Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Principal Component Analysis-Informer Model for Fault Prediction of Nuclear Valves

In this paper, a deep learning fault detection and prediction framework combining principal component analysis (PCA) and Informer is proposed to solve the problem of online monitoring of nuclear power valves which is hard to implement. More specifically, PCA plays the role of dimensionality reduction and fault feature extraction. It maps data with multi-dimensional space to low-dimensional space and extracts the main features. At the same time, the T-square and Q statistic thresholds are also provided to realize abnormal status monitoring. Meanwhile, Informer is a long-term series prediction method. It encrypts and decrypts data through the encoder and decoder to train a prediction model. Through the training of fault data, fault prediction can be realized. Experiments based on the sound waves collected from real valves can be continued, which also illustrates the effectiveness of the PCA–Informer model for fault diagnosis and fault prediction of nuclear power valves. Therefore, the online monitoring and maintenance of nuclear valves and other important equipment, without shutting down the nuclear station, can be achieved.
Fixed Settling Time Control for Self-Driving Car: Two-Timescales Approach

This article involves the design of a novel path tracking control technique for the self-driving car. Fixed settling time sliding mode control (FSTSMC) with barrier Lyapunov function is implemented to deal with the non-linear lateral dynamics and to ensure stable standard double-lane-change (DLC) maneuver of self-driving cars in the presence of unknown lateral tire forces and parametric uncertainties. A two-time scale-based approach is employed to deal with the slow and fast dynamics of the car separately. The proposed control scheme efficacy is investigated using simulations based on CarSim and Simulink. The simulation results validate the path-tracking ability of the proposed controller for self-driving cars while accomplishing the stable double-lane-change maneuver at various forward speeds.
Calculation of the T-X phase diagram for the first-order smectic–hexatic transitions in binary mixtures

This work gives the T-X phase diagram calculated from the Landau mean field model for the smectic–hexatic transitions in binary mixtures, particularly, in THI-13+THI-17. It is calculated near the SmC-SmF (Hex F)–Hex B triple point by considering transitions of SmC-SmF, SmF-HexB, and SmC-Hex B as the first order. The phase line equations are fitted to the experimental T-X phase diagram from the literature for this binary mixture by assuming the temperature and concentration dependence of the coefficients in the Landau free energy expansion. Calculations are given in some detail to describe the smectic–hexatic transitions in the THI-13+THI-17, which can also be considered for other binary mixtures under the Landau mean field model studied here.
Automatic Sleep Scoring Using Intrinsic Mode Based on Interpretable Deep Neural Networks

Sleep experts manually label sleep stages via polysomnography (PSG) to diagnose sleep disorders. However, this process is time-consuming, requires a lot of labor from sleep experts, and makes the participants uncomfortable with the attachment of multiple sensors. Thus, automatic sleep scoring methods are essential for practical sleep monitoring in our daily lives. In this study, we propose an automatic sleep scoring model based on intrinsic oscillations in a single channel electroencephalogram (EEG) signal. We applied noise assisted bivariate empirical mode decomposition (NA-BEMD) to extract the intrinsic mode components and an attention mechanism in deep neural networks to provide weights to the components depending on their significance to sleep scoring. In particular, through the attention mechanism, we found an interpretable model by examining the oscillations that correspond to specific sleep stages. Therefore, we analyzed which frequency components are more weighted to a sleep stage than the others, when the model classifies sleep stages, and, as a result, confirmed that the model assigns convincing weights to the frequency components for each sleep stage. Additionally, the model consists of a one-dimensional convolutional neural network (1D-CNN) to extract features of an epoch and bidirectional long short-term memory (Bi-LSTM) to learn the sequential information of the consecutive epochs. We evaluated proposed model using Fpz-Cz, Pz-Oz, and F3-M2 channel EEG from three different public datasets (Sleep-EDF-2013, Sleep-EDF-2018, WSC) and demonstrated that our model yielded the best overall accuracy (Fpz-Cz: 86.22%-82.67%, Pz-Oz: 83.63%-80.15%, F3-M2: 84.20%) and macro F1-score (Fpz-Cz: 80.79%-76.90%, Pz-Oz: 76.89%-72.98%, F3-M2: 74.88%) compared with the state-of-the-art sleep scoring algorithms using single channel EEG. As a benchmark test, FIR bandpass filters were compared, and it was confirmed that NA-BEMD was superior to the traditional filters in all experiments, demonstrating that the proposed model is interpretable and a state-of-the-art sleep scoring algorithm.
RANCANG BANGUN APLIKASI COMPUTER LABORATORY RESOURCE INVENTORY SYSTEM BERBASIS WEB PADA SEKOLAH MENENGAH KEJURUAN PLUS PONTREN YABAFA

Tujuan dari penelitian ini adalah membangun aplikasi manajemen inventory laboratorium berbasis web sehingga memberikan kemudahan dalam melakukan proses inventarisasi peralatan/ bahan yang ada pada laboratorium baik dari segi pengarsipan, perawatan, maupun alat keluar . Metodologi yang digunakan dalam penelitian ini adalah Evolutionary Web Development , dimana metodologi ini sangat direkomendasikan untuk keberhasilan sebuah aplikasi berbasis web . Hasil penelitian ini berupa analisis proses bisnis yang sedang berjalan dan rekomendasi proses bisnis yang disesuaikan dengan prosedur dalam pembuatan aplikasi Computer Laboratory Resource inventory system (CLRIS) . Penelitian ini dibatasi pada manajemen device dan manage location serta metodologi yang digunakan hanya sampai pada tahap website development . Penelitian ini menghasilkan sebuah aplikasi berbasis web yang siap digunakan dan diimplementasikan untuk mengelola sumberdaya laboratorium dengan kelebihan memberikan report secara real time, dapat diakses kapan saja dan dimana saja.
Close TIES in relationships: A dynamic systems approach for modeling physiological linkage

We explore complex dynamic patterns of autonomic physiological linkage (i.e., statistical interdependence of partner’s physiology; PL), within the sympathetic and parasympathetic nervous systems (SNS and PNS), as potential correlates of emotional and regulatory dynamics in close relationships. We include electrodermal activity (EDA) as an indicator of SNS activation and respiratory sinus arrhythmia (RSA) as an indicator of regulatory and/or homeostatic processes within the PNS. Measures of EDA and RSA were collected in 10-second increments from 53 heterosexual couples during a mixed-emotion conversation in the laboratory. We used the R statistical package, rties (Butler & Barnard, 2019), to model the dynamics of EDA and RSA with a coupled oscillator model and then categorized couples into qualitatively distinct profiles based on the set of parameters that emerged. We identified two patterns for EDA and three patterns for RSA. We then investigated associations between the PL patterns and self-report measures of relationship and conversation quality and emotional valence using Bayesian multilevel and logistic regression models. Overall, we found robust results indicating that PL profiles were credibly predicted by valence and relationship quality reported prior to the conversations. In contrast, we found very little evidence suggesting that PL patterns predict self-reported conversation quality or valence following the conversation. Together, these results suggest that PL across autonomic subsystems may reflect different processes and therefore have different implications when considering interpersonal dynamics.
Validation of a geometric diffraction model with respect to level-time history prediction

Noise induced wake-up reactions strongly depend on single noise events, which are characterized by the maximum sound pressure level and the steepest slope of rise in level time-history. In this paper the applicability of the CNOSSOS-EU guidelines in terms of assessing the level-time history of moving sound sources is investigated. Generally, major changes in noise level occur due to shadowing effects. Therefore, the focus of investigation lies on the diffraction model. This model distinguishes between three different diffraction cases: the partial diffraction, when the direct ray comes close to an edge, the single diffraction and the multi diffraction. All three diffraction cases are investigated in one scenario of a sound source passing-by a box. The results are compared to numerical simulations using a Discontinuous-Galerkin method. The comparison shows an overestimation of the level by the diffraction model in case of double diffraction, while in the single diffraction case an underestimation occurs. The deviation between the Discontinuous-Galerkin and the geometric model in case of partial diffraction is below 3 dB. In terms of level history, the geometric diffraction model shows an unrealistic discontinuity when the model switches between the single and double diffraction case. The jump is increasing with higher frequencies.
Management of Hypertension in Older People

WIN and TEO: Management of Hypertension in Older People: Systolic hypertension above >160 mmHg is associated with cardiac, renal and cerebrovascular complications. In older people, treating hypertension offers cardiovascular benefits. Reduced salt intake and weight loss for obese older people improves blood pressure without any risk of adverse drug reactions. Blood pressure reduction is more important than the type of antihypertensive for cardiovascular risk reduction. The recommended drugs to start an older patient with isolated systolic hypertension are thiazides, calcium-channel blockers or angiotensin II receptor blocker. Studies were performed on relatively fit older patients, so benefits may not be generalisable to frail elderly. Alpha-blockers and beta-blockers are not recommended for first line therapy of hypertension but may be considered if there are other indications for their use. (J HK Coll Cardiol 2017;25:1-8)
TIPPING THE BALANCE WITH DIELECTRO- PHORETIC FORCES - AN ELECTRIC DETERMI- NISTIC LATERAL DISPLACEMENT DEVICE

We present experimental results and simulations on a simple method for tunable particle separation based on a combination of Deterministic Lateral Displacement (DLD) and Insulator Based Dielectrophoresis (I-DEP). Rather than deriving its tunability from its elastic properties[1], our present device uses an applied AC field to perturb the particle trajectories in the pressure-driven flow and is thereby capable of scanning the critical size over a range of factor two. Potential benefits include: extended dynamic range, facilitated fabrication and less clogging for given particle sizes, and combination of the precision afforded by DLD with the versatility of DEP.
Broadband 1.5 GHz analog monolithic vector modulator

A novel 1.5-GHz vector modulator has been developed which has improved performance over conventional circuits. The vector modulator uses vector addition to provide analog amplitude control and 360 degrees of analog phase control of incident signals over an octave bandwidth. This novel vector modulator demonstrates the advantages of broadband operation and small size while providing for virtually infinite phase and amplitude control. <<ETX>>
Framing as an Information Control Strategy in Times of Crisis

Abstract How can authoritarian regimes effectively control information to maintain regime legitimacy in times of crisis? We argue that media framing constitutes a subtle and sophisticated information control strategy in authoritarian regimes and plays a critical role in steering public opinion and cultivating an image of competent government during a tremendous crisis. Using structural topic models (STM), we conduct a textual analysis of more than 4,600 news reports produced by seven Chinese media outlets during the COVID-19 pandemic. We find that Chinese media, instructed by the propaganda authorities, used a heroism frame to feature frontline medics’ sacrifices when saving others in need and resorted to a contrast frame to highlight the poor performance of the United States in the fight against COVID-19. We also show that both state and commercial media outlets used these two frames, though the tone of commercial media coverage was generally more moderate than the state media version.
QoS-Aware Algorithm Based on Task Flow Scheduling in Cloud Computing Environment

This paper deals with the challenging problem of scheduling users’ tasks, while taking into consideration users’ quality of service (QoS) requirements, with the objective of reducing the energy consumption of physical machines. This paper presents a model to analyze the current state of the running tasks according to the results of the QoS prediction assigned by an ARIMA prediction model optimized with Kalman filter. Then, we calculate a scheduling policy with a combined particle swarm optimization (PSO) and gravitational search algorithm (GSA) algorithms according to the QoS status analysis. Experimental results show that the proposed HPSO algorithm reduces resources consumption 16.51% more than the original hybrid algorithm, and the violation of service-level agreement (SLA) is 0.053% less when the optimized prediction model is used.
Subnational violent conflict forecasts for sub-Saharan Africa, 2015–65, using climate-sensitive models

How will local violent conflict patterns in sub-Saharan Africa evolve until the middle of the 21st century? Africa is recognized as a particularly vulnerable continent to environmental and climate change since a large portion of its population is poor and reliant on rain-fed agriculture. We use a climate-sensitive approach to model sub-Saharan African violence in the past (geolocated to the nearest settlements) and then forecast future violence using sociopolitical factors such as population size and political rights (governance), coupled with temperature anomalies. Our baseline model is calibrated using 1° gridded monthly data from 1980 to 2012 at a finer spatio-temporal resolution than existing conflict forecasts. We present multiple forecasts of violence under alternative climate change scenarios (optimistic and current global trajectories), of political rights scenarios (improvement and decline), and population projections (low and high fertility). We evaluate alternate shared socio-economic pathways (SSPs) by plotting violence forecasts over time and by detailed mapping of recent and future levels of violence by decade. The forecasts indicate that a growing population and rising temperatures will lead to higher levels of violence in sub-Saharan Africa if political rights do not improve. If political rights continue to improve at the same rate as observed over the last three decades, there is reason for optimism that overall levels of violence will hold steady or even decline in Africa, in spite of projected population increases and rising temperatures.
Proteomic and Transcriptomic Profiling Reveals Mitochondrial Oxidative Phosphorylation as Therapeutic Vulnerability in Androgen Receptor Pathway Active Prostate Tumors

Simple Summary Metastatic prostate cancer (PC) is the second leading cause of cancer deaths in males. The lack of preclinical models and molecular characterization for advanced stage PC is a key barrier in understanding the aggressive subsets androgen receptor (AR) pathway active or AR-null castration-resistant prostate cancers (CRPC). Our study aimed to assess the potential of patient-derived xenograft (PDX) models and an approach integrating proteomic and transcriptomic techniques to explore the underlying drivers of metastatic PC. Transcriptomic and proteomic profiling of 42 PDX prostate tumors uncovered both previously established and unexpected molecular features of aggressive PC subsets. Of these, we confirmed the functional role of mitochondrial metabolism in AR-positive CRPC. Abstract Metastatic prostate cancer (PC) is the second leading cause of cancer deaths in males and has limited therapeutic options. The lack of preclinical models for advanced stage PC represents one of the primary barriers in understanding the key genetic drivers of aggressive subsets, including androgen receptor (AR) pathway active and AR-null castration-resistant prostate cancers (CRPC). In our studies, we described a series of LuCaP patient-derived xenograft (PDX) models representing the major genomic and phenotypic features of human disease. To fully exploit the potential of these preclinical models, we carried out a comprehensive transcriptomic and proteomic profiling of 42 LuCaP PDX prostate tumors. The collected proteomic data (~6000 data points) based on 71 antibodies revealed many of the previously known molecular markers associated with AR-positive and AR-null CRPC. Genomic analysis indicated subtype-specific activation of pathways such as Wnt/beta-catenin signaling, mTOR, and oxidative phosphorylation for AR-positive CRPC and upregulation of carbohydrate metabolism and glucose metabolism for AR-null CRPC. Of these, we functionally confirmed the role of mitochondrial metabolism in AR-positive CRPC cell lines. Our data highlight how the integration of transcriptomic and proteomic approaches and PDX systems as preclinical models can potentially map the connectivity of poorly understood signaling pathways in metastatic prostate cancer.
Genome-Wide Identification and Expression Analysis of the Basic Leucine Zipper (bZIP) Transcription Factor Gene Family in Fusarium graminearum

The basic leucine zipper (bZIP) is a widely found transcription factor family that plays regulatory roles in a variety of cellular processes including cell growth and development and various stress responses. However, the bZIP gene family has not been well studied at a genome-wide scale in Fusarium graminearum (Fg), a potent pathogen of cereal grains. In the present study, we conducted a genome-wide identification, characterization, and expression profiling of 22 F. graminearum bZIP (FgbZIP) genes at different developmental stages and under various abiotic stresses. All identified FgbZIPs were categorized into nine groups based on their sequence similarity and phylogenetic tree analysis. Furthermore, the gene structure analysis, conserved motif analysis, chromosomal localization, protein network studies, and synteny analysis were performed. The symmetry of the exon and intron varied with the phylogenetic groups. The post-translational modifications (PTMs) analysis also predicted several phosphorylation sites in FgbZIPs, indicating their functional diversity in cellular processes. The evolutionary study identified many orthogroups among eight species and also predicted several gene duplication events in F. graminearum. The protein modeling indicated the presence of a higher number of α-helices and random coils in their structures. The expression patterns of FgbZIP genes showed that 5 FgbZIP genes, including FgbZIP_1. 1, FgbZIP_1. 3, FgbZIP_2. 6 FgbZIP_3. 1 and FgbZIP_4. 3, had high expression at different growth and conidiogenesis stages. Similarly, eight genes including FgbZIP_1. 1, FgbZIP_1. 6, FgbZIP_2. 3, FgbZIP_2. 4, FgbZIP_4. 1, FgbZIP_4. 2, FgbZIP_4. 3 and FgbZIP_4. 6 demonstrated their putative role in response to various abiotic stresses. In summary, these results provided basic information regarding FgbZIPs which are helpful for further functional analysis.
Rac Inhibition Causes Impaired GPVI Signalling in Human Platelets through GPVI Shedding and Reduction in PLCγ2 Phosphorylation

Rac1 is a small Rho GTPase that is activated in platelets upon stimulation with various ligands, including collagen and thrombin, which are ligands for the glycoprotein VI (GPVI) receptor and the protease-activated receptors, respectively. Rac1-deficient murine platelets have impaired lamellipodia formation, aggregation, and reduced PLCγ2 activation, but not phosphorylation. The objective of our study is to investigate the role of Rac1 in GPVI-dependent human platelet activation and downstream signalling. Therefore, we used human platelets stimulated using GPVI agonists (collagen and collagen-related peptide) in the presence of the Rac1-specific inhibitor EHT1864 and analysed platelet activation, aggregation, spreading, protein phosphorylation, and GPVI clustering and shedding. We observed that in human platelets, the inhibition of Rac1 by EHT1864 had no significant effect on GPVI clustering on collagen fibres but decreased the ability of platelets to spread or aggregate in response to GPVI agonists. Additionally, in contrast to what was observed in murine Rac1-deficient platelets, EHT1864 enhanced GPVI shedding in platelets and reduced the phosphorylation levels of PLCγ2 following GPVI activation. In conclusion, Rac1 activity is required for both human and murine platelet activation in response to GPVI-ligands, but Rac1’s mode of action differs between the two species.
The Hypolipidemic and Antioxidant Activity of Wheat Germ and Wheat Germ Protein in High-Fat Diet-Induced Rats

Background: So far, no articles have discussed the hypolipidemic effect of wheat germ protein in in vivo experiments. Objective: In this study, we investigated the effects of wheat germ protein (WGP, 300 mg/kg/day) and wheat germ (WG, 300 mg/kg/day) on cholesterol metabolism, antioxidant activities, and serum and hepatic lipids in rats fed a high-fat diet through gavage. Methodology: We used 4-week-old male Wistar 20 rats in our animal experiment. Biochemical indicators of fecal, serum and liver were tested by kits or chemical methods. We also conducted the cholesterol micellar solubility experiment in vitro. Results: After 28 days of treatment, our results showed that WGP significantly reduced the serum levels of total cholesterol (p < 0.05) and nonhigh-density lipoprotein cholesterol (p < 0.05), improved the enzymatic activities of cholesterol 7-α hydroxylase (p < 0.01) and low-density lipoprotein receptor (p < 0.01) and increased bile acid excretion in feces (p < 0.05). Conclusion: WG did not significantly increase bile acid excretion in feces or decrease serum levels of total cholesterol. Moreover, WGP and WG both presented significant antioxidant activity in vivo (p < 0.05) and caused a significant reduction in cholesterol micellar solubility in vitro (p < 0.001). Therefore, WGP may effectively prevent hyperlipidemia and its complications as WGP treatment enhanced antioxidant activity, decreased the concentration of serum lipids and improved the activity of enzymes involved in cholesterol metabolism.
Rubrics and Teamwork Development in Online Higher Education Business Courses: Exploring the Connection

Effective teamwork is important in higher education business courses to prepare students for future professional contexts. Learning outcomes resulting from teamwork include motivation, knowledge retention, deep learning, critical thinking, and professional competency development. Effective teams typically work toward a common goal. When teams know what that goal is, they can collaborate and share their skills to achieve it. Instructors can assist in this process by making assignment goals clear through the use of rubrics that outline assignment expectations and by providing feedback to help students achieve the goals. This study examined the use of teamwork and rubrics in three different undergraduate courses in a school of business in an open admission regional public university to determine if rubrics improved the effectiveness of student teams. Findings indicate that in the course sections where rubrics were not used, students perceived greater effectiveness in three of the eight areas examined—understanding roles, dividing the work, and contributing equally, suggesting that rubrics may not have the impact expected.