Miracle-dz/UniFAR-FTUs huggingface dataset:
CLOUD-BASED TEMPERATURE MONITORING MECHANISM FOR COVID-19 PANDEMIC TRACKING

The unprecedented outbreak of novel coronavirus 2019 (COVID-19) globally has a huge impact to our daily life in numerous ways. To effectively minimize the spread of the virus, early symptom detection is crucial, especially in closed environment with high human traffic areas which post higher chances of human-to-human transmission. Body temperature measurement has been identified among the vital monitoring parameters. However, current available temperature monitoring mechanism is costly, limited to single individual and limited to locally without integrating to cloud and database. This led to difficulty in effective surveillance for suspicious COVID cases. Hence, the purpose of this paper is to introduce an end-to-end Internet of Things-enabled application for thermal monitoring as an early signal detection and screening method. This work integrates Raspberry Pi, thermal sensor, LCD display, buzzer, and LED light with Raspbian and Restful API for device-to-cloud communication. The system implemented is capable for user identification, body temperature remote monitoring and warning signal for fever symptoms. The result of this real-time system is capable to detect and screen the suspected contagious person in an organization effectively. Future works on integrating face recognition with machine learning and artificial intelligent enhancement.
Parental Response Style to Adolescent Self-Harm: Psychological, Social and Functional Impacts

Adolescent self-harm is a significant public health issue. We aimed to understand how parent stress response styles to their child’s self-harm affects their wellbeing and functioning and the wider family. Thirty-seven participants in Australia (parents; 92% female) completed a mixed methods survey regarding their adolescent child’s self-harm. We conducted Pearson zero-order correlations and independent t-tests to examine the impact of parent response style on their quality of life, health satisfaction, daily functioning, and mental health. We also used thematic analysis to identify patterns of meaning in the data. Two-thirds of participants reported mental ill health and reduced functional capacity due to their adolescent’s self-harm. Parents with a more adaptive response style to stress had better mental health. Qualitative analyses revealed parents experienced sustained feelings of distress and fear, which resulted in behavioural reactions including hypervigilance and parental mental health symptoms. In the wider family there was a change in dynamics and parents reported both functional and social impacts. There is a need to develop psychological support for the adolescent affected and parents, to support more adaptive response styles, and decrease the negative effects and facilitate the wellbeing of the family unit.
Acoustic diagnosis of high voltage circuit-breakers

A noninvasive technique for assessing the condition of circuit breakers by considering the acoustic signals generated during nonenergized switching is described. Mechanical malfunction, wear, and other types of abnormal behavior can be detected as changes in this acoustic signature. Digital signal processing techniques known from speech recognition were successfully applied to extract, compare, and present the information from the breaker signatures. A fault in the release mechanism which developed over time and eventually rendered one pole of a circuit-breaker inoperative was detected in an early stage, demonstrating the efficiency of this diagnostic technique. >
On e-convex functions and e-subdifferentials in locally convex spaces

We introduce and study the notion of e-subdifferential for an e-convex function in locally convex spaces. Some relationships between the e-subdifferential and the Clarke–Rockafellar subdifferential are established. Besides, the e-convex functions are characterized. Moreover, some results regarding the locally Lipschitz properties of e-convex functions are obtained.
Blind Modal Identification of Non-Classically Damped Systems from Free or Ambient Vibration Records

A significant segment of system identification literature on civil structures is devoted to response-only identification, simply because lack of measurements of input excitations for civil structures is a fairly common scenario. In recent years, several researchers have successfully adapted a second-order blind identification (SOBI) technique—a method originally developed for “blind source separation” of audio signals—to response-only identification of mechanical and civil structures. However, this development had been confined to fully instrumented classically damped systems. While several approaches have been proposed recently for extending SOBI to non-classically damped systems, they all require additional data such as velocity or analytic signals. Herein, we present a version of SOBI that requires only acceleration signals recorded during free or ambient vibration tests, and yields the system's complex mode shapes, natural frequencies, and damping ratios. Performance of the proposed technique is demonstrated through two synthetic examples: a ten-story structure possessing a passive control system, and a soil-structure system with seven degrees of freedom (seven-DOF).
Wage Dispersion and Team Performance: The Moderation Role of Club Size

Previous research on professional football offer conflicting results regarding the impact of wage dispersion on team performance. However, the existing intra-league heterogeneity among clubs is overlooked and could be the reason for the diverging outcomes. The aim of this paper is to reanalyze this relationship having the clubs’ size as moderator. Payroll – which captures the financial strength – is used as proxy of club size. Ordinary Least Squares regressions with season and league fixed effects are employed. Dispersion is measured by three indexes for robustness check. The outputs confirm the quadratic relationship between wage dispersion and performance, but adding that identical levels of dispersion have different impact on football clubs according to their financial strength.
A DISCRIMINANT ANALYSIS OF ACTUAL USE OF CLOUD TECHNOLOGY FOR VOCATIONAL AND TECHNICAL EDUCATION

The objectives of this research are 1) to study the independent variables that are used in the stepwise discriminant analysis of the actual use of cloud technology, 2) to create a discriminant function of the actual use of cloud technology. The sample consists of 1,620 Thai vocational and technical students who have used cloud technology. The data collection tool used in this study is a questionnaire. The statistical analysis used in this research is ‘Stepwise Discriminant Analysis (SDA)’. The results indicate that 1) the t-test results with regard to seven independent variables (Perceived Usefulness, Perceived Ease of Use, System Quality, Information Quality, Service Quality, Perceived Security, and Social Cloud) were at a significance level of . 05. This could be used to classify the groups in terms of ‘Actual Use of Cloud Technology’, and 2) the accuracy of the set of these seven variables that were used to predict the 3 groups was at 88.1 percent.
Multi-Label Classifier Design for Predicting the Functional Types of Antimicrobial Peptides

t has special meaning for drug design as well as basic research to study Antimicrobial peptides (AMPs) because they have been demonstrated to kill Gram negative and Gram positive bacteria, mycobacteria, enveloped viruses, fungi and even transformed or cancerous cells. In view of this, it is highly desired to develop an effective computational method for accurately predicting the functional types of AMPs because it can provide us with more candidates and useful insights for drug design. AMP functional recognition is in fact a multi-label classification problem. In this study, up to six kinds of physicochemical properties value are selected to code the AMP sequence as physical-chemical property matrix (PCM), and then auto and cross covariance transformation is performed to extract features from the PCM for AMP sequence expression; At last, a clever use of Fuzzy K nearest neighbor rule will help identify the multiple functions of a query AMP. As a result, the overall classification accuracy about 65% has been achieved through the rigorous Jackknife test on a newly constructed benchmark AMP dataset.
A novel development of head-set type computer mouse using gyro sensors for the handicapped

This paper describes the development of a novel head-set type computer mouse controlled by gyro sensors. This device operates on sensing the rotation of the human neck so that it may serve those who are physically disabled, for example spinal cord injuries and disabilities involving paralysis. For better performance, a novel hybrid operational mode is suggested, which combines the merits of an absolute pointing device and a relative pointing device. Actually, this device is a relative pointing device, but a hybrid mode can be accomplished by adjusting displacement rate of mouse pointer based on angular velocity of the head. The mouse click is controlled by eye blinking which is one of the most convenient behaviors in human behavior. Eye blinking is detected by measuring reflection of infrared rays exposed to muscles near eyes. Conscious and unconscious eye blinking is distinguished by the extent of reflection, because more infrared rays are reflected when user blinks his eyes consciously. This system can be attached to a head-set by virtue of its small bulk. Low cost, comfort and good performance render this system suitable for the design of a head-operating mouse for disabled people.
Flying through design spaces: efficient evolutionary optimisation of aircraft wings

Today’s high-tech products, such as civil aircraft wings, are designed by multidisciplinary teams of experts. Dedicated modeling and simulation tools are used to assess the behavior of the design for each relevant discipline. The required consistency among the different single discipline models is achieved by using an integrated design model, which includes a (large) set of design parameters on which each of the discipline models is based. In order to find the best design, the application of optimization algorithms in combination with the modeling and simulation tools is common practice nowadays. However, for products that require complex models and extensive simulations to assess their behavior, like aircraft wings, such design optimizations may become infeasible due to complicated computational sequences or excessive computational cost. To alleviate such complications, the products’ behavior should be assessed more efficiently. This paper presents a meta-modeling approach, applied to aircraft wing design where aircraft range and fuel consumption are optimized. This approach allows to quickly and conveniently evaluate the wing behavior, and to virtually fly through the considered wing design space. Extensive optimizations, exploiting thousands of metamodel evaluations, are performed using multi-objective genetic algorithms, yielding sets of Pareto optimal wing design points. These points represent those wing designs that have the best feasible fuel consumption for each value of range, and hence directly provide the designer with the most relevant design information.
Participatory-Deliberative Engagement: a literature review

This working paper arises from Lancaster’s literature review (work package 1.1) within the TSEC (Towards a Sustainable Energy Economy) project entitled “Beyond NIMBYism: a multidisciplinary investigation of public engagement with renewable energy technologies”. The paper is one of four working papers produced by project partners, the other papers representing reviews of “regulation and planning”, “NIMBYism” and “public perceptions of energy”.
Internal transport barrier simulation with pellet injection in tokamak and helical reactor plasmas

In the future fusion reactor, the plasma density peaking is important for the increase in the fusion power gain. The density control and the internal transport barrier (ITB) formation due to the pellet injection have been simulated in tokamak and helical reactors using the toroidal transport linkage code TOTAL. Firstly, the pellet injection simulation is carried out including the neutral gas shielding model and the mass relocation model in the TOTAL code, and the effectiveness of the high field side (HFS) pellet injection is clarified. Secondly, the ITB simulation with the pellet injection is carried out with the confinement improvement model based on the E×B shear effects, and it is found that the deep pellet penetration is helpful for the ITB formation as well as the plasma core fuelling in the reversed shear tokamak reactor, but the deep pellet penetration is not effective in the helical reactor.
United or divided in diversity? The heterogeneous effects of ethnic diversity on European and national identities

In this article, we argue that the size and cultural proximity of immigrant populations in people's residential surroundings shape national and European identities. This means that the type of migrant population activates cultural threat perceptions and opportunities for contact to varying degrees. Geocoded survey data from the Netherlands suggests that large non-Western immigrant shares are associated with more exclusive national identities, while mixed contexts with Western and non-Western populations show more inclusive identities. These results suggest that highly diverse areas with mixed immigrant populations hold a potential for more tolerance. In contrast, exclusive national identities become strongly pronounced under the presence of sizeable culturally distant immigrant groups.
Assessment of PDE4 Inhibitor-Induced Hypothermia as a Correlate of Nausea in Mice

Simple Summary Type 4 cAMP-phosphodiesterases (PDE4s) comprise a family of four isoenzymes, PDE4A to D, that hydrolyze and inactivate the second messenger cAMP. Non/PAN-selective PDE4 inhibitors, which inhibit all four PDE4 subtypes simultaneously, produce many promising therapeutic benefits, such as anti-inflammatory or cognition- and memory-enhancing effects. However, unwanted side effects, principally, nausea, diarrhea, and emesis, have long hampered their clinical and commercial success. Targeting individual PDE4 subtypes has been proposed for developing drugs with an improved safety profile, but which PDE4 subtype(s) is/are actually responsible for nausea and emesis remains ill-defined. Based on the observation that nausea is often accompanied by hypothermia in humans and other mammals, we used the measurement of core body temperatures of mice as a potential correlate of nausea induced by PDE4 inhibitors in humans. We find that selective inactivation of any of the four PDE4 subtypes did not change the body temperature of mice, suggesting that PAN-PDE4 inhibitor-induced hypothermia (and hence nausea in humans) requires the simultaneous inhibition of multiple PDE4 subtypes. This finding contrasts with prior reports that proposed PDE4D as the subtype mediating these side effects of PDE4 inhibitors and suggests that subtype-selective inhibitors that target any individual PDE4 subtype, including PDE4D, may not cause nausea. Abstract Treatment with PAN-PDE4 inhibitors has been shown to produce hypothermia in multiple species. Given the growing body of evidence that links nausea and emesis to disturbances in thermoregulation in mammals, we explored PDE4 inhibitor-induced hypothermia as a novel correlate of nausea in mice. Using knockout mice for each of the four PDE4 subtypes, we show that selective inactivation of individual PDE4 subtypes per se does not produce hypothermia, which must instead require the concurrent inactivation of multiple (at least two) PDE4 subtypes. These findings contrast with the role of PDE4s in shortening the duration of α2-adrenoceptor-dependent anesthesia, a behavioral surrogate previously used to assess the emetic potential of PDE4 inhibitors, which is exclusively affected by inactivation of PDE4D. These different outcomes are rooted in the distinct molecular mechanisms that drive these two paradigms; acting as a physiologic α2-adrenoceptor antagonist produces the effect of PDE4/PDE4D inactivation on the duration of α2-adrenoceptor-dependent anesthesia, but does not mediate the effect of PDE4 inhibitors on body temperature in mice. Taken together, our findings suggest that selective inhibition of any individual PDE4 subtype, including inhibition of PDE4D, may be free of nausea and emesis.
Public Perceptions around mHealth Applications during COVID-19 Pandemic: A Network and Sentiment Analysis of Tweets in Saudi Arabia

A series of mitigation efforts were implemented in response to the COVID-19 pandemic in Saudi Arabia, including the development of mobile health applications (mHealth apps) for the public. Assessing the acceptability of mHealth apps among the public is crucial. This study aimed to use Twitter to understand public perceptions around the use of six Saudi mHealth apps used during COVID-19: “Sehha”, “Mawid”, “Sehhaty”, “Tetamman”, “Tawakkalna”, and “Tabaud”. We used two methodological approaches: network and sentiment analysis. We retrieved Twitter data using specific mHealth apps-related keywords. After including relevant tweets, our final mHealth app networks consisted of a total of 4995 Twitter users and 8666 conversational relationships. The largest networks in size (i.e., the number of users) and volume (i.e., the conversational relationships) among all were “Tawakkalna” followed by “Tabaud”, and their conversations were led by diverse governmental accounts. In contrast, the four remaining mHealth networks were mainly led by the health sector and media. Our sentiment analysis approach included five classes and showed that most conversations were neutral, which included facts or information pieces and general inquires. For the automated sentiment classifier, we used Support Vector Machine with AraVec embeddings as it outperformed the other tested classifiers. The sentiment classifier showed an accuracy, precision, recall, and F1-score of 85%. Future studies can use social media and real-time analytics to improve mHealth apps’ services and user experience, especially during health crises.
Safety, Tolerability and Immunogenicity of Oxford-AstraZeneca ChAdOx1 Vaccine Among Polish School-Teachers

Methods Teachers were invited for serological testing ≥ 8 weeks after second vaccination. Quantitative post-vaccination anti-spike antibody responses were measured using the Abbott SARS-CoV-2 IgG II Quant assay (detection threshold: ≥ 7.1 BAU/ml). Multivariable logistic regression methods were used to identify predictors of immunogenicity.
Self-Reported Olfactory Dysfunction and Diet Quality: Findings from the 2011–2014 National Health and Nutrition Examination Survey (NHANES)

We identified associations between self-reported olfactory dysfunction (OD) and dietary attributes in participants aged ≥40 years (n = 6,356) from the nationally representative 2011–2014 National Health and Nutrition Examination Survey (NHANES). The chemosensory questionnaire and 24-h dietary recalls were administered by trained interviewers. OD was defined as self-report of either smell problems in the last year, worse smell relative to age 25, or perceiving phantom odors. Dietary outcomes included Healthy Eating Index 2015 score (HEI) with adequacy and moderation components (higher scores indicated higher diet quality), dietary diversity, energy density, and intake of major food groups. Survey-weighted linear regression models estimated OD–diet associations, adjusting for socio-demographic, lifestyle, and clinical factors. Adjusted mean difference (95% CI) between those with versus without OD, showed that adults with OD had significantly lower HEI moderation score (−0.67 (−1.22, −0.11)) and diets higher in energy density (0.06 (0.00, 0.11)), and percent energy from saturated fat (0.47 (0.12, 0.81)), total fat (0.96 (0.22, 1.70)), and added sugar (1.00 (0.33, 1.66)). Age and sex-stratified analyses showed that younger females (40–64 years) primarily accounted for the associations with diet quality and total/saturated fat intake. These findings inform dietary screening and recommendations for adults who report OD, including those experiencing transient or persistent smell loss with COVID-19.
Predicting COVID-19 Cases in South Korea with All K-Edited Nearest Neighbors Noise Filter and Machine Learning Techniques

The application of machine learning techniques to the epidemiology of COVID-19 is a necessary measure that can be exploited to curtail the further spread of this endemic. Conventional techniques used to determine the epidemiology of COVID-19 are slow and costly, and data are scarce. We investigate the effects of noise filters on the performance of machine learning algorithms on the COVID-19 epidemiology dataset. Noise filter algorithms are used to remove noise from the datasets utilized in this study. We applied nine machine learning techniques to classify the epidemiology of COVID-19, which are bagging, boosting, support vector machine, bidirectional long short-term memory, decision tree, naïve Bayes, k-nearest neighbor, random forest, and multinomial logistic regression. Data from patients who contracted coronavirus disease were collected from the Kaggle database between 23 January 2020 and 24 June 2020. Noisy and filtered data were used in our experiments. As a result of denoising, machine learning models have produced high results for the prediction of COVID-19 cases in South Korea. For isolated cases after performing noise filtering operations, machine learning techniques achieved an accuracy between 98–100%. The results indicate that filtering noise from the dataset can improve the accuracy of COVID-19 case prediction algorithms.
FACTORS DETERMINING GOLD PRICES IN MALAYSIA

Gold is a valuable asset to a country because of its liquidity. Gold reserve can stabilize the currency in a country. The objective of this paper is to identify the factors contributing to the volatility of gold prices, such as Real Malaysia GDP, inflation rates, crude oil prices and exchange rates. The data was analysed using Autoregressive Distributed Lag (ARDL) approach with time series data, with 30-year coverage from 1987 to 2016. Findings showed that only Real Malaysia GDP and crude oil prices were significantly related to gold prices. As a conclusion, this study can be used as reference by other investors. The author suggests to other researchers to further improve upon this study by adding more variables or diversifying the variables that relate to volatility of gold prices
A Comparison of Lipid Contents in Different Types of Peanut Cultivars Using UPLC-Q-TOF-MS-Based Lipidomic Study

Peanuts are a rich dietary source of lipids, which are essential for human health. In this study, the lipid contents of 13 peanut cultivars were analyzed using UPLC-Q-TOF-MS and GC–MS. The OXITEST reactor was used to test their lipid oxidation stabilities. A total of 27 subclasses, 229 individual lipids were detected. The combined analysis of lipid and oxidation stability showed that lipid unsaturation was inversely correlated with oxidation stability. Moreover, lipid profiles differed significantly among the different peanut cultivars. A total of 11 lipid molecules (TG 18:2/18:2/18:2, TG 24:0/18:2/18:3, TG 20:5/14:1/18:2, TG 18:2/14:1/18:2, PE 17:0/18:2, BisMePA 18:2/18:2, PG 38:5, PMe 18:1/18:1, PC 18:1/18:1, MGDG 18:1/18:1, TG 10:0/10:1/18:1) might be employed as possible indicators to identify high oleic acid (OA) and non-high OA peanut cultivars, based on the PLS-DA result of lipid molecules with a VIP value greater than 2. This comprehensive analysis will help in the rational selection and application of peanut cultivars.