Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel Processing of Sensor Data in a Distributed Rules Engine Environment through Clustering and Data Flow Reconfiguration

An emerging reality is the development of smart buildings and cities, which improve residents’ comfort. These environments employ multiple sensor networks, whose data must be acquired and processed in real time by multiple rule engines, which trigger events that enable specific actuators. The problem is how to handle those data in a scalable manner by using multiple processing instances to maximize the system throughput. This paper considers the types of sensors that are used in these scenarios and proposes a model for abstracting the information flow as a weighted dependency graph. Two parallel computing methods are then proposed for obtaining an efficient data flow: a variation of the parallel k-means clustering algorithm and a custom genetic algorithm. Simulation results show that the two proposed flow reconfiguration algorithms reduce the rule processing times and provide an efficient solution for increasing the scalability of the considered environment. Another aspect being discussed is using an open-source cloud solution to manage the system and how to use the two algorithms to increase efficiency. These methods allow for a seamless increase in the number of sensors in the environment by making smart use of the available resources.
The Causal Association of Irritable Bowel Syndrome with Multiple Disease Outcomes: A Phenome-Wide Mendelian Randomization Study

Background: This study aimed to identify novel associations between irritable bowel syndrome (IBS) and a broad range of outcomes. Methods: In total, 346,352 white participants in the U.K. Biobank were randomly divided into two halves, in which a genome-wide association study (GWAS) of IBS and a polygenic risk score (PRS) analysis of IBS using GWAS summary statistics were conducted, respectively. A phenome-wide association study (PheWAS) based on the PRS of IBS was performed to identify disease outcomes associated with IBS. Then, the causalities of these associations were tested by both one-sample (individual-level data in U.K. Biobank) and two-sample (publicly available summary statistics) Mendelian randomization (MR). Sex-stratified PheWAS-MR analyses were performed in male and female, separately. Results: Our PheWAS identified five diseases associated with genetically predicted IBS. Conventional MR confirmed these causal associations between IBS and depression (OR: 1.07, 95%CI: 1.01–1.14, p = 0.02), diverticular diseases of the intestine (OR: 1.13, 95%CI: 1.08–1.19, p = 3.00 × 10−6), gastro-esophageal reflux disease (OR: 1.09, 95%CI: 1.05–1.13, p = 3.72 × 10−5), dyspepsia (OR: 1.21, 95%CI: 1.13–1.30, p = 9.28 × 10−8), and diaphragmatic hernia (OR: 1.10, 95%CI: 1.05–1.15, p = 2.75 × 10−5). The causality of these associations was observed in female only, but not men. Conclusions: Increased risks of IBS is found to cause a series of disease outcomes. Our findings support further investigation on the clinical relevance of increased IBS risks with mental and digestive disorders.
Rapid Appraisals of the Transformation Strategy Required to Sustain Dengue Vector Control During and After the COVID-19 Pandemic in Indonesia

Purpose This research aimed to observe the gap for improvement in dengue vector control during COVID-19, considering two stakeholders: the government and society. We formulated two research questions: 1) How is the government managing dengue vector control during the COVID-19 pandemic? 2) What is the situation of dengue disease, its vectors, and vector control in the community? Methods This study uses multiple approaches: policy review, social listening using Twitter analysis, and interviews. A policy review was employed to capture the journey of dengue vector control in Indonesia from dengue found in Indonesia until the COVID-19 pandemic. Twitter data captured public opinions through social media about dengue and vector control. Interviews involved program implementers that consider knowing the situation in the field of dengue and its vector control. The informant was selected through purposive sampling. Results To control dengue disease, the Indonesian government has released regulations about dengue vector control that adjusts the COVID-19 situation, but vector control is still not running optimally, resulting in the data supply for policy not running well. Conclusion Dengue cases continued during the COVID-19 pandemic, even in some places stated an outbreak occurred. Vector control does not work correctly during the COVID-19 pandemic due to social restrictions. It is recommended to encourage the implementation of community empowerment through one house, one jumantik, which is equipped with self-reporting to mitigate and respond to similar situations as the pandemic.
Engaging Employers in Apprentice Training: Focus Group Insights from Small-to-Medium-Sized Employers in Ontario, Canada

Several factors have been identified to influence the registration and retention of apprentices in the construction trades. Employer engagement is a key factor to promote growth in apprenticeships in the construction trades as participation rates continue to be low among small-to-medium-sized employers. In this study, we evaluated the effectiveness of the Ontario Electrical League’s (OEL) employer mentorship program through the perspectives of small-to-medium-sized employers using a qualitative approach. Two focus groups were conducted virtually with 11 employers. Focus group audio transcripts were recorded and transcribed for thematic analysis. Themes were generated using a data-driven approach to examine the relationships between mentorship program outcomes and perspectives on industry-related recruitment and retention barriers. Three themes were identified: (a) long-term apprentice recruitment and retention challenges; (b) equity and mental health in the workplace; and (c) industry challenges and mentorship program outcomes. Generally, this sample of employers appreciated the value of the OEL mentorship program through praise of the continued educational support, employer management expertise, hiring resources, and apprentice onboarding tools despite industry barriers in trade stigma, equity and mental health in the workplace, and recruitment and retention challenges. Industry partners should work with these small-to-medium-sized employers to develop workplace initiatives and engage external partners to provide ongoing apprenticeship mentorship support to address the recruitment and retention barriers identified in this study.
Field Investigation into Tree Fates from Recent Apple Tree Decline: Abrupt Hydraulic Failure Versus Gradual Hydraulic Loss

In the last decade, a sporadic tree health syndrome affecting high-density apple plantings in North America has become known as Rapid Apple Decline (RAD) or Sudden Apple Decline (SAD). The affected apple trees were typically grafted on small dwarfing rootstocks, often displayed necrosis at the graft union, and suffered from sudden mortality that occurred over 2–3 weeks amid the growing season or a gradual decline. In 2019 and 2020, we conducted a multi-site investigation in the south Okanagan, British Columbia, Canada, to assess the stem hydraulic characteristics, stomatal conductance, leaf δ13C‰, and fruit dry matter accumulation of the declining trees during disease progression. In trees that died, mortality appeared to be associated with severe disruption in xylem water transport at the damaged graft union, followed by abrupt hydraulic failure. In contrast, symptomatic trees that did not die exhibited the moderately declined plant water relations and a reduction in fruit dry matter accumulation followed by either further deterioration or eventual recovery. This pattern indicates the risk of carbohydrate depletion over gradual hydraulic decline and the importance of timely horticultural remedies. In the present study, we discuss potential horticultural practices to mitigate hydraulic dysfunctions and enhance crop tolerance.
Risk Assessment of Pesticide Residues by GC-MSMS and UPLC-MSMS in Edible Vegetables

In recent years, there has been a significant increase related to pesticide residues in foods, which may increase the risks to the consumer of these foods with the different quality and concentrations of pesticide residues. Pesticides are used for controlling pests that reduce yields. On the other hand, it has become a major public health concern due to its toxic properties. Thus, the objective of the current study employed the application of Quick Easy Cheap Effective Rugged Safe (QuEChERS) method, in combination with gas and liquid chromatography-tandem mass spectrometric detection (GCMSMS, LCMSMS) in order to determine 137 pesticide residues (63 insecticides, 41 acaricides, 40 herbicide, 55 fungicide, nematicide, growth regulator, Chitin synthesis inhibitors, and Juvenile hormone mimics), in 801 vegetables such as 139 tomatoes, 185 peppers, 217 squash, 94 eggplants, and 166 cucumbers from different locations in Hail and Riyadh cities. The results showed that the majority of pesticide residues were detected for each of the following pesticides: acetaimpride, metalaxyl, imidaclopride, bifenthrin, pyridaben, difenoconazole, and azoxystrobien, which were repeated in the samples studied 39, 21, 11, 10, 8, 7, and 5, respectively. In addition, results observed that the tomato was the most contaminated with pesticide residues; it was contaminated with 19 compounds and was followed by pepper, cucumber, and squash, and the last commodity in the contaminated ranking was eggplant. The highest calculated estimated daily intakes (EDIs) were recorded for tomatoes which were estimated between 0.013 to 0.516 mg/kg of body weight per day (bw/day) while the lowest EDIs value was between 0.000002 to 0.0005 mg/kg of bw/day for cucumber. Results indicated that the EDIs values were lower than the acceptable daily intake (ADI) values. Results observed that the most of pesticide residues exposure in food consumption in Saudi Arabia were lower than ADIs. In addition, the highest value for health risk index (HRI) was recorded with Ethion residue in tomato, but in sweet pepper, the highest value for HRI was 127.5 in the form of fipronil residue. On the other hand, results found that the highest values of HRI were 1.54, 1.61, and 0.047 for difenoconazole, bifenthrin, and pyridaben residues in squash, eggplant, and cucumber.
Supercritical Fluid Extraction of Oils from Cactus Opuntia ficus-indica L. and Opuntia dillenii Seeds

This study aimed to assess the capability of supercritical fluid extraction (SFE) as an alternative and green technique compared to Soxhlet extraction for the production of oils from Opuntia ficus-indica (OFI) seeds originating from Yemen and Italy and Opuntia dillenii (OD) seeds from Yemen. The following parameters were used for SFE extraction: a pressure of 300 bar, a CO2 flow rate of 1 L/h, and temperatures of 40 and 60 °C. The chemical composition, including the fatty acids and tocopherols (vitamin E) of the oils, was determined using chromatographic methods. The highest yield was achieved with Soxhlet extraction. The oils obtained with the different extraction procedures were all characterized by a high level of unsaturated fatty acids. Linoleic acid (≤62% in all samples) was the most abundant one, followed by oleic and vaccenic acid. Thirty triacylglycerols (TAGs) were identified in both OFI and OD seed oils, with trilinolein being the most abundant (29–35%). Vanillin, 4-hydroxybenzaldehyde, vanillic acid, and hydroxytyrosol were phenols detected in both OFI and OD oils. The highest γ-tocopherol content (177 ± 0.23 mg/100 g) was obtained through the SFE of OFI seeds from Yemen. Overall, the results highlighted the potential of SFE as green technology to obtain oils suitable for functional food and nutraceutical products.
Safe Travel Practices and Awareness among Diabetic Patients

Objective To measure the knowledge of Saudi patients with diabetes in coping with their condition and to assess their practice of disease control during travels. Study Design. Cross-sectional study using a self-administered questionnaire. Method This study was conducted between September 2018 and May 2019 at a University hospital in Riyadh, Saudi Arabia. The questions were adopted from guidelines and advices provided by the CDC, American Diabetic Association, and other references. Bivariate and multivariate analyses were used to identify factors associated with diabetic control during travels. Results From the included 242 patients, 33.6% showed the good practice of diabetic control during travels. 23.7% of patients were communicated by their doctors about the importance of consultations before traveling and 20.7% encountered complications during travels. Factors associated with doctors' consultation before travel are patients' concerns about travel duration and possible risks during trip. (OR = 2.588, 95% CI = 5.308–1.261), (OR = 3.525, 95% CI = 8.152–1.525); respectively. Conclusion Patient awareness and education about the importance of proper diabetic self-monitoring and control during travels is crucial as the study showed suboptimal diabetes management practice. Practice Implications. Physicians should proactively educate patients about the importance of seeking advice before their travels.
Approximate Riemann Solvers and Robust High-Order Finite Volume Schemes for Multi-Dimensional Ideal MHD Equations

We design stable and high-order accurate finite volume schemes for the ideal MHD equations in multi-dimensions. We obtain excellent numerical stability due to some new elements in the algorithm. The schemes are based on three- and five-wave approximate Riemann solvers of the HLL-type, with the novelty that we allow a varying normal magnetic field. This is achieved by considering the semi-conservative Godunov-Powell form of the MHD equations. We show that it is important to discretize the Godunov-Powell source term in the right way, and that the HLL-type solvers naturally provide a stable upwind discretization. Second-order versions of the ENO- and WENO-type reconstructions are proposed, together with precise modifications necessary to preserve positive pressure and density. Extending the discrete source term to second order while maintaining stability requires non-standard techniques, which we present. The first- and second-order schemes are tested on a suite of numerical experiments demonstrating impressive numerical resolution as well as stability, even on very fine meshes.
FREE CONVECTION HEAT TRANSFER FROM AN ISOTHERMAL WAVY SURFACE IN A POROUS ENCLOSURE

The coupled streamfuction–temperature equations governing the Darcian flow and convection process in a fluid-saturated porous enclosure with an isothermal sinusoidal bottom sun face, has been numerically analyzed using a finite element method (FEM). No restrictions have been imposed on the geometrical non-linearity arising from the parameters like wave amplitude (a), number of waves per unit length (N), wave phase (Φ), aspect ratio (A) and also on the flow driving parameter Rayleigh number (Ra). The numerical simulations for varying values of Ra bring about interesting flow features, like the transformation of a unicellular flow to a multicellular flow. Both with increasing amplitude and increasing number of waves per unit length, owing to the shift in the separation and reattachment points, a row–column pattern of multicellular flow transforms to a simple row of multicellular flow. A cycle of n celluar and n+1 cellular flows, with the flow in adjacent cells in the opposite direction, periodically manifest with phase varying between 0 and 360°. The global heat transfer into the system has been found to decrease with increasing amplitude and increasing number of waves per unit length. Only marginal changes in the global heat flux are observed, either with increasing Ra or varying Φ. Effectively, sinusoidal bottom surface undulations of the isothermal wall of a porous enclosure reduces the heat transfer into the system. © 1998 John Wiley & Sons, Ltd.
Learn by Oneself: Exploiting Weight-Sharing Potential in Knowledge Distillation Guided Ensemble Network

Recent CNNs (convolutional neural networks) have become more and more compact. The elegant structure design highly improves the performance of CNNs. With the development of knowledge distillation technique, the performance of CNNs gets further improved. However, existing knowledge distillation guided methods either rely on offline pretrained high-quality large teacher models or online heavy training burden. To solve the above problems, we propose a feature-sharing and weight-sharing based ensemble network (training framework) guided by knowledge distillation (EKD-FWSNet) to make baseline models stronger in terms of representation ability with less training computation and memory cost involved. Specifically, motivated by getting rid of the dependence of offline pretrained teacher model, we design an end-to-end online training scheme to optimize EKD-FWSNet. Motivated by decreasing the online training burden, we only introduce one auxiliary classmate branch to construct multiple forward branches, which will then be integrated as ensemble teacher to guide baseline model. Compared to previous online ensemble training frameworks, EKD-FWSNet can provide diverse output predictions without relying on increasing auxiliary classmate branches. Motivated by maximizing the optimization power of EKD-FWSNet, we exploit the representation potential of weight-sharing blocks and design efficient knowledge distillation mechanism in EKD-FWSNet. Extensive comparison experiments and visualization analysis on benchmark datasets (CIFAR-10/100, tiny-ImageNet, CUB-200 and ImageNet) show that self-learned EKD-FWSNet can boost the performance of baseline models by large margin, which has obvious superiority compared to previous related methods. Extensive analysis also proves the interpretability of EKD-FWSNet. Our code is available at https://github.com/cv516Buaa/EKD-FWSNet.
The effect of corporate governance elements on corporate social responsibility reporting of listed companies in Vietnam

Abstract This paper examines the impact of various corporate governance characteristics on the disclosure of corporate social responsibility (CSR) information in the context of developing markets during the COVID-19 pandemic. We used data from the annual reports of the top 100 companies listed on the Ho Chi Minh Stock Exchange from 2019 to 2021 to investigate the relationship between board independence, board size, CEO duality, foreign ownership, government ownership, and the disclosure level of CSR reporting. We employed a content analysis to measure CSR disclosure level by using the CSR reporting index (CSRRI) with 17 items. The panel regressions including three techniques like the pooled-ordinary least squares (OLS), fixed effects model (FEM), and random effects model (REM), were used to analyze the data, and FEM) shows its best fit to the model. The results suggest that board independence and government ownership correlate positively and significantly with companies’ decisions to disclose CSR information. In contrast, board size, CEO duality, foreign ownership and was found to be insignificant. Our study extends the literature on CSR particularly in developing countries where governments play a significant role in promoting economic development. It also evaluates the CSR disclosure level of the top listed companies in Vietnam. Since then, the paper’s results provide several insights to the policymakers to identify the corporate governance characteristics that will promote CSR reporting in Vietnam’s listed companies.
Application of ARIMA, and hybrid ARIMA Models in predicting and forecasting tuberculosis incidences among children in Homa Bay and Turkana Counties, Kenya

Tuberculosis (TB) infections among children (below 15 years) is a growing concern, particularly in resource-limited settings. However, the TB burden among children is relatively unknown in Kenya where two-thirds of estimated TB cases are undiagnosed annually. Very few studies have used Autoregressive Integrated Moving Average (ARIMA), and hybrid ARIMA models to model infectious diseases globally. We applied ARIMA, and hybrid ARIMA models to predict and forecast TB incidences among children in Homa Bay and Turkana Counties in Kenya. The ARIMA, and hybrid models were used to predict and forecast monthly TB cases reported in the Treatment Information from Basic Unit (TIBU) system by health facilities in Homa Bay and Turkana Counties between 2012 and 2021. The best parsimonious ARIMA model that minimizes errors was selected based on a rolling window cross-validation procedure. The hybrid ARIMA-ANN model produced better predictive and forecast accuracy compared to the Seasonal ARIMA (0,0,1,1,0,1,12) model. Furthermore, using the Diebold-Mariano (DM) test, the predictive accuracy of ARIMA-ANN versus ARIMA (0,0,1,1,0,1,12) model were significantly different, p<0.001, respectively. The forecasts showed a TB incidence of 175 TB cases per 100,000 (161 to 188 TB incidences per 100,000 population) children in Homa Bay and Turkana Counties in 2022. The hybrid (ARIMA-ANN) model produces better predictive and forecast accuracy compared to the single ARIMA model. The findings show evidence that the incidence of TB among children below 15 years in Homa Bay and Turkana Counties is significantly under-reported and is potentially higher than the national average.
Analysis Of Mapping The Potential Of The Creative Economy In Bintan Regency During The Covid-19

The Creative Economy is one of the economic activities that have an essential meaning in supporting the financial resilience of the people of Bintan Regency, developing innovation, creativity, and competitiveness, realizing economic growth, and creating job opportunities in Bintan Regency. The purpose of this study is to analyze several potentials during the COVID-19 pandemic in the Creative Economy sector in Bintan Regency, which prioritizes the Need for Human Resources and Natural Resources that have the opportunity to be appropriately managed. The research method used is descriptive qualitative with a case study approach in Bintan Regency. Secondary data regarding the Creative Economy are collected and subsequently studied in depth. The findings show that the Creative Economy in Bintan Regency is in bad condition. Due to the prevalence of tourism activities that attract tourists as targets for expanding the Creative Economy in border regions with neighboring nations, it has become identified that there is neither a strong appeal nor a substantial market. In addition, there is a need to strengthen capital and identify potential, lay the economic base, and support future policies for the Creative Economy during the COVID-19 pandemic in Bintan Regency.
A WKB asymptotic analysis of baroclinic instability

Abstract A modest extension of conventional WKB methods of solving second-order differential equations asymptotically is developed and applied to the problem of baroclinic instability. Accurate results are obtained for the Charney problem using simple expressions. More important, the present expressions can be used immediately for a wide variety of basic velocity profiles.
Finite full transformation semigroups as collections of random functions

The collection of all self-maps on a non-empty set X under composition is known in algebraic semigroup theory as the full transformation semigroup on X and is written x. Its importance lies in the fact that any semigroup S can be embedded in the full transformation semigroup (where S1 is the semigroup S with identity 1 adjoined, if S does not already possess one). The proof is similar to Cayley's Theorem that a group G can be embedded in SG, the group of all bijections of G to itself. In this paper X will be a finite set of order n, which we take to be and so we shall write Tn for X.