Miracle-dz/UniFAR-FTUs huggingface dataset:
KMSA-Net: A Knowledge-Mining-Based Semantic-Aware Network for Cross-Domain Industrial Process Fault Diagnosis

Process fault diagnosis is of great importance to ensure the safe and stable operation of industrial systems. Many existing deep-learning-based process fault diagnosis methods assume that the samples are sufficient and obey the same distribution; however, it is almost impossible to achieve in practical industrial applications due to changing working conditions and the high cost of acquiring fault samples, which leads to a prominent performance degradation. In essence, those methods do not fully exploit the intrinsic and relevant knowledge under different working conditions. To address the above issue, a knowledge-mining-based semantic-aware network (KMSA-Net) is proposed in this article. First, a self-correlation knowledge mining subnet is proposed, where unshared attention mechanism is designed to extract knowledge inherent in each working condition so that the discriminative features can be captured. Second, a cross-correlation knowledge mining subnet is proposed, where we develop a fault relational knowledge graph so as to explicitly constrain the local consistency between the source domain, target domain, and cross-domain. Third, a semantic-aware knowledge transfer subnet is designed to impose a semantic constraint during knowledge transfer by encouraging the output of KMSA-Net to be consistent and distinguishable. These three subnets are jointly trained and then applied for cross-domain industrial process fault diagnosis. Finally, benchmark simulated experiments and real-world application experiments are conducted, and the experimental results validate the effectiveness and superiority of the proposed method.
Approximations for Brillouin and its reverse function

Purpose The mathematical complexity of the BJ(x) Brillouin function makes it unsuitable for most calculations and its application difficult for computer programming in magnetism. Here, its approximation with the tanh function is proposed to ease the mathematical operations for most cases. The approximation works with good accuracy, acceptable in practical calculations. This approximation has already formed the foundation of the “hyperbolic model” in magnetism for the study of hysteretic phenomena. The reversal of the Brillouin function is an important but difficult mathematical problem for practical purposes. Here, a proposal has been put forward for an easy approximation using an analytical expression. This provides a good workable solution for the BJ(x)−1 function dependent on J, the angular momentum quantum number of the material used. The proposed approximation is applicable within the working range of practical applications. The paper aims to discuss these issues. Design/methodology/approach The multi-variant Brillouin function is closely approximated by the tanh function to ease calculations. Its mathematically unsolved reversed function is approximated by a simple analytical expression with a good working accuracy. Findings The Brillouin function and its reversal can be approximated for practical users mostly for professionals working in Magnetism. Research limitations/implications Most if not all practical problems in Magnetism can be solved within the limitations of the two approximations. Practical implications Both proposed functions can ease the mathematical problems faced by researchers and other users in Magnetism. Social implications Ease the frustration of most users working in the field of Magnetism. Originality/value The application of the tanh function for replacing the Brillouin function led to the creation of the hyperbolic model of hysteresis. To the author's knowledge, the reverse function was mathematically only solved in 2015 with a vastly complicated mathematics, and is hardly suitable for practical calculations in Magnetism. The proposed simple expression can be very useful for theorists and experimental scientists.
Trust model of privacy-concerned, emotionally-aware agents in a cooperative logistics problem

In this paper, we propose a trust model to be used in a hypothetical mixed environment where humans and unmanned vehicles cooperate. We address the inclusion of emotions inside a trust model in a coherent way to investigate the practical approaches to current psychological theories. The most innovative contribution of this work is the elucidation of how privacy issues play a role in the cooperation decisions of the emotional trust model. Both emotions and trust were cognitively modeled and managed with the beliefs, desires and intentions (BDI) paradigm in autonomous agents implemented in GAML (the programming language of the GAMA agent platform), that communicate using the IEEE FIPA standard. The trusting behavior of these emotional agents was tested in a cooperative logistics problem wherein agents have to move objects to destinations and some of the objects and places are associated with privacy issues. Simulations of the logistic problem show how emotions and trust contribute to improving the performance of agents in terms of both time savings and privacy protection.
Investigating the Gamma-Ray Burst – Supernova Connection

We have undertaken a literature search for associations of gamma-ray bursts (GRBs) with supernovae (SNe), and we have constructed a much larger table of cases than has been published until now. The table contains a suite of physical properties for the GRBs (and the SNe when available), which will allow us and others to infer valuable knowledge about the GRBs and their physical mechanisms. From this basic table, we have undertaken a very preliminary examination, looking at the intrinsic GRB properties at hand, i.e. duration, isotropic energy output, peak spectrum energy, fluence, spectral index, redshift etc., and we present initial results. Future analyses will be performed to try to determine whether GRBs with no associated SNe constitute a subclass or category of bursts with particular characterizing properties.
Search for ttbar resonances using the ATLAS detector

Le Modele Standard (MS) de la physique des particules decrit les particules elementaires et leurs interactions a l'exception de la gravite. Jusqu'a present, la plupart des resultats experimentaux sont en accord avec les predictions du MS. Cependant, il existe encore des questions de nature experimentale ou theorique qui restent sans reponse. Les particules massives qui se desintegrent en une paire de quarks top-antitop sont predites par certains des modeles de physique au-dela du Modele Standard, qui tentent de repondre a ces questions.Une recherche de nouvelles resonances tt est presentee dans ce manuscrit, en utilisant l'ensemble de donnees 2015 (debut des Run 2) a partir des collisions proton-proton produites par le Large Hadron Collider (LHC) avec une energie de faisceau de 13 TeV dans le centre de masse et avec une luminosite integree de 3.2 fb-1 recueillie par le detecteur ATLAS. La signature de l'etat final recherche est caracterisee par la presence d'un electron ou d'un muon, d'un certain nombre de jets de hadrons et de l'energie transverse manquante. La masse invariante des systemes tt (mrecott ) est la principale observable sur cette recherche, et est utilisee pour tester la compatibilite des donnees avec l'hypothese MS seule. Pour la region a grand mtt, les quarks top sont produits avec un grande impulsion et leurs produits de desintegration sont collimates. Dans cette region, la sous-structure des jets doit etre utilisee pour identifier les paires tt (scenario « boosted »), tandis que pour de basses valeurs de mtt, les produits de desintegration des quark top sont bien separes (scenario « resolved »). Les resultats preliminaires sur l'analyse « boosted » sont presentes dans ce manuscrit. Dans les spectres de masse analyses, aucune preuve de l'existence de nouvelles particules n'a ete trouvee. Pour une boson Z’TC2 « Topcolor assisted technicolor » avec une largeur relative de 1.2 %, des masses inferieures a 2 TeV sont exclues, l'ameliorant les limites anterieures obtenues lors du Run 1. Des etudes de perspective pour inclure les topologies « resolved » sont egalement discutees, avec en particulier l'estimation du bruit de fond multi-jet en utilisant la « methode de la matrice ». En outre, la methode d'etalonnage des jets in-situ est proposee pour ameliorer la resolution sur mtt. L'impact apres chaque etape de la procedure de mise a l'echelle est presentee en utilisant des simulations a 8 TeV.
Dynamic Threshold SIFT for Image Matching

Despite the good results obtained in various applications, the performance of SIFT declined under conditions of insufficient illumination and blur imaging. The main reason is that SIFT key points are discarded if the DoG response is less than a fixed preset threshold. We proposed a dynamic threshold assign method based on both global and local information. Firstly Initial threshold is obtained according to contrast of GLCM, making it adaptive to insufficient illumination and blur imaging. Secondly, in order to control the number of feature points, the threshold is adjusted once again according to feature points’ distribution. So every feature point is assigned a different threshold adapting to surrounding situation. At last, the mismatch removing algorithm is also been improved by incorporating the global distribution context. Experiment results show that the improved SIFT algorithm is not only well adapted to low light and image blur, but also can adjust the number of feature points and reduce clustering effects.
Characteristics and Functional Properties of Maillard Reaction Products from α-Lactalbumin and Polydextrose

The characteristics and the functions of Maillard reaction products (MRPs) produced by polydextrose (PD), a new type of prebiotic, and α-lactalbumin (α-LA) were valued. PD and α-LA were incubated at 60 °C and 79% relative humidity for up to 72 h to prepare MRPs. The results showed that the absorbance and fluorescence intensity of heated α-LA-PD increased, and the amount of free amino groups reduced as the reaction progressed, which confirmed the formation of different stages of MRPs. Electrophoresis revealed an increase in molecular mass and the degree of covalent cross-linking. The secondary structure of MRPs experienced no significant changes with the measurement of circular dichroism (CD), while the tertiary structure gradually unfolded, exposing hydrophobic groups. Furthermore, a significant increase was detected in the radical-scavenging activity of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the ferric reducing/antioxidant power (FRAP) of MRPs. The findings offer a foundation for understanding the structural and functional features of MRPs in formula milk powder.
A Visual-Inertial Dynamic Object Tracking SLAM Tightly Coupled System

Most existing dynamic simultaneous localization and mapping (SLAM) systems simply remove dynamic objects, resulting in the loss of dynamic object motion information that helps the system itself localize and navigate. Aiming at the above problems, a visual inertial (VI) dynamic object tracking SLAM tightly coupled system is proposed. First, a method for classifying dynamic and static feature points is proposed to solve the problem that dynamic objects cannot be extracted by learning-based or vision-only methods. Second, the system accurately extracts and tracks dynamic rigid-body objects in the scene through a combination of visual information, inertial measurement unit (IMU) data, and associated matching point labels, without modeling the shape or geometry of the dynamic objects. Subsequently, a novel pipeline is proposed to jointly optimize the camera poses, trajectories of dynamic objects, the maps of the environment, and IMU information, improving the self-localization performance of the system. Finally, the performance of the system is tested on indoor and outdoor datasets and real dynamic scenes. Experimental results show that the proposed system achieves improved performance in self-localization and dynamic object tracking compared to other state-of-the-art methods. Especially under adverse conditions of partial occlusion and far-field of view, the system can still track dynamic objects robustly and accurately to optimize self-localization performance.
How to build nomogram for type 2 diabetes using a naïve Bayesian classifier technique

ABSTRACT In this study, we introduced a method for building a Bayesian nomogram and proposed an appropriate nomogram for type 2 diabetes (T2D) using data from 13,474 subjects collected from the 2013–2015 Korean National Health and Nutrition Examination Survey (KNHANES) data. We identified risk factors related to T2D, proposed a visual nomogram for T2D from a naïve Bayesian classifier model, and predicted incidence rates. Additionally, we computed confidence intervals for the influence of risk factors (attributes) and verified the proposed Bayesian nomogram using a receiver operating characteristic curve. Finally, we compared logistic regression and the Bayesian nomogram for T2D. The results of the analysis of the T2D data showed that the most influential factor among all attributes in the Bayesian nomogram was age group, and the highest risk factor for T2D incidence was cardiovascular disease. Dyslipidemia and hypertension also had significant impacts on T2D incidence while the effects of sex, smoking status, and employment status were relatively small compared to those of other variables. Using the proposed Bayesian nomogram, we can easily predict the incidence rate of T2D in an individual, and treatment plans can be established based on this information.
Pyronaridine as a Bromodomain-Containing Protein 4-N-Terminal Bromodomain (BRD4-BD1) Inhibitor: In Silico Database Mining, Molecular Docking, and Molecular Dynamics Simulation

BRD4 (bromodomain-containing protein 4) is an epigenetic reader that realizes histone proteins and promotes the transcription of genes linked to cancer progression and non-cancer diseases such as acute heart failure and severe inflammation. The highly conserved N-terminal bromodomain (BD1) recognizes acylated lysine residues to organize the expression of genes. As such, BD1 is essential for disrupting BRD4 interactions and is a promising target for cancer treatment. To identify new BD1 inhibitors, a SuperDRUG2 database that contains more than 4600 pharmaceutical compounds was screened using in silico techniques. The efficiency of the AutoDock Vina1.1. 2 software to anticipate inhibitor-BRD4-BD1 binding poses was first evaluated based on the co-crystallized R6S ligand in complex with BRD4-BD1. From database screening, the most promising BRD4-BD1 inhibitors were subsequently submitted to molecular dynamics (MD) simulations integrated with an MM-GBSA approach. MM-GBSA computations indicated promising BD1 binding with a benzonaphthyridine derivative, pyronaridine (SD003509), with an energy prediction (ΔGbinding) of −42.7 kcal/mol in comparison with −41.5 kcal/mol for a positive control inhibitor (R6S). Pharmacokinetic properties predicted oral bioavailability for both ligands, while post-dynamic analyses of the BRD4-BD1 binding pocket demonstrated greater stability for pyronaridine. These results confirm that in silico studies can provide insight into novel protein–ligand regulators, specifically that pyronaridine is a potential cancer drug candidate.
A National Case-Crossover Study on the Risk of Kidney Injury Requiring Dialysis after Sepsis

Background: Patients with sepsis-associated acute kidney injury (AKI) are at risk of kidney damage, potentially necessitating acute temporary or chronic dialysis. Our study aims to estimate the odds ratio (OR) of preceding sepsis among patients requiring their first dialysis. Methods: A nationwide population-based case-only study was conducted using claims records from the National Health insurance database of Taiwan. All patients over 20 years of age who underwent their first dialysis between 2004 and 2016 were included in the study. The six months prior to their first dialysis served as a self-control period. Results: The study included 147,201 patients who required acute temporary and 75,031 patients who required chronic dialysis. The odds ratios for patients needing acute temporary dialysis after 1, 2, 3, and 4 weeks of exposure periods were 15.8, 10.7, 9.2, and 8.4, respectively. The ORs for patients requiring chronic dialysis were 7.0, 4.1, 4.2, and 3.7, respectively. Conclusions: Our findings indicate that sepsis was substantially associated with an increased risk of renal failure. The risk was highest during the first week following sepsis for both acute temporary and chronic dialysis cases.
Primitive structural method for high capacity text steganography

High capacity for hiding secret information is typically the main concern in text steganography, as well as robustness and perceptual invisibility in a perfect steganography algorithm. The major issue in text steganography is the difficulty of using a large amount of redundant information to hide secret bits (1 and 0) in perceptible appearance. We propose a Primitive Structural algorithm for Arabic text steganography to encounter this issue. This algorithm hides the secret bits in the primitive structure (i.e. sharp edges, dots, typographical proportion) for the Arabic character. Therefore, this new algorithm presents a high data-embedding capacity since each character has more than one potential place to hide the secret information. The main processes involved are the preparation of the secret message as a binary process, identifying the Primitive Structural for each character in the cover-text process, and finally the bit hiding process. The experiments have shown that the data-embedding capacity percentage is increased up to 4% for our first experiment and for the second experiment the results show the increase in capacity up to 21% compared to the our previous method, thus resolving the capacity issue.
Low-dissipation low-dispersion explicit Taylor-Galerkin schemes from the Runge-Kutta kernels

A multi-stage approach was adopted to investigate similarities and differences between the explicit Taylor-Galerkin and the explicit Runge-Kutta time integration schemes. It was found that the substitution of some, but not all, of second-order temporal derivatives in a Taylor-Galerkin scheme by additional stages makes it analogous to a Runge-Kutta scheme while preserving its original dissipative property for node-to-node oscillations. The substitution of all second-order temporal derivatives transforms Taylor-Galerkin schemes into Runge-Kutta schemes with zero attenuation at the grid cut-off. The application of this approach to an existing two-stage Taylor-Galerkin scheme yields a low-dissipation low-dispersion Taylor-Galerkin formulation. Two one-dimensional benchmarks were simulated to study the performance of this new scheme. The reverse process yields a general approach for transforming m-stage Runge-Kutta schemes into (m−1)-stage Taylor-Galerkin schemes while preserving the same order of accuracy. The dissipation and dispersion properties for several new Taylor-Galerkin schemes were compared to those of their corresponding Runge-Kutta form.
Precoding Design for Ensuring Data Freshness in Multi-User MISO Networks

The existing multiple-input single-output (MISO) design to transmit data reliably to multiple mobile users (MUs) has become insufficient as MUs require fresh data, not just data. Therefore, in this paper, we consider multi-user MISO networks, where a base station (BS) equipped with multiple antennas serves MUs that want to maintain data freshness. To analyze the data freshness in this network, we first define the age-of-information (AoI) violation ratio, which is the ratio of duration that the AoI is larger than the AoI violation threshold to a sensing period. We then obtain the upper bound on the AoI violation ratio using the smooth maximum/minimum unit. We consider an optimization problem that minimizes the AoI violation ratio of multiple MUs. We propose a generalized power iteration (GPI) precoding algorithm to find a principal precoding vector that satisfies a first-order optimality condition of the optimization problem. Furthermore, for the scenario where the BS has the imperfect channel state information (CSI) of MUs, we provide the upper bound on the AoI violation time using the lower bound on the ergodic spectral efficiency, and also design the GPI precoding algorithm. Simulation results show proposed methods outperform baseline methods and demonstrate the effect of network parameters on the AoI violation probability.
Nanostructured Vanadium Dioxide Materials for Optical Sensing Applications

Vanadium dioxide (VO2) is one of the strongly correlated materials exhibiting a reversible insulator–metal phase transition accompanied by a structural transition from a low-temperature monoclinic phase to high-temperature rutile phase near room temperature. Due to the dramatic change in electrical resistance and optical transmittance of VO2, it has attracted considerable attention towards the electronic and optical device applications, such as switching devices, memory devices, memristors, smart windows, sensors, actuators, etc. The present review provides an overview of several methods for the synthesis of nanostructured VO2, such as solution-based chemical approaches (sol-gel process and hydrothermal synthesis) and gas or vapor phase synthesis techniques (pulsed laser deposition, sputtering method, and chemical vapor deposition). This review also presents stoichiometry, strain, and doping engineering as modulation strategies of physical properties for nanostructured VO2. In particular, this review describes ultraviolet-visible-near infrared photodetectors, optical switches, and color modulators as optical sensing applications associated with nanostructured VO2 materials. Finally, current research trends and perspectives are also discussed.
Glass ceiling or glass cliff: an examination of the role of female board members on market performance in Poland

ABSTRACT We examine gender bias related to the effect of women in executive management leadership. Specifically, we examine when women are recruited to executive positions and follow companies’ market performance before and after their appointment. Our study is conceptually situated within the field of queuing theory, suggesting certain patterns of labour market queuing behaviour according to race, gender, and class. We formulate two hypotheses: (1) the presence of female executives is associated with lower firm value; and (2) companies with female-centric executive boards are valued lower by investors than companies with male-centric boards. We test these hypotheses employing panel data, using a unique sample of 159 companies listed on the Warsaw Stock Exchange in the years 2006–2015, with hand-collected data on the number of female directors on executive boards. Our results suggest that market queuing behaviour is evident in the case of Poland. Men are more often hired in executive roles than women, whereas females are more likely to be appointed to executive boards in firms which are performing poorly. Moreover, higher participation of women in executive positions is associated with resulting lower value in the long run. According to our interpretation, isomorphism and gender bias diffuse through the reproduction and valuation of capitalist markets.