Miracle-dz/UniFAR-FTUs huggingface dataset:
A brief assessment of eye blink drowsiness immediately prior to or following driving detects drowsiness related driving impairment

Drowsy driving is a major cause of fatal and serious injury motor vehicle accidents. The inability objectively to assess drowsiness has hindered the assessment of fitness to drive and the development of drowsy driving regulations. This study evaluated whether spontaneous eye blink parameters measured briefly pre‐ and post‐drive could be used to detect drowsy driving impairment. Twelve healthy participants (6 female) drove an instrumented vehicle for 2 h on a closed‐loop track during a rested (8–10 h awake) and an extended wake condition (32–34 h awake). Pre‐ and post‐drive, the participants completed a 5 min eye blink task, a psychomotor vigilance task (PVT), and the Karolinska sleepiness scale (KSS). Whole drive impairment was defined as >3.5 lane departures per hour. Severe end of drive impairment was defined as ≥2 lane departures in the last 15 min. The pre‐drive % of time with eyes closed best predicted the whole drive impairment (area under the curve [AUC] 0.87). KSS had similar prediction ability (AUC 0.85), while PVT reaction time (AUC 0.72) was less accurate. The composite eye blink parameter, the Johns drowsiness scale was the best retrospective detector of severe end of drive impairment (AUC 0.99). The PVT reaction time (AUC 0.92) and the KSS (AUC 0.93) were less accurate. Eye blink parameters detected drowsy driving impairment with an accuracy that was similar to, or marginally better than, PVT and KSS. As eye blink measures are simple to measure, are objective and have high accuracy, they present an ideal option for the assessment of fitness for duty and roadside drowsiness.
The Effect of North Pacific Sea Surface Temperature Anomalies on the January Climate of a General Circulation Model

Abstract Four perpetual January integrations of an atmospheric general circulation model have been performed, in each of which a different sea surface temperature (SST) anomaly was specified in the North Pacific. The observed SST anomaly for the 1976/77 winter was chosen as the basic anomaly, and 1200-day runs were carded out in which this anomaly was multiplied by ±1 and ±2. A fifth run was performed which combined the basic midlatitude SST anomaly from 1976/77 with a tropical Pacific SST anomaly representative of the mature phase of a warm El Nino/Southern Oscillation (ENSO) episode. An ensemble of eight, independent 90-day averaged realizations was extracted from each simulation. Maps of ensemble-mean differences from the model climatology are presented in this paper, together with estimates of the statistical significance of some of the features which appear on these maps. The model response to the basic SST anomaly and to twice the basic SST anomaly is a midiatitude teleconnection pattern, the Pacifi.
An Improved MPC With Reduced CMV and Current Distortion for PMSM Drives Under Variable DC-Bus Voltage Condition in Electric Vehicles

The conventional reduced-common-mode-voltage model predictive control (RCMV-MPC) faces the challenges of low control accuracy and high switching frequency at low speeds. To reduce CMV, improve steady-state performance and lower switching frequency, an improved MPC is proposed for permanent magnet synchronous motor (PMSM) drives with variable dc-bus voltage in electric vehicles (EVs). First, the virtual vectors with low CMV and switching frequency are defined, the optimal virtual vector and its duty cycle are determined. Then, the limitation of designed virtual vectors with fixed dc-bus voltage is illustrated. Furthermore, based on the analysis of the effect of dc-bus voltage on current distortion, the optimal reference dc-bus voltage is adopted to minimize the current distortion. At last, the dc-bus voltage is adjusted to track the reference value by dc–dc converter. An experimental comparison of the conventional methods and the proposed scheme is carried out. The results have verified that the proposed scheme can reduce CMV, current harmonics and switching frequency, especially in low-speed regions. As dc–dc converter has become more popular in motor drives of EVs, the proposed scheme could have a promising application perspective.
Coloring H-free hypergraphs

Fix r ≥ 2 and a collection of r-uniform hypergraphs $\cal{H}$. What is the minimum number of edges in an $\cal{H}$-free r-uniform hypergraph with chromatic number greater than k? We investigate this question for various $\cal{H}$. Our results include the following: An (r,l)-system is an r-uniform hypergraph with every two edges sharing at most l vertices. For k sufficiently large, there is an (r,l)-system with chromatic number greater than k and number of edges at most c(kr-1 log k)l-(l-1), where $$c=2\left( {100(r)^{2}_{l} \over {l! }}\right)^{1/(l-1)} \left( {10(r-1) \over {l-1}}\right)^{l/(l-1)}. $$This improves on the previous best bounds of Kostochka et al. (Random Structures Algorithms 19 (2001), 87–98). The upper bound is sharp apart from the constant c as shown in (Random Structures Algorithms 19 (2001) 87–98). The minimum number of edges in an r-uniform hypergraph with independent neighborhoods and chromatic number greater than k is of order kr+1-(r-1) log O(1)k as k → ∞. This generalizes (aside from logarithmic factors) a result of Gimbel and Thomassen (Discrete Mathematics 219 (2000), 275–277) for triangle-free graphs. Let T be an r-uniform hypertree of t edges. Then every T-free r-uniform hypergraph has chromatic number at most 2(r - 1)(t - 1) + 1. This generalizes the well-known fact that every T-free graph has chromatic number at most t. Several open problems and conjectures are also posed. © 2009 Wiley Periodicals, Inc. Random Struct. Alg. , 2010
Investigation of diverse biosynthetic secondary metabolites gene clusters using genome mining of indigenous Streptomyces strains isolated from saline soils in Iran

Background and Objectives: Bioactive secondary metabolites are the products of microbial communities adapting to environmental challenges, which have yet remained anonymous. As a result of demands in the pharmaceutical, agricultural, and food industries, microbial metabolites should be investigated. The most substantial sources of secondary metabolites are Streptomyces strains and are potential candidates for bioactive compound production. So, we used genome mining and bioinformatics to predict the isolates secondary metabolites, biosynthesis, and potential pharmaceuticals. Materials and Methods: This is a bioinformatics part of our previous experimental research. Here, we aimed to inspect the underlying secondary metabolite properties of 20 phylogenetically diverse Streptomyces species of saline soil by a rationalized computational workflow by several software tools. We examined the Metabolites’ cytotoxicity and antibacterial effects using the MTT assay and plate count technique, respectively. Results: Among Streptomyces species, three were selected for genome mining and predicted novel secondary metabolites and potential drug abilities. All 11 metabolites were cytotoxic to A549, but ectoine (p≤0.5) and geosmin (p≤0.001) significantly operated as an anti-cancer drug. Metabolites of oxytetracycline and phosphinothricin (p≤0.001), 4Z-annimycin and geosmin (p≤0.01), and ectoine (p≤0.5) revealed significant antibacterial activity. Conclusion: Of all the 11 compounds investigated, annimycin, geosmin, phosphinothricin, and ectoine had antimicrobial properties, but geosmin also showed very significant anti-cancer properties.
Stress Hyperglycemia Drives the Risk of Hospitalization for Chest Pain in Patients With Ischemia and Nonobstructive Coronary Arteries (INOCA).

OBJECTIVE Ischemia with nonobstructive coronary arteries (INOCA) is a prevailing finding in patients with angina. However, the main factors underlying the risk of being rehospitalized for chest pain in patients with INOCA remain mostly unknown. RESEARCH DESIGN AND METHODS We evaluated INOCA patients referred to the "Casa di Cura Montevergine" in Mercogliano (Avellino), Italy, from January 2016 to January 2021 for percutaneous coronary intervention (PCI). In these subjects, we assessed the impact of the stress hyperglycemia ratio (SHR), defined as the ratio of mmol/L blood glucose and % HbA1c, on the risk of rehospitalization for chest pain. RESULTS A total of 2,874 patients with INOCA successfully completed the study. At the 1-year follow-up, the risk of rehospitalization for chest pain was significantly higher (P < 0.001) in INOCA patients with SHR >1 compared to patients with SHR ≤1. These findings were confirmed by multivariable analyses (adjusting for potential confounders, including age, BMI, blood pressure, heart rate, chronic kidney disease, and cholesterol), propensity score matching, and inverse probability of treatment weighting. CONCLUSIONS Our data indicate, to our knowledge for the first time, that SHR on hospital admission significantly and independently increases the risk of rehospitalization for chest pain in INOCA patients.
Harvested Power Fairness-Based Multi-Carrier NOMA IoT Networks With SWIPT

The integration of simultaneous wireless information and power transfer (SWIPT) in multi-carrier non-orthogonal multiple access (NOMA) systems has been recently investigated as a potential paradigm to improve the lifespan of energy-constrained Internet-of-Things networks. In this letter, we develop a fairness-aware design for a multi-carrier NOMA SWIPT-based system that attempts to maximize the minimum harvested power subject to quality-of-service constraints. With this design, each user’s power allocation, and the power splitting ratio are jointly computed by solving the corresponding optimization problem. To deal with the non-convexity nature of the formulated max-min optimization problem, an iterative mechanism with a second-order cone method is proposed. Simulation results indicate that our design maintains a better user fairness with respect to the harvested power.
On the relative merits of correlated and importance sampling for Monte Carlo integration

Given a totally finite measure space (S, S, μ) and two μ-integrable, non-negative functions f(x) and φ(x) defined in S, such that when then we define correlated sampling as the technique of estimating by sampling an estimator function where ξ is uniformly distributed in S with respect to μ (i.e. for any T ∈ S, p(T) = μ(T)/μ(S) is the probability that ξ lies in T): and importance sampling as estimating L by sampling the estimator function where η is distributed in S with probability density φ(x)/Φ Then, clearly, It follows that υ(ξ) and ν(η) are both unbiased estimators of L, and that their variances can both be made to approach zero arbitrarily closely by making φ(x) a sufficiently close approximation to f(x).
Estimated Flatness-Based Active Disturbance Rejection Control for Load Frequency Control of Power Systems

Abstract An estimated flatness-based active disturbance rejection control (EF-ADRC) is proposed for the load frequency control (LFC) of power systems in this paper. Different from the traditional ADRC design, the selections of the order and the gain of the flatness-based ADRC controller are based on the flatness output, which is a linear combination of the system states, rather than the nominal integral cascade model. In addition, an extra extended state observer (ESO) is adopted to estimate the system states and the unknown external disturbance. The former is used to replace the actual system states in the flat output, and the latter is used in trajectory planning of the estimated flat output to achieve the unbiased tracking. The proposed method is applied to single-area systems with reheat turbine and hydro turbine, as well as a four-area system, and the simulation results show that the proposed method can achieve satisfactory performance.
Nano-Dimensional Carbon Nanosphere Supported Non-Precious Metal Oxide Composite: A Cathode Material for Sea Water Reduction

Generation of hydrogen fuel at cathode during the electrolysis of seawater can be economically beneficial considering the vast availability of the electrolyte although it faces sluggishness caused by the anode reactions. In this regard a carbon nanosphere-protected CuO/Co3O4 (CCuU) composite was synthesized through heat treatment and was used as the cathode material for electrocatalytic seawater splitting. CCuU showed a significantly low overpotential of 73 mV@10 mA cm−2, Tafel slope of 58 mV dec−1 and relatively constant activity and morphology over a long time electrocatalytic study. A synergy within metal oxide centers was observed that boosted the proton-electron transfer at the active site. Moreover, the presence of carbon support increased the electroactive surface area and stability of the composite. The activity of the CCuU was studied for HER in KOH and alkaline NaCl solution to understand the activity. This work will pave the way for designing mesoporous non-precious electrocatalysts towards seawater electrocatalysis.
Influence of each Zernike aberration on the propagation of laser beams through atmospheric turbulence

We study the influence of each Zernike mode on the propagation of a laser beam through the atmosphere by two different numerical methods. In the first method, an idealized adaptive optics system is modeled to subtract a certain number of Zernike modes from the beam. The effect of each aberration is quantified using the Strehl ratio of the longterm exposure in target/receiver plane. In the second method, the strength of each Zernike mode is varied using a numerical space-filling design during the generation of the phase screens. The resulting central intensity for each point of the design is then studied by a linear discriminant analysis, which yields to the importance of each Zernike mode. The results of the two methods are consistent. They indicate that, for a focused Gaussian beam and for certain geometries and turbulence strengths, the hypothesis of diminishing gains with correction of each new mode is not true. For such cases, we observe jumps in the calculated criteria, which indicate an increased importance of some particular modes, especially coma. The implications of these results for the design of adaptive optics systems are discussed.
Prognostic Value of Left Ventricular Global Longitudinal Strain in Patients With Congenital Heart Disease

Background: Left ventricular global longitudinal strain (LVGLS) has been shown to improve risk stratification in patients with LV systolic dysfunction and subsequent recovery of LV ejection fraction (LVEF) in the acquired heart disease population. The purpose of this study was to assess the relationship between LVGLS and cardiovascular events (heart failure hospitalization, sustained ventricular tachycardia/appropriate shock, heart transplant, or cardiovascular death) and deterioration in LVEF (absolute decrease in LVEF ≥10% to LVEF <50%) in adults with congenital heart disease. Methods: Retrospective cohort study of congenital heart disease patients with previous diagnosis of LV systolic dysfunction (LVEF <50%) and subsequent recovery of LVEF (absolute increase in LVEF of ≥10% to LVEF ≥50%) on subsequent echocardiogram (index echocardiogram). Based on the index echocardiogram, patients were divided into normal LVGLS (absolute LVGLS >18%) versus abnormal LVGLS (absolute LVGLS ≤18%) groups. Results: Of 193 patients with recovered LVEF, 86 (45%) had normalization of LVGLS at index echocardiogram. A higher absolute LVGLS and use of renin angiotensin aldosterone system antagonist was associated with a lower risk of cardiovascular events and subsequent deterioration in LVEF, while hypertension was associated with higher risk of cardiovascular events and deterioration in LVEF. Conclusions: These results suggest that patients with congenital heart disease with recovered LVEF remained at risk for adverse outcomes, and LVGLS can be used to identify patients at risk for adverse outcomes. Medical therapy for heart failure and treatment of hypertension may reduce the risk of adverse outcome, but these findings require empirical validation, hence the need for a clinical trial.
Holographic Recording on Azo-benzene Functionalized Polymer Film

Surface relief holograms are fabricated by irradiation of laser intensity pattern on the azo-benzene functionalized polymer films. The diffraction efficiency and the surface relief depth depend on the writing energy and the polarization of the laser beam. This structure is very stable at temperatures below the glass transition temperature Tg. The relief depth increases approximately ten times with the electric field by corona discharge at the temperature near Tg even if there is no recording laser light. On the other hand, the surface relief disappears keeping the film temperature near Tg, neither recording laser beam nor external electric field. Using this material as a holographic memory, we demonstrate some memory modes, such as write-once, erase, rewritable, overwrite and data holding, under the combination of recording laser beam, external electric field and film temperature.
Properties of Predictors in Misspecified Autoregressive Time Series Models

Abstract This article investigates major effects of misspecification in stationary linear time series models when we fit a pth-order autoregressive model. The true model can be an autoregressive moving average model. We derive the formulas of bias and mean squared error (MSE) of the least squares estimator and the hth period ahead prediction MSE in the time domain. Contrary to previous studies, the process in estimation is not necessarily independent of the process in prediction, and the distribution of process is not necessarily Gaussian. We examine the effects of this dependence and nonnormality on prediction in misspecified models.
Appealing to the health-conscious: low glycaemic food purchase behaviour

Frequent consumption of high glycaemic food may increase the risk of chronic diseases such as diabetes, high blood pressure, high cholesterol, heart disease and more. Low glycaemic food has the benefit of controlling ideal weight, lowering total cholesterol, better blood glucose control and more. Consumers tend to consume low glycaemic food due to various reasons, such as health issues, environmental concerns, peer pressure and others. In this study, various factors such as food attributes, environmental concerns, price fairness, knowledge of low glycaemic food and health concern are investigated on their impact on the purchasing behaviour of low glycaemic food. Quantitative research with the use of a survey questionnaire was adopted. The convenience sampling method was used to ensure the largest possible sample with the least amount of administration and was distributed via online Google form. A final 313 valid responses via online survey were analysed. Based on the findings, health concerns, environmental concerns and knowledge of glycaemic food had a positive relationship to the purchasing behaviour of low glycaemic food. The findings can be used by food manufacturers, food technologists and retailers to increase health awareness to bring positive benefits to the general well-being of consumers.
Proactive malware detection

Small-to-medium sized businesses lack resources to deploy and manage high-end advanced solutions to deter sophisticated threats from well-funded adversaries, but evidence shows that these types of businesses are becoming key targets. As malicious code and network attacks become more sophisticated, classic signature-based virus and malware detection methods are less effective. To augment the current malware methods of detection, we developed a proactive approach to detect emerging malware threats using open source tools and intelligence to discover patterns and behaviors of malicious attacks and adversaries. Technical and analytical skills are combined to track adversarial behavior, methods and techniques. We established a controlled (separated domain) network to identify, monitor, and track malware behavior to increase understanding of the methods and techniques used by cyber adversaries. We created a suite of tools that observe the network and system performance looking for anomalies that may be caused by malware. The toolset collects information from open-source tools and provides meaningful indicators that the system was under or has been attacked. When malware is discovered, we analyzed and reverse engineered it to determine how it could be detected and prevented. Results have shown that with minimum resources, cost effective capabilities can be developed to detect abnormal behavior that may indicate malicious software.
Mixture models in survival analysis: Are they worth the risk?

There has been a recurring interest in models for survival data which hypothesize subpopulations of individuals highly susceptible to some type of adverse event. Other individuals are assumed to be at much less risk. Most commonly, in clinical trials, these models attempt to estimate the fraction of patients cured of disease. The use of such models is examined, and the likelihood function is advocated as an informative inference tool. On sait l'interět soutenu qu'ont suscite les modeles de donnees de survie qui supposent l'existence de sous-populations d'individus hautement susceptibles a un certain type de risque. Ces modeles supposent que les autres individus sont exposes a un risque beaucoup moins eleve. La plupart du temps, les modeles de ce genre sont employes dans les tests cliniques pour estimer la proportion de patients qui se retabliront d'une maladie. Dans cet article, nous portons un regard critique sur l'emploi de tels modeles et nous prǒnons l'utilisation de la fonction de vraisemblance comme outil d'inference.
Potential Role of Peroxisome Proliferator-activated Receptor Gamma Coactivator-1 Alpha (PGC-1α) Gene Polymorphism in Patients with Type 2 Diabetes Mellitus

Background: Peroxisome Proliferator-activated Receptor Gamma Coactivator-1 Alpha ( PGC-1α ) is a cellular modulator of oxidative and lipid metabolism. It has a vital role in the regulation of mitochondrial activity. Patients with type 2 diabetes mellitus (T2DM) have mitochondrial abnormality and reduced mitochondrial numbers within the cells of skeletal muscles. Objective: To evaluate the correlation between PGC-1α gene polymorphism and T2DM in Egyptian patients attending Zagazig University Hospitals. Patients and Methods: This was a case-control study including 136 participants of both sexes recruited from the Zagazig University Hospitals. The participants were divided into two equal groups: control group with normal individuals and T2DM group with 68 participants in each group. Results: The incidence of A allele was significantly higher in T2DM group. Also, there were statistically significant elevations in waist hip ratio (WHR) and fasting blood sugar (FBS) among carriers of GA and AA genotypes. However, there was no significant correlation between gene polymorphism and lipid profile in T2DM group. After applying multivariate analysis, A allele carriers and increased values of WHR, FBS, HOMA-IR and low-density lipoprotein-cholesterol (LDL-c) were detected in T2DM. Conclusion: We concluded that A allele of PGC-1α polymorphism was a possible predictor of T2DM occurrence in Egyptian patients. Additionally, WHR and FBS were significantly higher among carriers of GA and AA genotypes