Miracle-dz/UniFAR-FTUs huggingface dataset:
A Magnetically Controlled Current Transformer for Stable Energy Harvesting

The magnetically controlled current transformer (MCCT) is proposed to harvest stable energy from the magnetic field induced by the transmission-line fluctuating current. Compared with the conventional current transformer (CT), the advance of the proposed MCCT originates from the so-called constant magnetic flux control, which is achieved by connecting an electronic load on the secondary side of MCCT, and adjust the load impedance to make it equivalent to the corresponding resistive-capacitive impedance for magnetization or demagnetization. Furthermore, the working principle and the excitation characteristic of the MCCT system have been analyzed using the equivalent magnetic circuit and equivalent circuit methods. In addition, the details of the electronic load circuit and control system of the MCCT are presented in this paper, and the stability of the system is verified using logarithmic criterion and total harmonic current distortion (THDi) analysis. Finally, the co-simulation and experimental results show that MCCT can produce a stable output power of 13 W in the range of 50–500 A current fluctuations, demonstrating that the proposed magnetic energy harvester is capable of a high conversion efficiency and output stability.
CFD Simulations of Macroscopic and Microscopic Multiphase Fluid Flow and Droplet Interaction

v Chapter 1. General Information . 1 1.1. Computational Fluid Dynamics (CFD) Models . 1 Chapter 2. Euler-Euler Method for Modeling Liquid-Gas Flow . 4 2.1. Euler-Euler Model . 4 2.2. Turbulence Modeling . 4 2.3. Interfacial Forces . 5 Chapter 3. Subcooled Boiling Multiphase Flow . 7 3.
An investigative study on the Application of different statistical Tools and methods for optimizing the Hole machining on polymer matrix Composites – A review

Machining is one of the unavoidable operation after the processing of any type of material. Because of the advancement in the technology and innovation in the materials area, the composite materials are replacing and occupying the traditional materials market rapidly. Among these composite materials, the Fiber Reinforced Polymer (FRP) composite materials are found to be technically and structurally competitive and are widely used in a number of engineering industrial applications. The machining of these composites is found to be a complex phenomenon due to the influence of a number of machining and material parameters related to machining. Since drilling is the most frequently applied machining operation on composites, many research works were done on the drilling of composites, which resulted in numerous parameters that have influence on the drilling operation, impact on work material and cutting tool damage, cost of machining, material removal rate etc. So, at the background, it was thought to have a review on the issues related to drilling on the composite materials, which could help the manufacturing sectors and researchers in order to enhance the productivity. Thus the aim of this technical paper is to provide a detailed study of various issues related to drilling of FRP composite materials. This paper also comprehensively addresses the success and the failures of drilling operations, the factors associated with the drilling operation, their impact on the various output parameters. In addition, this review paper also discusses about the influences of a number of machining parameters and their influence on machining.
A scoping review of randomized clinical trials for pain management in pediatric tonsillectomy and adenotonsillectomy

Abstract Objectives To examine the volume, topics, and reporting trends in the published literature of randomized clinical trials for pharmacologic pain management of pediatric tonsillectomy and adenotonsillectomy and to identify areas requiring further research. Data Sources PubMed (National Library of Medicine and National Institutes of Health), Scopus (Elsevier), CINAHL (EBSCO), and Cochrane Library (Wiley). Methods A systematic search of four databases was conducted. Only randomized controlled or comparison trials examining pain improvement with a pharmacologic intervention in pediatric tonsillectomy or adenotonsillectomy were included. Data collected included demographics, pain‐related outcomes, sedation scores, nausea/vomiting, postoperative bleeding, types of drug comparisons, modes of administration, timing of administration, and identities of the investigated drugs. Results One hundred and eighty‐nine studies were included for analysis. Most studies included validated pain scales, with the majority using visual‐assisted scales (49.21%). Fewer studies examined pain beyond 24 h postoperation (24.87%), and few studies included a validated sedation scale (12.17%). Studies have compared several different dimensions of pharmacologic treatment, including different drugs, timing of administration, modes of administration, and dosages. Only 23 (12.17%) studies examined medications administered postoperatively, and only 29 (15.34%) studies examined oral medications. Acetaminophen only had four self‐comparisons. Conclusion Our work provides the first scoping review of pain and pediatric tonsillectomy. With drug safety profiles considered, the literature does not have enough data to determine which treatment regimen provides superior pain control in pediatric tonsillectomy. Even common drugs like acetaminophen and ibuprofen require further research for optimizing the treatment of posttonsillectomy pain. The heterogeneity in study design and comparisons weakens the conclusions of potential systematic reviews and meta‐analyses. Future directions include more noninferiority studies of unique comparisons and more studies examining oral medications given postoperatively.
Understanding Social Media in Journalism Practice: A Typology

Abstract: Although the intersection of social media usage and journalism practice enjoys a prominent place in many scholarly inquiries throughout the field of journalism studies, a comprehensive understanding of this body of literature is lacking. This study attempts to alleviate this problem. Through a systematic analysis of more than 150 studies primarily focusing on how journalists utilize social media in newswork, this article first classifies social media usage into three broad categories: news construction, news dissemination, and branding. Next, this study introduces a typology that visualizes and explores three dimensions of social media use: motivation (self vs. organization), prevalence (sporadic vs. prevalent), and disruption (disruptive vs. normalization). Our findings illustrate potential future research areas.
The Effect of Trust in Politicians and Perceptions of Macro Control on Attitudes towards Vaccines During the Covid-19 Pandemic Process

Objective: The purpose of this study is to investigate the effect of trust in politicians and perceptions of macro control on positive and negative attitudes towards vaccines during the Covid-19 pandemic process. Method: This is a cross-sectional field study. 1198 Turkish citizens at the age of 18 and over filled out an online questionnaire between May 6 and June 6, 2021. The questionnaire form consists of the scales of Trust in Politicians, Perception of Pandemic Macro Control, Attitudes towards Vaccines in addition to the demographic variables. In the analysis of the data, frequency, reliability, correlation, and regression analyzes were performed using the SPSS V.26 program, respectively. Results: Trust in politicians during the pandemic process has a statistically significant and positive effect on the perception of pandemic macro control. While trust in politicians and perception of pandemic macro control have a statistically significant and positive effect on positive attitude towards vaccines, they have a negative effect on a negative attitude towards vaccines. Conclusion: It was concluded that the trust in politicians and the perception of the adequacy of macro control measures taken by governments play an important role in people's adopting a positive attitude towards the developed vaccines to fight against the Covid-19, which has turned into a global pandemic.
Influence of different protection levels of PPE on nurses' physical fatigue during the COVID-19 pandemic.

BACKGROUND The continuous spread of COVID-19 globally has led to busier medical practices and nurses are having to provide medical services to patients while suffering from high levels of fatigue. OBJECTIVE This study experimentally investigated the influence of different levels of personal protection equipment (PPE) on nurses' physical fatigue. METHODS We collected data from 12 participants by simulating a series of nursing tasks. The participants wore one of three different protection levels of PPE, and data recording their heart rate (HR), oral temperature, task completion time, and subjective fatigue were collected. Following this, relationship models between subjective fatigue and objective fatigue indices was established using multiple linear regression analysis. RESULTS By analyzing the variation trends of single indices of HR, oral temperature, task completion time, and subjective fatigue, it was found that the higher the level of protection levels of PPE worn by the participants, the higher the degree of fatigue experienced by them. In addition, taking subjective fatigue variation as the dependent variable and objective fatigue indices as independent variables, relationship models of the three different protection levels of PPE were established. CONCLUSIONS The results confirmed the influence of different protection levels of PPE on nurses' physical fatigue levels. They also provide a basis for medical administrators to monitor the degree of fatigue experienced by nurses, attempt to arrange nurses' work content accordingly, and schedule suitably to combat and manage recorded increases in fatigue.
Encapsulated droplet interface bilayers as a platform for high-throughput membrane studies

Whilst it is highly desirable to produce artificial lipid bilayer arrays allowing for systematic high-content screening of membrane conditions, it remains a challenge due to the combined requirements of scaled membrane production, simple measurement access, and independent control over individual bilayer experimental conditions. Here, droplet bilayers encapsulated within a hydrogel shell are output individually into multi-well plates for simple, arrayed quantitative measurements. The afforded experimental throughput is used to conduct a 2D concentration screen characterising the synergistic pore-forming peptides Magainin2 and PGLa. Maximal enhanced activity is revealed at equimolar peptide concentrations via a membrane dye leakage assay, a finding consistent with models proposed from NMR data. The versatility of the platform is demonstrated by performing in situ electrophysiology, revealing low conductance pore activity (∼15 to 20 pA with 4.5 pA sub-states). In conclusion, this array platform addresses the aforementioned challenges and provides new and flexible opportunities for high-throughput membrane studies. Furthermore, the ability to engineer droplet networks within each construct paves the way for “lab-in-a-capsule” approaches accommodating multiple assays per construct and allowing for communicative reaction pathways.
Towards lead-free all-inorganic perovskite solar cell with theoretical efficiency approaching 23%

ABSTRACT Single junction solar cells with organic-inorganic perovskites have achieved efficiency > 25%, yet they suffer from long-term durability and toxicity. Additionally, all the best-performing perovskite light harvesters contain lead, hindering their real-time application. Herein, we report preliminary studies with the SCPAS-1D software package on three different perovskite light harvesters, namely FAPbI3, FASnI3, and CsSnI3, considering an approach towards stable and environmentally benign perovskite light harvesters. Additionally, to extract the best performance, each perovskite light harvester is analysed with four electron transport layers, namely TiO2, SnO2, BaSnO3, and La doped BaSnO3. The physical parameters such as thickness, doping, and defect density are optimised for the subsequent films to deliver high performance. Further, the operating temperature-dependent variation in power conversion efficiency and other solar cell parameters are also analysed. In an attempt to replace the high-cost gold counter electrode, a comparative study on the performance of other possible counter electrodes is also comprehensively detailed.
Bioconjugated Thymol-Zinc Oxide Nanocomposite as a Selective and Biocompatible Antibacterial Agent against Staphylococcus Species

Owing to the rapid spread of antibiotic resistance among Staphylococcus species, effective and low-risk alternatives to antibiotics are being actively searched. Thymol (THO), the most abundant component of the oil extracted from thyme, can be considered as a natural antibacterial alternative. However, the low antibacterial activity and non-selectivity of THO limit its usage as a universal anti-Staphylococcus agent. Herein, we report the bioconjugation of THO with ZnO nanoparticle (ZO), which resulted in the TZ nanocomposite (NC), as a potent and selective antibacterial agent against Staphylococcus species, particularly S. epidermidis. The cell-free supernatant (CFS) of ATCC 25923 cultures was employed for the production of TZ NC. Successful production of TZ NC was confirmed via X-ray diffraction (XRD), Fourier-transform infrared (FT-IR) spectroscopy, and ultraviolet–visible (UV–Vis) studies. TZ NC had selective efficacy against Staphylococcus species, with MIC values 2–32-fold lower than THO. The antibacterial mechanisms of TZ NC are proposed to involve membrane rupture, suppression of biofilm formation, and modulation of new cell wall and protein-synthesis-associated cellular pathways. Its biocompatibility against HCT116 cells was also checked. Our findings suggest that the TZ nanocomposite could improve the selectivity and bactericidal activity of THO against target species.
Interpersonal Family Dynamics Relate to Hippocampal CA Subfield Structure

Social environments that are extremely enriched or adverse can influence hippocampal volume. Though most individuals experience social environments that fall somewhere in between these extremes, substantially less is known about the influence of normative variation in social environments on hippocampal structure. Here, we examined whether hippocampal volume tracks normative variation in interpersonal family dynamics in 7- to 12-year-olds and adults recruited from the general population. We focused on interpersonal family dynamics as a prominent feature of one’s social world. Given evidence that CA1 and CA2 play a key role in tracking social information, we related individual hippocampal subfield volumes to interpersonal family dynamics. More positive perceptions of interpersonal family dynamics were associated with greater CA1 and CA2/3 volume regardless of age and controlling for socioeconomic status. These data suggest that CA subfields are sensitive to normative variation in social environments and identify interpersonal family dynamics as an impactful environmental feature.
An extended primal-dual algorithm framework for nonconvex problems: application to image reconstruction in spectral CT

Using the convexity of each component of the forward operator, we propose an extended primal-dual algorithm framework for solving a kind of nonconvex and probably nonsmooth optimization problems in spectral computed tomography (CT) image reconstruction. Following the proposed algorithm framework, we present six different iterative schemes or algorithms, and then establish the relationship to some existing algorithms. Under appropriate conditions, we prove the convergence of these schemes for the general case. Moreover, when the proposed schemes are applied to solving a specific problem in spectral CT image reconstruction, namely, total variation regularized nonlinear least-squares problem with nonnegative constraint, we also prove the particular convergence for these schemes by using some special properties. The numerical experiments with densely and sparsely data demonstrate the convergence and accuracy of the proposed algorithm framework in terms of visual inspection of images of realistic anatomic complexity and quantitative analysis with metrics structural similarity, peak signal-to-noise ratio, mean square error and maximum pixel difference. We analyze the computational complexity of these schemes, and discuss the extended applications of this algorithm framework in other nonlinear imaging problems.
Analytic Illumination with Polygonal Light Sources

Modeling the effects of finite-sized light sources has been an active area of research for many years. Most methods simplify the problem by approximating the area source with a collection of point sources. The only existing analytic method works in screen space to compute a single image. This paper presents an object-space algorithm to model illumination from polygonal light sources. The result is a collection of smooth-shaded polygonal facets which may be rendered from any viewing position. Binary Space Partitioning trees are used to compute the umbra and penumbra boundaries efficiently. Fast analytic techniques are developed for illumination calculations. Numerical optimization techniques are used to sample the shading function in unshadowed regions finely enough to find all significant illumination gradations. Illumination calculations are optimized to concentrate computational effort on parts of the scene where they are most needed.
A General Map of Transcriptional Expression of Virulence, Metabolism, and Biofilm Formation Adaptive Changes of Staphylococcus aureus When Exposed to Different Antimicrobials

Biofilm formation of Staphylococcus aureus is the major cause of implant-associated infections (IAIs). Antimicrobial treatment is one of the most effective therapeutic options for S. aureus infections. However, it can also lead to adaptive transcriptomic changes due to extreme selective pressure, which may increase the risk of antimicrobial resistance. To study the transcriptional changes in S. aureus upon exposure to antimicrobial agents, we obtained expression profiles of S. aureus treated with six antimicrobials (flucloxacillin, vancomycin, ciprofloxacin, clindamycin, erythromycin, and linezolid, n = 6 for each group). We also included an untreated control group (n = 8) downloaded from the Gene Expression Omnibus (GEO) database (GSE70043, GSE56100) for integrated bioinformatic analyses. We identified 82 (44 up, 38 down) and 53 (17 up, 36 down) differentially expressed genes (DEGs) in logarithmic and stationary phases, respectively. When exposed to different antimicrobial agents, we found that manganese import system genes and immune response gene sbi (immunoglobulin G-binding protein Sbi) were upregulated in S. aureus at all stages. During the logarithmic phase, we observed adaptive transcriptomic changes in S. aureus mainly in the stability of protein synthesis, adhesion, and biofilm formation. In the stationary phase, we observed a downregulation in genes related to amino biosynthesis, ATP synthesis, and DNA replication. We verified these results by qPCR. Importantly, these results could help our understanding of the molecular mechanisms underlying the proliferation and antimicrobial resistance of S. aureus.
Learning Noise Robust ResNet-Based Speaker Embedding for Speaker Recognition

The presence of background noise and reverberation, especially in far distance speech utterances diminishes the performance of speaker recognition systems. This challenge is addressed on different levels from the signal level in the front end to the scoring technique adaptation in the back end. In this paper, two new variants of ResNet-based speaker recognition systems are proposed that make the speaker embedding more robust against additive noise and reverberation. The goal of the proposed systems is to extract x-vectors in noisy environments that are close to their corresponding x-vector in a clean environment. To do so, the speaker embedding network minimizes the speaker classification loss function and the distance between pairs of noisy and clean x-vectors jointly. The experimental results obtained by our systems are compared with the baseline ResNet system. In different situations with real and simulated noises and reverberation conditions, the modified systems outperform the baseline ResNet system. The proposed systems are tested with four evaluation protocols. In the presence of artificial noise and reverberation, we achieved 19% improvement of EER. The main advantage of the proposed systems is their efficiency against real noise and reverberation. In the presence of real noise and reverberation, we achieved 15% improvement of EER.
Thermo-Responsive Shape Memory Vanillin-Based Photopolymers for Microtransfer Molding

Novel thermo-responsive shape-memory vanillin-based photopolymers have been developed for microtransfer molding. Different mixtures of vanillin dimethacrylate with tridecyl methacrylate and 1,3-benzenedithiol have been tested as photocurable resins. The combination of the different reaction mechanisms, thiol-acrylate photopolymerization, and acrylate homopolymerization, that were tuned by changing the ratio of monomers, resulted in a wide range of the thermal and mechanical properties of the photopolymers obtained. All polymers demonstrated great shape-memory properties and were able to return to their primary shape after the temperature programming and maintain their temporary shape. The selected compositions weretested by the microtransfer molding technique and showed promising results. The developed thermo-responsive shape-memory bio-based photopolymers have great potential for forming microtransfered structures and devices applicable on non-flat surfaces.