Miracle-dz/UniFAR-FTUs huggingface dataset:
Resveratrol; an inflammasome inhibitor and a potential therapy for severe cases of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 126 million people worldwide and deaths exceed two million. Virological features of SARS-CoV-2, including its genomic sequence, have been identified but the mechanisms governing coronavirus disease 2019 (COVID-19) immunopathogenesis have remained uncertain. Severe COVID-19 is associated with a cytokine storm, chronic inflammation, neutrophilia, lymphocyte dysfunction, lymphopenia, reduction in T-lymphocytes and natural killer (NK) cells, disruption in viral clearance, and neutrophil/macrophage infiltration in the lungs. In many cases, patients develop acute lung injury (ALI), acute respiratory distress syndrome (ARDS), and/or multiple-organ dysfunction syndrome (MODS). Resveratrol reduces the expression of inflammasome activators such as thioredoxin-interacting protein (TXNIP) and nuclear factor erythroid 2 (NrF2) and increases that of the inflammasome inhibitor, i.e., NAD-dependent deacetylase sirtuin-1 (SIRT1). Resveratrol is able to inhibit the production of reactive oxygen species (ROS) and the activation of inducible nitric oxide synthases (iNOS). It affects signaling pathways including mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-ĸB) thereby further inhibiting inflammasomes. Because of its anti-inflammasome, anti-inflammatory, and anti-oxidant effects and considering the key role of inflammation and cytokine storm in disease severity and poor patient outcomes, it is concluded that resveratrol can be useful in the treatment of COVID-19. Given the persistence of the COVID-19 pandemic and the challenges of extensive vaccination in all countries, it is important to achieve more effective treatments to decrease the mortality rate and severity of severe injuries following COVID-19. Given all the effects reviewed in this article, resveratrol at a dose of up to 600 mg per day can be exploited as a potential adjunctive therapy for COVID-19 patients.
Under the Dome: A 3D Urban Texture Model and Its Relationship with Urban Land Surface Temperature

The spatial distribution of buildings is one of the key factors influencing the local environment within a city. The quantitative measurement of building distribution can provide critical information for exploring local climate patterns in urban areas. Previous studies mainly focused on the two-dimensional spatial distribution of buildings and ignored the differences in height. In this study, a three-dimensional (3D) urban texture model based on an improved radial distribution function is proposed to describe the 3D spatial distribution of urban buildings. Using a set of concentric domes above the ground, a texture curve can be generated at any location in a city, from which a variety of numerical features are extracted to depict the local 3D urban landscape quantitatively. The proposed model was applied to Wuhan, one of the largest cities in central China, and the results demonstrated that the proposed model could identify various building distribution patterns in the city. Additionally, the relationship between urban texture and land surface temperature in Wuhan was analyzed. It was found that the 3D urban texture model effectively improved the accuracy of land surface temperature estimation. This study provides a new tool for urban environmental assessment and urban planning decision making.
Analysis and Prognosis of Tumor Immune Infiltrates and Immune Microenvironment of m6A-Related LncRNAs in Patients with Gastric Cancer

Background Studies have shown that long noncoding RNAs and N6-methyladenosine play an important role in gastric cancer. The purpose of this study was to determine the correlation and prognostic value of m6A-related lncRNAs and immune infiltration in gastric cancer. Methods We downloaded the clinically related information and RNA-Seq transcriptome data of gastric cancer patients from the TCGA database. Univariate Cox regression analysis and Pearson analysis were used to screen out m6A-related lncRNAs. Consensus cluster analysis was used to divide the sample into two clusters, and LASSO analysis and minimum absolute shrinkage were used to construct a risk scoring model. Results A total of 25 lncRNA expression profiles were screened, and gastric cancer patients were divided into different subtypes. Cluster 2 had a better prognosis, but its matrix score, estimate score and immune score were low. Cluster 1 was rich in resting memory CD4 T cells, regulatory T cells, monocytes, and resting mast cells, and Cluster 2 was rich in activated memory CD4 T cells and follicular helper T cells. Thirteen lncRNAs were selected to construct a risk model, and the prognosis of gastric cancer patients in the high-risk group was poor. The expression of PD-L1 in tumors is significantly higher than that in normal tissues. Univariate and multivariate Cox regression analysis results showed that the overall survival rate was significantly related to stage and risk score, which can be used as an independent prognostic factor. The results of the heat map and scatter plot showed that clusters (P=0.0045) and grade (G1-2, G3, P=0.0037) were significantly related to prognosis. The results of the relationship between the risk score and immune cell infiltration showed that memory B cells, resting dendritic cells, M0 macrophages, and M2 macrophages were positively correlated with risk scores, while resting mast cells, monocytes, activated NK cells, and follicular helper T cells were negatively correlated with risk scores. Conclusion The results of this study indicate that m6A-related lncRNAs may play an important role in the prognosis of gastric cancer patients and the tumor immune microenvironment and provide help for the treatment of gastric cancer patients.
Classification of Existing Health Model of India at the End of the Twelfth Plan using Enhanced Decision Tree Algorithm

The high rate of urbanisation has increased the need for state-of-art health models that can meet the growing needs of society during any pandemic. Information-theoretic algorithms based on decision tree can mine the data to establish standards for the final decision by classifying the related data. Classification is an effective tool to analyse the existing health system in India’s states and union territories. For this purpose, the data is categorised and then treated with the enhanced Shannon Entropy-based C4.5 decision tree algorithm to set some rules. These rules are capable of finding the major gaps in the health care systems after the analysis. Supposedly, these gaps are taken care of properly in the affected regions. In that case, the health care models will accomplish the endeavouring Sustainable Development Goals.
Kaposi's Sarcoma and Lymphoedema in a HIV Sero-positive Patient: A Case Report and Literature Review

Kaposi sarcoma (KS) is one of the most common neoplasms diagnosed in HIV- seropositive subjects. KS is an angioproliferative disorder of endothelial origin and is a locally aggressive multicentric mucocutaneous malignant neoplasm. Aggressive HIV-KS is associated with increased HHV8 viral load, disseminated lesions, and intraoral exophytic lesions, and may also present with facial lymphoedema which may be life-threatening or mild. A 26 -year-old, male, presented with severe oral pain and facial swelling. He had multiple oral lesions and an incisional biopsy confirmed Kaposi sarcoma. A multiple site incisional biopsy and immunohistochemistry for HHV8 was done and based on the clinical, histopathological, and immunohistochemical results a diagnosis of HIV associated oral and cutaneous KS with severe lymphoedema was confirmed. This aim of this case presentation is to describe a case of immunodeficiency virus-related lymphadenitis, oral and cutaneous KS associated with the complication severe lymphoedema in a HIV infected patient who was not on HAART therapy for three years after being diagnosed with HIV.
Modulation of breathing parameters between treadmill and cycle ergometer tests in endurance trained and recreationally active individuals

This study aimed at comparing breathing patterns during incremental-load tests to exhaustion performed on both cycle (CE) and treadmill (TE) ergometers. The hypothesis for this study is two fold; (i) during an incremental to exhaustion test treadmill running will evoke a higher breathing frequency and cycling will evoke a larger tidal volume at isometabolic conditions due to the different muscle contractions. Secondly, (ii) during an incremental to exhaustion test a higher breathing frequency during treadmill running and a higher tidal volume during cycle ergometery ought to be observed at isometabolic conditions in well-trained endurance athletes as compared to recreationally active individuals, due to changes in the periphery from years of chronic training. Ten specifically trained endurance individuals (S) (Five cross-country runners and five cyclists), and eight non-specifically trained individuals (NS) underwent a maximal oxygen uptake determination test (VO₂max) on both a CE and TE. Cardiorespiratory variables (VO₂max, VCO₂, RER, VE, VT, and ƒR) and movement frequency (MF), were collected and calculated relative to fixed percentages of VO₂max, ranging from 50 to 100%. ANOVA revealed significantly higher values at each percentage of VO₂max on the TE compared to the CE in the NS group (p < 0.05) whereas the S group did not significantly differ. There was no significant difference in VCO₂and RER, between the S and NS groups on both the CE and the TE. The minute ventilation (VE) was similar between the S and NS groups on both ergometers except for 50 to 60% of VO₂max. Concurrently, VT was significantly higher, while ƒR was significantly lower on the CE compared to the TE in both groups (p < 0.05). A significant MF group effect was observed, with S reaching higher values on both ergometers, upon examining percent entrainment (%ENT) there was no difference observed between groups or modes. The outcomes demonstrated that at isometabolic intensities no difference in breathing patterns between specifically trained endurance individuals and non-specifically trained individuals was reached on both ergometers despite an MF group effect. Although (S) reached higher cardiorespiratory values on both ergometers compared to non-specifically trained individuals, their ventilatory patterns did not differ.
Non‐equilibrium molecular dynamics simulation of the thermal conductivity of crystals film

Purpose – To give a new method to calculate the thermal conductivity of thin films which thickness is less than micro‐nanometer when non‐Fourier effect will appear in heat conduction and Fourier law is not applicable for calculating the thermal conductivity.Design/methodology/approach – The Cattaneo equation based on the heat flow relaxation time approximation is used to calculate the thermal conductivity.Findings – The results show that the thermal conductivity is not the thermophysical properties of material, but is the non‐linear function of temperature and film thickness when the dimension of film is less than micro‐nanometer.Research limitations/implications – The application of this method is limited by little experimental data of heat flow relaxation time for materials other than Ar crystals.Originality/value – The paper demonstrates how the thermal conductivity of Ar crystals film can be calculated by NEMD algorithm and considers the non‐Fourier effect in the simulation.
Playful reflective thinking in a HyFlex classroom: using nostalgic games to engage students

Amidst the ever-changing government guidelines in response to the Covid-19 pandemic, universities have had to balance the safety of students and staff with attempting to maintain as much face-to-face teaching as possible. Consequently, a specific challenge some Learning Developers will have faced is the HyFlex classroom, a combination of students who are present in the physical classroom and those participating virtually (Columbia University, 2021). While some Institutions were operating in this way before the pandemic in order to offer students increased flexibility, I had not encountered this situation before when teaching the topic of reflection.
Comparison K-Nearest Neighbors (K-NN) and Artificial Neural Network (ANN) in Real Time Entrants Recognition

— Regional Financial Management Information System (SIMDAKEU) is a key e-government application to implement integrated financial management. The objective of this research is to investigate the factors that influence the achievement of the application in Palangka Raya Government. Model of Delone and McLean's information systems success and technology acceptance model (TAM) are applied as the research concept and model. Data were collected through questionnaires from 126 employees of Palangka Raya Government. A Structural Equation Modeling (SEM) approach was applied in this study. The results of this research showed that from 11 hypotheses proposed from eight constructs namely quality of information, system, service, intention to use, net benefit, users' perception about the ease of use and the usefulness, there are 10 hypotheses proven and 1 hypothesis not proven. The quality of information is highly influencing the achievement of regional financial information system based on the research outcomes. The findings of this research can assist the government in developing the regional financial management information system, so the government can maximize the function of the system as a tool for realizing good and clean governance.
High-speed 850 nm oxide-confined VCSELs for DATACOM applications

Vertical cavity surface emitting lasers (VCSELs) are low cost and reliable light sources for high-speed local area and storage area network (LAN/SAN) optical fiber data communication systems and short-reach computer interconnects. The continuing rapid increase of serial transmission data rates driven by multi-core microprocessor's bandwidth upgrades cannot be sustained via conventional copper-based links as bit rates move beyond 10 Gbit/s and distances greater than 1 m. The intrinsic limitation of copper at high single-channel data rates facilitates the need to transition to optical fiberbased links at ever shorter distances. For LAN/SAN applications the 850 nm wavelength is standard. This same wavelength is also the standard for several other evolving short-reach application areas including Fibre Channel, CEI, USB, InfiniBand, and HDMI optical link systems. Herein we present our recent results on 850 nm oxide-confined VCSELs operating at data bit rates up to 40 Gbit/s. The low operational current density in the range of ~10 kA/cm2 ensures viable device reliability and long-term stability based on well-known industry certification specifications. Key VCSEL device parameters including the relaxation resonance frequency, damping, and parasitic cut-off frequency are determined for VCSELs with oxide-confined apertures of various diameters. We find that a parasitic cut-off frequency of 24-28 GHz limits the VCSEL's high speed operation at the highest optical modulation rates. We believe that with some effort the device parasitics can be further reduced such that current modulated VCSELs can be realized with larger than 30 GHz optical modulation bandwidth and reliable and practical operation beyond 40 Gbit/s.
Improvement of control characteristics of interior permanent magnet synchronous motor for electric vehicle

This paper describes a method to improve the control characteristics of an interior permanent magnet synchronous motor for an electric vehicle. At the motor for electric vehicle, d- and q-axis inductances are varied to a great extent. So, variation characteristics for d- and q-axis inductance are analyzed as function of current magnitude and also current phase angle. The proposed method makes use of the learning capability of neural networks to implement an adaptive vector control structure. Also, a distribution law of torque reference to improve the driving characteristics of a two motor-driven EV is proposed. A advanced performances are verified through numerical methods and experiments.
Specific emitter identification (SEI) and classical parameter fusion technology

Specific emitter identification (SEI), coupled with classical parameter technology, provides signal identification in a dynamic threat environment where both sides employ exotic emitters and/or utilize identical platforms, thereby creating chaotic battlefield situations. Signal identification using classical techniques, needs to be extended to handle these future conflicts because existing Radar Warning Receiver (RWR) and other collection systems employing classical parameters such as frequency, amplitude, pulse width, and pulse repetition rate, are unable to reliably distinguish between lethal and non-lethal threats.
Graphene as a Platform for Novel Nanoelectronic Devices

Graphene's superlative electrical and mechanical properties, combined with its compatibility with existing planar silicon-based technology, make it an attractive platform for novel nanoelectronic devices. The development of two such devices is reported—a nonvolatile memory element exploiting the nanoscale graphene edge and a field-effect transistor using graphene for both the conducting channel and, in oxidized form, the gate dielectric. These experiments were enabled by custom software written to fully utilize both instrument-based and computer-based data acquisition hardware and provide a simple measurement automation system. Graphene break junctions were studied and found to exhibit switching behavior in response to an electric field. This switching allows the devices to act as nonvolatile memory elements which have demonstrated thousands of writing cycles and long retention times. A model for device operation is proposed based on the formation and breaking of carbon-atom chains that bridge the junctions. Information storage was demonstrated using the concept of rank coding, in which information is stored in the relative conductance of multiple graphene switches in a memory cell. The high mobility and two dimensional nature of graphene make it an attractive material for field-effect transistors. Another ultrathin layered material—graphene's insulating analogue, graphite oxide—was studied as an alternative to bulk gate dielectric materials such as Al2O3 or HfO2. Transistors were fabricated comprising single or bilayer graphene channels, graphite oxide gate insulators, and metal top-gates. Electron transport measurements reveal minimal leakage through the graphite oxide at room temperature. Its breakdown electric field was found to be comparable to SiO2, typically 1–3 × 108 V/m, while its dielectric constant is slightly higher, κ ≈ 4.3. As nanoelectronics experiments and their associated instrumentation continue to grow in complexity the need for powerful data acquisition software has only increased. This role has traditionally been filled by semiconductor parameter analyzers or desktop computers running LabVIEW. Mezurit 2 represents a hybrid approach, providing basic virtual instruments which can be controlled in concert through a comprehensive scripting interface. Each virtual instrument's model of operation is described and an architectural overview is provided.
Multi-objective design optimization of an inverted-S antenna

The design of dual-frequency band Inverted-S Antennas (ISA) involves a great deal of tuning works. In this point of view, two optimal methodologies are proposed to synthesis this type of antennas in a more efficient way. The two optimal methodologies, one based on a vector optimizer and the other on scalar optimizer, take advantage of a novel formula to optimize the bandwidths in dual bands. The scalar methodology employs some constraint handling technique to improve its speed of convergence, while the vector methodology without using any preference information strives to accelerate its convergence by means of response surface models. The comparison of numerical results shows the feasibility of the proposed optimal methodology for ISA synthesis. Also, the advantages and limitations of the methodologies are discussed.
Evaluation of Speaker Anonymization on Emotional Speech

Speech data carries a range of personal information, such as the speaker's identity and emotional state. These attributes can be used for malicious purposes. With the development of virtual assistants, a new generation of privacy threats has emerged. Current studies have addressed the topic of preserving speech privacy. One of them, the VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology. The task selected for the VoicePrivacy 2020 Challenge (VPC) is about speaker anonymization. The goal is to hide the source speaker's identity while preserving the linguistic information. The baseline of the VPC makes use of a voice conversion. This paper studies the impact of the speaker anonymization baseline system of the VPC on emotional information present in speech utterances. Evaluation is performed following the VPC rules regarding the attackers' knowledge about the anonymization system. Our results show that the VPC baseline system does not suppress speakers' emotions against informed attackers. When comparing anonymized speech to original speech, the emotion recognition performance is degraded by 15\% relative to IEMOCAP data, similar to the degradation observed for automatic speech recognition used to evaluate the preservation of the linguistic information.
Analysis and design of wideband widescan planar tapered slot antenna array

Phased arrays have been required to operate over wide bandwidths and wide scan angle to support multifunction operation in both telecommunication and radar. In response to that need, this study firstly analyses the performance of the connected planar tapered slot antenna array and finds that the mutual coupling is essential and has good effect in wideband antenna array design. Then the authors design a wideband widescan planar tapered slot antenna array system with novel dual-parabola tapered slot antenna elements and feed network. This array can operate from 1.6 to 9 GHz and scan angle up to 45 . Both simulation and measurement results are shown to certificate the performance of the proposed antenna array.
PRI Control Methodology for Grid-Connected Inverters in Harmonic Distorted Grid Utility

The impacts of grid voltage on grid current in distributed generation grid-connected inverters are analyzed, and a control strategy that can compensate harmonics and suppress DC bias is proposed. In comparison with traditional PR controller, the proposed PRI controller with an additional integral part obtains a higher gain in low frequency, and the controller has an apparent effort especially for suppressing DC bias. Finally the PRI controller is verified in a 50KW. The experimental results show that the PRI controller not only can reduce harmonics of grid current in the steady state but also can suppress DC bias rapidly in a dynamic process. The PRI controller is suitable for DGs since they typically contain low order harmonics which caused by nonlinear l three-level inverter loads.