Miracle-dz/UniFAR-FTUs huggingface dataset:
Management Service Initiatives as Predictors of Employees’ Job Satisfaction and Employees’ Customer Service Behaviors: The Case of Hotels in Adama City

The study was aimed to examine management commitment initiatives as predictors of employees’ job satisfaction and customer service behaviors in Hotels of Adama city. For this purpose, out of 14 international standard hotels, 6 hotels were randomly selected using random sampling technique. The total number of employees was also obtained from the front office managers of the participating hotels, and then the required sample size was selected using stratified random sampling technique. The survey questionnaire for this study was adapted from the work of Kim, et al.(2009). The collected data were analyzed using descriptive and inferential statistics. Results of the findings revealed that Adama city hotel employees have a significant positive relationship between management commitment initiatives (organizational support, reward, empowerment, and training) and their job satisfaction. In contrast, there was no significant relationship between management commitment initiatives (reward, empowerment, and training) and employees’ service behaviors. Providing good training programs, increasing rewards, developing the empowerment, and AJSI Vol. 1 October 2016 improving the organizational support will increase employees’ job satisfaction and employees’ service behaviors.
Designing physics board games: a practical guide for educators

Board games can be a highly engaging and motivating resource to support physics teaching at all educational levels. However, the development of board games to facilitate the communication of complex science subjects may not be an easy task for those with no prior experience in designing games. For instance, the various classification of educational game features, proliferation of game mechanics and lack of scholarly guidance for designing and on their efficacy in formal learning may hinder the game development process. To address this issue, this study presents a hands-on game development framework for science educators and researchers on how to design educational science games. The framework is divided into five steps with simple exercises that build upon each other to create a student-centred educational resource as well as providing a means of evaluation.
Contrail coverage over the United States before and during the COVID-19 pandemic

Contrails are potentially the largest contributor to aviation-attributable climate change, but estimates of their coverage are highly uncertain. No study has provided observation-based continental-scale estimates of the diurnal, seasonal, and regional variability in contrail coverage. We present contrail coverage estimates for the years 2018, 2019 and 2020 for the contiguous United States, derived by developing and applying a deep learning algorithm to over 100 000 satellite images. We estimate that contrails covered an area the size of Massachusetts and Connecticut combined in the years 2018 and 2019. Comparing 2019 and 2020, we quantify a 35.8% reduction in distance flown above 8 km altitude and an associated reduction in contrail coverage of 22.3%. We also find that the diurnal pattern in contrail coverage aligns with that of flight traffic, but that the amount of contrail coverage per distance flown decreases in the afternoon.
Reinforcement Learning Optimized Intelligent Electricity Dispatching System

With the rapid development of artificial intelligence, new changes are coming to all walks of life including traditional manufacturing industry, bio-pharmaceutical industry, electric-power industry, etc. For electric-power industry, many machine learning algorithms have been used to achieve intelligent dispatch of electricity, intelligent electricity equipment fault diagnosis and more optimized customer management, among which the automation of power network is one of the most important issue ensuring safe operation of electricity grid. In the recent years, intelligent dispatch method based on big data analysis has been used in intellectual scheduling of electricity and has got significant promotion. However, the intelligent dispatch on big data analysis needs tremendous history data that is sometime not that easy to get. Moreover, once a small probability event happens, the big data based intelligent dispatch method may lose efficacy, thus in this paper we proposed a new intelligent dispatch model based on the reinforcement learning that is more robust, safer and with higher efficiency. Finally, according to the empirical study result, our model outperforms the traditional methods, where the average economic benefit in the test area increases more than 25%, fluctuation of distribution is more stable than before and the carbon emission decreases about 30%.
A Methodology Based on Model-Driven Engineering for IoT Application Development

—The Internet of Things can be understood as an infrastructure of the dynamic global network with a capacity of self-configuration, based on standard communication protocols, where things -physical and virtual-have an identity, physical attributes, and virtual personalities. In this paper, we propose a methodology based on Model-Driven Engineering with different levels of abstraction, points of view, and granularity, with the objective of guiding the development of software applications for Internet of Things. The methodology is supported by methods of model transformation, enabling the generation of the code of the software applications for Internet of Things. In addition, a Service-Oriented Architecture is presented for the deployment of software applications, composed of four layers that allow the identification of the components required for the implementation of the Internet of Things systems.
Foreground Mining via Contrastive Guidance for Weakly Supervised Object Localization

Weakly supervised object localization (WSOL) locates the target object within an image using only image-level labels. Recent methods try to extend the feature activation to cover entire object regions by dropping the most discriminative parts. However, they either overextend the activation into the background or are still limited to covering the most discriminative parts. In this paper, we propose a novel WSOL framework that localizes the entire object to the right extent via contrastive learning. Our framework contains three key components: 1) scheduled region drop, 2) contrastive guidance, and 3) pairwise non-local block. The scheduled region drop progressively erases the most discriminative parts of the original feature at a region-level. The erased feature facilitates the network to discover less discriminative regions in the original feature. Then, our contrastive guidance encourages the foregrounds of the original and erased features to be closer while pushing away from each background. In this manner, the network earns the capacity to differentiate the foregrounds from backgrounds, spreading out the activation within object regions. Last but not least, we utilize the pairwise non-local block, which provides an enhanced attention map to strengthen the spatial correlations between each pixel. In conclusion, our method achieves the state-of-the-art performance on CUB-200-2011 and ImageNet benchmarks regarding Top-1 Loc , GT-Loc and MaxBoxAccV2 .
Job Burnout and Job Satisfaction in the Banking Sector

Job satisfaction and job burnout are two concepts strongly mentioned in the literature, having confirmed a negative correlation between job satisfaction and job burnout. In the banking sector, research shows that job burnout is a frequent occurrence, highlighting the negative correlation between job burnout of bank employees and their job satisfaction. This paper explores the perceptions of bank employees in Greece regarding their level of job satisfaction and job burnout. The possible correlations between these two variables and the possible impact of demographics are also studied. The results are believed to offer significant implications for future research and practice in the Greek banking sector that has received a number of changes such as procedures from acquisitions and mergers and voluntary withdrawals in the human resource area, trying to find a way out of the consequences of the crisis.
International Journal of Material Science Innovations (IJMSI) 2(6): 236-245, 2014

Nanofiber, Electrospinning, Transparent, Composite, Tensile Strength. In this work nanofiber layers reinforced composites with nylon 66 and PAN have been prepared and compared in terms of tensile properties and light transparency. Nylon 66 and PAN nanofiber layers are fabricated using electrospinning method with the approximately same size of nanofiber’s diameter. The nanocomposites prepared with nylon 66 nanofibers shown better transparency compared to the PAN nanofibers. Results indicated that nylon 66 and PAN nanofiber layers significantly enhanced the tensile stress (increased by 80% and 102%, respectively) and the Young’s modulus of the composite (increased by 15% and 54%, respectively). The contact angle analysis indicated that the nanofibers with hydrophobic nature have better wettability by epoxy resin, leading to the better mechanical performance of the composite. The priority of this work to others is in the use of two polymers with different chemical properties and considering their effect on the properties of nanofiber reinforced composites.
The Development of Subjective Well-Being across the Lifespan

Throughout life, individuals are constantly required to make decisions about how to spend their time and where to engage their efforts. Which career should I pursue? Which relationship partner is right for me? Should I continue following this diet and eat this apple or splurge for a bit with the chocolate cake? Each of these decisions—from the minor and inconsequential to the life-defining—requires us to consider our idiosyncratic goals and attempt to predict the ways in which our actions allow us to achieve these goals. And ultimately, many of us believe that if we make the right decisions—and have a little bit of luck—the final outcome will be a satisfying life full of happiness. Indeed, people seem to make decisions large and small based on the assumption that their choices will promote or maintain their happiness. Indeed, most people believe that the achieving a happy and satisfying life is a goal worth pursuing—and it might even be the ultimate goal in life for many people (Adler, Dolan, & Kavetsos, 2017; Diener, 2000; Gilbert, 2006). But what is this state of happiness that seems to motivate much of what people do in life? Is “happiness” just a superficial feeling of mindless pleasure, or is it something deeper and more fulfilling? Does happiness actually improve when good things happen (and drop when misfortune occurs)—or is happiness relatively stable, with lasting changes difficult to achieve? We all know those people who seem able to maintain their cheerful disposition despite repeated, severe setbacks; do these cases reflect a broader pattern where stable tendencies toward happiness or misery persist despite changing life circumstances? These and other questions motivate researchers who study what is colloquially referred to as “happiness” and more precisely described as “subjective well-being” (SWB; Diener, Suh, Lucas, & Smith, 1999) in the psychological literature. In this chapter, we discuss the concept of SWB, paying particular attention to people’s intuitions about it and the specific research questions that are motivated by these intuitions. We start with an overview of the definitions of SWB, focusing both on what it is and what it is not. We then move to a discussion of questions that are especially relevant when considering SWB in the context of lifespan development. For instance, we discuss reasons why one might expect stability or change in well-being over time, focusing specifically on the empirical evidence about the extent to which SWB actually changes. Next, we review evidence about the C H A P T E R 29
Real-Time Implementation of Isolated-Word Speech Recognition System on Raspberry Pi 3 Using WAT-MFCC

Summary The automatic speech recognition (ASR) is a field of research that has been emerged in the early 1950s, and has been used in the literature for convenient and efficient human-machine interaction. For voice command system, it is based on implementation of isolated-word speech recognition and it can include many applications, such as voice-activated devices, robots, access control system, etc. In this paper, such isolated-word speech recognition system has been implemented on Raspberry-Pi 3 (RPi 3) board by combining Wave Atoms Transform (WAT) approach and Frequency-Mel Cepstral Coefficients (MFCC) (WAT-MFCC) with Support Vector Machine (SVM). The experiments have been tested on Arabic words database and the achieved results have proven the reliability of the proposed WAT-MFCC-SVM recognition approach with a rate of 100% and a Real-Time Factor (RTF) of 1.50.
Hypertension and Type 2 Diabetes Mellitus as Risk Factors for Prostate Cancer Patients in Southern Nigerians

Background: Prostate cancer (PCa) is one of the most commonly diagnosed cancers in Nigerian men and worldwide. Some comorbidities, such as hypertension, diabetes, and cardiovascular diseases have been investigated as potential risk factors for developing PCa. Hypertension and Type2 diabetes mellitus (DM) are common with the middle age and elderly and could be a conundrum during treatment. Aims and Objectives: This study highlights the associated comorbidities with prostate and describes the relationship between Type 2 Diabetes Mellitus and hypertension with prostate cancer among southern Nigerian men. Materials and Methods: This was a retrospective study carried out over ten years ago on all patients with histologically confirmed prostate cancer at the University of Port Harcourt and two other private urology hospitals from where the study population was evaluated. The folders were retrieved and their age, prostate-specific antigen levels, Gleason grade, comorbidities, and treatment received were analyzed. Patients with incomplete data were excluded from the study. The data were collated using Microsoft excel 2020. Data collected were then analyzed using SPSS version 20. Results: There were a hundred and fifty-two patients with histologically confirmed PCa. Sixty-four were reported with a known Gleason score fifty-four (35.5%) of the patients had no associated comorbidity. Hypertension was the commonest associated comorbidity seen in sixty-one (40.1%) of the patients, followed by Type 2 Diabetes Mellitus in nineteen (12.5%). The poorly differentiated cancers were commonest among the patients with hypertension, Type 2 DM, and patients with both. There was no association between Type 2 DM, hypertension, and Gleason’s score. Conclusion: Diabetes and hypertension are still the commonest comorbidities associated with Prostate cancer. There is no statistically significant association was found between Gleason’s score, diabetes, and hypertension in patients with prostate cancer.
Eye-opening products: Uncertainty and surprise in cataract surgery outcomes∗

For experience goods, benefits from consumption are ex-ante unknown but revealed after repeated interactions. This uncertainty might lead to underconsumption. We use data from a large cataract surgery provider in Mexico City to estimate demand, given uncertainty in surgical outcomes. We consider forward-looking consumers with a surgery demand per eye and information revealed after the first surgery. We exploit data from sales agents to identify structural demand parameters; namely, price elasticities and the value of the uncertain shock. We simulate counterfactual policies, showing that budget-neutral price changes are more effective at increasing welfare than persuasive advertising.
The mediating role of technology perception in the relationship between customer experience and the adoption of e-payment cards during the COVID-19 pandemic

By integrating the technology acceptance model, the theory of planned behavior, and regulatory focus theory, this study assesses the mediating role of technology perception attributes (i.e., perceived ease of use and perceived usefulness) in the relationship between customer experience and the adoption of e-payment cards during the COVID-19 pandemic in Sudan. A questionnaire survey was conducted with 368 e-payment users in Khartoum and Southern Darfur, the two most highly populated states in Sudan. This study employed convenience sampling and quantitative methodology to clarify the relationship based on structural equation modeling. The empirical findings showed that the customer experience dimensions of cognition and emotion had a significant influence in e-payment adoption and technology perception. Further, they indicated that technology perception had a significant mediating role in the relationship between customer experience and e-payment adoption. © 2021 Growing Science Ltd. All rights reserved.
Development of an Attention Test using the VitalSky

Delirium occurs in upto 80% of the ICU patients and is one of the most common source of morbidity and mortality in the ICU. Inattention is one of the core features and affects 97%-100% of the delirium patients. This indicates that attention can be a good parameter for detecting delirium. In literature, it has been found that the use of visual attention tests have been successful in detecting delirium among the ICU patients. The VitalSky is a luminous ceiling used for providing light therapy to the ICU patients. Since, the VitalSky is already available in the ICU and allows to render visual contents, it can be used for detecting delirium in the ICU patients by performing visual attention tests. In this thesis, visual attention tests are developed for the VitalSky. Moreover, different interaction devices are explored that can be used by the ICU patients to respond to the tasks of the attention test and help in automation of the test. The technical feasibility and usability of the automated setup is also evaluated in this thesis. The validation of the performance of the attention tests and user preference of the response devices is assessed by conducting a pilot study on 10 healthy volunteers and collecting their subjective feedback.
The distribution, concentration and composition of microplastics in beach sediments and coastal waters of Jersey, C.I

Secondary microplastics are thought to be the most abundant within the marine environment with the majority of microplastic debris found in the ocean considered to originate from land-based sources. The global pollution of the marine environment by microplastic contamination is linked to several environmental threats including species death (through ingestion, toxicity and starvation), and the spread of invasive species and disease (both for natural species and humanity itself).
Acute temporal effect of ambient air pollution on common congenital cardiovascular defects and cleft palate: a case-crossover study

This symmetric bidirectional case-crossover study examined the association between short-term ambient air pollution exposure during weeks 3-8 of pregnancy and certain common congenital anomalies in Ulaanbaatar, Mongolia, between 2014 and 2018. Using predictions from a Random Forest regression model, authors assigned daily ambient air pollution exposure of particulate matter <2.5 um aerodynamic diameter, sulphur dioxide, nitrogen dioxide, and carbon monoxide for each subject based on their administrative area of residence. We used conditional logistic regression with adjustment for corresponding apparent temperature to estimate relative odds of select congenital anomalies per IQR increase in mean concentrations and quartiles of air pollutants. The adjusted relative odds of cardiovascular defects (ICD-10 subchapter: Q20-Q28) was 2.64 (95% confidence interval: 1.02-6.87) per interquartile range increase in mean concentrations of particulate matter <2.5 um aerodynamic diameter for gestational week 7. This association was further strengthened for cardiac septal defects (ICD-10 code: Q21, odds ratio: 7.28, 95% confidence interval: 1.6-33.09) and isolated ventricular septal defects (ICD-10 code: Q21.0, odds ratio: 9.87, 95% confidence interval: 1.6-60.93). We also observed an increasing dose-response trend when comparing the lowest quartile of air pollution exposure with higher quartiles on weeks 6 and 7 for Q20-Q28 and Q21 and week 4 for Q21.0. Other notable associations include increased relative odds of cleft lip and cleft palate subchapter (Q35-Q37) and PM2.5 (OR: 2.25, 95% CI: 0.62-8.1), SO2 (OR: 2.6, 95% CI: 0.61-11.12), and CO (OR: 2.83, 95% CI: 0.92-8.72) in week 4. Our findings contribute to the limited body of evidence regarding the acute effect of ambient air pollution exposure on common adverse birth outcomes.
Culture and identification of a “Deltamicron” SARS‐CoV‐2 in a three cases cluster in southern France

Multiple SARS‐CoV‐2 variants have successively, or concomitantly spread worldwide since the summer of 2020. A few co‐infections with different variants were reported and genetic recombinations, common among coronaviruses, were reported or suspected based on co‐detection of signature mutations of different variants in a given genome. Here we report three infections in southern France with a Delta 21J_AY.4‐Omicron 21K/BA.1 “Deltamicron” recombinant. The hybrid genome harbors signature mutations of the two lineages, supported by a mean sequencing depth of 1163–1421 reads and a mean nucleotide diversity of 0.1%–0.6%. It is composed of the near full‐length spike gene (from codons 156–179) of an Omicron 21K/BA.1 variant in a Delta 21J/AY.4 lineage backbone. Importantly, we cultured an isolate of this recombinant and sequenced its genome. It was observed by scanning electron microscopy. As it is misidentified with current variant screening quantitative polymerase chain reaction (qPCR), we designed and implemented for routine diagnosis a specific duplex qPCR. Finally, structural analysis of the recombinant spike suggested its hybrid content could optimize viral binding to the host cell membrane. These findings prompt further studies of the virological, epidemiological, and clinical features of this recombinant.
A qualitative examination of the factors affecting the adoption of injury focused wearable technologies in recreational runners

Purpose: Understanding users perceived usefulness and ease of use of technologies will influence their adoption and sustained use. The objectives of this study were to determine the metrics deemed important by runners for monitoring running-related injury (RRI) risk, and identify the barriers and facilitators to their use of injury focused wearable technologies. Methods: A qualitative focus group study was undertaken. Nine semi-structured focus groups with male (n=13) and female (n=14) recreational runners took place. Focus groups were audio and video recorded, and transcribed verbatim. Transcripts were thematically analysed. A critical friend approach was taken to data coding, and multiple methods of trustworthiness were executed. Results: Excessive loading and inadequate recovery were deemed the most important risk factors to monitor for RRI risk. Other important factors included training activities, injury status and history, and running technique. The location and attachment method of a wearable device and the design of a smartphone application were identified as important barriers and facilitators, with receiving useful injury-related feedback identified as a further facilitator. Conclusions: Overtraining, training-related and individual-related risk factors are essential metrics that need to be monitored for RRI risk. RRI apps should include the metrics deemed important by runners, once there is supporting evidence-based research. The difficulty and/or ease of use of a device, and receiving useful feedback will influence the adoption of injury focused running technologies. There is a clear willingness from recreational runners to adopt injury focused wearable technologies whilst running.