Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct Stator Flux Vector Control Strategy for IPMSM using a Full-order State Observer

A direct stator flux vector control scheme in discrete-time domain is proposed in this paper for the interior permanent magnet synchronous motor (IPMSM) drive to remove the proportional-integral (PI) controller from the direct torque control (DTC) scheme applied to IPMSM and to obtain faster dynamic response and lower torque ripple output. The output of speed outer loop is used as the desired torque angle instead of the desired torque in the proposed scheme. The desired stator flux vector in dq coordinate is calculated with a given amplitude. The state-space equations in discrete-time for IPMSM are established, the actual stator flux vector is estimated in deadbeat manner by a full-order state observer, and then the closed-loop control is achieved by the pole placement. The stator flux error vector is utilized to calculate the reference stator voltage vector. Extracting the angle position and amplitude from the estimated stator flux vector and estimating the output torque are eliminated for the direct feedback control of the stator flux vector. The proposed scheme is comparatively investigated with a PI-SVM DTC scheme by experiment results. Experimental results show the feasibility and advantages of the proposed control scheme.
Intracranial Aneurysm Rupture after SARS-CoV2 Infection: Case Report and Review of Literature

Background: SARS-CoV virus infection results in a dysbalanced and severe inflammatory response with hypercytokinemia and immunodepression. Viral infection triggers systemic inflammation and the virus itself can potentially cause vascular damage, including blood–brain barrier (BBB) disruption and alterations in the coagulation system, which may result in cardiovascular and neurovascular events. Here, we review the literature and present a case of COVID-19 infection leading to an aneurysmal subarachnoid haemorrhage (aSAH). Case Description: A 61-year-old woman presented with dyspnea, cough, and fever. She had a history of hypertension and was overweight with a body mass-index of 34. There was no history of subarachnoid hemorrhage in the family. Due to low oxygen saturation (89%) she was admitted into ICU. A chest CT showed a typical picture of COVID-19 pneumonia. The PCR-based test of an oropharyngeal swab was COVID-19-positive. In addition to oxygen support she was prescribed with favipiravir and hydroxychloroquine. She experienced a sudden headache and lost consciousness on the second day. Computer tomography (CT) with CT-angiography revealed a subarachnoid haemorrhage in the basal cisterns from a ruptured anterior communicating artery aneurysm. The aneurysm was clipped microsurgically through a left-sided standard pterional approach and the patient was admitted again to the intensive care unit for further intensive medical treatment. Post-operatively, the patient showed slight motor dysphasia. No other neurological deficits. Conclusion: Systemic inflammation and ventilator support-associated blood pressure fluctuations may trigger aneurysmal subarachnoid haemorrhage secondary to COVID-19 infection. COVID-19 infection could be considered as one of the possible risk factors leading to instability and rupture of intracranial aneurysm.
Enablers and Barriers for Quality Assurance: A Comparative Study of Vietnamese Case and International Trends

The study aimed to explore the internal and external enablers to quality assurance (QA) and identify barriers to QA in Vietnam as compared with international trends. Data was collected through a survey questionnaire on enablers and barriers to QA which were delivered to institutional leaders, middle administrators, lecturers, and support staff of 13 HEIs. Stratified sampling was used to select 13 out of 44 HEIs (both public and private) in one city of Vietnam. Data analysis includes descriptive statistics of factors or variables of interest identified. The results show that both internal and external forces contributed to the development of QA. Wide participation of all staff and the quantity and quality of QA staff were perceived as the most influential internal drivers respectively, followed by other internal factors. The desires to enhance HEI’s image and the state policies were prompted as the major external drivers, followed by other external factors. The biggest challenges to the QA implementation were staff resistance and incompetent QA staff. The comparison across responding universities reveals several significant differences among the surveyed universities. The findings suggest that decentralisation in governance and autonomy be given to HEIs so that their responsibilities to QA endeavours can be exercised through self-regulation and self-improvement.
On Transfer Learning for Building Damage Assessment from Satellite Imagery in Emergency Contexts

When a natural disaster occurs, humanitarian organizations need to be prompt, effective, and efficient to support people whose security is threatened. Satellite imagery offers rich and reliable information to support expert decision-making, yet its annotation remains labour-intensive and tedious. In this work, we evaluate the applicability of convolutional neural networks (CNN) in supporting building damage assessment in an emergency context. Despite data scarcity, we develop a deep learning workflow to support humanitarians in time-constrained emergency situations. To expedite decision-making and take advantage of the inevitable delay to receive post-disaster satellite images, we decouple building localization and damage classification tasks into two isolated models. Our contribution is to show the complexity of the damage classification task and use established transfer learning techniques to fine-tune the model learning and estimate the minimal number of annotated samples required for the model to be functional in operational situations.
Association of Interleukin-1 Beta and Interleukin-1 Receptor Antagonist Gene Polymorphisms and Plasma Levels with Diabetic Nephropathy

Objective We investigated the relationships between interleukin- (IL-) 1β and IL-1 receptor antagonist (IL-1Ra) gene polymorphism and plasma levels in patients with diabetic nephropathy (DN). Methods The genotype and allele frequency distribution of IL-1β and IL-1Ra in 61 patients with DN and 48 healthy controls (HCs) were determined by kompetitive allele-specific PCR (KASP), and the plasma concentrations of IL-1β and IL-1Ra in DN patients and HCs were measured by enzyme-linked immunosorbent assays (ELISA). Results Significant differences were detected in the distribution of IL-1β (−511C/T) genotype and allele frequencies between the DN and HC groups (P < 0.05), with the T genotype being more frequent in DN patients than HCs (OR = 2.84, 95% CI: 1.489–5.416). The IL-1β (+3953C/T) and IL-1Ra (+8006C/T) genotypes and allele frequencies were not significantly different between the two groups (P > 0.05). The plasma IL-1β level was significantly higher (P < 0.01), while the plasma IL-1Ra concentration was significantly lower in the DN group than the HC group (P < 0.05). Furthermore, the plasma IL-1β level was significantly different between IL-1β (−511C/T) locus variants (P < 0.05). Conclusion The IL-1β (−511C/T) gene polymorphism was significantly associated with DN risk in the population of northern Guangxi, China, and the T allele maybe responsible for genetic susceptibility to DN.
Detection Method of Helmet Wearing in Complex Scenes

In complex scenes, the standard wearing of helmets is the basic key to ensuring personnel safety, its effective detection is affected by the small targets, dense targets, and mutual occlusion. This study proposed a detection algorithm based on the You Only Look Once version 5(YOLOv5) algorithm to detect the wearing of helmets in complex scenes effectively. Data enhancement and other processing on the data set were performed to determine the personnel area and obtain personnel location information. The complete downsampling information was preserved for subsequent feature extraction through Focus processing. Then, the head area of the subject person was extracted to expand the location area and improve the fault tolerance of the algorithm. Finally, given the overlapping area between the target frame and the detection frame, the Complete Intersection over Union (CIoU) loss function was selected for the center point distance and aspect ratio to improve the positioning accuracy. Moreover, a dynamic adjustment strategy was adopted for the learning rate during the training process. Results show that the algorithm can effectively detect and mark the wearing situation of the subject persons’ helmets. The experiment is conducted in the test set of 2000 pictures. The accuracy rate of the experiment is 0.995, and the average response speed reaches 0.035 s. This study provides a technical reference for the detection of safety protective equipment among staff and the improvement of work safety factors in complex scene environments.
Selfie-taking Behavior and Narcissistic Tendencies of College Students

The increasing popularity of selfies and social media made users vulnerable to excessive selfie-related behaviors. This maladaptive behavior can cause people to develop several mental disorders such as depression and body dysmorphic disorder. Thus, this study determined the relationship between selfietaking behavior and narcissistic tendencies of selected college students. Selfitis Behavior Scale (SBS) and Narcissistic Personality Inventory (NPI-13) are research instruments used to measure selfie-taking behavior and narcissistic tendencies, respectively. The descriptive-correlational research revealed that 120 college students, selected through stratified sampling technique, are more likely to engage in selfie-taking behavior which in turn, may lead to narcissistic tendencies. Respondents showed high level of selfietaking behavior and low level of narcissistic tendencies, therefore displaying ‘seldom narcissistic’ features. Only the frequency of selfies taken was significantly related to selfie-taking behavior. Selfietaking behavior was also significantly related to narcissistic tendencies. Thus, this study concludes that selfie-taking and narcissistic behaviors can be positive and negative, influenced primarily by the motives of selfie-taking, and cultural differences play an important role in mediating selfie-taking and narcissistic behaviors. This study suggests a deeper exploration on the narcissistic tendencies and providing more specific details on the nature, causes, classification, as well as possible diagnostic criteria of these narcissistic features.
Sequentially targeting and intervening mutual Polo-like Kinase 1 on CAFs and tumor cells by dual targeting nano-platform for cholangiocarcinoma treatment

Rationale: Synergistic treatment strategies for two or more drugs have gradually developed as the main options in clinics for cholangiocarcinoma (CCA) owing to the complicated crosstalk between the tumor and stroma. However, the different synergetic mechanisms pose great challenges to the dosages and order of administration of drugs. Thus, a strategy for exploring and intervening in mutual targets derived from stromal cells and cholangiocarcinoma cells was proposed. Methods: Genes with overexpression patterns in tumors and displaying a significant association with overall survival were identified from RNA-seq data of human CCA patients and CCA mouse models. Western blotting, qRT-PCR, immunofluorescence (IF), colony formation and flow cytometry assays were conducted to determine the biological roles of the key oncogene in cholangiocarcinoma and stromal cells respectively. Additionally, a dual-targeting drug delivery system (AA-HA-ODA) for cancer-associated fibroblasts (CAFs) and tumor cells was constructed to verify the effectiveness of intervening the screened genes in vivo. Results: Polo-like kinase 1 (PLK1) was verified to play vital role in the malignant proliferation of CCA by regulating the cell cycle pathway. PLK1 also decreased stromal production by regulating the CAF phenotype. In addition, a PLK1 inhibitor (Ro3280) loaded dual-targeting drug delivery system (AA-HA-ODA) was prepared and exhibited high affinity for CAFs and cholangiocarcinoma cells. The in vivo distribution pattern and antitumor efficacy of AA-HA-ODA/Ro also verify the effectiveness of inhibiting PLK1 in CCA in vivo. Conclusion: In summary, PLK1 is a mutual target derived from tumor cells and stroma due to its crucial role in the proliferation of tumor cells and stroma regulation in CAFs, which might provide enlightenment for multitarget treatment strategies and guidance for clinical cholangiocarcinoma treatment.
The impact of Southern Ocean topographic barriers on the ocean circulation and the overlying atmosphere.

Southern Ocean bathymetry constrains the path of the Antarctic Circumpolar Current (ACC), but the bathymetric influence on the coupled ocean-atmosphere system is poorly understood. Here, we investigate this impact by respectively flattening large topographic barriers around the Kerguelen Plateau, Campbell Plateau, Mid-Atlantic Ridge, and Drake Passage in four simulations in a coupled climate model. The barriers impact both the wind and buoyancy forcing of the ACC transport, which increases by between 4% and 14% when barriers are removed individually and by 56% when all barriers are removed simultaneously. The removal of Kerguelen Plateau bathymetry increases convection south of the plateau and the removal of Drake Passage bathymetry reduces convection upstream in the Ross Sea. When the barriers are removed, zonal flattening of the currents leads to sea surface temperature (SST) anomalies that strongly correlate to precipitation anomalies, with correlation coefficients ranging between r=0.92 and r=0.97 in the four experiments. The SST anomalies correlate to the surface winds too in some locations. However, they also generate circumpolar waves of sea level pressure (SLP) anomalies which induce remote windspeed changes that are unconnected to the underlying SST field. The meridional variability in the wind stress curl contours over the Mid-Atlantic Ridge, the Kerguelen Plateau and the Campbell Plateau disappears when these barriers are removed, confirming the impact of bathymetry on surface winds. However, bathymetry-induced wind changes are too small to affect the overall wave-3 asymmetry in the Southern Hemisphere Westerlies. Removal of Southern Hemisphere orography is also inconsequential to the wave-3 pattern.
Pulsed Electric Field: Fundamentals and Effects on the Structural and Techno-Functional Properties of Dairy and Plant Proteins

Dairy and plant-based proteins are widely utilized in various food applications. Several techniques have been employed to improve the techno-functional properties of these proteins. Among them, pulsed electric field (PEF) technology has recently attracted considerable attention as a green technology to enhance the functional properties of food proteins. In this review, we briefly explain the fundamentals of PEF devices, their components, and pulse generation and discuss the impacts of PEF treatment on the structure of dairy and plant proteins. In addition, we cover the PEF-induced changes in the techno-functional properties of proteins (including solubility, gelling, emulsifying, and foaming properties). In this work, we also discuss the main challenges and the possible future trends of PEF applications in the food proteins industry. PEF treatments at high strengths could change the structure of proteins. The PEF treatment conditions markedly affect the treatment results with respect to proteins’ structure and techno-functional properties. Moreover, increasing the electric field strength could enhance the emulsifying properties of proteins and protein-polysaccharide complexes. However, more research and academia–industry collaboration are recommended to build highly effective PEF devices with controlled processing conditions.
Deep learning-based residual control chart for count data

Abstract Statistical process control for count data has difficulty overcoming multicollinearity. In this paper, we propose a new deep learning residual control chart based on the asymmetrical count response variable when there are highly correlated explanatory variables. We implement and compare different methods such as neural network, deep learning, principal component analysis based Poisson regression, principal component analysis based negative binomial regression, nonlinear principal component analysis based Poisson regression, and nonlinear principal component analysis based negative binomial regression in terms of the root mean squared error. Using two asymmetrical simulated datasets generated by the combined multivariate normal, binary and copula functions, the neural network and deep learning have a smaller mean, median, and interquartile range when compared to the principal component analysis based Poisson regression, principal component analysis based negative binomial regression, nonlinear principal component analysis based Poisson regression, and nonlinear principal component analysis based negative binomial regression. We also compare the deep learning and neural network based residual control charts in terms of the average run length with the copula based asymmetrical simulated data and real takeover bids data.
Ring Finger Protein 125 Is an Anti-Proliferative Tumor Suppressor in Hepatocellular Carcinoma

Simple Summary HCC is a leading cause of cancer-related deaths worldwide. However, its tremendous inter- and intra-tumor heterogeneity has made it difficult to identify driver genes for HCC. Transposon mutagenesis is a versatile in vivo tool to identify cancer genes in tissues of interest. Herein, we analyzed transposon mutagenesis screening data in the liver and discovered a novel tumor suppressor gene, RNF125. This gene functions as a negative regulator of cell proliferation through transcriptional suppression of multiple genes important for cell proliferation and liver regeneration. This gene is frequently inactivated in human HCC and has a significant impact on patient prognosis. Our findings identify a new regulatory network of cell proliferation mediated by RNF125 and its contribution to HCC development and progression. Abstract Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide and the only cancer with an increasing incidence in the United States. Recent advances in sequencing technology have enabled detailed profiling of liver cancer genomes and revealed extensive inter- and intra-tumor heterogeneity, making it difficult to identify driver genes for HCC. To identify HCC driver genes, we performed transposon mutagenesis screens in a mouse HBV model of HCC and discovered many candidate cancer genes (SB/HBV-CCGs). Here, we show that one of these genes, RNF125 is a potent anti-proliferative tumor suppressor gene in HCC. RNF125 is one of nine CCGs whose expression was >3-fold downregulated in human HCC. Depletion of RNF125 in immortalized mouse liver cells led to tumor formation in transplanted mice and accelerated growth of human liver cancer cell lines, while its overexpression inhibited their growth, demonstrating the tumor-suppressive function of RNF125 in mouse and human liver. Whole-transcriptome analysis revealed that RNF125 transcriptionally suppresses multiple genes involved in cell proliferation and/or liver regeneration, including Egfr, Met, and Il6r. Blocking Egfr or Met pathway expression inhibited the increased cell proliferation observed in RNF125 knockdown cells. In HCC patients, low expression levels of RNF125 were correlated with poor prognosis demonstrating an important role for RNF125 in HCC. Collectively, our results identify RNF125 as a novel anti-proliferative tumor suppressor in HCC.
Uplink NOMA-MIMO Systems with Rayleigh Power Distribution

The article is devoted to multiple-input multiple-output antenna systems, also called MIMO systems, which are widely used in wireless communication systems. In this article we consider a case when the MIMO system works in overloaded mode. In this mode MIMO systems can be considered as a system with non-orthogonal multiple access NOMA. The main goal of this article is to analyze this interesting case using statistical computer simulation. Based on the analysis of the capacity of a discrete-continuous multiuser MIMO uplink channel, the possibility of such systems functioning in overload mode is proved.
Acoustic models of bus interior regarding the different points of working combustion engine

The article presents an analysis of sound propagation inside the selected road transport vehicles in the city of Poznan. The research was based on the measurements of the levels of acoustic pressure generated by several bus combustion engines during an acceleration process – at various rotation speed of the crankshaft in combustion engines. Then taking into consideration the measurements and the assumptions of acoustic holography in domain of time, several acoustic models of sound propagation inside the buses at various points on the working combustion engines were elaborated.
A Novel Genetic Neural Network Algorithm with Link Switches and Its Application in University Professional Course Evaluation

This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional course comprehensively and objectively, and the traditional artificial evaluation methods cannot achieve this goal. The presented data-driven modeling method, EGA-NNLS, combines a neural network with link switches (NN-LS) with an enhanced genetic algorithm (EGA) and the Levenberg–Marquardt (LM) algorithm. It employs an optimized network structure combined with EGA and NN-LS to learn the relationships between the system's input and output from historical data and uses the network's gradient information via the LM algorithm. Compared with the traditional backpropagation neural network (BPNN), EGA-NNLS achieves a faster convergence speed and higher evaluation precision. In order to verify the efficiency of EGA-NNLS, it is applied to a collection of experimental data for modeling the professional university course evaluating system.