Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Multilevel Hybrid Cascaded Inverter for High Power Motion Control Systems

The paper presents an analysis of a novel multilevel inverter that can be used in the power modules of motion control systems for soft starting and speed control of high power medium voltage synchronous and induction motors. The inverter is constructed from hybrid cascaded H-bridge cells. The advantages of the proposed inverter upon standard topologies are significant reduction of electrical components and as a result, smaller size and weight. The proposed approach can be extended to any desired number of voltage levels. Extensive simulation results validate the practicability of the proposed inverter. Several aspects, such as Total Harmonic Distortion Factor of the inverter output currents and voltages, harmonic content, and frequency spectrum distribution are studied.
Autonomous Aerial Vehicle Sensor Sensitivity Modeling Using Signal Detection Theory

Autonomous aerial vehicles require unique approaches to be able to adapt their own behavior and examine their past experiences to increase their future mission performance, especially for achieving adaptive behavior and decisionmaking capabilities under uncertain environment and imperfect sensor conditions. In this study, we modeled the sensor sensitivity through Signal Detection Theory (SDT), to investigate its effect on the Reinforcement Learning (RL) behavior of a Monte Carlo (MC) based agent, for a simulated target recognition mission for autonomous vehicles. Three levels of sensor sensitivity (low, medium, high) were simulated. The dependent measure includes time taken to locate all the targets, number of incorrect declarations, and total reward for the task performance. Results showed that for the MC Search Agents with only the perfect and worst MC systems exhibiting a significant difference in the number of incorrect declarations with the rest showing no differences in the performance measure. Findings of this study will have great impact for human machine interaction of unmanned systems designs.
Design of Neutral Network–Sliding Model Based Large Envelope Flight Control Law

Applying neutral network-sliding model control design methods to large envelope flight control law of aircraft whose model parameter varies greatly with flight condition was studied in this paper. Neural network theory is used to approximately linearize the nonlinear system and cancel the errors brought with approximate inversion, and the residual error is solved by sliding model control. So it can approximate the nonlinear model accurately, and improve robustness and anti-jamming capability of the flight control system. Simulation results show the design neural network – sliding model large envelope flight controller has excellent control performance.
Direct vs. Video-Laryngoscopy for Intubation by Paramedics of Simulated COVID-19 Patients under Cardiopulmonary Resuscitation: A Randomized Crossover Trial

A safe way of securing the airway with an endotracheal tube is one of the priorities of an advanced cardiovascular life support algorithm for suspected or confirmed COVID-19 patients. The aim of this study was to compare intubation success rates (ISR) and intubation time (IT) of different laryngoscopes for simulated COVID-19 patients under cardiopulmonary resuscitation. The study was designed as a prospective, randomized, crossover trial. Fifty four active paramedics performed endotracheal intubation with a Macintosh direct laryngoscope (MAC) and McGrath videolaryngoscope (McGrath) with and without personal protective equipment (PPE). Without PPE, ISRs were 87% and 98% for MAC and McGrath, respectively (p = 0.32). ITs were 22.5 s (IQR: 19–26) and 19.5 s (IQR: 17–21) for MAC and McGrath, respectively (p = 0.005). With PPE, first-pass ISR were 30% and 89% with MAC and McGrath, respectively (p < 0.001). The overall success rates were 83% vs. 100% (p = 0.002). Median ITs were 34.0 s (IQR: 29.5–38.5) and 24.8 s (IQR: 21–29) for MAC and McGrath, respectively (p < 0.001). In conclusion, the McGrath videolaryngoscope appears to possess significant advantages over the Macintosh direct laryngoscope when used by paramedics in suspected or confirmed COVID-19 intubation scenarios.
Determination of the correlation spectrum of oscillators with low noise

A general expression for the correlation spectrum of an oscillator, described by a set of nonlinear ordinary differential equations with intrinsic noise sources, is derived by a first-order perturbation theory. The analytical derivations are well suited to the numerical determination of the correlation spectrum by Poincare mapping methods. The theory is applied to a lumped circuit model of Colpitts oscillator. It is concluded that the noise behavior of complex oscillator circuits used in microwave engineering can be simulated by the derived method. >
Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting

We introduce an end-to-end (E2E) deep neural network architecture designed to perform seismo-volcanic monitoring focused on detecting change. Due to the complexity of volcanic processes, this requires a polyphonic detection, segmentation, and classification approach. Through evolving epistemic uncertainty, invoking a Bayesian network strategy, we detect change and demonstrate its significance as an indicator for possible forecasting of eruptions using data from the Bezymianny and Etna volcanoes. Specifically, we propose morphing the scattering transform from previous work into a novel E2E hybrid and recurrent learnable deep scattering network to adapt to multi-scale temporal dependencies from streaming data. The time-dependent scattering is in some sense physics informed, namely, through time–frequency representation (TFR) of the data. At the same time, with a carefully designed deep convolutional LSTM (ConvLSTM) architecture, we learn intra-event, temporal dynamics from the scattering coefficients or features. We verify the effectiveness of transfer learning switching between volcanoes. Our experimental results set a new norm for semi-supervised seismo-volcanic monitoring.
Modeling and Layout Optimization for On-chip Inductive Coupling

In this paper, we study the modeling and layout optimization for on-chip interconnect structures to minimize the inductive coupling. We first investigate the characteristics of mutual (as well as self) inductance for coplanar, micro-stripline, and stripline structures, and examine the effectiveness of design freedoms such as wire sizing, spacing, and shielding. We then propose formula-based models as the figures of merit for inductive coupling in the three interconnect structures, and apply the proposed models to automatically synthesize on-chip interconnect structures. Experiments show that compared to the coupling coefficients computed by a numerical field solver, the models have about 15% difference for coplanar structures, and have negligible difference for micro-stripline and stripline structures. In addition, interconnect structures meeting given noise specifications can be synthesized instantly using proposed models.
Temporal response characterization across individual multiomics profiles of prediabetic and diabetic subjects

Longitudinal deep multiomics profiling, which combines biomolecular, physiological, environmental and clinical measures data, shows great promise for precision health. However, integrating and understanding the complexity of such data remains a big challenge. Here we utilize an individual-focused bottom-up approach aimed at first assessing single individuals’ multiomics time series, and using the individual-level responses to assess multi-individual grouping based directly on similarity of their longitudinal deep multiomics profiles. We used this individual-focused approach to analyze profiles from a study profiling longitudinal responses in type 2 diabetes mellitus. After generating periodograms for individual subject omics signals, we constructed within-person omics networks and analyzed personal-level immune changes. The results identified both individual-level responses to immune perturbation, and the clusters of individuals that have similar behaviors in immune response and which were associated to measures of their diabetic status.
Altertoxin II, a Highly Effective and Specific Compound against Ewing Sarcoma

Simple Summary Ewing sarcoma is a cancer of the bone and soft tissues that affects children and adolescents. Unfortunately, only 20–30% of patients with metastatic Ewing sarcoma survive, necessitating the need to identify new, more effective therapies. We screened natural product extracts from plants and fungal cultures to identify compounds with selective cytotoxic activity against Ewing sarcoma cells, which led to the identification of altertoxin II as a compound with highly selective activity against Ewing sarcoma cells. Mechanism of action studies showed that altertoxin II selectively induces DNA damage in Ewing sarcoma cells, but does not bind to DNA. Additionally, we found that altertoxin II has antitumor activity in a mouse model of Ewing sarcoma, suggesting it will be useful as a lead compound to help identify new molecular targets for the development of new Ewing-sarcoma-specific therapies. Abstract A screening program designed to identify natural products with selective cytotoxic effects against cell lines representing different types of pediatric solid tumors led to the identification of altertoxin II as a highly potent and selective cytotoxin against Ewing sarcoma cell lines. Altertoxin II, but not the related compounds altertoxin I and alteichin, was highly effective against every Ewing sarcoma cell line tested, with an average 25-fold selectivity for these cells as compared to cells representing other pediatric and adult cancers. Mechanism of action studies revealed that altertoxin II causes DNA double-strand breaks, a rapid DNA damage response, and cell cycle accumulation in the S phase. Our studies also demonstrate that the potent effects of altertoxin II are partially dependent on the progression through the cell cycle, because the G1 arrest initiated by a CDK4/6 inhibitor decreased antiproliferative potency more than 10 times. Importantly, the cell-type-selective DNA-damaging effects of altertoxin II in Ewing sarcoma cells occur independently of its ability to bind directly to DNA. Ultimately, we found that altertoxin II has a dose-dependent in vivo antitumor efficacy against a Ewing sarcoma xenograft, suggesting that it has potential as a therapeutic drug lead and will be useful to identify novel targets for Ewing-sarcoma-specific therapies.
How Does Nitrogen Application Rate Affect Plant Functional Traits and Crop Growth Rate of Perennial Ryegrass-Dominated Permanent Pastures?

High doses of nitrogen (N) fertiliser input on permanent pastures are crucial in terms of N surplus and N losses. Quantitative analyses of the response of plant functional traits (PFT) driving crop growth rate (CGR) under low N input are lacking in frequently defoliated pastures. This study aimed to understand the significance of PFTs for productivity and N uptake in permanent grasslands by measuring dynamics in tiller density (TD), tiller weight (TW), leaf weight ratio (LWR), leaf area index (LAI), specific leaf area (SLA), as well as leaf N content per unit mass (LNCm) and per unit area (LNCa) in perennial ryegrass (Lolium perenne)-dominated pastures, in a simulated rotational grazing approach over two consecutive growing seasons. Annual N application rates were 0, 140 and 280 kg N ha−1. The phenological development of perennial ryegrass was the main driver of CGR, N uptake and most PFTs. The effect of N application rate on PFTs varied during the season. N application rate showed the greatest effect on TD, LAI and, to a lesser extent, on SLA and LNCm. The results of this study highlight the importance of TD and its role in driving CGR and N uptake in frequently defoliated permanent pastures.
Changes in forest structure drive temperature preferences of boreal understorey plant communities

The local climate in forest understories can deviate substantially from ambient conditions. Moreover, forest microclimates are often characterized by cyclic changes driven by management activities such as clear‐cutting and subsequent planting. To understand how and why understorey plant communities change, both ambient climate change and temporal variation in forest structure have to be considered. We used inventories from 11,436 productive forest sites in Sweden repeated every 10th year 1993–2017 to examine how variation in forest structure influences changes in the average value of minimum and maximum temperature preferences of all species in a community, that is, community temperature indices (CTIs). We then evaluated to what extent these changes were driven by local extinctions and colonizations, respectively, and to what extent the difference in CTI value between two inventories was related to changes in forest density and in macroclimate. Lastly, we tested whether effects on CTI change by these two drivers were modified by topography, soil moisture and tree species composition. CTI values of the understorey plant communities increased after clear‐cutting, and decreased during periods when the forest grew denser. During the period immediately after clear‐cutting, changes were predominately driven by colonizations of species with a preference for higher temperatures. During the forest regeneration phase, both colonizations by species preferring lower temperatures and local extinctions of species preferring higher temperatures increased. The change in understorey CTI over 10‐year periods was explained more by changes in forest density, than by changes in macroclimate. Soil moisture, topography and forest tree species composition modified to some extent the effects of changes in forest density and in macroclimate on understorey CTI values. Synthesis. Via stand manipulation, forest management impacts the effects of regional climate on understorey plant communities. This implies that forest management by creating denser stands locally even can counterbalance the effects of regional changes in climate. Consequently, interpretations of changes in the mean temperature preference of species in forest understorey communities should take forest management regimes into account.
The Temporal Pattern of Arterial Stiffness during Aging: A Large-Scale Cross-Sectional Study

Brachial-ankle pulse wave velocity (baPWV) is a noninvasive clinical test that provides quantification for the stiffness of both the aorta and peripheral arteries by measuring the brachial and tibial arterial wave velocities. The temporal pattern of baPWV values during aging was investigated in this paper. A gradual increase in baPWV with respect to age was observed, suggesting an increase in the stiffness of arterial vessels as age increases. The ΔbaPWV value, defined as the absolute value of the difference between bilateral baPWV, also showed a positive correlation with aging. Many underlying physiological conditions such as hyperlipidemia, hypertension, diabetes, and hyperglycemia have previously been shown to elevate baPWV and contribute to the decline of arterial function. The effect of factors including biological sex, blood pressure, and blood glucose levels on the baPWV temporal pattern were also investigated. Between the ages of 18 and 50, men in the study had significantly higher baPWV readings than females of comparable age on average. However, after the age of 50, mean baPWV values increased at a greater rate in females than in males. In addition, blood pressure and blood glucose were shown to be associated with baPWV values. The results will improve existing prediction models for future cardiovascular episodes induced by arterial hardening in different age groups.
Multi-Criteria Optimization of Bridge Management

Optimizing investment funding levels and combinations of treatment types and timings, as an aid to management decision making, are vital functions of any bridge management system (BMS). Bridge management is always involved the bridge performance assessment which is essentially a multiple criteria decision making (MCDM) problem, which involves multiple assessment criteria such as traffic safety enhancement, preservation of bridge condition, protection from extreme events, agency cost minimization and user cost minimization. In this paper, a multi-criteria optimization methodology was developed not only to take due cognizance of costs but also to include a wide range of performance criteria to facilitate balanced decision-support practices in bridge management. The proposed methodology uses the AHP to determine the weights of criteria, linguistic terms to assess bridge performance under each criterion and aggregate bridge performance under different criteria into an overall performance score for each bridge structure. A numerical example illustrated the integrated methodology and the optimization process.
Comparative transcriptome profiling of Termitomyces sp. between monocultures in vitro and link‐stipe of fungus‐combs in situ

The edible mushroom Termitomyces is an agaric‐type basidiomycete fungus that has a symbiotic relationship with fungus‐growing termites. An understanding of the detailed development mechanisms underlying the adaptive responses of Termitomyces sp. to their growing environment is lacking. Here, we compared the transcriptome sequences of different Termitomyces sp. samples and link‐stipe grown on fungus combs in situ and monocultured in vitro. The assembled reads generated 8052 unigenes. The expression profiles were highly different for 2556 differentially expressed genes (DEGs) of the treated samples, where the expression of 1312 and 1244 DEGs was upregulated in the Mycelium and link‐stipe groups respectively. Functional classification of the DEGs based on both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed an expected shift in fungal gene expression, where stress response genes whose expression was upregulated in link‐stipe may adaptively be involved in cell wall hydrolysis and fusion, pathogenesis, oxidation‐reduction, transporter efflux, transposon efflux and self/non–self‐recognition. Urease has implications in the expression of genes involved in the nitrogen metabolism pathway, and its expression could be controlled by low‐level nitrogen fixation of fungus combs. In addition, the expression patterns of eleven select genes on the basis of qRT‐PCR were consistent with their changes in transcript abundance, as revealed by RNA sequencing. Taken together, these findings may be useful for enriching the knowledge concerning the Termitomyces adaptive response to in situ fungus combs compared with the response of monocultures in vitro.
In Silico Molecular Docking on Bioactive Compounds from Indian Medicinal Plants against Type 2 Diabetic Target Proteins: A Computational Approach

Natural chemical compounds from medicinal plants used for the healing of diseases and disorders with fewer side effects, easy accessibility and economically cheap. The current study was aimed at finding novel drug like molecules as anti-diabetic compounds using in silico approach. Intermolecular interactions between target proteins and different antidiabetic compounds were observed. Five phytocompounds were selected from Plumbago zeylanica, Neolitsea cassia and Wrightia tinctoria and taken for molecular docking against human pancreatic alpha-amylase and human dipeptidyl peptidase IV using Autodock 4.2. Among the five phyto compounds, 6 urs-12-en-24-oic acid Plumbago zeylanica is the best compound for both the human pancreatic alpha-amylase and human dipeptidyl peptidase IV inhibition, as it possessed higher value in molecular dockings.
LONG-DISTANCE MicroPIV MEASUREMENTS OF A COMMERCIAL AIRCRAFT MODEL AT LOW

Velocity measurements from a sufficietly long standoff distance with micron scale resolution have significant potential in boundary layer flow diagnostics and in resolving small turbulent structures. Long-distance microParticle Image Velocimetry (LDµPIV) technique is applied for velocity measurements around a commercial aircraft model. Experiments are performed using a closed-return open test section wind tunnel in combination with a single-camera LDµPIV system. Two-dimensional, two-component (2D2C) velocity measurements are performed in a 12mm x 12mm field of view around the fuselage nose and in the wake of nose landing gear. The velocities are calculated using proven adaptive cross correlation algorithms. The instantaneous and averaged vector map results indicate that the LDµPIV provides sufficient spatial resolution to perform nose stagnation flow, fuselage boundary layer and nose landing gear wake measurements.
Performance Evaluation of Polyamide Reverse Osmosis Membrane for Removal of Contaminants in Ground Water Collected from Chandrapur District

This paper examines the influence of different operating parameters such as pressure, temperature, pH on the performance of polyamide reverse osmosis membrane. Varying these parameters, intensive trials were undertaken to study the performance of Reverse Osmosis (RO) membrane. Water samples for experiment were collected from Moradgaon village in Chandrapur district with high fluoride, TDS, sulphate and iron concentrations. Removal efficiency of contaminants due to the effect of different operating parameters of RO membrane was studied in detail. Results indicate that polyamide reverse osmosis membrane can successfully remove 95 to 98% of fluoride, TDS, sulphate, iron and ground water contaminants. Different parameters such as pH, pressure and temperature affects RO membrane efficiency. Thus, proper control of these factors is essential for successful operation and maintenance. RO Membrane generates huge quantity of reject water (i.e. 65%-75%), which was further passed through RO Membrane to study its reuse potential. The results showed that water received from RO membrane after recycling of reject water is within BIS limit of drinking water.
The Effect of Tetrathionate Ions on the Surface Chemistry and Flotation Response of Selected sulphide Minerals

ABSTRACT This study investigated the impact of tetrathionate ions on selected sulfide mineral surfaces and their flotation response to tetrathionates using X-ray photoelectron spectroscopy (XPS), zeta potential and batch flotation studies and linking the results to previously reported electrochemistry, FTIR and microflotation studies. XPS revealed that tetrathionates have the propensity to oxidize minerals, changing the chemical composition of the mineral surface. This surface alteration renders the sulfide minerals hydrophilic through sulphoxy and hydroxy entities reducing collector adsorption as noted in FTIR and mixed potential studies. Zeta potentials showed little specific adsorption of tetrathionates on the sulfides except at moderately high concentrations, i.e., 1000 mg/L. Batch flotation showed that tetrathionates in solution depressed sulfide minerals, particularly galena, reducing its recovery to the concentrates in support of earlier microflotation results.