Miracle-dz/UniFAR-FTUs huggingface dataset:
Confluence of Integrated Magnetics and TCM for a ZVS Based Higher Order Differential-Mode Rectifier

Two driving performance metrics in modern power-electronic systems are power density and efficiency: usually, improvement in one result in sacrificing the other. In this article, triangular conduction mode (TCM) is used alongside integrated magnetics to achieve both performance metrics simultaneously. TCM is implemented by extending the switch current high enough to reverse direction and provide enough energy at the onset of the deadtime to discharge the parasitic capacitance of the SiC mosfet. The elevated current ripple is alleviated by distributing the rectifier low-frequency current among parallel interleaved sub-modules. Taking advantage of the symmetrical topology of the differential mode Ćuk rectifier, an integrated interleaved magnetic (IIM) structure is proposed to house all the inductors in a module. In doing so, flux cancellation technique is used between the ac-and dc-side inductors to reduce the losses and size while using a custom core structure to control the flux coupling between the interleaved windings. A step by step design algorithm is presented to manage the different types of coupling within IIM. Challenges in design, fabrication, and testing of the system are analyzed and appropriate solutions are presented in each section. The solutions are supported by mathematical analysis to optimize the power stage design and validated by circuit as well as finite element simulations. An experimental setup is assembled to test this concept and multiple time-domain and parametric results are presented for proof of the concept in rectifier mode and single module mode.
Tracking Atmospheric Instabilities with the Kalman Filter. Part 1: Methodology and One-Layer Resultst

Abstract Sequential data assimilation schemes approaching true optimality for sizable atmospheric models are becoming a reality. The behavior of the Kalman filter (KF) under difficult conditions needs therefore to be understood. In this two-part paper we implement a KF for a two-dimensional shallow-water model, with one or two layers. The model is linearized about a basic flow that depends on latitude; this permits the one-layer (1-L) case to be barotropically unstable. Constant vertical shear in the two-layer (2-L) case induces baroclinic instability. A model-error covariance matrix for the KF simulations is constructed based on the hypothesis that an ensemble of slow modes dominates the errors. In the 1-L case, the system is stable for a meridionally constant basic flow. Assuming equipartition of energy in the construction of the model-error covariance matrix has a deleterious effect on the process of data assimilation in both the stable and unstable cases. Estimation errors are found to be smaller for .
POLD1 as a Prognostic Biomarker Correlated with Cell Proliferation and Immune Infiltration in Clear Cell Renal Cell Carcinoma

DNA polymerase delta 1 catalytic subunit (POLD1) plays a vital role in genomic copy with high fidelity and DNA damage repair processes. However, the prognostic value of POLD1 and its relationship with tumor immunity in clear cell renal cell carcinoma (ccRCC) remains to be further explored. Transcriptional data sets and clinical information were obtained from the TCGA, ICGC, and GEO databases. Differentially expressed genes (DEGs) were derived from the comparison between the low and high POLD1 expression groups in the TCGA–KIRC cohort. KEGG and gene ontology (GO) analyses were performed for those DEGs to explore the potential influence of POLD1 on the biological behaviors of ccRCC. The prognostic clinical value and mutational characteristics of patients were described and analyzed according to the POLD1 expression levels. TIMER and TISIDB databases were utilized to comprehensively investigate the potential relevance between the POLD1 levels and the status of the immune cells, as well as the tumor infiltration of immune cells. In addition, RT-qPCR, Western blot, immunohistochemistry and several functional and animal experiments were performed for clinical, in vitro and in vivo validation. POLD1 was highly expressed in a variety of tumors including ccRCC, and further verified in a validation cohort of 60 ccRCC samples and in vitro cell line experiments. POLD1 expression levels in the ccRCC samples were associated with various clinical characteristics including pathologic tumor stage and histologic grade. ccRCC patients with high POLD1 expression have poor clinical outcomes and exhibit a higher rate of somatic mutations than those with low POLD1 expression. Cox regression analysis also showed that POLD1 could act as a potential independent prognostic biomarker. The DEGs associated with POLD1 were significantly enriched in the immunity-related pathways. Moreover, further immune infiltration analysis indicated that high POLD1 expression was associated with high NK CD56bright cells, Treg cells, and myeloid-derived suppressor cells’ (MDSCs) infiltration scores, as well as their marker gene sets of immune cell status. Meanwhile, POLD1 exhibited resistance to various drugs when highly expressed. Finally, the knockdown of POLD1 inhibited the proliferation and migration, and promoted the apoptosis of ccRCC cells in vitro and in vivo, as well as influenced the activation of oncogenic signaling. Our current study demonstrated that POLD1 is a potential prognostic biomarker for ccRCC patients. It might create a tumor immunosuppressive microenvironment and inhibit the susceptibility to ferroptosis leading to a poor prognosis.
Dealing with ‘fragile identities’: resistance and refiguring in women mathematics students

Many learners may be successful in mathematics but nevertheless see themselves as existing only on the margins of the practice, or as lacking stability in it – in this sense, they have what can be called a fragile identity. Although this kind of relationship with mathematics is not limited to girls and women, they do appear to express such fragile identities more often or more readily. Drawing on qualitative and quantitative data from undergraduates in three English universities, this paper presents an analysis of the way in which university mathematics is differentially experienced by men and women, and of the part this may play in women’s ongoing narratives of self as mathematicians. It is suggested that some women resist traditional positionings in the mathematics world, drawing on local resources which enable a sense of agency as successful students and a refiguring of their relationships with mathematics.
Molecular dynamics simulation on CH4 combustion in CO2/O2/N2 atmosphere subjected to electric field

ABSTRACT In this paper, the CH4 combustion characteristics in CO2/O2/N2 atmosphere subjected to electric field were studied by the molecular dynamics simulation method. Conventional and unique pathways were obtained. The evolution law of reactants and main products and the first reaction time of main intermediates under the influence of different electric field intensities were analysed. Results showed that the addition of external electric fields increased conventional responses and species diversity. The generation of new pathways induced the production of new species, and the further reactions of new species produced other new pathways, thus accelerating the generation of new pathways and species in the electric field. It was noteworthy that, the applied external electric field could advance the reaction start time and reinforce the combustion process, but its effect on the reaction rate was highly nonlinear. The CH4 reaction with CO2 was significantly intensified at E ≥ 105 V/m, while suppressed at E = 104 V/m. Furthermore, electric fields could promote the oxidation degree of CH4, especially at E = 106 V/m. The studies provide theoretical guidance for revealing the mechanism of methane combustion under a high concentration CO2 atmosphere and promoting the efficient capture of CO2.
Researches Advanced in Finance based on Generative Adversarial Networks

Topics about how to apply Generative Adversarial Networks (GANs) to finance industry and research to promote financial market prosperity and progress with deep learning technology never fail to arouse public attention. For instance, financial academic realm such as portfolio optimization, trade execution strategies and financial information progressing have made use of machine learning. After a large number of literature retrieval and attempts to classify from different aspects, we ultimately find out that GAN is one of the most famous and appropriate technologies widely adopted in academic research and commercial applications. Aiming at assisting reader with having insight into how GAN improved financial work’s efficiency, in this paper, we propose three research perspectives of GAN in financial work: Stock Market Prediction, Fault Detection, and Time Series. By organizing from an innovative and macro perspective, we present and classify the application methods of GAN and the improvement of the basic model of GAN in order to adapt to the corresponding fields under the corresponding research directions. In general, the following improved models based on the basic GAN model for the corresponding financial perspective are involved: GAN of three-layer dense network, GAN with the MLP and LSTM separately as the discriminator and the generator, GAN-FD stock projection model, BERT and GAN in Stock Prediction; SSGANs, DAEGAN in Fault Detection; SeqGAN, Quant GAN, RNN-GAN, PSA-GAN in Time Series.
Asymptotic expansions of density of normalized extremes from logarithmic general error distribution

ABSTRACT Logarithmic general error distribution is an extension of the log-normal distribution. In this paper, the asymptotic expansions of densities of normalized maximum from logarithmic general error distribution are derived under two different kinds of normalized constants. By applying the main results, the higher-order expansions of moments of maxima are established.
Electron-neutral collision cross sections for H2O: II. Anisotropic scattering and assessment of the validity of the two-term approximation

This work proposes a complete and consistent set of cross sections (CS) for electron collisions with water gas molecules to be published in the IST-Lisbon database on LXCat. The set is validated by the electron swarm analysis technique. The anisotropic angular distribution of electrons in rotational collisions is considered by means of the Born approximation in a two-term Boltzmann solver (LisbOn KInetics two-term Boltzmann solver (LoKI-B)) and a Monte Carlo simulations code (LoKI-MC), both freely available as open-source codes. The inclusion of electron anisotropic scattering in rotational collisions significantly improves the agreement between calculations and measurements of the electron drift velocity, reduced mobility, characteristic energy, reduced Townsend ionisation coefficient, reduced effective Townsend coefficient and reduced attachment coefficient. The MC simulations are deemed more accurate and shown to yield similar results as LoKI-B with the proposed set. The use of LoKI-MC also validates the set of CSs against parameters that cannot be obtained by LoKI-B, such as the longitudinal diffusion coefficient or the bulk transport coefficients.
Wavelet Markov Random Field Based on Context and Hidden Class Label for SAR Image Segmentation

② (National Key Lab. of Radar Signal Processing , Xidian Univ., Xi'an 710071, China) Abstract: Because of the property that Synthetic Aperture Radar (SAR) images include plenty of multiplicative speckle noise, an effective image segmentation algorithm is proposed based on the wavelet hidden-class-label Markov Random Field (MRF) to suppress the affect of speckle. To consider the clustering and persistence of wavelet, the hidden-class-label MRF is extended to the wavelet domain with a new wavelet model for segmented image named hidden-class-label mixture heavy-tailed model, and interscale transition probability is estimated with improved context, then a new Maximum A Posteriori (MAP) classification is obtained. The experimental results show that the method suppresses the affect of noise effectively to achieve exact and robust segmentation result.
Studying the effect of antioxidants (Origanum Vulgare and N-Acetylcysteine ) administration on productive and reproductive performance of Damascus goats and their offspring.

Thirty Damascus does aged 1.5-2 years and weighed 46.9±1.64 kg were used to define the influence of Origanum Vulgare oil or N-acetyl cysteine supplementation on reproductive performance, milk yield and composition, growth performance in addition to changes in some blood metabolites during late pregnancy and suckling periods of Damascus does. Does were randomly divided into three equal groups (10 each) and،fed basal ration according to NRC (1981) . The first group, acted as control (G1), received a basal diet made up of 60% concentrate feed mixture (CFM), 20% berseem hay, and 20% rice straw. While the second (G2) and third (G3) groups consumed the same basic ration and supplemented daily with Origanum vulgare oil (OV oil) at a level of 1m. / kg concentrate (G2) and 0.3 gm / kg live body weight of N-acetyl-cysteine (NAC) after being dissolved in 200 ml of water and administered once daily for seven consecutive days during pregnancy and the same period after birth (Start before the first day of breastfeeding) (G3). Results indicated that both treated groups, during late pregnancy and suckling periods, showed improve in fecundity, prolificacy, kids born per does joined, kids born or weaned per does kidded and kg born and weaned per doe kidded, taking in consideration that the flock have history of high mortality rates and still birth which indicated in the values presented for the control group. The high mortality rate of control group (30%) efficiently reduced by NAC (6.67%) while lightly reduced by OV oil (22.22%). Daily milk yield of both treated groups were significantly higher than control group (G1). Fat, protein and lactose percentages for both treated groups also were significantly (P≤0.05) higher compared to the control group. Either Origanum Vulgare oil or N-acetyl cysteine supplement led to a significant increase in weaning weights, daily gain and total gain of kids, while birth weight value does not show any differences between treatments. The best weights occurred with N-acetyl cysteine. Origanum Vulgare oil or N-acetyl cysteine significantly (P<0.05) increased glucose, ALT and Vit C, while, the concentration of urea and AST significantly (P<0.05) decreased as result of Origanum Vulgare oil or N-acetyl cysteine treatment during late pregnancy and lactation periods as compared to the control does.
Calculation of the effective emissivity of a cavity having non-Lambertian isothermal surfaces

A method to calculate the directional local effective emissivity for a cavity having non-Lambertian isothermal surfaces is presented. Numerical calculation is carried out for a cylindrocone. The directional local effective emissivity directed to the cavity bottom is smaller than that directed to the cavity opening, and the local effective emissivity for a Lambertian takes a value close to the middle. The integrated effective emissivities are computed for a nonimaging system and an imaging optical system.
Pedestrian Recognition using Adaboost Algorithm based on Cascade Method by Curvature and HOG

In this paper, we suggest an advanced algorithm, to recognize pedestrian/non-pedestrian using second-stage cascade method, which applies Adaboost algorithm to make a strong classification from weak classifications. First, we extract two feature vectors: (i) Histogram of Oriented Gradient (HOG) which includes gradient information and differential magnitude; (ii) Curvature-HOG which is based on four different curvature features per pixel. And then, a strong classification needs to be obtained from weak classifications for composite recognition method using both HOG and curvature-HOG. In the proposed method, we use one feature vector and one strong classification for the first stage of recognition. For the recognition-failed image, the other feature and strong classification will be used for the second stage of recognition. Based on our experiment, the proposed algorithm shows higher recognition rate compared to the traditional method.
C1q/TNF-Related Proteins 1, 6 and 8 Are Involved in Corneal Epithelial Wound Closure by Targeting Relaxin Receptor RXFP1 In Vitro

Inadequate wound healing of ocular surface injuries can lead to permanent visual impairment. The relaxin ligand-receptor system has been demonstrated to promote corneal wound healing through increased cell migration and modulation of extracellular matrix formation. Recently, C1q/tumor necrosis factor-related protein (CTRP) 8 was identified as a novel interaction partner of relaxin receptor RXFP1. Additional data also suggest a role for CTRP1 and CTRP6 in RXFP1-mediated cAMP signaling. However, the role of CTRP1, CTRP6 and CTRP8 at the ocular surface remains unclear. In this study, we investigated the effects of CTRP1, CTRP6, and CTRP8 on epithelial ocular surface wound closure and their dependence on the RXFP1 receptor pathway. CTRP1, CTRP6, and CTRP8 expression was analyzed by RT-PCR and immunohistochemistry in human tissues and cell lines derived from the ocular surface and lacrimal apparatus. In vitro ocular surface wound modeling was performed using scratch assays. We analyzed the effects of recombinant CTRP1, CTRP6, and CTRP8 on cell proliferation and migration in human corneal and conjunctival epithelial cell lines. Dependence on RXFP1 signaling was established by inhibiting ligand binding to RXFP1 using a specific anti-RXFP1 antibody. We detected the expression of CTRP1, CTRP6, and CTRP8 in human tissue samples of the cornea, conjunctiva, meibomian gland, efferent tear ducts, and lacrimal gland, as well as in human corneal, conjunctival, and meibomian gland epithelial cell lines. Scratch assays revealed a dose-dependent increase in the closure rate of surface defects in human corneal epithelial cells after treatment with CTRP1, CTRP6, and CTRP8, but not in conjunctival epithelial cells. Inhibition of RXFP1 fully attenuated the effect of CTRP8 on the closure rate of surface defects in human corneal epithelial cells, whereas the CTRP1 and CTRP6 effects were not completely suppressed. Conclusions: Our findings demonstrate a novel role for CTRP1, CTRP6, and CTRP8 in corneal epithelial wound closure and suggest an involvement of the relaxin receptor RXFP1 signaling pathway. This could be a first step toward new approaches for pharmacological and therapeutic intervention.
Towards fracture risk assessment by deep-learning-based classification of prevalent vertebral fractures

Osteoporosis is a complex multifactorial skeletal disease and has become a major socioeconomic issue, causing tremendous hospitalization and rehabilitation costs. In addition to age, premature menopause or the use of oral corticosteroids, vertebral fractures are regarded as main risk factors for developing osteoporosis and associated fractures. In this work, we adapt an existing automated pipeline to classify fracture grades of individual vertebrae and the spine as a whole: First, vertebral body centers were identified on CT images by a hierarchical neural network. Next, the fracture grades of individual vertebrae were processed by a multi-head, feed-forward convolutional neural network. The sum of the classified grades was then evaluated according to the German radiology guidelines. A hyperparameter search on validation data showed the most promising results for an output configuration based on three sequentially applied binary classification outputs trained using binary cross-entropy: Grade 0–1 vs 2–3, and 0 vs 1–3, and 0–2 vs 3. In a cross-validation setting on 159 low-dose CT images, our pipeline accurately classified patients to have sum-scores ≥ 2 with sensitivities and specificities of 90 % ± 5.0 % and 87 % ± 2.7 %, respectively. As our method was based on classifying individual vertebrae, we were able to provide both the fracture position and severity to enhance transparency, interpretability and usability.
Determinants of proper disposal of single-use masks: knowledge, perception, behavior, and intervention measures

Background Although many studies testify to consumer behavior’s role in the context of waste-related sustainability objectives, little research examined what people know, think, and feel about the environmental impacts of their personal protective equipment (PPE) or their behavior towards them, in general. Therefore, the present article complements existing information about the public perceptions, knowledge, and behavior of single-use masks in a context where the pandemic has put increasing pressure on waste management public services. From February to June 2020, municipal solid waste increased ten times in Romania. The study identified the factors that predicted the proper disposal of single-use masks and the measures preferred to prevent or minimize the negative impact of single-use mask waste. Method Data from a representative sample of 705 Romanians were collected using a structured questionnaire. The data were analyzed with SPSS and SmartPLS. The Cochran’s Q test was run to determine the existence of differences between percentages of people who preferred various measures. Dunn’s test with a Bonferroni correction was used to identify the exact pair of groups where the differences were located. The study utilized structural equation models (SEM) based on at least partial squares with SmartPLS software (3.2.8) to investigate causal links between constructs. The model considered that the dependent variable (environmentally friendly behavior: proper disposal of single-use masks) could be influenced by the knowledge, perception, behavior, and demographics variables. Results The findings indicated that knowledge of the type of material of single-use masks had a direct positive (β = 0.173) and significant effect on their proper disposal. The perception of mask waste impact has a negative and significant (β = −0.153, p < 0.001) impact on the proper disposal of single-use masks. This path coefficient illustrates that the worse the perceived impact of single-use masks on waste management activity, the higher the proper disposal of single-use masks. Gender has a positive (β = 0.115) and significant (p < 0.001) effect on the proper disposal of single-use masks. Conclusions It was concluded that the 5Rs waste management approach should be reconsidered for single-use mask waste. For example, “Reuse” and the classic “Recycle” have limited applications since they may lead to virus transmission and possible infection. “Reducing” the use of single-use masks could have repercussions on one’s health. Summing up, the study outlined recommendations for effective interventions for the proper disposal of single-use masks from the perspective of behavioral studies.
Gamification-Based Cybersecurity Awareness Course for Self-regulated Learning

Present era of massive use of the internet has brought us enormous access to information and knowledge, yet has exposed us to such cybersecurity threats as personal information fraudulency and theft. Therefore, to safely and beneficially use cyberspace’s information services, it is necessary and inevitable to raise awareness of cybersecurity. Aiming at building an environment to support cyberspace users in focusing and strengthening such awareness, we think that providing users with self-regulated learning courses about cybersecurity topics will be a practical approach. With that purpose in mind, in this paper, we introduce a framework for developing a gamification-based cybersecurity awareness course on the Moodle learning management system.