Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless Charging of Large-Scale Energy Storage Systems: A Hybridized Ad-Hoc Approach for High Efficiency

This article presents a solution to the challenges faced by wireless power transfer (WPT)-based equalizers in supporting high-voltage large-scale energy storage systems while improving efficiency. The proposed solution is an efficient hybridized ad-hoc wireless charger that balances cascaded energy storage modules without imposing high current stress on each cell. Unlike multiple-coil solutions, the proposed solution requires only one receiving coil, eliminating the impact of parameter inconsistency. An algorithm is also proposed to switch the balancing and charging modes, reducing conduction loss compared to conventional WPT-based equalizers with only a balancing mode. The proposed algorithm enables ad-hoc balancing for targeted cells instead of balancing the entire cell string at all times. A scaled-down prototype with 12 cells was fabricated, and experimental results show that the proposed system achieves both charging and balancing functions for the energy storage system. During the balancing process, the system can achieve up to 76.1% efficiency for 25-W balancing, whereas, during the charging process, it can achieve up to 88.6% efficiency for 65-W charging. The proposed WPT-based equalizer provides an efficient hybridized ad-hoc wireless charging/balancing approach that supports large-scale energy storage systems.
Dynamic Programming-Based Antenna Resource Allocation Algorithm for Wireless Powered Sensor Networks

In a wireless powered sensor network (WPSN), wireless sensors can receive energy from energy transmitters for operation. To improve the performance of the WPSN, the multisource wireless power transfer technique based on the beamforming multi-antenna architecture has emerged as an attractive solution. Thus, in this paper we consider the WPSN system which includes multiple wireless sensors and multiple multi-antenna energy transmitters. We proposed a dynamic programming-based antenna resource allocation algorithm, which takes the diverse distances among various energy transmitting antennas into account, for the radio frequency-based WPSN to maximize the energy transfer efficiency. According to the numerical results, the proposed dynamic programming-based antenna resource allocation algorithm can achieve near-optimal energy transfer efficiency while reducing the computation complexity significantly, compared with the backtracking algorithm which always achieves the optimal allocation but usually not tractable in practical scenarios.
Effect of QT interval-prolonging drugs taken in pregnancy on the neonatal QT interval

Introduction: Acquired QT interval prolongations due to drug side effects can result in detrimental arrhythmia. Maternal use of placenta-permeable drugs may lead to fetal exposure, thus leading to an increased risk of neonatal QT prolongation and arrhythmia. Objectives: This study aimed to evaluate the influence of maternal QT-prolonging medication on the neonatal QT interval. Methods: In the prospective KUNO-Kids health study, an ongoing population-based birth cohort, we classified maternal medications according to the known risk of QT interval prolongation. Effects on the neonatal QT interval were tested by linear regression analyses, correcting for perinatal confounders (birth weight, gestational age, birth mode, and age at ECG recording). Subgroup analyses were performed for selective serotonin reuptake inhibitors, proton pump inhibitors, and antihistamine dimenhydrinate. Logistic regression analysis was performed using a QTc of 450 ms as the cut-off value. Results: A total of 2,550 pregnant women received a total of 3,990 medications, of which 315 were known to increase the risk of QT prolongation, resulting in 105 (4.1%) neonates exposed in the last month of pregnancy. Overall, the mean age of the neonates at ECG was 1.9 days and the mean QTc (Bazett) was 414 ms. Univariate (regression coefficient −2.62, p = 0.288) and multivariate (regression coefficient −3.55, p = 0.146) regression analyses showed no significant effect of fetal medication exposure on the neonatal QT interval, neither in the overall nor in the subgroup analysis. Logistic regression analysis showed no association of exposure to maternal medication with an increased risk of neonatal QT interval prolongation (OR (odds ratio) 0.34, p = 0.14). Conclusion: The currently used maternal medication results in a relevant number of fetuses exposed to QT interval-prolonging drugs. In our cohort, exposure was found to have no effect on the neonatal QT interval.
Current and Future PET Imaging for Multiple Myeloma

Positron emission tomography (PET) is an imaging modality used for the noninvasive assessment of tumor staging and response to therapy. PET with 18F labeled fluorodeoxyglucose (18F-FDG PET) is widely used to assess the active and inactive lesions in patients with multiple myeloma (MM). Despite the availability of 18F-FDG PET for the management of MM, PET imaging is less sensitive than next-generation flow cytometry and sequencing. Therefore, the novel PET radiotracers 64Cu-LLP2A, 68Ga-pentixafor, and 89Zr-daratumumab have been developed to target the cell surface antigens of MM cells. Furthermore, recent studies attempted to visualize the tumor-infiltrating lymphocytes using PET imaging in patients with cancer to investigate their prognostic effect; however, these studies have not yet been performed in MM patients. This review summarizes the recent studies on PET with 18F-FDG and novel radiotracers for the detection of MM and the resulting preclinical research using MM mouse models and clinical studies. Novel PET technologies may be useful for developing therapeutic strategies for MM in the future.
Vibrational Spectra of the thioglycolate complexes of Zn(II) and Cd(II), structure and natural bond orbitals

The objective of this research was to characterize the vibrational spectrum of the Zn(II) and Cd(II) thioglycolate complexes, as well as their structures, vibrational analysis and the natural orbitals of bonds, through the infrared spectrum with Fourier transform (FT -IR) and Raman. The thioglycolate complexes of Zn(II) and Cd(II) were synthesized following procedures given by the graphical method, and structural analysis was performed through a theoretical-experimental method using both, the hybrid RHF/MP2:STO-3G and the experimental FT-IR and FT-Raman spectra. Calculations were performed on the optimized structure and harmonic vibrational wavenumbers for both complexes were obtained. Second derivative of the vibrational spectra and deconvolution analysis were also performed. The infrared and Raman spectra show many combination and overtone bands in both cases. Calculated and experimental spectra confirmed the structural hypothesis considering two ATG (thioglycolic acid) with two water molecules in the coordination sphere of the central atoms. The natural bond orbital analysis (NBO) was also carried out to study the Zn(II) and Cd(II) hybridization leading to a pseudo-octahedral geometry for both complexes.
Feasibility insights into the application of Paenibacillus pabuli E1 in animal feed to eliminate non-starch polysaccharides

The goal of the research was to find alternative protein sources for animal farming that are efficient and cost-effective. The researchers focused on distillers dried grains with solubles (DDGS), a co-product of bioethanol production that is rich in protein but limited in its use as a feed ingredient due to its high non-starch polysaccharides (NSPs) content, particularly for monogastric animals. The analysis of the Paenibacillus pabuli E1 genome revealed the presence of 372 genes related to Carbohydrate-Active enzymes (CAZymes), with 98 of them associated with NSPs degrading enzymes that target cellulose, hemicellulose, and pectin. Additionally, although lignin is not an NSP, two lignin-degrading enzymes were also examined because the presence of lignin alongside NSPs can hinder the catalytic effect of enzymes on NSPs. To confirm the catalytic ability of the degrading enzymes, an in vitro enzyme activity assay was conducted. The results demonstrated that the endoglucanase activity reached 5.37 U/mL, while beta-glucosidase activity was 4.60 U/mL. The filter paper experiments did not detect any reducing sugars. The xylanase and beta-xylosidase activities were measured at 11.05 and 4.16 U/mL, respectively. Furthermore, the pectate lyase and pectin lyase activities were found to be 8.19 and 2.43 U/mL, respectively. The activities of laccase and MnP were determined as 1.87 and 4.30 U/mL, respectively. The researchers also investigated the effect of P. pabuli E1 on the degradation of NSPs through the solid-state fermentation of DDGS. After 240 h of fermentation, the results showed degradation rates of 11.86% for hemicellulose, 11.53% for cellulose, and 8.78% for lignin. Moreover, the crude protein (CP) content of DDGS increased from 26.59% to 30.59%. In conclusion, this study demonstrated that P. pabuli E1 possesses various potential NSPs degrading enzymes that can effectively eliminate NSPs in feed. This process improves the quality and availability of the feed, which is important for animal farming as it seeks alternative protein sources to replace traditional nutrients.
A Hybrid System for Myocardial Infarction Classification with Derived Vectorcardiography

The 12-lead electrocardiography (ECG) remains the most rapid and widely used diagnostic test for patients with myocardial infarction (MI). Most wearable ECG devices only provide single limb-lead measurement, limiting their practical applicability for MI diagnosis. The ability to transform from single-lead ECG to 3-lead vectorcardiography (VCG) enables wider use of wearable devices in clinical diagnostics. This study presents a patient-specific transformation for VCG synthesis using temporal convolutional networks in variational mode decomposition domain. MI-induced changes in morphological and temporal wave features are extracted from the derived VCG via spline curve approximation. After feature extraction, a multilayer perceptron classifier is used to classify different types of MI. Experiments on the PTB diagnostic database show that the proposed system achieves satisfactory performance in differentiating MI patients from healthy subjects and localizing infarcted area.
Energy Management System for Smart Microgrid Systems using Adaptive Fuzzy Logic

Population growth, industrialization, and commercialization all contribute to an enormous demand for electricity that frequently depends on fossil fuels. The focus is now on the usage of renewable energy sources because of the sudden reduction in fossil fuels, increased cost of electricity production, and pollution. The use of the smart microgrid systems in hospitals, schools, colleges, small businesses, government buildings, etc. has proven to be successful. The unpredictable nature of renewable energy sources, however, leads to poor energy management and an inability to supply the applications with the necessary power. In order to increase energy efficiency, this research provides an autonomous energy management system (EMS) for a smart microgrid that uses a fuzzy logic algorithm. The suggested method FOFFers an energy and money-saving alternative.
Early transcriptome changes associated with western diet induced NASH in Ldlr−/− mice points to activation of hepatic macrophages and an acute phase response

Background Nonalcoholic fatty liver disease (NAFLD) is a global health problem. Identifying early gene indicators contributing to the onset and progression of NAFLD has the potential to develop novel targets for early therapeutic intervention. We report on the early and late transcriptomic signatures of western diet (WD)-induced nonalcoholic steatohepatitis (NASH) in female and male Ldlr−/− mice, with time-points at 1 week and 40 weeks on the WD. Control Ldlr−/− mice were maintained on a low-fat diet (LFD) for 1 and 40 weeks. Methods The approach included quantitation of anthropometric and hepatic histology markers of disease as well as the hepatic transcriptome. Results Only mice fed the WD for 40 weeks revealed evidence of NASH, i.e., hepatic steatosis and fibrosis. RNASeq transcriptome analysis, however, revealed multiple cell-specific changes in gene expression after 1 week that persisted to 40 weeks on the WD. These early markers of disease include induction of acute phase response (Saa1-2, Orm2), fibrosis (Col1A1, Col1A2, TGFβ) and NASH associated macrophage (NAM, i.e., Trem2 high, Mmp12 low). We also noted the induction of transcripts associated with metabolic syndrome, including Mmp12, Trem2, Gpnmb, Lgals3 and Lpl. Finally, 1 week of WD feeding was sufficient to significantly induce TNFα, a cytokine involved in both hepatic and systemic inflammation. Conclusion This study revealed early onset changes in the hepatic transcriptome that develop well before any anthropometric or histological evidence of NALFD or NASH and pointed to cell-specific targeting for the prevention of disease progression.
Nitrates in Groundwater

Fundamental Aspects of Nitrates in Groundwater The Nitrogen Cycle The Nitrogen Cycle in Soil and Groundwater Sources of Nitrate to Groundwater National Survey of Nitrates (and Pesticides) in Drinking Water Wells Health Concerns Related to Nitrates Influence of Subsurface Processes Nitrogen Transformations Nitrogen Transport and Fate Factors Influencing Nitrogen Leaching from Fertilizers Usage of Laboratory Studies Illustrations of Nitrate Pollution of Groundwater Illustrations from the United States Illustrations from European and Other Countries Vulnerability Mapping of Groundwater Resources Context of Vulnerability Mapping Summary of 10 Mapping Techniques Vulnerability Mapping in Belgium Groundwater Vulnerability to Agricultural Nitrate Pollution in the United Kingdom Terrain Suitability Rating for Septic Tank Systems in Canada Groundwater Contamination Susceptibility in Minnesota DRASTIC: A Standardized System for Evaluating Groundwater Pollution Potential in the United States Soil/Aquifer Field Evaluation (SAFE) Advantages and Limitations Relative to Vulnerability Mapping Development of a Nitrate Pollution Index Conceptual Framework for Development of an Index Identification of Pertinent Factors Assignment of Relative Importance Weights Establishing Methods for Evaluating Pertinent Factors Determining Aggregation Approach for the Index Field Testing of the Index Models for Nitrates in the Subsurface Environment Source Characterization Models Nitrate Transport Models Plume Model for Nitrogen Point Source Management Models for Prevention and Control Management Measures for Nitrate Pollution Prevention Fertilizer Management Measures Other Management Measures Treatment Measures for Nitrates in Groundwater Treatment by Ion Exchange, Reverse Osmosis, or Electrodialysis Treatment by Biological Denitrification Treatment by In Situ Denitrification Treatment by Other Measures Each chapter concludes with a summary and selected references
Heart Arrhythmia Detection Using FPGA

The VLSI attained incredible growth from the 1980s in all areas, especially after the invention of ARTIX-7 Low voltage FPGA, which is mainly designed for biomedical applications. This paper focuses on one of the leading global causes of illness. Heart disease contributes to a large number of demise in the world. This life saving biomedical application concentrates on the heart arrhythmia detection of different heart disease. This heart arrhythmia detection is implemented in FPGA using Verilog code for Convolutional Neural Network architecture in Vivado and Modelsim. This paper devises a methodology to detect three types of abnormal cardiac signals.
Announcement Effect Study of Issuing Tier 2 Capital Bonds on the Stock Price of China Construction Bank

Abstract This article uses event study methodology to empirically analyze the announcement effect of China Construction Bank's issuance of Tier 2 capital bonds. The results show that firstly, the announcement of the issuance of Tier 2 capital bonds has a positive impact on the stock price of China Construction Bank, with a positive abnormal return during the event study window. Secondly, the abnormal return is significantly higher from the 6th day to the 14th day after the announcement, indicating that the positive announcement effect occurs approximately one week after the announcement and lasts for one week. Based on these findings, policy recommendations are proposed: Firstly, China Construction Bank should choose an appropriate opportunity to issue Tier 2 capital bonds to achieve the goal of reducing capital costs and increasing the bank's market value. Secondly, regulatory authorities should strengthen supervision to prevent insider trading and enhance financial market reform. Thirdly, short-term investors can choose to buy after the announcement of the issuance of Tier 2 capital bonds by China Construction Bank and sell around 14 days after the announcement to obtain abnormal returns. Keywords: Tier 2 capital bonds, Announcement effects, China Construction Bank.
Analytical Approach for Losses in Differential Amplifier Using Double-Gate MOSFET

This research work entails designing and analyzing a differential amplifier that utilizes BF988 Double-Gate (DG) MOSFET. Different parameters have been analyzed to observe the performance of the amplifier. The active load has been used instead of the resistive load to improve the differential gain of the system significantly. The simulated results of differential gain, switching losses, conduction losses, and total power losses were obtained as 15.85 V/V, 0.1 μW, 85.8 mW, and 1.73 W, respectively. From these results, the proposed amplifier is suitable for RF applications, input stages of the operational amplifier, medical measuring instruments, etc.
DeEN: Deep Ensemble Framework for Neuroatypicality Classification

This paper proposes a Machine Learning (ML) based ensemble framework to identify neuroatypicality among individuals. The focus of this study is neuroatypicality, which refers to individuals who suffer from irregular neurological functioning. The neuroatypicality conditions includes ASD, ADHD and Dyslexia. The neuroatypical individuals face challenges in emotional regulation, educational intervention, decision-making, and problem-solving. Diagnosis of neuroatypicality is a difficult task due to the varied symptoms among individuals. Brain signal analysis is one of the common parameters to identify neuroatypicality. This paper focuses on brain signal based ML framework to classify the typically and neuroatypically developed individuals. The contribution of this paper is to propose an ensemble framework for early diagnosis of neuro disorder which forms a basis to enable Artificial Intelligence (AI) to generate heuristics for further academic and medical research.
Bilateral Bi-Level Erector Spinae Plane Blocks as a Part of Opioid-Sparing Multimodal Analgesia in Scoliosis Surgery: A Case Series of Six Pediatric Patients

Background and Aim: Postoperative pain after scoliosis surgery is severe and usually requires long-term intravenous opioid therapy. Local anesthetic options, such as wound infiltration, are limited and include neuraxial analgesia. However, they are rarely used due to side effects and inconsistent efficacy. We report an opioid-sparing multimodal analgesia regimen with bilateral erector spinae plane blocks. This case series evaluated the analgesic effect of the bilateral bi-level erector spinae plane blocks (ESP) in congenital and neurogenic scoliosis surgery. Patients and Methods: Six pediatric patients with congenital or neurogenic scoliosis underwent posterior spinal fusion involving 5 to 12 vertebral levels. Bilateral single-injection ESPB was performed at one or two levels before incision. Preoperatively, patients received intravenous dexamethasone. General anesthesia with endotracheal intubation and volume-controlled ventilation was performed via TIVA with remifentanil and propofol. During and after the procedure, the basic hemodynamic parameters, opioid consumption, pain scores (numerical rating scale/NRS), and possible block complications were monitored. Results: All the patients experienced minimal postoperative pain levels. In addition, on the first day after surgery, they had low opioid requirements with no side effects. Conclusions: ESPB in patients undergoing congenital and neurogenic scoliosis correction surgery seems to be an essential analgesic technique that may reduce both severities of pain and opioid consumption.
Além da fluido-responsividade: o conceito de fluido-tolerância e sua potencial implicação no manejo hemodinâmico

Apesar das diferentes metodologias e definições na literatura, a concepção mais comumente aceita de fluido-responsividade (FR) é o aumento do débito cardíaco maior que 10-15% induzido pelo aumento da pré-carga. Dessa forma, a expansão volêmica é a medida inicial mais frequentemente utilizada na tentativa de otimização de perfusão tecidual num paciente hemodinamicamente instável. No entanto, a prevalência de FR em unidade de terapia intensiva (UTI) gira ao redor de 50%;(1) assim, a administração indiscriminada de volume em todo paciente com instabilidade hemodinâmica, além de não auferir os possíveis benefícios induzidos pelo aumento do débito cardíaco, tem o potencial de agravar disfunções orgânicas ocasionadas pela sobrecarga hídrica, já que o excesso de fluidos, representado pelo balanço hídrico acumulado, é fator independente para aumento do tempo de internação em UTI, tempo de ventilação mecânica, probabilidade de lesão renal aguda e mortalidade. (2-4) A definição de fluido-tolerância (FT), por sua vez, é a capacidade do organismo de receber infusão de fluidos sem evoluir com disfunção orgânica(5) (Tabela 1). Possíveis mecanismos relacionados à gênese dessas disfunções incluem o dano tecidual na microcirculação por aumento na distância de difusão do oxigênio às células e pela diminuição do número de hemácias oxigenadas devido à hemodiluição; a alteração do glicocálix endotelial(6) com alteração da permeabilidade vascular(7) e maior edema tecidual; e o aumento da pressão intraparenquimatosa em órgãos encapsulados, como fígado e rim,(8) resultando numa menor pressão de perfusão e num menor fluxo sanguíneo tecidual. Desse modo, a avaliação conjunta de FR e FT é de fundamental importância no manejo de um paciente hemodinamicamente instável, pois a ausência de FT, ainda que num paciente fluido-responsivo, pode mitigar qualquer suposto benefício induzido pela expansão volêmica e até mesmo agravar ou ocasionar novas disfunções orgânicas.
Advanced CNN-Based Approach for Accurate Tomato Plant Disease Recognition

Artificial intelligence has a lot of potential to boost crop output and promote food security by identifying plant diseases and pests Tomato is one of the most essential and widely consumed vegetables globally, but it is susceptible to various diseases that can cause severe yield loss. Early detection of these diseases is critical for effective management and control. In this study, we propose a deep learning-based approach for the automatic detection of tomato crop diseases using Effective Convolutional Neural Networks (CNN). We trained a CNN model on a large dataset of tomato crop images with modified layers to classify them into healthy or diseased plants. The proposed approach achieved an accuracy of over 91.66% in detecting three common tomato diseases, namely Early Blight, Late Blight, and Septoria Leaf Spot, demonstrating its effectiveness for practical use. The results show that the proposed method can help farmers and researchers to detect crop diseases at an early stage, which can prevent yield losses and improve overall crop productivity