcomes, depending on how the information is processed. If a judge focuses on similarities between the self and the target person, the judge expects the counterpart to act alike. However, if a judge focuses on differences, the target is expected to behave in ways opposite to the self. In Study 1 natural variations in self-ascribed levels of trustworthiness correlate positively with expectations of a target person’s trustworthiness. Inducing a similarity-focus increases this correlation as compared to a difference-focus. Interestingly, this effect holds even if information speaks to the target’s trustworthiness. In manipulating the perception of the participants’ own trustworthiness as well as the processing focus, Studies 2-4 demonstrate that when individuals focus on similarities, those who perceive themselves as highly (vs. less) trustworthy perceive others as similarly highly (less) trustworthy. However, when they focus on differences, the reverse pattern tends to occur. These effects hold for trust judgments (Study 2-3) and trust behavior in an economic game (Study 4). Together, these findings demonstrate that trust involves egocentric inferences that are flexible enough to adjust for basic social relations.
Tecnología para la formación temprana de resistencia al estrés en el sistema de prevención de la mala adaptación escolar de alumnos de primer grado Technology for early formation of stress-resistance in the system of school maladaptation prevention of first-graders

The relevance of the stated problem of the crisis of 6-7-year old’s is dictated by the recently growing tendency to bring back children to preschool institutions after a short period at school by parents who notice the child’s painful condition associated with school maladaptation. In this regard, many researchers and practicing educators recommend reviewing the start dates for children at school so that the child starts school at the age of seven. Other teachers notice a significant increase in the work load on primary schoolchildren connected to the introduction of the Federal State Educational Standard for Primary General Education and the corresponding forms of control and assessment activities. Thus, there was a need to develop new technologies to preserve the health of younger students and allow them to overcome the crisis of the onset of education. The purpose of this article is to describe the developed technology aimed at helping 6-7-year old to overcome the age crisis and prevent school maladaptation with the help of early formation of stress tolerance. The main method in the study is the design of a technology for early formation of stress tolerance and prediction of the results of its implementation in the experimental groups of 6-7-year-old children. The technology is based on the principles of continuity of the educational process between preschool educational organizations and schools. With the implementation of the developed technology the following results were achieved: increased motivation for success and higher somatic health level manifested in sport and creative activities. The above-mentioned results in their turn contributed to crisis prevention, school deprivation of first graders and comfortable overcoming of the crisis of 6-7 year olds. The materials of the article can be useful to organizers of sport and creative activities in preschool educational institutions, educators of preparatory groups, teachers, methodologists in preschool and primary education, as well as physical education teachers and primary school teachers. The materials of the article can be used in the system of advanced training of teachers of physical education and elementary school, as well as in the preparation for professional activities in preschool educational institutions and elementary schools of students of teacher training colleges and universities.
Trastuzumab Modulates the Protein Cargo of Extracellular Vesicles Released by ERBB2+ Breast Cancer Cells

Cancers overexpressing the ERBB2 oncogene are aggressive and associated with a poor prognosis. Trastuzumab is an ERBB2 specific recombinant antibody employed for the treatment of these diseases since it blocks ERBB2 signaling causing growth arrest and survival inhibition. While the effects of Trastuzumab on ERBB2 cancer cells are well known, those on the extracellular vesicles (EVs) released from these cells are scarce. This study focused on ERBB2+ breast cancer cells and aimed to establish what type of EVs they release and whether Trastuzumab affects their morphology and molecular composition. To these aims, we performed immunoelectron microscopy, immunoblot, and high-resolution mass spectrometry analyses on EVs purified by differential centrifugation of culture supernatant. Here, we show that EVs released from ERBB2+ breast cancer cells are polymorphic in size and appearance and that ERBB2 is preferentially associated with large (120 nm) EVs. Moreover, we report that Trastuzumab (Tz) induces the expression of a specific glycosylated 50 kDa isoform of the CD63 tetraspanin and modulates the expression of 51 EVs proteins, including TOP1. Because these proteins are functionally associated with organelle organization, cytokinesis, and response to lipids, we suggest that Tz may influence these cellular processes in target cells at distant sites via modified EVs.
Hybrid Sampling/Optimization-based Planning for Agile Jumping Robots on Challenging Terrains

This paper proposes a hybrid planning framework that generates complex dynamic motion plans for jumping legged robots to traverse challenging terrains. By employing a motion primitive, the original problem is decoupled as path planning followed by a trajectory optimization (TO) module that handles dynamics. A variant of a kinodynamic Rapidly-exploring Random Trees (RRT) planner finds a path as a parabola sequence between stance phases. To make this fast, a reachability informed control sampling scheme leverages a precomputed velocity reachability map. The path is post-processed to eliminate redundant jumps and passed to the TO module to find a dynamically feasible trajectory. Simulation results are presented where the proposed hybrid planner solves challenging terrains by executing multiple consecutive jumps, producing novel strategies to leap over large gaps by leveraging dynamics. In a physical experiment, the hybrid planner is tested on a real robot successfully traversing a challenging terrain.
Machine Learning Models for Breast Lesions Based on Ultrasound Imaging Features: A Observational Study

Background: The accuracy of breast cancer (BC) screening based on conventional ultrasound imaging examination largely depends on the experience of clinicians. Further, the effectiveness of BC screening and diagnosis in primary hospitals need to be improved. This study aimed to establish and evaluate the usefulness of a simple, practical, and easy-to-promote machine learning model based on ultrasound imaging features for diagnosing BC.Methods: Logistic regression, random forest, extra trees, support vector, multilayer perceptron, and XG boost models were developed. The modeling data set was divided into a training set and test set in a 75%:25% ratio, and these were used to establish the models and test their performance, respectively. The validation data set of primary hospitals was used for external validation of the model. The area under the receiver operating characteristic curve (AUC) was used as the main evaluation index, and pathological biopsy was used as the gold standard for evaluating each model. Diagnostic capability was also compared with those of clinicians. Results: Among the six models, the logistic model showed superior capability, with an AUC of 0.771 and 0.906 in the test and validation sets, respectively, and Brier scores of 0.18 and 0.165. The AUC of the logistic model in tertiary class A hospitals and primary hospitals was 0.875 and 0.921, respectively. The AUCs of the clinician diagnosis and the logistic model were 0.913 and 0.906. Their AUCs in the tertiary class A hospitals were 0.890 and 0.875, respectively, and were 0.924 and 0.921 in primary hospitals, respectively. Conclusions: The logistic regression model has better overall performance in primary hospitals, and the logistic regression model can be further extended to the basic level. A more balanced clinical prediction model can be further established on the premise of improving accuracy to assist clinicians in decision making and improve diagnosis.Trial Registration: http://www.clinicaltrials. gov. ClinicalTrials.gov ID: NCT03080623.
Head-Mounted Display Integration for Orthopedic Surgery

Orthopedic surgery has been very commonly conducted these years, yet it suffers from the lack of efficient harmless guidance system. Current guidance system uses X-rays to only provide the images without any tool-tracking. It starts with acquiring multiple X-ray images from different views to locate the point of entry, under the help of a reference tool. The medical instrument is then invaded and moved inside the patient’s body with small displacements. A set of anteroposterior X-ray images are acquired during each small displacement, until the target position is reached. The current workflow is harmful and inefficient. It requires numerous X-ray images for placing wires and screws, which not only harms the patient and surgeon in a direct way, but also increases the probability of potentially damaging the patient’s soft tissues and nervous system. This paper comes up with an approach that uses camera and markers for tool tracking and displays the tracking data in 3D using a head mounted display. The presented method is less time-consuming, more efficient and prevents the frequent use of 2D X-rays. It could serve as a road sign indicating that integrating head-mounted display for orthopedic surgery is a path that is worth exploration.
A Class-E-Based Resonant AC-DC Converter With Inherent PFC Capability

This paper investigates the use of the class-E inverter for power factor correction (PFC) applications. Analytical and state-space models are derived showing the class-E inverter’s capability of achieving inherent PFC operation with a constant duty cycle. The inherent PFC operation limits the controller responsibility to the regulation of the output voltage, which is key for resonant converters with challenging control. A converter incorporating a diode bridge, a class-E inverter, and a class-D rectifier is presented for the PFC stage in single-phase offline converters. A prototype is designed to validate the analysis and presented design method. The prototype operates with zero-voltage switching (ZVS) across the load range and achieves up to 211 W of output power at an efficiency of 88%, with an inherent power factor of 0.99 and a total harmonic distortion (THD) of 8.8 %. Frequency modulation is used to achieve lower output power down to 25 W, with a power factor of 0.95, THD of 28 %, and an efficiency of 88 %.
Storytelling in US Political Campaigns

Recent work in communications and psychology has shown that stories have different psychological effects than other forms of persuasive messages. Stories use plot, character, and narrative suspense to communicate an experience, in contrast to arguments, which use evidence of logical reasoning to support a claim. Despite growing scholarly interest in narrative and storytelling, political science has largely ignored the role of storytelling in political communication. In this paper, we address this gap, focusing on the experiences that are communicated by stories told in political advertisements. We first offer a descriptive analysis of campaign ads aired during the 2010 and 2012 US congressional elections. We show that stories appear in a substantial minority of advertisements, and that most of these stories communicate one of a few types of experiences associated with a small number of social groups. We then evaluate the impact of these stories using an experiment that tests the effects of different kinds of stories on voters’ attitudes towards the candidates implicated in the ads and their perceptions of the candidate’s association with social groups implicated in the advertisements.