Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential antifungal activity of novel carbohydrate derivatives validated by POM, molecular docking and molecular dynamic simulations analyses

ABSTRACT Our current study focuses on the molecular structures of the series of methyl 4,6-O-benzylidene-α-D-glucopyranoside 1–9 as potential antifungal agents to obtain more insight into the origin of their encouraging bioactivity. In vitro antimicrobial testing and the prediction of activity spectra for substances revealed that these carbohydrate derivatives have promising antifungal functionality compared to their antibacterial activities. In support of this finding, molecular docking was performed against lanosterol 14α-demethylase (CYP51A1) and Altemaria alternata (6LCC) by screening carbohydrate derivatives whereby significant binding affinities and non-bonding interactions have been observed against both microbial proteins. The majority of the derivatives studied here could bind near the critical catalytic residues. The molecular dynamics study has revealed that the complexes formed by these derivatives with the proteins lanosterol 14α-demethylase and Altemaria alternata can remain stable, both over time and in physiological conditions. The POM analysis shows the clear presence of an antifungal (O1δ-—O2δ-) pharmacophore site. ADMET and QSAR predictions were analysed to assess their pharmacokinetic and drug-likeness properties, showing promising results in silico. This work demonstrates that potential carbohydrate derivatives bind to fungal pathogens in an effort to circumvent their activities and open avenues for the development of newer antibiotics, which may target fungal pathogens.
Clinical Outcomes of Individuals with COVID-19 and Tuberculosis during the Pre-Vaccination Period of the Pandemic: A Systematic Review

Background: Tuberculosis, like COVID-19, is most often a pulmonary disease. The COVID-19 pandemic has severely disrupted tuberculosis services in myriad ways: health facility closures, lockdowns, travel bans, overwhelmed healthcare systems, restricted export of antituberculous drugs, etc. The effects of the shared risk on outcomes of the two diseases is not known, particularly for the first year of the pandemic, during the period before COVID-19 vaccines became widely available. Objective: We embarked on a systematic review to elucidate the consequences of tuberculosis on COVID-19 outcomes and of COVID-19 on tuberculosis outcomes during the pre-vaccination period of the pandemic. Methods: The systematic review protocol is registered in PROSPERO. We conducted an initial search of PubMed, Embase, Web of Science, WHO coronavirus database, medRxiv, bioRxiv, preprints.org, and Google Scholar using terms relating to COVID-19 and tuberculosis. We selected cohort and case–control studies for extraction and assessed quality with the Newcastle-Ottawa scale. Results and Conclusion: We identified 2108 unique abstracts published between December 2019 and January 2021. We extracted data from 18 studies from 8 countries. A total of 650,317 persons had a diagnosis of COVID-19, and 4179 had a diagnosis of current or prior tuberculosis. We explored links between tuberculosis and COVID-19 incidence, mortality, and other adverse outcomes. Nine studies reported on mortality and 13 on other adverse outcomes; results on the association between tuberculosis and COVID-19 mortality/adverse outcomes were heterogenous. Tuberculosis outcomes were not fully available in any studies, due to short follow-up (maximum of 3 months after COVID-19 diagnosis), so the effects of COVID-19 on tuberculosis outcomes could not be assessed. Much of the rapid influx of literature on tuberculosis and COVID-19 during this period was published on preprint servers, and therefore not peer-reviewed. It offered limited examination of the effect of tuberculosis on COVID-19 outcomes and even less on the effect of COVID-19 on tuberculosis treatment outcomes.
The Millimeter- and Submillimeter-Wave Spectrum of 13C1-Methyl Formate (H13COOCH3) in the Ground State

A large number of rotational transitions of 13C1-methyl formate in its ground A and E torsional substates were measured in the 110-380 GHz region with the Fast Scan Submillimeter Spectroscopic Technique (FASSST). Besides strong a-type transitions, many b-type transitions through rotational quantum numbers J′′ = 59 and Ka′′ = 16 were newly measured, and some forbidden c- and x-type transitions in the E substate were also assigned. The new lines were analyzed together with previous submillimeter-wave data using an effective rotational-torsional Hamiltonian method designated “ERHAM” developed for a molecule with one or two internal rotors. In total, over 4900 transitions of 13C1-methyl formate were analyzed. Systematic deviations due to perturbations were found in Q-branch transitions at high J, and higher order Coriolis-type interaction terms were included to fit the data better. A standard deviation of 86 kHz was obtained by varying 33 parameters. In addition to 13C1-methyl formate, the normal isotopologue was studied anew and some high-Ka transitions were newly assigned. The previous data of the normal species in the ground state were reanalyzed with the ERHAM method together with new transitions measured in the present study. The same deviations in Q-branch transitions, not observed in previous studies, were also found in the normal species. Using spectroscopic parameters obtained in this study, predictions have been made for many strong lines of 13C1-methyl formate through 620 GHz in frequency not analyzed in the fit.
Channel Measurement and Ray-Tracing Simulation for 77 GHz Automotive Radar

Millimeter-wave automotive radar is essential for realizing autonomous driving. Realistic channel model and simulation are important for system and sensing algorithm design. This work introduces channel measurements and ray-tracing (RT) channel simulations for frequency modulated continuous wave (FMCW) automotive mmWave radar. The 77 GHz channel measurements in an urban crossroads environment are presented. The dominant echoes (multi-path components) of the measurement are detected and matched with corresponding objects for each frame. A measurement-based electromagnetic (EM) parameter estimation method is proposed to find the optimal parameter set that minimizes the error of simulated radar cross section (RCS). As a result, the issue of lacking reliable EM material parameters for RT simulation at 77 GHz frequency band is tackled. Simulation results are validated in power, range, velocity, and angle domains with the provided EM parameter set. Extending validated RT simulations in similar environments with various configurations allows more reliable channels for rigorous testing without the limitation of channel measurement.
Investigation of the large-scale and statistical properties of Richtmyer-Meshkov instability-induced mixing

The weighted essentially non-oscillatory method (Jiang & Shu 1996; Shu 1999) is applied to study the evolution of single- and two-mode Richtmyer-Meshkov instability-induced mixing. The numerical method is validated using two-dimensional simulations of the Mach 1.21 air/SF6 shock tube experiments of Collins and Jacobs (2002) that include reshock of the evolving interface. The flow structure and perturbation amplitude growth obtained from the simulations are shown to be in very good agreement with the corresponding experimental data. The amplitude growth is also compared to the growth predicted by several nonlinear analytical models. High-resolution, three-dimensional simulations are performed to study the spatial structure, spectra, and statistics in the Mach 1.5 air/SF6 shock tube experiment of Vetter and Sturtevant (1995). The interfacial perturbation, including the embedded wire mesh, is modeled following the two-scale representation of Cohen et al. (2002). The mixing layer width is compared to the experimental data. The time-evolution of the kinetic energy spectra corresponding to velocity fluctuations in both the streamwise and spanwise directions and the density variance spectra are investigated. The balance of terms in the kinetic energy and enstrophy evolution equations is studied to provide insight into the baroclinic production and vortex stretching mechanisms that drive the instability and turbulence. Simulations using different orders of spatial accuracy are compared at different grid resolutions to investigate the dependence of quantities on the resolution.
Decomposition Based Quantum Inspired Salp Swarm Algorithm for Multiobjective Optimization

Various real-world problems are essentially multiobjective optimization problems (MOPs), which involve several conflicting objectives. We propose a Quantum-inspired multiobjective Salp Swarm Algorithm based on the Decomposition technique to locate the multiple Pareto-optimal solutions (POS). The main objective while designing the algorithms for the multiobjective optimization problems is to attain a good convergence and uniform dissemination of the solutions, which remains a significant challenge for the algorithms. The proposed Decomposition-based Quantum-inspired Salp Swarm Algorithm for Multiobjective Optimization (DMQSSA) extends the primary form of SSA by using the quantum-inspired framework and a basic decomposition strategy to improve the balance between exploration and exploitation for MOPs. The Delta potential-well model (DPWM) from quantum mechanics is known for enhancing the convergence and diversity in the population, and the decomposition strategy is proved to be effective to generate evenly distributed solutions set on the Pareto front for simultaneous optimization of the subproblems. In this paper, the existing DPWM model is analysed and redesigned for MOPs with a modification in the contraction equation, and decomposition strategy is used along with an intelligent selection technique to ensure non-dominated solutions. The proposed hybrid approach is evaluated and compared with other techniques on a set of well-known benchmark problems. The results show that DMQSSA can handle the multiobjective optimization problems to find better and well-distributed Pareto optimal set. Also, success of the proposed algorithm is further illustrated on a real-world application.
A Leaky Integrate-and-Fire Neuron Based on Hexagonal Boron Nitride (h-BN) Monocrystalline Memristor

As a competitive candidate for artificial neurons, memristors have become the focus of intense research owing to their intrinsic ion migration tunability, enabling an authentic implementation of biomimicry. However, they still suffer from variability issues due to 3-D uncontrollable filament dynamics in an amorphous medium and modeling of switching dynamics underlying filament growth and rupture is still under investigation. In this work, we present volatile memristors that exhibit desired characteristics for neuromorphic computing with low performance variations utilizing a hexagonal boron nitride (h-BN) monocrystalline as a switching medium. Theoretical investigations assisted by the Monte Carlo simulation combined with experimentally detected <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula> characteristics described that the electric field dominates the set process, whereas the Gibbs–Thomson interfacial energy minimization and heat dissipation influence the relaxation process mostly. Additionally, h-BN memristors with high switching uniformity provide an ideal hardware platform for credible neuron emulation and software identification of digital images.
Facial Expression Recognition Using CNN

Facial is the most dynamic part of the human body that conveys information about emotions. The level of diversity in facial geometry and facial look makes it possible to detect various human expressions. To be able to differentiate among numerous facial expressions of emotion, it is crucial to identify the classes of facial expressions. The methodology used in this article is based on convolutional neural networks (CNN). In this paper Deep Learning CNN is used to examine Alex net architectures. Improvements were achieved by applying the transfer learning approach and modifying the fully connected layer with the Support Vector Machine(SVM) classifier. The system succeeded by achieving satisfactory results on icv-the MEFED dataset. Improved models achieved around 64.29 %of recognition rates for the classification of the selected expressions. The results obtained are acceptable and comparable to the relevant systems in the literature provide ideas a background for further improvements.
Initial Propulsion System Study for the Futuristic Hyperloop Transportation System: Design, Modeling, and Hardware in the Loop Verification

Recently, the proposal for a futuristic mode of transportation known as the Hyperloop has been popularized. Currently, there are only some reports regarding the design of the Hyperloop. More specifically, reports regarding the propulsion system design methodology for Hyperloop is minimal. Thus, this paper provides an initial steppingstone to modeling and simulation study for the propulsion system in a Hyperloop. The main contribution of this study is to provide a relatively simple design methodology for any future Hyperloop endeavors. This is shown using state of the art simulators to aid in designing the propulsion system. The design revolves around the linear synchronous motor based on field-oriented control through a three – phase inverter. PSIM is used to develop the model and design the full power system and controller. This includes the DC-DC converter, battery system model, three – phase inverter, and the motor controller. The motor used for modelling is a rotary permanent magnet synchronous motor. Finally, hardware in the loop technology is used to verify and validate the design. The controller design is tested through a Texas Instrument digital signal processor. The real time verification shows matching results with the offline simulation model.
Using cultivated organic soil depth to form soil conservation management zones

Abstract Cultivated Organic soils in Montreal's southwest plain are the most productive soils in the province of Quebec. After their initial drainage to enable farming, Organic soils are susceptible to many forms of degradation and soil loss. In this study, we characterized the physical, chemical, and pedological properties of 114 sites from five peatlands to form soil conservation management zones. We attempted to use the maximum peat thickness (MPT) as a soil degradation proxy. The MPT can be defined as the thickness of the layer of peat until coprogenous or mineral materials are reached. The latter are undesired growing media and are not considered in MPT calculation. A series of multivariate analysis of variance indicated that MPT was moderately related to soil degradation (optimal model's Pillai's trace = 0.495). Three soil degradation groups were defined, separated by two MPT thresholds: 60 and 100 cm. When looking at 17 different depth-property combinations, shallower sites (MPT < 60 cm) showed signs of soil degradation significantly higher than sites with an MPT above 60 cm. The second threshold was proposed for practical purposes. Then, these thresholds were used to separate the study area into spatially distinct management zones. Important spatial contrasts were found. This supports the theory that precision agriculture techniques are needed to target fields to optimize soil conservation interventions. The relationship between the MPT and soil degradation should be further explored to account for other degradation factors, and to better identify degraded soils and soils at risk.
The Effects of Coaching Techniques on Well-Being of Digital-Technology Users

As digital technology has become indispensable, its overuse has resulted in mental health issues for many users. While it benefits people by providing fast and plentiful information, it also creates sadness, anxiety, and stress. This study aimed to assess the well-being of digital technology users before, during, and six months after attending a coaching session that was designed according to the International Coaching Federation (ICF) approach. Seligman’s well-being model, consisting of positive emotion, engagement, relationships, meaning, and accomplishment (PERMA), was applied for the measurement, and then analyzed with descriptive statistics, repeated ANOVA, and paired-sample t-tests. The findings showed that coaching techniques can enhance well-being and that their results were maintained for six months after participation. In conclusion, coaching techniques should be promoted as a procedure for improving the well-being of digital technology users who face mental health issues.
ESTIMATING FUNCTIONS IN FAILURE TIME DATA ANALYSIS

The relative risk model of Cox (1972) has become the standard for the regression analysis of univariate failure time data. Cox's maximum partial likelihood estimator is shown to arise from a mean parameter estimating function for the cumulative baseline hazard variate, after allowing for right censorship and upon inserting the usual baseline hazard function estimator. Mean and covariance parameter estimating functions applied to these same cumulative baseline hazard vari? tes lead to estimation procedures for the regression analysis of multivariate failure time data. For example these estimating procedures may be used to simultaneously estimate marginal hazard ratio parameters and pairwise cross ratio parameters. Such estimation allows assessment of regression effects on marginal hazard functions while providing summary measures of the strength of dependency among pairs of failure time vari? tes. Some additional topics in the analysis of multivariate failure time data are briefly discussed.
A Nine-Level Inverter With Single DC-Link and Low-Voltage Capacitors as Stacked Voltage Sources With Capacitor Voltage Control Irrespective of Load Power Factor

This article proposes a multilevel inverter topology with single dc-link and series-connected capacitors as stacked voltage sources for multilevel voltage generation. The voltage deviation of a dc-link capacitor will occur whenever a phase terminal connects to the balanced neutral points (NPs: terminal joints of dc-link capacitors). On the contrary, if the voltage of a dc-link capacitor deviates from the nominal voltage, the same phase currents can be utilized to balance these NPs. This new technique is being proposed for the first time in the literature. Any voltage disturbance of the dc-link capacitors is balanced using the motor phase currents, irrespective of load power factor and modulation indices. For the balanced NPs, whenever a phase connects to an NP, the other phase terminal tapping positions are varied on the dc link to establish $i_{A}+i_{B}+i_{C}=0$ for that NP. The pole voltage level variation at motor phase terminals is undisturbed by adding extra cascaded H-bridges (CHBs) at each phase leg. The voltages of CHB capacitors are controlled conventionally by inverter pole voltage redundancies. The detailed experimental results for open-loop V/f and closed-loop field-oriented control on an induction motor are presented using a nine-level laboratory prototype.
Tillage-Induced Fragmentation of Large Soil Macroaggregates Increases Nitrogen Leaching in a Subtropical Karst Region

Tillage leads to rapid loss of soil nitrogen (N) over a short period of time in karst areas. N leaching is the primary pathway of soil N loss and therefore is key to understanding the mechanisms of N loss induced by tillage. However, the factors affecting N leaching under tillage are not fully understood. Effects of tillage at various frequencies on leached N were examined in a one-year in situ simulation experiment using five tillage treatments: no tillage (T0), semiannual tillage (T1), and tillage every four months (T2), two months (T3), and monthly (T4). Concentration and amount of leached N had peaks in dry–rewetting months. Tillage significantly increased total amounts of leached N during the one-year experiment, and the largest amount of leached N was under tillage at the highest frequency. The primary form of N in leachate was NO3¯ (88.49–91.11%), followed by DON (7.80–9.87%), and then NH4+ with the lowest amount (1.09–2.10%). Tillage increased the amount of leached NO3¯ and DON, but had no significant effect on leached NH4+. Additionally, the amount of leached N had significantly negative correlations with 5–8 mm soil aggregate, NO3¯, DON, and sand content, and positive correlations with 2–5 and 0.25–2 mm. Soil 5–8 mm aggregate and DON were the main factors explaining the variation in leached N according to the RDA analysis. Tillage increased the breakdown of large aggregates, appearing to have increased the mineralization of organic matter, which resulted in increased N leaching. Our results emphasize the importance of reducing or eliminating physical disturbance indued by tillage and maintenance of large soil aggregates for decreasing N leachate in lime soil of karst regions.
Social Acceptability in Context: Stereotypical Perception of Shape, Body Location, and Usage of Wearable Devices

Assessing social acceptability is vital when designing body-worn mobile devices. Previous research found evidence that using stereotyping content model (SCM) mobile devices can systematically predict ratings of the warmth and competence of their wearers. However, it is currently unknown if other contextual dimensions of mobile device usage can also systematically affect those ratings. In two studies, we investigate if and how shape and body location of a body-worn mobile device as well as the activity in which the device is being used can systematically influence stereotypical ratings. Our results suggest that this is evident in some but not all cases. We conclude that people further differentiate between the placement of the device, particularly devices in the user’s hand, and during an activity in which the device can contextually be misused. This indicates that users further differentiate the context and that more contexual information is helpful while operationalizing the SCM as a measure for social acceptability.
Ultrathin BaTiO3 templates for multiferroic nanostructures

The structural, electronic and dielectric properties of high-quality ultrathin BaTiO3 films were investigated. The films, which were grown by ozone-assisted molecular beam epitaxy on Nb-doped SrTiO3(001) substrates and have thicknesses as low as 8 unit cells (u.c.) (3.2 nm), are unreconstructed and atomically smooth with large crystalline terraces. A strain-driven transition to three-dimensional (3D) island formation is observed for films of 13 u.c. thickness (5.2 nm). The high structural quality of the surfaces, together with dielectric properties similar to bulk BaTiO3 and dominantly TiO2 surface termination, makes these films suitable templates for the synthesis of high-quality metal-oxide multiferroic heterostructures for the fundamental study and exploitation of magneto-electric effects, such as a recently proposed interface effect in Fe/BaTiO3 heterostructures based on Fe–Ti interface bonds.