Miracle-dz/UniFAR-FTUs huggingface dataset:
An Immersed Boundary Method Enabling Large-Eddy Simulations of Flow over Complex Terrain in the WRF Model

AbstractThis paper describes a three-dimensional immersed boundary method (IBM) that facilitates the explicit resolution of complex terrain within the Weather Research and Forecasting (WRF) model. Two interpolation methods—trilinear and inverse distance weighting (IDW)—are used at the core of the IBM algorithm. This work expands on the previous two-dimensional IBM algorithm of Lundquist et al., which uses bilinear interpolation. Simulations of flow over a three-dimensional hill are performed with WRF’s native terrain-following coordinate and with both IB methods. Comparisons of flow fields from the three simulations show excellent agreement, indicating that both IB methods produce accurate results. IDW proves more adept at handling highly complex urban terrain, where the trilinear interpolation algorithm fails. This capability is demonstrated by using the IDW core to model flow in Oklahoma City, Oklahoma, from intensive observation period 3 (IOP3) of the Joint Urban 2003 field campaign. Flow in Oklahoma C.
On the Lefschetz Number of Quasiconformal Self‐Mappings of Compact Riemann Surfaces

A well‐known theorem of Hurwitz states that if τ:S→S is a conformal self‐mapping of a compact Riemann surface of genus g⩾2, then it has at most 2g+2 fixed points and that equality occurs if and only if τ is a hyperelliptic involution.
Facial Skin Analysis for Detection of Dark Circles and Acne

The aim of this research is to analyze and detect the most commonly found facial skin conditions like acne vulgaris and dark circles. In the skin analysis algorithm, the occurrences of facial acne and dark circles are detected by using existing Computer Vision algorithms such as Otsu’s thresholding algorithm and Deep Learning (DL) techniques. These techniques are further modified to suit the prepared dataset and achieve greater value of evaluation metrics. This article proposes two techniques for the detection of dark circles, which are the difference in Skin Tone Pixel Values and the Thresholding Technique and compare their performance. In the Thresholding Technique, the IoU obtained was 0.737, which provided better visualization of the affected region. Further, acne detection was carried out using two deep learning backbones viz, Inception ResNet 50 and MobileNet. The accuracy obtained for both the methods was 99%.
Spare Parts Allocation Management Strategy Based on Binary Demand Forecasting

In order to solve the problem of inadequate spare parts allocation and management capability of power communication networks, the spare parts allocation management strategy based on binary demand forecasting which includes four core functions of spare parts inbound, spare parts outbound, spare parts interchange, and spare parts transfer is proposed. The spare parts binary demand forecasting algorithm is designed to enhance the spare parts demand forecasting capability. The mutual aid and sharing strategy can effectively balance the surplus of spare parts among nodes and reduce the cost in the process of allocation. The strategy enhances the efficiency of spare parts allocation in power communication networks.
LncRNA SNHG4 Modulates EMT Signal and Antitumor Effects in Endometrial Cancer through Transcription Factor SP-1

Long non-coding RNAs (lncRNAs) are implicated in the initiation and progression of a variety of tumors, including endometrial cancer. However, the mechanisms of lncRNA in endometrial cancer formation and progression remain largely unknown. In this study, we confirmed that the lncRNA SNHG4 is upregulated in endometrial cancer and correlates with lower survival rates in endometrial cancer patients. Knock-down of SNHG4 significantly reduced cell proliferation, colonization, migration, and invasion in vitro, as well as modulating the cell cycle and reduced tumor growth of endometrial cancer in vivo. In addition, the effect of SNHG4 by the transcription factor SP-1 was confirmed in vitro. We found in this study that SNHG4/SP-1 plays an important role in endometrial cancer progression and may be used as a potential therapeutic and prognostic biomarker for endometrial cancer.
An Intelligent System for Bearing Fault Diagnosis of Induction Motor using Wavelet Transform Based Deep Learning Framework

Induction motor (IM) plays a significant role in the production sectors, owing to its high durability, rugged nature, high efficiency and low cost. Electrical motor condition monitoring is a revolutionary technique for detecting defects in induction motors. As a result, bearing degeneration has become the most common cause of induction motor rotor failures. The detection of these defects has gained momentum globally since it can lessen the number of unexpected breakdowns of a crucial system. Aiming to the objective, this paper proposes an intelligent system for classification of bearing faults in an IM using wavelet transform aided deep learning (DL) technology. Continuous wavelet transform (CWT) has been employed to generate the time frequency (TF) representations from the bearing fault signals. The TF images are fed to a cascaded dense convolutional network (CAD-CN) for necessary feature extraction followed by classification. The primary aim of this article is to analyze various TF patterns, obtained from four mother wavelets, and process those patterns for necessary diagnosis. The proposed module extracts feature maps in several stages and strengthen features by concatenation operation unlike classical DL frameworks. Experimental findings reveal the superiority of the proposed module in terms of performance metrics, and it is found that CWT using Morlet performs the best.
Coordination and Cognition in Pure Nutritional Wernicke’s Encephalopathy with Cerebellar Degeneration after COVID-19 Infection: A Unique Case Report

Background: Alcoholic cerebellar degeneration is a restricted form of cerebellar degeneration, clinically leading to an ataxia of stance and gait and occurring in the context of alcohol misuse in combination with malnutrition and thiamine depletion. However, a similar degeneration may also develop after non-alcoholic malnutrition, but evidence for a lasting ataxia of stance and gait and lasting abnormalities in the cerebellum is lacking in the few patients described with purely nutritional cerebellar degeneration (NCD). Methods: We present a case of a 46-year-old woman who developed NCD and Wernicke’s encephalopathy (WE) due to COVID-19 and protracted vomiting, resulting in thiamine depletion. We present her clinical course over the first 6 months after the diagnosis of NCD and WE, with thorough neuropsychological and neurological examinations, standardized clinical observations, laboratory investigations, and repeated MRIs. Results: We found a persistent ataxia of stance and gait and evidence for an irreversible restricted cerebellar degeneration. However, the initial cognitive impairments resolved. Conclusions: Our study shows that NCD without involvement of alcohol neurotoxicity and with a characteristic ataxia of stance and gait exists and may be irreversible. We did not find any evidence for lasting cognitive abnormalities or a cerebellar cognitive-affective syndrome (CCAS) in this patient.
Research on Frequency Selection Method for Spatial Terahertz Communication under Multiple Constraints

The terahertz frequency band has the advantages of large bandwidth, narrow beam, strong penetration, and high security, and is an important direction for the frequency expansion of the next generation of satellite communications. In this paper, according to the satellite-ground and inter-satellite terahertz communication frequency bands divided by the International Telecommunication Union, the atmospheric transmission loss model of the satellite-ground terahertz communication link is constructed and simulated, and the key components of terahertz communication in different frequency bands are analyzed based on the research status at home and abroad. At the same time, the transmission performance comparison of satellite-ground and inter-satellite terahertz communication links in different frequency bands was carried out. Finally, through a comprehensive analysis of the transmission loss, device availability and link transmission performance of different terahertz communication frequency bands, the recommendations for the selection of frequencies for satellite-ground and inter-satellite terahertz communication.
Molecular docking analysis of a virulence factor protein dentilisin from Treponema denticola with oxazole piperazine derivatives

Dentilisin is a surface protease synthesized by the cell wall of Treponema denticola. This protein aids in the invasion of the periodontal tissue by causing infection. To identify drug molecules that have better results, homology modeling of the dentilisin protein was constructed, and molecular docking was performed with the oxazole compounds (1-6) taken from previous studies that are not yet clinically used. Data shows that compounds 1, 2, 3 show better inhibiting properties.
Treatment of the Paretic Hand with a Robotic Glove Combined with Physiotherapy in a Patient Suffering from Traumatic Tetraparesis: A Case Report

Background: cervical spinal cord injury leads to loss of upper limb functionality, which causes a decrease in autonomy to perform activities of daily living. The use of robotic technologies in rehabilitation could contribute to improving upper limb functionality and treatment quality. This case report aims to describe the potential of robotic hand treatment with Gloreha Sinfonia, in combination with conventional rehabilitation, in a tetraparetic patient. Material: fifteen rehabilitative sessions were performed. Evaluations were conducted pre-treatment (T0), post-treatment (T1), and at two-months follow-up (T2) based on: the upper-limb range of motion and force assessment, the FMA-UE, the 9-Hole Peg Test (9HPT), and the DASH questionnaire. A virtual reality game-based rating system was used to evaluate the force control and modulation ability. Results: the patient reported greater ability to use hands with less compensation at T1 and T2 assessments. Improvements in clinical scales were reported in both hands at T1, however, at T2 only did the dominant hand show further improvement. Improved grip strength control and modulation ability were reported for T1. However a worsening was found in both hands at T2, significant only for the non-dominant hand. The maximum force exerted increased from T0 to T2 in both hands. Conclusion: hand treatment combining physical therapy and Gloreha Sinfonia seems to have benefits in functionality and dexterity in tetraparetic patient in the short term. Further studies are needed to confirm these findings, to verify long-term results, and to identify the most appropriate modalities of robotic rehabilitation.
FLEET: Fluid Layout of End to End Topology

Clustering, virtualization and multi-tenancy are so ubiquitous across all layers of enterprise software deployments, that the overall topology of these stacks has reached unprecedented levels of complexity. A lot of stress is given on independently monitoring all layers of the stack. Almost all SaaS, IaaS and PaaS vendors along with traditional compute and storage vendors provide descriptive, prescriptive and predictive analytics for individual layers of software and hardware. However, with complex layouts and schemes possible for differently juxtaposed parts, often coming from multiple vendors, it is almost impossible to sift through the barrage of dashboards, events, alerts and recommendations. The fundamental problem in deriving holistic insights lies in the fact that these layers are opaque to each other, or at least they have been treated as such for the most part. With Fluid Layout of End to End Topology (FLEET), we establish that adjacent layers of the stack have clues about each other which can be used to ‘‘stitch’’ them together and infer the exact footprint of entities across layers. We standardize a mechanism to collect dynamic configuration information across the stack, process it and store the woven topology at scale.
Novel SVPWM Method Based on Zero-Voltage Notch of Resonant DC-Link Inverter

In order to decrease the switching loss of the auxiliary circuit of the resonant dc-link (RDCL) inverter and improve the voltage utilization and system efficiency, this article presents a new space vector pulsewidth modulation (SVPWM) method based on the zero-voltage notch of the RDCL inverter. This RDCL inverter reduces the current stress in the main circuit by paralleling auxiliary switch. And this method makes the operation of the auxiliary resonant circuit (ARC) less frequent, thus reducing the losses of the ARC and, therefore, improving the system efficiency. At the same time, this method analyzes and compensates for the missing voltage vectors based on the ideal output voltage so that the inverter output voltage vector under this modulation is the same as the ideal SVPWM output voltage vector. Compared with the original modulation of RDCL inverter, this method does not change the switching sequence, the switching times, and the action time of the vector while reducing the switching ripple. The effectiveness and feasibility of the modulation strategy is verified in this article through theoretical analysis as well as experiments.
A Systematic Review of Task Offloading & Load Balancing Methods in a Fog Computing Environment: Major Highlights & Research Areas

Fog computing allows for the availability of services and resources exterior of the computing resources, closer to end devices on the network edge, and finally at regions mandated by service level agreement. Fog nodes along with deployed Cloud is a strong additional support for computation. It allows for processing at the edge while yet allowing for cloud interaction. A crucial component of fog networks is load balancing, which put off some fog nodes from getting unutilized or extra loaded. Load balancing can improve service quality (QoS) factors such latency, resource usage, throughput, response or execution time, cost incurred and energy consumed for passive nodes. The job offloading and load redistribution strategies which are used in a fog network are reviewed in detail in this study. The review is divided into two categories: single parameter optimization algorithms and multi-objective parameter optimization algorithms, both with their suggested ideas. The review is also analysed in various ways, including the proportion of articles published by publisher, methods based on optimization parameters, performance evaluation metrics, simulation evaluation tools, and upcoming research areas in the fog computing field.
Conforming approximations for Kirchhoff plates and shells

Finite element interpolations of arbitrary polynomial degree which are exactly and minimally C1 continuous across interelement boundaries are studied. A perspective view of the techniques proposed by other authors is presented and some new possibilities are considered. The problem is discussed with reference to the plate and shell finite element approximations, based on the principle of minimum potential energy. The approach also permits identification of sufficient conditions for guaranteeing full rank of stiffness matrices based on modified principles of potential energy. The results of this analysis can be used to investigate the linear dependencies among nodal variables which also occur in the formulation of other fourth-order problems.
Comparative study of Heart Rate Variability for Capacitive Electrocardiography and Reference Electrocardiography

Heart rate variability (HRV) is a clinical term for the fluctuation in heartbeat intervals influenced by the sympathetic and parasympathetic activity of the autonomic nervous system. The aim of this study is to investigate the significant difference between the Capacitive Electrocardiogram (cECG) and reference ECG (rECG) signals of the same subjects by comparing the corresponding HRV parameters extracted from the ECG signal, which is available in the UnoViS_clin2009 dataset containing 92 patients. The statistical tests are used for the evaluation of the results of both clinical signals. Nonparametric statistical analysis using the Wilcoxon rank sum test, was performed for both conditions to compare significant differences (p-value <0.05) between the two signals according to the variable’s distribution. The purpose of this test is to determine whether the median of the two sets is different or not. The p-value for the features derived for the two groups of data is provided by this test. A low p-value (p<0.05) is desirable statistically. All significant difference was tested by this method since the HRV of cECG and rECG were compared with each other. None of the frequency domain parameters (LF Power, HF Power, or LF/HF Ratio) showed a statistically significant difference. However, in time domain and non-linear (SD1 and SD2) analysis, significant difference (p<0.05) was found.
Phylogenetic diversity in conservation: a brief history, critical overview, and challenges to progress

Species that are evolutionarily distinct have long been valued for their unique and irreplaceable contribution to biodiversity. About 30 years ago, this idea was extended to the concept of phylogenetic diversity (PD): a quantitative, continuous-scale index of conservation value for a set of species, calculated by summing the phylogenetic branch lengths that connect them. This way of capturing evolutionary history has opened new opportunities for analysis, and has therefore generated a huge academic literature, but to date has had only limited impact on conservation practice or policy. In this review, I present a brief historical overview of PD research. I then examine the empirical evidence for the primary rationale of PD that it is the best proxy for “ feature diversity, ” which includes both known and unknown phenotypic characters, contributing to utilitarian value, ecosystem function, future resilience, and evolutionary potential. Surprisingly, it is only relatively recently that this rationale has been subject to systematic empirical scrutiny, and to date, there are mixed results on the connection between PD and phenotypic diversity. Finally, I examine the least well-studied, but potentially greatest challenge for PD: its dependence on the reliability of phylogenetic inference itself. The very few studies that have investigated this so far show that the ranking ofspecies assemblages by their PD values can vary substantially under alternative, routine, phylogenetic methods and assumptions. If PD is to become more widely adopted into conservation decision-making, it will be important to better understand the conditions under which it performs well, and those under which it performs poorly.
Spectrographic Study of Vowel Reduction

Measurements of formant frequencies and duration are reported for 8 Swedish vowels uttered by a male talker in three consonantal environments under varying timing conditions. An exponential function is used to describe the extent to which formant frequencies in the vowels reach their target values as a function of vowel‐segment duration. A target is specified by the asymptotic values of the first two formant frequencies of the vowel and is independent of consonantal context and duration. It is thus an invariant attribute of the vowel. The results suggest an interpretation in terms of a simple dynamic model of vowel articulation.
Generation of Microbubbles with Applications to Industry and Medicine

We provide a comprehensive and systematic description of the diverse microbubble generation methods recently developed to satisfy emerging technological, pharmaceutical, and medical demands. We first introduce a theoretical framework unifying the physics of bubble formation in the wide variety of existing types of generators. These devices are then classified according to the way the bubbling process is controlled: outer liquid flows (e.g., coflows, cross flows, and flow-focusing flows), acoustic forcing, and electric fields. We also address modern techniques developed to produce bubbles coated with surfactants and liquid shells. The stringent requirements to precisely control the bubbling frequency, the bubble size, and the properties of the coating make microfluidics the natural choice to implement such techniques.
Unintended Consequences of Expanding Teacher Preparation Pathways: Does Alternative Licensure Attenuate New Teacher Pay?

Texas reduced new teacher preparation requirements in 2001 to allow more alternate paths to licensure. Within 5 years, this policy change resulted in more than half of the state’s new teachers being alternatively licensed. Using a series of first difference models, this study examines the relationship between the increased supply of new teachers in Texas and new teacher salaries prior to the policy change and in the 15 years thereafter. We find that the policy change did increase the supply of new teachers via alternative licensing, but pay for new EC-6 teachers declined by 2%–13% with differential effects based on the rate at which districts hired alternatively licensed teachers.
An improved support vector regression and its modelling of manoeuvring performance in multidisciplinary ship design optimization

Abstract In this paper, the combination of the Laplace loss function and support vector regression (SVR) is presented for the estimation of manoeuvring performance in multidisciplinary ship design optimization, and a new SVR algorithm was proposed, which has only one parameter to control the errors and automatically minimized with ν, and adds b2/2 to the item of confidence interval. It is shown that the proposed SVR algorithm in conjunction with the Laplace loss function can estimate the ship manoeuvring performance appropriately compared to the simulation results with Napa software and other approximation methods such as artificial neural network and classic SVR. In this article, we also gather enough ship information about the offshore support vessel; the Latin Hypercube Design is employed to explore the design space. Instead of requiring the evaluation of expensive simulation codes, we establish the metamodels of ship manoeuvring performance; all the numerical results show the effectiveness and practicability of the new approximation algorithms.