Miracle-dz/UniFAR-FTUs huggingface dataset:
Insight into the interaction of human pancreatic lipase with potential anti-obesity drug, Cetilistat, using a molecular docking and molecular dynamics simulation

Background: Obesity is a lifestyle disease that involves an excessive amount of body fat deposition. Cetilistat is being used to treat obesity. It mainly inhibits human pancreatic lipase, an enzyme that helps to break down the oil into small molecules of glycerol and fatty acids in the intestine. Therefore, pancreatic lipase inhibition is a potential therapeutic approach for obesity control and treatment. Methods: cetilistat’s binding mode and interaction with human pancreatic lipase are not well understood. In this study, the human pancreatic lipase inhibitory activity of cetilistat was investigated by employing molecular docking and molecular dynamics simulation. Human pancreatic lipase has two states: closed state and open state which is controlled by a surface loop i.e. “lid region” which normally undergoes conformational changes only upon addition of lipids and then breakdown into glycerol and fatty acid. In the present study, open state conformation of the human pancreatic lipase structure was used (2OXE.pdb). The docking study reveals that the cetilistat prefers to bind at the “lid region” of pancreatic lipase. Furthermore, molecular dynamics simulation reveals that the cetilistat affects the structure and dynamics of human pancreatic lipase. Mainly, cetilistat affects the conformational changes in the “lid region” of pancreatic lipase which is important for the breakdown of lipids. Furthermore, the radius of gyration (Rg) and solvent-accessible surface area shows that the cetilistat-bound pancreatic lipase affects the compactness of the lipase structure. Thus, our computational modeling study reveals the inhibitory action of cetilistat with human pancreatic lipase and may be further useful for the design and development of anti-obesity drugs. Results: To explore the binding mode and interaction of HPL with cetilistat, we employed molecular docking, a molecular dynamics simulation study. The details of which are discussed below. Conclusion: Thus, our computational modeling study reveals the inhibitory action of cetilistat with human pancreatic lipase and may be further useful for the design and development of anti-obesity drugs.
Relation between Restricted and Repetitive Behaviors and Anxiety in Autism Spectrum Disorder: A Meta-Analysis

Abstract Background Restricted and repetitive behaviors (RRBs) are increasingly being reported to limit the social adaptability of children with autism. Method Three databases (PubMed, PsycINFO, & Web of Science) were selected to conduct a systematic review to examine the consistency in which theoretical frameworks and instruments have been used to evaluate the presence and impact of RRBs in young children who may have ASD. Results Among the 36 articles examined in this review, young males represented 78.5% of the totality of participants (n = 62,339). Approximately one-third of the studies (n = 11) provided an explanation of RRBs through utilizing a theoretical framework. With respect to instrument utility, of the 35 instruments recorded, the Autism Diagnostic Observation Schedule (ADOS) was most frequently used. Conclusions The ADOS and the Autism Diagnostic Interview – Revised (ADI-R) are highly revered as they both are consistently referenced as “a gold standard. ” However, due to the expensiveness of those assessments, they are underutilized, likely among vulnerable populations (e.g., economically disadvantaged, ethnic minorities, LGBTQ+), as many practitioners and parents cannot afford access to them.
Compete or Cooperate with ‘Dr. Google’? Small Animal Veterinarians’ Attitudes towards Clients’ Use of Internet Resources—A Comparative Study across Austria, Denmark and the UK

Simple Summary Owners of dogs, cats, and other companion animals increasingly make use of the internet to find out how to best care for their animals. This may affect owners’ relations with veterinarians in both positive and negative ways. A positive consequence could be that owners are better informed when they approach a veterinarian. However, there can also be challenging situations in which the owners may question veterinarians’ professional advice based on online information. Using a questionnaire, we found that a majority of Austrian, Danish, and UK veterinarians (n = 641) surveyed were occasionally confronted with clients who question their medical advice based on information obtained from the internet. In addition, the veterinarians were concerned about the potential for clients to misunderstand information found on the internet, or to develop unrealistic expectations of what is possible in small animal practices. As internet use becomes ever more widespread, we suggest that the types of resources that are available and used by animal owners should be further explored. Abstract Veterinary medicine is increasingly affected by animal owners having the opportunity to become better informed on pet health issues by using various internet resources. Using an online questionnaire including a section on clients’ use of internet resources to obtain medical information, this study aimed to investigate veterinarians’ estimates of the percentage of clients using internet resources, how often clients question veterinarians’ professional medical advice based on online information, and veterinarians’ attitudes towards clients’ use of internet resources, across Austrian, Danish, and UK veterinarians (n = 641). The results show that 48.8% of respondents estimated that 40–79% of their clients use internet resources to find medical information. Further, 70–80% of respondents stated that they are occasionally challenged by clients questioning their advice based on online information. Although veterinarians recognized the potential advantages related to clients’ use of internet resources, such as an increased acceptance of advanced diagnostics and treatments, they also highlighted clients’ increased expectations or false impressions of small animal practices as potentially negative aspects in this context. As internet use increases, it seems likely that these issues will become increasingly important in the future.
Design of a mmWave Antenna Printed on a Thick Vehicle-Glass Substrate Using a Linearly Arrayed Patch Director and a Grid-Slotted Patch Reflector for High-Gain Characteristics

This paper proposes a 5G glass antenna that can be printed on the thick window glass of a vehicle. The proposed antenna consists of a coplanar waveguide (CPW), a printed monopole radiator, parasitic elements, a linearly arrayed patch director, and a grid-slotted patch reflector. The linearly arrayed patch director and grid-slotted patch reflector are applied to improve the bore-sight gain of the antenna. To verify the performance improvement and feasibility, the proposed antenna is fabricated, and a reflection coefficient and a radiation pattern are measured and compared with the simulation results. The measured reflection coefficient shows broadband characteristics of less than −10 dB from 24.1 GHz to 31.0 GHz (fractional bandwidth of 24.6%), which agrees well with the simulation results. The reflection coefficients are −33.1 dB by measurement and −25.7 dB by simulation, and the maximum gains are 6.2 dBi and 5.5 dBi at 28 GHz, respectively. These results demonstrate that the proposed antenna has high-gain characteristics being suitable for 5G wireless communications.
Numerical Modelling of Nitrogen Oxides Formation During Combustion of Pulverised Fuel

Pollutants originating from pulverised solid fuel combustion systems are investigated with numerical simulations augmented by data from the fundamental experimental research. Nitrogen oxides formation model, with fuel nitrogen as a main pathway mechanism, was implemented in the computational fluid dynamics model for coal combustion. Partitioning of nitrogen contained in fuel is among the main characteristics influencing the final production of pollutants, but it is highly dependent on fuel type and combustion parameters. The experimental determination of intermediate chemical species during the pyrolysis of a coal sample was performed on a thermogravimetric analysis-mass spectrometry system, and it shows that the fuel nitrogen is uniformly emitted as hydrogen cyanide and ammonia-52.2% and 47.8%-while the hydrogen cyanide production pathway from char is dominant over the volatiles-84.3% and 15.7% respectively. The obtained results on the ratio of ammonia to hydrogen cyanide during fuel nitrogen devolatilisation were used as input parameters in numerical simulations. The improved model shows good results in simulating pyrolysis, making it suitable for modelling and optimisation of thermal utilisation processes on industrial scales.
Recovery Behavior of the Macro-Cracks in Elevated Temperature-Damaged Concrete after Post-Fire Curing

Studying the recovery of fire-damaged concrete is of huge economic and environmental significance. The recovery of thermal-induced cracks of fire-damaged concrete leads to the recovery of strength after post-fire curing. To identify the crack recovery behavior of fire-damaged concrete after post-fire curing and its relationship with the recovery of strength, in this study, concrete samples exposed to 400, 600, and 800 °C were treated with the post-fire curing process. The compressive strength recovery was investigated, as well as the crack recovery in terms of the crack length. Moreover, the recovery of the cracks was studied and divided into the categories of mortar cracks and mortar-aggregate interfacial cracks. The results indicate that, after being exposed to high temperatures, the interfacial crack was the main type of crack, and it could clearly be recovered by post-fire curing. The recovery of compressive strength mainly resulted from the recovery of interfacial cracks. The findings of this study can provide practical guidance for the application of post-fire curing to the recovery of fire-damaged concrete structures.
‘What if I was not adopted’: transnational Chinese adoptee English teachers negotiating identities in Taiwan

ABSTRACT While race in TESOL has gained traction in recent years, less research has focused on Asian American teachers working in Asian contexts, not to mention Chinese adoptees from the US working as English teachers in Asia. Drawing from our larger study on the work narratives of Asian Americans teaching English in Taiwan, this paper examines how Chinese adoptees negotiate their linguistic and cultural competencies and identities in Taiwan. We uncover the various forms of emotional labor that they experienced. Similar to other Asian American teachers, they also grappled with notions of authenticity and legitimacy in the ELT field in Taiwan. However, teaching in Taiwan provided Chinese adoptees with the opportunity to negotiate the roots and routes of transnational adoptee identities and simultaneously deploy their adoptee identities as pedagogical tools for teaching about racial and family diversity, which complicates and extends research on racial identities as pedagogy in ELT. It is inevitable that their racial identity and transracial family makeup are invoked, and they are confronted to take action on it. The process can be laborious, yet teaching students about diversity through these adoptees’ own vantage points also constitutes their professional identity as a competent teacher.
Low Latency Speech Enhancement for Hearing Aids Using Deep Filtering

Noise reduction is an important feature supporting hearing aid (HA) users in their daily routines and is thus included in most commercially available devices. Latency requirements of HAs require short processing windows resulting in a poor frequency resolution in the whole processing chain including noise reduction. Previous studies have shown that deep neural network (DNN) based algorithms outperform conventional noise reduction algorithms especially for non-stationary noises. This study explores a DNN based noise reduction method using deep filtering targeted for wideband spectrograms given the employed HA filter bank. That is, we predict complex filter coefficients that are linearly applied to the noisy spectrum. We assess different filter sizes over time and frequency axis, and provide evidence for a superior performance over a complex ratio mask. Furthermore, we introduce a frequency response loss that operates on a per-frequency-band basis to fully utilize the deep filtering concept. We objectively demonstrate on-par performance with related state-of-the-art deep learning methods and show in a subjective user study that our method is perceptually preferred to existing HA noise reduction algorithms.
Realizing Opportunistic Routing in Multi-Channel Environments

Opportunistic Routing (OR), which utilizes the broadcast nature of wireless communication to route packets in a dynamic way, significantly improves the transmission quality. Most of the researches focus on the single channel scenario; however, multi-channel (MC) is widely adopted over wireless communication systems. How to apply OR over MC environments is quite challenging and still an unsolved issue. OR operating over single channel environments collects acknowledgements mainly through overhearing data packets. In contrast, MC environments increase the performance by reducing interference and providing more bandwidth. Since users scatter over multiple channels, the chance of overhearing is reduced. Without overhearing acknowledgements (ACKs), the performance of OR degrades due to duplicate transmissions. To better understand the behavior of OR over MC environments, this paper first surveys current OR methods and constructs a simplified scenario to observe how they behave as the number of interfaces and channels increases. Then, analyze and compare their costs and penalties to find out a potential method. Finally, refine the potential method for MC environments. It is observed that token passing is the most potential method for its high efficiency of utilizing control packets. To apply token passing to OR in MC environments, this paper proposed multi-channel token passing (MCTP) to resolve the hazards of token passing paths and dynamic rate for multiple flows. Simulation results show that MCTP has high performance with low and consistent overheads. In addition, MCTP is scalable with increasing interface and channel numbers, which makes it a prototype for the future OR research in MC environments.
Bone Mineral Density Is Inversely Associated With Mortality in Chronic Kidney Disease Patients: A Meta‐Analysis

Low bone mineral density (BMD) is suggested to be associated with increased mortality in the general health population, but the relationship in chronic kidney disease (CKD) patients is still unclear. We performed a meta‐analysis to investigate the association of BMD in different sites with risk of all‐cause mortality in CKD patients. We searched PubMed, EMBASE, and Web of Science to identify eligible cohort studies that evaluated the association between BMD at different sites and risk of all‐cause mortality in CKD patients. Twelve cohort studies were identified, which included 2828 CKD patients and 1052 deaths. Compared with normal/high level of total body BMD, lower total body BMD was associated with 25% higher risk of all‐cause mortality. The pooled relative risk (RR) was 1.25 (95% confidence interval [CI] 1.09, 1.42) with little heterogeneity across studies. Regarding BMD measured at different sites, the risk of all‐cause mortality was highest for lower BMD at hip/femoral neck (pooled RR = 1.69; 95% CI 1.20, 2.40). The pooled RRs were 1.26 (95% CI 1.04, 1.53) and 1.17 (95% CI 1.00, 1.37) for lower BMD at arm and spine, respectively. Similarly, the risk of death for per SD decrease in BMD was also higher at hip/femoral neck (pooled RR = 1.43, 95% CI 1.15, 1.77) compared with arm (pooled RR = 1.03, 95% CI 1.00, 1.06) and spine (pooled RR = 1.17, 95% CI 0.98, 1.39). In conclusion, lower BMD values at hip, arm, spine, as well as the whole body are associated with increased risk of all‐cause mortality in CKD patients. The excess risk is highest for patients with lower BMD at hip/femoral neck, suggesting BMD measured at hip region may be the best indicator of mortality risk in CKD patients. © 2022 American Society for Bone and Mineral Research (ASBMR).
How Hydrodynamic Phonon Transport Determines the Convergence of Thermal Conductivity in Two-Dimensional Materials

The phonon Boltzmann transport equation combined with first-principles calculation has achieved great success in exploring the lattice thermal conductivity (κ) of various materials. However, the convergence of the predicted κ is a critical issue, leading to quite scattered results recorded in the literature, even for the same material. In this paper, we explore the origin for the convergence of thermal conductivity in two-dimensional (2D) materials. Two kinds of typical 2D materials, graphene and silicene, are studied, and the bulk silicon is also compared as a control system for a three-dimensional material. The effect of the cutoff radius (rc) in the third-order interatomic force constants on κ is studied for these three materials. It is found that that κ of these three materials exhibits diverse convergence behaviors with respect to rc, which coincides very well with the strength of hydrodynamic phonon transport. By further analyzing the phonon lifetime and scattering rates, we reveal that the dominance of the normal scattering process gives rise to the hydrodynamic phonon transport in both graphene and silicene, which results in long-range interaction and a large lifetime of low-frequency flexural acoustic phonons, while the same phenomenon is absent in bulk silicon. Our study highlights the importance of long-range interaction associated with hydrodynamic phonon transport in determining the thermal conductivity of 2D materials.
Perfomance Evaluation of Java Serialization Frameworks on Geospatial Big Data

Geospatial Big Data refers to spatial datasets exceeding the capacity of current computing systems. These datasets usually contain millions of vector geometries (such as points, polygons and linestrings) that are used to represent the spatial component of geographic features. Each geometry consists of one or more interconnected vertices, where each vertex describes a geographic location. Due to its large volume or high frequency of generation, Geospatial Big Data must be stored and processed in a distributed manner, usually using an open-source Big Data platform such as Apache Spark. This often requires serialization and deserialization of geometries when sending and receiving them among distributed computers. Therefore, the performance of serialization and deserialization has a significant impact on the overall processing performance of Geospatial Big Data. In this paper, we first briefly present seven popular Java serialization frameworks that can work with geometries and then experimentally evaluate and compare their serialization and deserialization performance on Geospatial Big Data.
Purulent Pericarditis Due to Pneumococcal Bacteremia Caused by Acupuncture: An Autopsy Case Report

Purulent pericarditis is an infection of the pericardial cavity that produces purulent fluid and is commonly caused by Streptococcus pneumoniae. We herein report an autopsy case that is unique in two respects: the patient had pneumococcal bacteremia from a skin and soft tissue infection associated with acupuncture as well as purulent pericarditis from pneumococcal bacteremia. This case suggests that bloodstream infection should be included in the differential diagnosis on observing pneumococcal pericarditis. Furthermore, it is necessary to recognize that S. pneumoniae may be the organism responsible for skin and soft tissue infections caused by trauma in immunosuppressed patients.
Neuroprotective effects of tannic acid in the postischemic brain via direct chelation of Zn2+

ABSTRACT Tannic acid (TA) is a polyphenolic compound that exerts protective effects under pathological conditions. The diverse mechanisms of TA can exert beneficial anti-oxidative, anti-inflammatory, and anti-cancer effects. Herein, we reported that TA affords robust neuroprotection in an animal model of stroke (transient middle cerebral artery occlusion; tMCAO) and exhibits Zn2+-chelating and anti-oxidative effects in primary cortical neurons. Following tMCAO induction, intravenous administration of TA (5 mg/kg) suppressed infarct formation by 32.9 ± 16.2% when compared with tMCAO control animals, improving neurological deficits and motor function. We compared the chelation activity under several ionic conditions and observed that TA showed better Zn2+ chelation than Cu2+. Furthermore, TA markedly decreased lactate dehydrogenase release following acute Zn2+ treatment and subsequently reduced the expression of p67 (a cytosolic component of NADPH oxidase), indicating the potential mechanism underlying TA-mediated Zn2+ chelation and anti-oxidative effects in primary cortical neurons. These findings suggest that anti-Zn2+ toxicity and anti-oxidative effects participate in the TA-mediated neuroprotective effects in the postischemic brain.
Multi-Optimization Objective Online Tracking-Based Parameter Self-Tuning Method for Sensorless PMSM Drives

It is important to optimize control parameters for the high-performance operation of position sensorless permanent magnet synchronous motor (PMSM) drives. In this article, a multi-optimization objective online tracking (MOOT)-based parameter self-tuning method is proposed to improve the sensorless control performance when the high-frequency signal injection (HFSI) method is used, which involves both offline and online stages. By the parameter self-learning and the model analysis, the injection signal, the position observer, the speed, and current regulators are preliminarily designed offline to ensure that the system can start smoothly. Based on the parameter characteristics analysis, an adaptive law with the speed ripple and torque ripple as the optimization index is designed to realize the online tracking of control and observation parameters. To solve the issues of tuning delay and mistuning, a moving window-based error detection strategy is investigated, which improves the parameter self-tuning speed and accuracy. The proposed method can improve the steady- and transient-state performance and realize the sensorless debug-free operation for HFSI-based method. The effectiveness is verified by experiments on a 2.2-kW PMSM drive platform.