Miracle-dz/UniFAR-FTUs huggingface dataset:
Single Power-Conversion Active-Clamped AC/DC Converter Employing Si/SiC Hybrid Switch

This article proposes a single power-conversion voltage-fed active-clamped ac/dc converter that uses an Si IGBT/SiC MOSFET hybrid switch. By incorporating two switches at the primary side of the circuit, we removed the full-bridge diode rectifier, and thereby reduced the required number of power devices. Inherent bidirectional active-clamp circuit naturally limits the voltage spike at bottom switches and reuses the energy accumulated in the leakage inductor during both positive and negative grid half cycles. Also, it offers dual-resonant power transfer paths, so it can deliver the high power with less circuit components. The alternating switching modulation makes one of the bottom switches turn-off with hard switching per grid half cycle while holding other bottom switch on to conduct the current. In contrast, top switches are softly switched with low root-mean-square current. Therefore, the converter with proposed switching modulation enables direct substitution of Si IGBT for an SiC MOSFET at the top on the primary side, and thereby which cuts down the circuit implementation cost. We built a 1-kW prototype converter and confirmed its validity.
Intention to Use eSanjeevani-OPD App: An Empirical Investigation Using Health Belief Model

Digital health interventions have become an essential component of every public health system since the COVID-19 pandemic. “eSanjeevani OPD - Stay at Home OPD” is a telemedicine system that connects doctors and patients launched as part of the Ayushman Bharat project of the Indian government. This study analyses various factors affecting the intention to use eSanjeevani. A theoretical model integrating the health belief model and the theory of reasoned action was framed and empirically tested. Responses were collected using a survey questionnaire(n=248). A partial least square-structural equation modeling was used to analyze the linkages between the constructs. Perceived susceptibility and benefits were found to be the most contributing variables. Attitude has a significant mediating effect on the intention to use eSanjeevani.
Singular integral operators on sobolev spaces on domains and quasiconformal mappings

En aquesta tesi s’obtenen nous resultats sobre l’acotacio d’operadors de Calderon-Zygmund en espais de Sobolev en dominis de Rd. En primer lloc es demostra un teorema de tipus T(P) valid per a Wn,p(U), a on U es un domini uniforme acotat de Rd, n es un nombre natural arbitrari, i p>d. Essencialment, el resultat obtingut afirma que un operador de Calderon-Zygmund de convolucio es acotat en aquest espai si i solament si per a tot polinomi P de grau menor que n restringit al domini, T(P) pertany a Wn,p(U). Per a indexs p menors o iguals que d, es demostra una condicio suficient per a l'acotacio en termes de mesures de Carleson. En el cas n=1 i p 2. La darrera aportacio de la tesi es l'aplicacio dels resultats anteriorment descrits a l'estudi de la regularitat de l'equacio de Beltrami que satisfan les aplicacions quasiconformes. Essencialment, es demostra que si el coeficient de Beltrami pertany a l'espai Wn,p(U), essent U un domini Lipschitz del pla complex amb parametritzacions de la frontera en un cert espai de Besov i p>2, llavors l'aplicacio quasiconforme associada esta en l'espai Wn,p(U).
Invalidity of the Ehrenfest theorem in the computation of high-order-harmonic generation within the strong-field approximation

It is known that the strong-field approximations commonly used in models for computing high-order-harmonic generation invalidate the Ehrenfest theorem. Therefore, the time derivative of the atomic dipole or of the dipole velocity does not correspond to the dipole acceleration. We study the consequences of this invalidation for the quantitative evaluation of high-order-harmonic spectra in hydrogen at different wavelengths and intensities. As a main result, we propose a form for the time derivative of the kinetic momentum that allows a quantitatively accurate computation of the acceleration spectra using the dipole-velocity matrix elements.
Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion

Background Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs). DESeq2 and edgeR are well-established computational tools used for this purpose and they are based upon generalized linear models (GLMs) that consider only fixed effects in modeling. However, the inclusion of random effects reduces the risk of missing potential DEGs that may be essential in the context of the biological phenomenon under investigation. The generalized linear mixed models (GLMM) can be used to include both effects. Methods We present DEGRE (Differentially Expressed Genes with Random Effects), a user-friendly tool capable of inferring DEGs where fixed and random effects on individuals are considered in the experimental design of RNA-Seq research. DEGRE preprocesses the raw matrices before fitting GLMMs on the genes and the derived regression coefficients are analyzed using the Wald statistical test. DEGRE offers the Benjamini-Hochberg or Bonferroni techniques for P-value adjustment. Results The datasets used for DEGRE assessment were simulated with known identification of DEGs. These have fixed effects, and the random effects were estimated and inserted to measure the impact of experimental designs with high biological variability. For DEGs’ inference, preprocessing effectively prepares the data and retains overdispersed genes. The biological coefficient of variation is inferred from the counting matrices to assess variability before and after the preprocessing. The DEGRE is computationally validated through its performance by the simulation of counting matrices, which have biological variability related to fixed and random effects. DEGRE also provides improved assessment measures for detecting DEGs in cases with higher biological variability. We show that the preprocessing established here effectively removes technical variation from those matrices. This tool also detects new potential candidate DEGs in the transcriptome data of patients with bipolar disorder, presenting a promising tool to detect more relevant genes. Conclusions DEGRE provides data preprocessing and applies GLMMs for DEGs’ inference. The preprocessing allows efficient remotion of genes that could impact the inference. Also, the computational and biological validation of DEGRE has shown to be promising in identifying possible DEGs in experiments derived from complex experimental designs. This tool may help handle random effects on individuals in the inference of DEGs and presents a potential for discovering new interesting DEGs for further biological investigation.
Systematic Evaluation of Different Fresh Cow Monitoring Procedures

Simple Summary Metabolic and infectious diseases in dairy cows around parturition are frequent. The routine monitoring of fresh cows is recommended to detect diseases at an early stage. This, however, prevents the cows from eating and lying down, which decreases milk yield, and is time consuming for farmers, resulting in reluctant implementation on farms. Optimizing fresh cow management procedures can therefore improve efficiency and increase farmers’ acceptance of the programs. In this study, the duration of different routine examinations and treatments during fresh cow management procedures were systematically evaluated under practical conditions. In addition, different workflow strategies were investigated to determine how lock-up times could be reduced. Moreover, the proportion of examination and treatment times relative to the total headlock time was analyzed. Different examination and treatment times were found during routine fresh cow checks. Furthermore, the lock-up times differed significantly among the different strategies, as well as the proportion. This study provides information that can be used as a basis for the development of time-efficient strategies, and to minimize the impact on cows’ time budgets as well as for future herd health management strategies, including economic evaluations. Abstract Establishing fresh cow monitoring procedures is considered beneficial for cow health, welfare, and productivity. However, they are time consuming and require the cows to be locked up, which restricts their natural behavior. In this study, different fresh cow monitoring procedures were evaluated. Two experiments were conducted to determine: (1) the duration of various examinations and treatments; (2) the time cows remain locked up in headlocks; and (3) the proportion of examination and treatment times relative to the total headlock time. In advance, standard operating procedures were established. Three veterinarians conducted the examinations and treatments based on changes in milk yield, clinical symptoms, and alarms by an accelerometer system. The headlock time was evaluated for three workflow strategies, which differed in the order of examinations and treatments. To determine the duration, cameras were installed, and the video footage was analyzed. The examinations lasted between 1 and 227 s, and the cows were locked up in headlocks between 0.01 and 1.76 h. The lock-up times differed significantly among the three strategies, as well as the proportion. This study provides information that can be used as a basis for the development of time-efficient strategies, and to minimize the impact on cows’ time budgets.
To Interact or Not to Interact with News Posts: The Role of Algorithmic Awareness & Self-Monitoring in Facebook News Consumption

While algorithms govern our newsfeed on social networking sites, most studies have sought to explore conditions to encourage audience interaction with news content. Few, however, have examined how audiences may refrain from content interaction which provides key indicators for news organizations gauging content impact and reflects online civic engagement. Through the theoretical lens of self-presentation and hyperpersonal model, this study examines the role of algorithmic awareness and self-monitoring in SNS news consumption. Using an online survey of Facebook news consumers (N = 808), findings reveal an association between algorithmic awareness, self-monitoring, and active news consumption on Facebook. The mediating role of self-monitoring indicates that levels of algorithmic awareness encourage active consumption when the stakes for self-presentation on the platform are high. Differences in algorithmic awareness levels by gender, age, and education are identified. The study provides promising preliminary evidence on how algorithmic awareness impacts SNS news consumption and practical implications for practitioners.
Active Learning for Hyperspectral Image Classification Using Kernel Sparse Representation Classifiers

Active learning (AL) is one of the popular approaches that can mitigate some of the drawbacks of supervised classification. Although sparse representation classifier (SRC) has already proven to be a robust classifier and successfully used in many applications, it is seldom used jointly with AL. In this letter, we propose a novel AL technique for SRCs. In the proposed model, the query function is designed by combining uncertainty and diversity criteria, both of which are defined by using the SRC in kernel space. The proposed technique outperforms other state-of-the-art methods in terms of classification performance.
Reconfigurable negative bit line collapsed supply write-assist for 9T-ST static random access memory cell

This paper presents a reconfigurable negative bit line collapsed supply (RNBLCS) write driver circuit for the 9T Schmitt trigger-based static random-access memory (SRAM) cell (9T-ST), significantly improving write performance for real-time memory applications. In deep sub-micron technology, increasing device parameter deviations significantly reduce SRAM cells' write-ability. The proposed RNBLCS write-assist driver for 9T-ST SRAM cell has 0.84×, 0.48×, 0.27× optimized write access delay and 1.05×, 1.08×, 1.19× improvement in write static noise margin (WSNM), 1.05×, 1.13×, and 1.39× improvement in write margin (WM), 0.96×, 0.89× and 0.72× minimum write trip-point (WTP) from transient-negative bit line (Tran-NBL), capacitive charge sharing (CCS), and conventional write circuits respectively. The proposed RNBLCS is functionally verified using a synopsys custom compiler with a 16 nm BSIM4 model card for bulk complementary metal-oxide semiconductor (CMOS).
Severity of functional tricuspid regurgitation is associated with mortality in patients with pulmonary hypertension in long‐term follow‐up

Abstract Pulmonary hypertension (PH) is a hemodynamic and pathophysiologic state present in many cardiovascular, respiratory, and systemic diseases. PH is considered to have a higher risk of cardiovascular events and mortality. The most common type of functional tricuspid regurgitation (FTR) is associated with PH. The aim of this study was to evaluate the association between FTR severity and mortality in PH in western China. This is a retrospective analysis in PH patients and all patients underwent right‐heart catheterization (RHC) for hemodynamic measurements. The FTR severity was determined according to the guidelines. Uni‐ and multivariate analyses were used to identify risk factors for mortality. From 2015 to 2021, 136 patients with PH with a median age of 50 years (interquartile range [IQR]: 35–64 years). During 26‐month median follow‐up (mean 27.7 ± 15.1 months), 40 (29.2%) patients died (mean after 21.7 ± 14.1 months). In the univariate Cox regression analysis, World Health Organization functional class (WHO FC) III/IV, elevated B‐type natriuretic peptide, pulmonary vascular resistance (≥16.2 Wood units), pulmonary artery oxygen saturation, severe FTR and right ventricular diameter/left ventricular diameter (≥0.62) were significantly associated with mortality. In the multivariate Cox regression analysis, severe FTR, WHO FC III/IV, and right ventricular end‐diastolic pressure (RVEDP) were risk factors for mortality. Severe FTR at baseline was strongly associated with mortality in both precapillary and postcapillary PH patients, independent of the other risk factors as RVEDP, HO FC III/IV, optimal pulmonary arterial hypertension targeted therapy.
Decision biases and environmental attitudes among conservation professionals

The importance of human behavior in biodiversity conservation is widely recognized, but there is little published evidence about how conservation professionals make decisions when conservation values are at stake. We take a behavioral economics approach, administering simplified decision problems (“choice experiments”), questions about choice‐relevant preferences and views (“elicitation questions”), and a psychometric scale (the New Ecological Paradigm scale) to a difficult‐to‐recruit sample (n = 100) of Canadian professionals involved in managing Rangifer tarandus caribou (Woodland Caribou). Our choice experiments reveal the importance of several decision biases (risk aversion, commission bias, and a bias towards fairness) in this influential group of conservation stakeholders. We then examine in‐sample differences between categories of professional affiliation (e.g., resource industry, environmental nongovernmental organization, or federal/provincial government), finding significant variation in responses to one elicitation question (reference points) and in psychometric scores. We discuss the implications of our findings for choice in conservation practice and for multistakeholder conservation policy. Comparing our findings to prior work on choice under uncertainty in nonconservation contexts suggests a possible replication problem in applying behavioral science insights to conservation problems, pointing to the need for a systematic research program. Results from development testing with a convenience sample of university students are presented for comparison throughout the study.
Energy-Efficient Distributed Clustering Algorithm for WSNs in Smart Grid

For the problems of uneven clustering, unreasonable selection of cluster heads and excessive energy consumption in wireless sensor networks for smart grid, an energy efficient clustering algorithm for wireless sensor networks in smart grid (EECSG) is proposed. The algorithm first calculates the optimal number of cluster heads, and then uses k-means algorithm to evenly divide the whole network based on the optimal number of cluster heads. In the selection of cluster head, residual node energy and distance influence factor are introduced to comprehensively select, and finally the data is transmitted stably. The simulation results show that EECSG can dynamically determine the cluster head through the introduction of cluster head selection factor, which reduces the energy loss during data communication in the network and improves the overall life of the wireless sensor network.
Classifying Skin Cancer and Acne using CNN

Several hospitals and dermatological clinics have adopted computer-vision-based diagnosis tools to aid in the early identification of skin cancer. The most frequent skin diseases are acne vulgaris and skin cancer. Acne Vulgaris affects 85% of the population in their lives, usually during adolescence. Benign Skin Cancer is the cancer commonly affecting people among all other types in developed and developing countries. To measure the success of medical treatment techniques, an objective evaluation of the lesion is required. Traditionally, dermatologists manually count the number of lesions by visual examination or scanning obtained photographs of the patient’s skin and divide them into several categories. This old procedure is time intensive and necessitates a significant amount of work on the part of the physician. Using computer vision, automated the lesion detection, lesion classification, counting of Acne, counting of benign skin cancer and tracking of Acne Severity, making it simple for patients to analyse and track the results of their acne treatment. The goal of this study is to develop a Convolutional Neural network model to classify the lesions into acne and benign skin cancer. The proposed model is developed and trained on acne and different types of benign skin cancer images and achieved an accuracy of 96.4%.
Applications of rotational excitations in Bose-Einstein condensates

This thesis contains theoretical studies of weakly interacting, trapped Bose-Einstein condensed gases. The main emphasis is on the rotational properties of these systems. A typical Bose-Einstein condensate reacts to external rotation by forming singly quantized vortices. By the word ”typical” we refer to a condensate with repulsive interparticle interactions and with a frozen spin degree of freedom. However, there are some atomic species for which the low-energy interactions are attractive. Moreover, the tuning of different condensate properties is relatively easy. For example, there are ways to experimentally change the effective interaction from repulsive to attractive. For an attractively interacting condensate the vortex is not the only possible rotational state but the sample may also experience rotation through its center of mass. In the first part of the thesis, we analyze some properties of a rotating attractive Bose gas at the zero temperature limit. First, we note that in order to maintain energetical stability, the gas has to be rotated in an external trap which is steeper than a harmonic trap. We study the system in an anharmonic quadratic + quartic potential. The rotating ground state phase-space is determined with analytical and numerical methods. If the interactions are strong enough, the rotating ground state appears to be a state with the rotating center of mass. On the other hand, at the limit of weak interactions the system experiences rotation by forming a multiply quantized vortex. We also determine the spectrum of elementary excitations for these quantum many-particle states. We find that the broken symmetry of the center of mass rotating state induces an additional zero-energy (Goldstone) mode and that the small oscillations of the ground state exhibit the decoupling between the center of mass and relative motions. If the spin of the atoms is allowed to change freely, a rich variety of topological excitations in condensates can be studied. External rotation is one of the tools for examining the excitations in spinor condensates. In a spinless scalar condensate the appearance of a quantized vortex is manifested by the vortex line in which the condensate density vanishes. In the plane perpendicular to the vortex line, one speaks of the vortex core for the density minimum. We study the properties of slowly rotated F = 1 spinor condensates and show that for ferromagnetic interactions the ground state is a coreless vortex. While the individual spin components may carry ordinary vortices the overall density of the system is coreless. We also study a method to create a point-like monopole structure in a ferromagnetic condensate by suitably imprinting vortices and solitons for different spin components of the condensate.
Literatur Review: Plant Efficacy as Biolarvicide for Anopheles Mosquito Vector Control

Mosquito vectors are a severe threat to the prevalence and incidence of malaria, dengue fever, yellow fever, and filariasis. Malaria is a Plasmodium infection that is transmitted by the female Anopheles mosquito. Malaria cases in tropical and subtropical countries have social and economic impacts. Mosquito vector control has been using chemical and synthetic compounds. This method can reduce malaria cases, but it creates new problems that also slow down the elimination of malaria in the long run. Vector control in the larval phase using bioactive compounds of various plants is an alternative to eradicating vectors; besides that, utilizing these bioactive compounds is relatively safer, cheaper, and more accessible. Plants contain several compounds that are toxic to Anopheles mosquito larvae. This literature study summarizes research on extracts of various plants that function as larvicides of the Anopheles mosquito. The research method uses a literature study. The literature related to the research topic was obtained from the databases of Google Scholar, Semantic Sholar, Garuda, PubMed, and Science Direct. The primary literature is a publication of the last ten years. The literature study results showed that the plants Vitex negundo Linn. , Lawsonia inermis Linn. , Stachys byzantina K.Koch. , Pithecellobium dulce Bth. , Olax dissiti? ora Oliv. , Ipomea cairica Linn. , Ricinnus communis Linn. , Carica papaya Linn. , Paederia foetida Linn. , Glycosmis pentaphylla Retz. , Terminalia chebula Retz. , Annona squamosa Linn. , Tagetes erecta Linn. and Azadiracha indica Juss. against mosquito vectors. This study concludes that secondary plant metabolites can be used as candidates and alternatives for controlling Anopheles mosquito larvae.