Miracle-dz/UniFAR-FTUs huggingface dataset:
Observability and criticality analysis in state estimation using integer‐preserving Gaussian elimination

SUMMARY This paper presents an efficient numerical method for observability and criticality analysis in power system state estimation based on integer Gaussian elimination of integer coefficient matrices. Because all computations performed are exact, no round-off error, numerical instability, or zero identification problems occur. The observable islands are identified in a noniterative manner by performing back substitutions on the integer triangular factors of the gain matrix. The additional measurements for placement are provided by a direct method, using the integer triangular factors of the Gram matrix associated with a reduced size Jacobian matrix. The critical measurements are identified by checking for diagonal entries of the integer residual sensitivity matrix. Implementation of the proposed method needs little additional effort, because it requires minor modifications of sparse triangular factorization and forward/backward substitution algorithms common to state estimators. The IEEE 14-bus system is used to illustrate the steps of the proposed algorithms. Test results for a 10 343-bus system are provided to demonstrate the features of the proposed algorithms. Copyright © 2012 John Wiley & Sons, Ltd.
Physical parameters of 62 eclipsing binary stars using the ASAS-3 data$-$I

We present a detailed light curve analysis of publicly available V band observations of 62 binary stars, mostly contact binaries, obtained by the All Sky Automated Survey (ASAS)-3 project between 2000 and 2009. Eclipsing binaries are important astronomical targets for determining the physical parameters of component stars from the geometry. They provide an independent direct method of measuring the radii of stars. We improved the ASAS determined periods, ephemeris and obtained the Fourier parameters from the phased light curves of these 62 stars. These Fourier parameters were used for preliminary classification of the stars in our sample. The phased light curves were then analysed with the aid of the Wilson-Devinney light curve modelling technique in order to obtain various geometrical and physical parameters of these binaries. The spectroscopic mass ratios as determined from the the radial velocity measurements available in the literature were used as one of the inputs to the light curve modelling. Thus reliable estimations of parameters of these binaries were obtained with combined photometric and spectroscopic data and error estimates were made using the heuristic scan method.
An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease

Healthcare occupies a central role in sustainable societies and has an undeniable impact on the well-being of individuals. However, over the years, various diseases have adversely affected the growth and sustainability of these societies. Among them, heart disease is escalating rapidly in both economically settled and undeveloped nations and leads to fatalities around the globe. To reduce the death ratio caused by this disease, there is a need for a framework to continuously monitor a patient's heart status, essentially doing early detection and prediction of heart disease. This paper proposes a scalable Machine Learning (ML) and Internet of Things-(IoT-) based three-layer architecture to store and process a large amount of clinical data continuously, which is needed for the early detection and monitoring of heart disease. Layer 1 of the proposed framework is used to collect data from IoT wearable/implanted smart sensor nodes, which includes various physiological measures that have significant impact on the deterioration of heart status. Layer 2 stores and processes the patient data on a local web server using various ML classification algorithms. Finally, Layer 3 is used to store the critical data of patients on the cloud. The doctor and other caregivers can access the patient health conditions via an android application, provide services to the patient, and inhibit him/her from further damage. Various performance evaluation measures such as accuracy, sensitivity, specificity, F1-measure, MCC-score, and ROC curve are used to check the efficiency of our proposed IoT-based heart disease prediction framework. It is anticipated that this system will assist the healthcare sector and the doctors in diagnosing heart patients in the initial phases.
Protocol Solutions for IEEE 802.11bd by Enhancing IEEE 802.11ad to Address Common Technical Challenges Associated With mmWave-Based V2X

A multi-gigabit (WiGig) system is designed based on IEEE 802.11ad standards by exploiting millimeter-wave (mmWave) bands to achieve extremely high data rates. Recently, IEEE 802.11bd and 3GPP NR-V2X technologies adopted new specifications for the next generation vehicle-to-everything (V2X) network with the ability to support mmWave bands. However, mmWave bands could be the solution for the high throughput and low latency. Still, the instability of blockages is a substantial challenge in mmWave bands, rendering mmWave ineffective in vehicular networks. Typically, technologies capable of operating at mmWave bands, such as IEEE 802.11ad, IEEE 802.11bd, NR-V2X, etc., share the same technical challenges due to the unique characteristics of the mmWave band. As a result, to achieve the aspirations of next generation connected mmWave V2X vehicles. This paper proposes novel classic, cooperative, and extension protocols for IEEE 802.11bd by enhancing IEEE 802.11ad. The proposed solution aims to mitigate some of the most common technical challenges associated with using mmWave bands in V2X networks, such as beam training overhead, link blockage, beam misalignment, limited coverage range, and delay. Simulation results demonstrate that the proposed approach effectively reduces the beam training overhead, achieves accurate beam alignment, increases the probability of line-of-sight (LOS), overcomes link blockage/ misalignment, extends the coverage range, and achieves low latency. Further, the proposed enhancement achieves significantly higher performance against the conventional solution and shows more link stability despite continuous changes in the density of the vehicles.
Spectroscopic Analysis of Subluminous B Stars in Binaries - Four Candidate Systems with Neutron Star/Black Hole Companions Discovered

The masses of compact objects like white dwarfs, neutron stars and black holes are fundamental to astrophysics, but very difficult to measure. We present the results of an analysis of subluminous B (sdB) stars in close binary systems with unseen compact companions to derive their masses and clarify their nature. Radial velocity curves were obtained from time resolved spectroscopy. The atmospheric parameters were determined in a quantitative spectral analysis. With high resolution spectra we were able to measure the projected rotational velocity of the stars with high accuracy. The assumption of orbital synchronization made it possible to constrain inclination angle and companion mass of the binaries. Five invisible companions have masses that are compatible with white dwarfs or late type main sequence stars. But four sdBs have very massive companions like heavy white dwarfs, neutron stars or even black holes. Such a high fraction of massive compact companions can not be explained with current models of binary evolution.
A Novel Computer-Based Assessment Tool for Evaluating Early Literacy Skills in Italian Preschoolers

ABSTRACT The present contribution aims at presenting an assessment tool (i.e., the TALK-assessment) built to evaluate the language development and school readiness of Italian preschoolers before they enter primary school, and its predictive validity for the children’s reading and writing skills at the end of the first year of primary school. The early literacy competences of 98 preschoolers were assessed and the statistical proprieties (item difficulty level and Discrimination Index, and the factorial structure using Confirmatory Factor Analysis) of each subtest of the assessment were presented (Study 1). Results showed that the subtests of the tool have good psychometric properties, with the only exception of the morpho-syntactic comprehension task, and are adequate for use with preschoolers in the school context. Study 2 investigated the early literacy skills of a group of 62 preschoolers and their reading and writing abilities at the end of primary school 1st grade. The scores obtained in the phonological awareness task of the final version of the assessment in preschool significantly predicted children’s reading scores 12 months later, at primary school. The scores obtained in the lexical comprehension and morpho-syntactic production (i.e., sentence repetition) tasks of the final version of the assessment in preschool significantly predicted children’s writing scores 12 months later, at primary school. The assessment has specific characteristics that make it a valuable candidate for adoption in educational settings, both to identify fragile areas in time to modify the children’s developmental paths to literacy and to prevent future language and literacy difficulties at primary school.
Path-Planning Strategy for Lane Changing Based on Adaptive-Grid Risk-Fields of Autonomous Vehicles

The quantification and effective representation of safety risks for scenarios in structured road traffic environments of autonomous driving are currently being investigated in an active way. Based on artificial potential fields, a risk-field model for the traffic environment that considers the motion state of an obstacle vehicle is established, and an adaptive-grid risk-field method is proposed for autonomous vehicles. In this method, the traffic environment is meshed initially, and adaptive-grid division is performed using a quadtree grid-dividing strategy for root grids where the grid risk values are within the division interval, which allows for a more accurate quantification of traffic environment risk values. Adding adaptive-grid risk-field parameters to the cost function of the path-planning algorithm improves the accuracy of path safety risk assessment and completes the evaluation and selection of the optimal lane-change path. Simulation results show that the adaptive-grid risk-field established in this paper can effectively express the safety risks of the traffic environment, and the path-planning algorithm incorporating the adaptive-grid risk-field can obtain better paths for lane change compared with the traditional path-planning algorithm, while ensuring the safety of lane change.
Lead-Free Copper-Based Perovskite Nanonets for Deep Ultraviolet Photodetectors with High Stability and Better Performance

Considering practical application and commercialization, the research of non-toxic and stable halide perovskite and its application in the field of photoelectric detection have received great attention. However, there are relatively few studies on deep ultraviolet photodetectors, and the perovskite films prepared by traditional spin-coating method have disadvantages such as uneven grain size and irregular agglomeration, which limit their device performance. Herein, uniform and ordered Cs3Cu2I5 nanonet arrays are fabricated based on monolayer colloidal crystal (MCC) templates prepared with 1 μm polystyrene (PS) spheres, which enhance light-harvesting ability. Furthermore, the performance of the lateral photodetector (PD) is significantly enhanced when using Cs3Cu2I5 nanonet compared to the pure Cs3Cu2I5 film. Under deep ultraviolet light, the Cs3Cu2I5 nanonet PD exhibits a high light responsivity of 1.66 AW−1 and a high detection up to 2.48 × 1012 Jones. Meanwhile, the unencapsulated PD has almost no response to light above 330 nm and shows remarkable stability. The above results prove that Cs3Cu2I5 nanonet can be a great potential light-absorbing layer for solar-blind deep ultraviolet PD, which can be used as light absorption layer of UV solar cell.
Statistical Methods in Environmental Health

Common sense, statistical reasoning and hypothesis testing. Basic statistics. Tests of hypotheses. The normal distribution, probability and hypothesis testing. Tests involving means. Estimation and confidence limits. Tests involving percentages. Correlation and regression. Non-parametric statistics. Estimation of sample size. Vital statistics. Sources of statistical data. Solutions to exercises. Index.
Layout Simulation of Prefabricated Building Construction Based on the Markov Model

In order to meet the needs of the simulation function of prefabricated building construction layout, the author proposes a technology based on the Markov model. The main content of this technology is based on Markov model technology and takes Jinzhong Zhaimen as an example to conduct spatial scale research, according to the sensitivity of spatial scale, and finally through analysis, a systematic research method is constructed. Experimental results show that in the cell size range used, 80 m and 400 m can be regarded as the cell size threshold and limit value affecting the simulation accuracy, and when the cell size is below 80 m, the simulation result coefficient values are all more accurate. Conclusion. A technical study demonstrates that the Markov model can meet the needs of prefabricated building construction layout simulation functions.
Modélisation micromécanique et identification inverse de l’endommagement par approches cohésives

Un modele micromecanique est propose pour une collection de zones cohesives inserees entre toutes les mailles d'une discretisation de type elements finis cohesifs-volumiques. Le principe de l'approche consiste a introduire un composite equivalent 'matrice-inclusions' comme une representation de la discretisation cohesive-volumique. Le modele obtenu a l'aide de techniques d'homogeneisation (schema de Hashin Shtrikman et approche de P. Ponte Castaneda) permet de decrire le comportement macroscopique elastique, fragile et ductile.Il est valable quel que soit le taux de triaxialite applique et la forme de la loi cohesive retenue, et permet de relier d'une facon explicite les proprietes macroscopiques du materiau aux differents parametres cohesifs ainsi qu'a la densite de maillage.Un premier resultat est l'etablissement d'un critere pratique permettant de definir les raideurs cohesives au regard de la souplesse additionnelle inherente a l'utilisation des modeles de zones cohesives intrinseques. L'extension du modele au cas de la rupture fragile et ductile, permet d'obtenir d'autres criteres pratiques pour calibrer les autres parametres cohesifs (contrainte cohesive maximale, ouverture critique, energie de fissuration, .). L'utilisation couplee des criteres obtenus permet une calibration inverse des parametres de la loi cohesive en fonction des proprietes macroscopiques du materiau et de la taille de maillage. De fait il est possible de predire un comportement homogene global independamment de la taille du maillage.
Interaction effects of sex on the sleep loss and social jetlag-related negative mood in Japanese children and adolescents: a cross-sectional study

Abstract Study Objectives Sleep problems, such as accumulated sleep loss and social jetlag (SJL), which is characterized by a discrepancy in a person’s sleep pattern between the weekday and the weekend, are associated with physical and mental health problems, and academic performance in young ages. However, sex differences in these associations are not fully understood. The purpose of this study was to investigate the effect of sex on sleep-related factors, mental health (negative mood), and academic performance in Japanese children and adolescents. Methods A cross-sectional online survey was conducted with 9270 students (boys: N = 4635, girls: N = 4635) ranging from the fourth grade of elementary school to the third grade of high school, which typically includes ages 9–18 years in Japan. Participants completed the Munich ChronoType Questionnaire, the Athens Insomnia Scale, self-reported academic performance, and negative mood-related questions. Results School grade-related changes in sleep behavior (e.g. delayed bedtime, shortened sleep duration, and increased SJL) were detected. Girls had greater sleep loss on weekdays and SJL on weekends than boys. Multiple regression analysis revealed that sleep loss and SJL were more associated with negative mood and higher insomnia scores in girls than in boys, but not with academic performance. Conclusions Sleep loss and SJL in Japanese girls had a higher correlation to their negative mood and tendency to insomnia than in boys. These results suggest the importance of sex-dependent sleep maintenance for children and adolescents.
Intelligent Detection of Hazardous Goods Vehicles and Determination of Risk Grade Based on Deep Learning

Currently, deep learning has been widely applied in the field of object detection, and some relevant scholars have applied it to vehicle detection. In this paper, the deep learning EfficientDet model is analyzed, and the advantages of the model in the detection of hazardous good vehicles are determined. The adaptive training model is built based on the optimization of the training process, and the training model is used to detect hazardous goods vehicles. The detection results are compared with Cascade R-CNN and CenterNet, and the results show that the proposed method is superior to the other two methods in two aspects of computational complexity and detection accuracy. Simultaneously, the proposed method is suitable for the detection of hazardous goods vehicles in different scenarios. We make statistics on the number of detected hazardous goods vehicles at different times and places. The risk grade of different locations is determined according to the statistical results. Finally, the case study shows that the proposed method can be used to detect hazardous goods vehicles and determine the risk level of different places.
Internet of things based real-time coronavirus 2019 disease patient health monitoring system

The coronavirus disease (COVID-19) outbreak has led to many infected worldwide and has become a global crisis. COVID-19 manifests in the form of shortness of breath, coughing and fever. More people are getting infected and healthcare systems worldwide are overwhelmed as healthcare workers become exhausted and infected. Thus, remote monitoring for COVID-19 patients is required. An internet of things (IoT) based real-time health monitoring system for COVID-19 patients was proposed. It features monitoring of five physiological parameters, namely electrocardiogram (ECG), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature. These vitals are processed by the main controller and transmitted to the cloud for storage. Healthcare professionals can read real-time patient vitals on the web-based dashboard which is equipped with an alert service. The proposed system was able to transmit and display all parameters in real-time accurately without any packet loss or transmission errors. The accuracy of body temperature readings, RR, SpO2 and HR, is up to 99.7%, 100%, 97.97% and 98.34%, respectively. Alerts were successfully sent when the parameters reached unsafe levels. With the proposed system, healthcare professionals can remotely monitor COVID-19 patients with greater ease, lessen their exposure to the pathogen, and improve patient monitoring.
Bacteriophages pass through candle‐shaped porous ceramic filters: Application for the collection of viruses in soil water

Despite the ubiquity of viruses in soils, their diversity in soil water has not been explored, mainly due to the difficulty of collecting them. In hydrology, soil water is usually collected using porous candles. This study proposes using these porous candles as a new tool for sampling viruses in soil water to analyze their passage through the ceramic part of the candles. The recovery of the viruses was determined after filtration under laboratory conditions using three model bacteriophages (MS2, ΦX174, and Φ6) and Escherichia coli, at neutral and acidic pH. Then, a field experiment was carried out where soil water filtration and viral identification by metagenomic shotgun were performed. At neutral pH, all bacteriophages tested successfully passed through the porous candles during the filtration process, with reductions of 0.02 log, 0.16 log, and 0.55 log for MS2 ΦX174 and Φ6, respectively. At pH 4.4, the passage of MS2 was not affected while ΦX174 underwent a slight reduction in recovery, probably caused by adsorption onto the filter material. Regarding the application of the porous candles in the field, the results obtained allowed the successful recovery of viruses, exposing porous candles as a new method suitable for the collection of viruses from soil water in the context of the study of viral communities.
Experimental comparative analysis of hybrid energy harvesters exposed to flow-induced vibrations

In this study, hybrid energy harvesting based on electromagnetic induction (EM) and piezoelectric transduction (PZT) is experimentally investigated under different conditions of flow-induced vibrations. The energy harvesting performance of the system is examined when the electromagnetic and piezoelectric mechanisms are used both separately and simultaneously. In this regard, firstly, only electromagnetic induction harvesting structure is attached to a beam, and time-dependent voltage and displacement are experimentally investigated. Then, PZT has adhered to the beam, and voltage outputs are measured in both the PZT and EM circuits. The third scenario is based on removing the electromagnetic harvesting structure and only the piezoelectric energy harvesting performance is studied. The mentioned cases are investigated under different excitation circumstances, that is, distinct bluff-body geometries and flow velocities. While the square bluff-body geometry is connected to the structure, both PZT and EM harvested power are determined by considering different electrical load resistances. It is mainly revealed that the total energy amount is higher in the hybrid configuration. After determining the hybrid structure is the most effective, elements with different splitters geometry are attached to the bluff-body geometry of the harvesting structure. Finally, the vibration enhancement potential of these new types of splitters on the harvesting structure is experimentally investigated. For the solo electromagnetic harvester, the maximum power is obtained at an external load resistance value of 10 kΩ, while for the solo PZT harvester, the maximum power is observed at the resistance value of 330 kΩ. Among the three types of splitter geometries examined, the highest voltage was obtained from type-1 as 14.168 V.
Ba(cid:400)al Slip in La(cid:448)e(cid:400) Pha(cid:400)e(cid:400)(cid:855) (cid:410)he S(cid:455)nchro(cid:400)hear Di(cid:400)loca(cid:410)ion

Two different mechanisms have been reported in previous ab initio studies to describe basal slip in complex intermetallic Laves phases: synchroshear and undulating slip. To date, no clear answer has been given on which is the energetically favourable mechanism and whether either of them could effectively propagate as a dislocation. Using classical atomistic simulations supported by ab initio calculations, the present work removes the ambiguity and shows that the two mechanisms are, in fact, identical. Furthermore, we establish synchroshear as the mechanism for propagating dislocations within the basal plane in Laves phases.