Miracle-dz/UniFAR-FTUs huggingface dataset:
Epigallocatechin Gallate Induces the Demethylation of Actinin Alpha 4 to Inhibit Diabetic Nephropathy Renal Fibrosis via the NF-KB Signaling Pathway In Vitro

Actinin alpha 4 (ACTN4) is expressed in the kidney podocytes. ACTN4 gene methylation in patients with diabetic nephropathy (DN) remains high. Underlying mechanism of epigallocatechin-3-gallate (EGCG) inducing ACTN4 demethylation, and its inhibitory effect on DN renal fibrosis remains unclear. Methods: Human podocyte cell line, HPC, was treated with high glucose to establish model of DN. The levels of cytokines, vascular endothelial growth factor (VEGF) and interleukin (IL)-8, and fibrosis markers, alpha smooth muscle actin (α-SMA) and fibronectin (FN), were determined using enzyme-linked immunosorbent assay. HPC cells were treated with EGCG, and cell viability was determined by MTT assay, ACTN4 gene methylation was analyzed by MSP. mRNA and protein expression levels were measured using RT-qPCR and Western blotting, respectively. Results: Actinin alpha 4 gene promoter was hypermethylated in the high glucose-treated groups. EGCG reversed the hypermethylated status of ACTN4, along with the upregulation of ACTN4 levels and downregulation of DNA methyltransferase 1 (DNMT1), NF-κB p65, p-NF-κB p65, IκB-α, VEGF, IL-8, α-SMA, and FN levels (P<.05). Conclusion: Epigallocatechin-3-gallate reduced hypermethylation of ACTN4 in HPC cells by downregulating DNMT1 expression and restoring ACTN4 expression, contributing to the upregulation of the NF-KB p65, p-NF-KB p65, IKB-α, VEGF, IL-8, α-SMA, and FN levels (P<.05).
Blockchain-Based Traceability System to Support the Indonesian Halal Supply Chain Ecosystem

The halal industry is constantly developing into a broader concept of the Islamic economy, an economic activity that follows the Islamic-based principle. As a populous Muslim country, Indonesia follows the growth trend by aiming to dominate the global halal market. The strategy is to improve the current halal assurance process. Presently, the technology and procedure do not provide enough process transparency, traceability, and granularity of information. To achieve the strategic goal, a technological change is needed. A new emerging technology, blockchain, may potentially answer the challenge. This study’s first objective is to discuss improving the current assurance practice in the Indonesian halal supply chain ecosystem, particularly in the meat industry. The second objective is to construct a traceability system model for the supply chain. Our goal is to propose a blockchain-based halal traceability system model. The model can be enhanced to be a national standard tool to develop the economy towards a sustainable supply chain.
Psychometric Properties and Measurement Invariance of the Academic Procrastination Scale-Short Form in Spanish Children and Adolescents

The objectives were to examine the factorial structure of the Academic Procrastination Scale-Short Form (APS-S) and the measurement invariance across gender and educational levels, to determine possible differences in procrastination across gender, educational levels, and grades. The sample was formed of 1486 Spanish primary and secondary school students between the ages of 7 and 19 years. A one-factor model provided an adequate fit. Scalar and partial scalar invariance were achieved through gender and educational levels, respectively. Internal consistency was good and slightly higher for secondary school students than primary school students. Moderate convergent validity was obtained. The APS-S scores showed a weak but significant correlation with math anxiety. Procrastination scores increased with grade, and males showed significantly higher procrastination scores than females. The Spanish APS-S demonstrated adequate reliability and validity scores and could be a useful tool for examining academic procrastination in children and adolescents.
Adaptive Method for Packet Loss Types in IoT: An Naive Bayes Distinguisher

With the rapid development of IoT (Internet of Things), massive data is delivered through trillions of interconnected smart devices. The heterogeneous networks trigger frequently the congestion and influence indirectly the application of IoT. The traditional TCP will highly possible to be reformed supporting the IoT. In this paper, we find the different characteristics of packet loss in hybrid wireless and wired channels, and develop a novel congestion control called NB-TCP (Naive Bayesian) in IoT. NB-TCP constructs a Naive Bayesian distinguisher model, which can capture the packet loss state and effectively classify the packet loss types from the wireless or the wired. More importantly, it cannot cause too much load on the network, but has fast classification speed, high accuracy and stability. Simulation results using NS2 show that NB-TCP achieves up to 0.95 classification accuracy and achieves good throughput, fairness and friendliness in the hybrid network.
The impact of faculty member's communication behaviours on student satisfaction: the role of cognitive and affective learning and student's motivation

Although the benefits of faculty member's communication behaviours have been examined and discussed in earlier studies, they have been mostly done in the context of traditional classrooms or online learning. This study examines the effect of faculty member's communication behaviours on student's motivation which further impacts students' affective and cognitive learning. Further, this study also investigates the relationship between student's learning (affective learning and cognitive learning) and students' satisfaction in the case study method of teaching. The hypothesised relationships were tested using a sample of 265 post-graduate management students from the Business School of India. The results indicated that faculty member's communication behaviours had a positive effect on student's motivation and student's motivation had a positive effect on the affective and cognitive learning. Further, cognitive learning and affective learning were found to have significant positive impact on student's satisfaction.
A two and three-dimensional CFD investigation into performance prediction and wake characterisation of a vertical axis turbine

This material is based upon work supported by the Science Foundation Ireland under Grant No. 12/RC/2302 through MaREI, the national centre for Marine and Renewable Energy Ireland. The authors wish to acknowledge the contribution of Professor Martin Wosnik of the School of Marine Science and Ocean Engineering from the University of New Hampshire, USA, for providing all experimental data for this research. The authors also wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.
What drives formal and informal cash and in-kind giving, and volunteering, and is the relationship substitutable or complementary? Evidence from Ghana

ABSTRACT Anecdotal evidence of philanthropic practices has accumulated over the years through oral traditions and all over the psyche of the African, yet it is seldom studied empirically. By decomposing charitable giving into its spheres of formal and informal, this study examined the determinants and relationship of charitable giving in Ghana. Our findings, based on survey data from 1,533 household heads and instrumental variable probit model, revealed that while marital status, education, household size, religiosity, ethnicity, and empathic concern are important predictors of formal cash and in-kind giving, informal cash and in-kind giving is driven by income, religiosity and empathic concern. On the other hand, it was evident that formal volunteering is mainly determined by income, household size, religiosity, and empathic concern, whereas gender and religiosity influence informal volunteering. Furthermore, we established that, in both spheres of formal and informal giving, the relationship between cash and in-kind giving and volunteering is complementary. Premised on these findings, we recommend nonprofits and policymakers to recognize the complementary role and distinctive determinants of the spheres of giving in designing tools and policies to raise the levels and effectiveness of fundraising and volunteering campaigns.
A Distributed Electricity Trading System in Active Distribution Networks Based on Multi-Agent Coalition and Blockchain

The prevalence of distributed energy resources encourages the concept of an electricity “Prosumer (Producer and Consumer)”. This paper proposes a distributed electricity trading system to facilitate the peer-to-peer electricity sharing among prosumers. The proposed system includes two layers. In the first layer, a multi-agent system is designed to support the prosumer network, and an agent coalition mechanism is proposed to enable the prosumers to form coalitions and negotiate electricity trading. In the second layer, a Blockchain based transaction settlement mechanism is proposed to enable the trusted and secure settlement of electricity trading transactions formed in the first layer. Simulations are conducted based on the java agent development environment to validate the proposed electricity trading process.
Knee Pain from Osteoarthritis: Pathogenesis, Risk Factors, and Recent Evidence on Physical Therapy Interventions

For patients presenting knee pain coming from osteoarthritis (OA), non-pharmacological conservative treatments (e.g., physical therapy interventions) are among the first methods in orthopedics and rehabilitation to prevent OA progression and avoid knee surgery. However, the best strategy for each patient is difficult to establish, because knee OA’s exact causes of progression are not entirely understood. This narrative review presents (i) the most recent update on the pathogenesis of knee OA with the risk factors for developing OA and (ii) the most recent evidence for reducing knee pain with physical therapy intervention such as Diathermy, Exercise therapy, Ultrasounds, Knee Brace, and Electrical stimulation. In addition, we calculated the relative risk reduction in pain perception for each intervention. Our results show that only Brace interventions always reached the minimum for clinical efficiency, making the intervention significant and valuable for the patients regarding their Quality of Life. In addition, more than half of the Exercise and Diathermy interventions reached the minimum for clinical efficiency regarding pain level. This literature review helps clinicians to make evidence-based decisions for reducing knee pain and treating people living with knee OA to prevent knee replacement.
Procedural Feasibility and Long-Term Efficacy of Catheter Ablation of Atypical Atrial Flutters in a Wide Spectrum of Heart Diseases: An Updated Clinical Overview

Atypical atrial flutters (AAFL) are difficult-to-manage atrial arrhythmias, yet potentially amenable to effective radiofrequency catheter ablation (CA). However, data on CA feasibility are only sparingly reported in the literature in different clinical settings, such as AAFL related to surgical correction of congenital heart disease. The aim of this review was to provide an overview of the clinical settings in which AAFL may occur to help the cardiac electrophysiologist in the prediction of the tachycardia circuit location before CA. Moreover, the role and proper implementation of cutting-edge technologies in this setting were investigated as well as which procedural and clinical factors are associated with long-term failure to maintain sinus rhythm (SR) to find out which patients may, or may not, benefit from this procedure. Not only different surgical and non-surgical scenarios are associated with peculiar anatomical location of AAFL, but we also found that CA of AAFL is generally feasible. The success rate may be as low as 50% in surgically corrected congenital heart disease (CHD) patients but up to about 90% on average after pulmonary vein isolation (PVI) or in patients without structural heart disease. Over the years, the progressive implementation of three-dimensional mapping systems and high-density mapping tools has also proved helpful for ablation of these macro-reentrant circuits. However, the long-term maintenance of SR may still be suboptimal due to the progressive electroanatomic atrial remodeling occurring after cardiac surgery or other interventional procedures, thus limiting the likelihood of successful ablation in specific clinical settings.
Efficacy of the intraoperative opioid-sparing anesthesia on quality of patients’ recovery in video-assisted thoracoscopic surgery: a randomized trial

Background We aimed to explore the impact of opioid-sparing anesthesia on patients’ quality of recovery after video-assisted thoracoscopic surgery (VATS). We tested the primary hypothesis that our predefined opioid-sparing anesthesia provides better quality of patients’ recovery compared to routine anesthesia in VATS. Methods Patients between 18 and 70 years, scheduled for elective VATS, had an American Society of Anesthesiologists (ASA) class I–III under general anesthesia, were randomly allocated to: routine anesthesia group and opioid-sparing anesthesia group. Patients in the opioid-sparing anesthesia group were mainly given preoperative thoracic paravertebral blockade with intraoperative withholding longer acting opioids. Patients in routine anesthesia group received opioid-based anesthesia. The primary outcome was the Quality of Recovery-15 scale (QoR-15) at 6 hours after surgery. The secondary outcomes included QoR-15 at 24 and 48 hours after surgery, Overall Benefit of Analgesia Score Satisfaction with pain treatment (OBAS) and acute pain intensity at 6, 24 and 48 hours after surgery, and clinical outcomes of recovery after surgery. Results A total of 159 patients were included in final analysis. The median difference in QoR-15 between opioid-sparing anesthesia and routine anesthesia was 4 (95% CI: 1–6) at 6 hours, 8 (95% CI: 4–12) at 24 hours and 4.7 (95% CI: 1–6) at 48 hours after surgery respectively; 73.4% of patient showed good recovery in opioid-sparing anesthesia group, compared to 53.8% in routine anesthesia group at 24 hours after surgery (P=0.01). Patients demonstrated lower OBAS in opioid-sparing anesthesia group compared to routine anesthesia at all time points after surgery (P<0.05). The pain at most was significantly lower in opioid-sparing anesthesia group compared to routine anesthesia at 6 and 48 hours after surgery (P<0.05). Patients exhibited faster recovery with opioid-sparing anesthesia on time to mobilize and time to first flatus (P<0.01). Conclusions Our intraoperative opioid-sparing anesthesia cannot improve patients’ recovery at 6 hours after VATS lung surgery, but it demonstrates better outcomes at 24 hours after surgery compared to routine anesthesia, reaching to a clinically important difference. Trial Registration This study is registered in the Chinese Clinical Trial Registry, ChiCTR2000031609.
Next generation sequencing for the water industry

The wastewater industry uses biotechnology to ensure that the discharge of sewage does not have deleterious effects on the environment, yet knowledge of the underlying microbiology is poor. This leads to over engineered and inefficient processes which occasionally and unexpectedly fail. Similarly the impact of sewage on the microbiology of receiving waters is unclear. Recent developments in DNA sequencing have enabled its use where cost was prohibitive. I investigated two applications of Next Generation Sequencing (NGS); activated sludge process monitoring for nitrification, foaming and bulking, and microbial source tracking of faecal contamination in bathing waters. Samples from 32 activated sludge plants (ASPs) were collected and analysed. Cell specific ammonia oxidation rates were calculated using the equation CSAOR = (A × M ×106) ×r AOB ×MLSS ×V where A = grams of ammonia oxidised, M = the number of moles of ammonia in a gram, r = correction factor of 0.9 due to some ammonia removal by adsorption and assimilation (Daims, Ramsing, et al. 2001), MLSS = mixed liquor suspended solids in mg/L and V = the volume of the aeration basin in litres. The CSAOR in nitrifying plants ranged from one to ten mmol / cell / hour, in agreement with other CSAOR studies using alternative techniques. Biological foaming in ASPs occurs when the abundance of filamentous bacteria with hydrophobic surface membranes becomes excessive, though the exact abundance threshold above which foaming occurs has not yet been established. The relative abundance of bacteria associated with foaming was measured for all ASPs which were then categorised as non-foaming, occasionally-foaming or currently-foaming based on operator assessment. There was a significant difference in the abundance of foaming bacteria between non-foaming and occasionally foaming plants (ANOVA p < 0.001), with all non-foaming plants having less than 1% relative abundance of foaming bacteria. These results demonstrate that NGS could be a useful ASP process monitoring tool. A bathing water catchment was sampled throughout a bathing season, including a storm event. Partial least squares analysis showed there was a significant correlation between faecal indicator bacteria and the cumulative apportioned fraction of sources (using Bayesian statistics) in the bathing water community (p < 0.001, r2 = 87%). Faecal host marker analysis detected human contamination upstream of any wastewater network inputs, illustrating the impact of diffuse human pollution. Whole community analysis apportioned the bathing water microbial community to point and diffuse sources, and found that whilst human sources were dominant during storm conditions, in dry weather the primary source of faecal contamination was variable and in some cases could not be attributed to known faecal sources.
Ice-nucleating particles from multiple aerosol sources in the urban environment of Beijing under mixed-phase cloud conditions

Abstract. Ice crystals occurring in mixed-phase clouds play a vital role in global precipitation and energy balance because of the unstable equilibrium between coexistent liquid droplets and ice crystals, which affects cloud lifetime and radiative properties, as well as precipitation formation. Satellite observations proved that immersion freezing, i.e., ice formation on particles immersed within aqueous droplets, is the dominant ice nucleation (IN) pathway in mixed-phase clouds. However, the impact of anthropogenic emissions on atmospheric IN in the urban environment remains ambiguous. In this study, we present in situ observations of ambient ice-nucleating particle number concentration (NINP) measured at mixed-phase cloud conditions (−30 ∘C, relative humidity with respect to liquid water RHw= 104 %) and the physicochemical properties of ambient aerosol, including chemical composition and size distribution, at an urban site in Beijing during the traditional Chinese Spring Festival. The impact of multiple aerosol sources such as firework emissions, local traffic emissions, mineral dust, and urban secondary aerosols on NINP is investigated. The results show that NINP during the dust event reaches up to 160 # L−1 (where “#” represents number of particles), with an activation fraction (AF) of 0.0036 % ± 0.0011 %. During the rest of the observation, NINP is on the order of 10−1 to 10 # L−1, with an average AF between 0.0001 % and 0.0002 %. No obvious dependence of NINP on the number concentration of particles larger than 500 nm (N500) or black carbon (BC) mass concentration (mBC) is found throughout the field observation. The results indicate a substantial NINP increase during the dust event, although the observation took place at an urban site with high background aerosol concentration. Meanwhile, the presence of atmospheric BC from firework and traffic emissions, along with urban aerosols formed via secondary transformation during heavily polluted periods, does not influence the observed INP concentration. Our study corroborates previous laboratory and field findings that anthropogenic BC emission has a negligible effect on NINP and that NINP is unaffected by heavy pollution in the urban environment under mixed-phase cloud conditions.
Exotic structures of a thin film of chiral liquid crystals: a numerical study based on the Landau–de Gennes theory

Chiral liquid crystals exhibit various intriguing ordered structures arising from helical distortions of the orientational order allowed by chirality. We present our numerical studies on such exotic structures of chiral liquid crystals, particularly focusing on those in a thin film whose thickness is on the order of or smaller than the characteristic helical pitch of the liquid crystal. We first review the Landau–de Gennes continuum theory we use in our calculations, in which the orientational order is described by a second-rank tensor and the free energy of a liquid crystal is given as a functional of . We show that a thin film of a chiral liquid crystal can exhibit a diverse variety of ordered structures involving topological line defects (disclination lines), depending on film thickness, temperature, and type of surface anchoring (normal, planar, and planar degenerate). Such exotic structures include a hexagonal lattice of Skyrmions, a whirl-like localized structure that finds in its place in a wide variety of condensed matter systems. A thin film of a chiral liquid crystal thus provides an interesting platform for the investigation of exotic structures of orientational order arising from the frustration between the bulk ordering and the spatial confinement with surface anchoring.
A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data

For decades, time series forecasting had many applications in various industries such as weather, financial, healthcare, business, retail, and energy consumption forecasting. An accurate prediction in these applications is a very important and also difficult task because of high sampling rates leading to monthly, daily, or even hourly data. This high-frequency property of time series data results in complexity and seasonality. Moreover, the time series data can have irregular fluctuations caused by various factors. Thus, using a single model does not result in good accuracy results. In this study, we propose an efficient forecasting framework by hybridizing the recurrent neural network model with Facebook’s Prophet to improve the forecasting performance. Seasonal-trend decomposition based on the Loess (STL) algorithm is applied to the original time series and these decomposed components are used to train our recurrent neural network for reducing the impact of these irregular patterns on final predictions. Moreover, to preserve seasonality, the original time series data is modeled with Prophet, and the output of both sub-models are merged as final prediction values. In experiments, we compared our model with state-of-art methods for real-world energy consumption data of seven countries and the proposed hybrid method demonstrates competitive results to these state-of-art methods.