Miracle-dz/UniFAR-FTUs huggingface dataset:
A data-driven approach to fault modeling and diagnosis of brake-by-wire system

E-Booster plays an important role in braking safety as the pressure source for vehicle hydraulic systems. According to the design feature of its series controller, the signals on key nodes, which can be directly measured, can be used as the data source for fault diagnosis. In this paper, a deep learning technique of residual 1-D CNN equipped with parallel structure is proposed for fault recognition and classification in a dynamic process. With the help of wavelet transform and probabilistic heat map, it is found that the phase current fault feature is distinct in the frequency domain. In contrast, the uniform demagnetization fault and pressure recession fault are more obvious in the time domain. Therefore, the parallel network structure with a wide and narrow convolutional kernel is used, which can handle multiple complex fault features simultaneously. Simulation models based on both data-driven and mathematical formulations are also established to better fit the actual nonlinear conditions. Finally, the proposed network structure can reach 92.1% classification accuracy compared with the commonly used lightweight 2-D CNN model. It can be concluded that 1-D CNN achieves similar classification results as 2-D CNN with less computational resource consumption.
Intelligent Speech Garbage Classification Based on Deep Residual Network

To solve the problem that there are many kinds of municipal solid waste and urban residents do not have a clear classification standard for garbage, an intelligent voice garbage classification system based on a deep residual neural network is designed. For the four kinds of common garbage in life, the voice commands of four kinds of typical garbage are collected. Through the speech endpoint detection algorithm, the silence and noise in the speech are removed, and the acoustic model based on the deep residual network is built to realize garbage classification. The experimental results show that after the model training is completed, the accuracy of the verification set reaches 98%, the accuracy of the test set reaches 96%, and the generalization ability is strong, which has a high application value.
DYNi\MIC, STRUCTURAL, AND REGlJLATORY ASPECTS OF A SITE-SPECIFIC RECOMBINATION

PROTEINS AND THEIR GENES . �t . Xis . ," ' , . , ' , . IHF . , . , . F1S , . , . ATT SITE STRUCTURE AND PROTEIN BINDING SITES . Overlap Region . , . Int Binding Sites . , . , . , . Xis Sites . , . IHF Sites . , . FIS Sites . , . COOPERATIVE INTERACTIONS AND HIGHER-ORDER STRUCTURES . SYNAPSIS AND STRAND EXCHANGE . Covalent Intermediates . , . The Order of Strand Exchange . DNA Homology . Synapsis . DIRECTIONALITY AND REGULATION .
Max-Pressure Controller for Networks of Signalized Intersection and simulation study

Urban intersections are faced with complex congestion problems and centralized control system has many drawbacks. To solve this problem, a relatively simple local control method - the maximum pressure (MP) control strategy is studied. Meanwhile, the simulation of the proposed MP control method is conducted. After analyzing the simulation results, it is found that MP control can realize the adaptive change of phase duration. The MP control makes the number of throughput vehicles at a high level and can stabilize the queue length within a certain range, ensuring the stability of the operation of the intersection. The control effect of MP is better than that of the fixed-time control.
Virtual Oscillator Control for inverters based on reduced-order Andronov-Hopf oscillator

This paper proposes a virtual oscillator control method by reducing the order of the amplitude term of the Andronov-Hopf dynamic process. The proposed oscillator retains its steady-state droop characteristic and power dispatchability in grid-connected mode, but with less nonlinearity. At the same time, based on the steady-state performance criterion of the inverter, the detailed parameter selection principle of the proposed controller is given, and its dispatchability is verified by simulation. Finally, we compared the proposed controller with the full-order virtual oscillation controller. The results show that the proposed controller has a stronger load capacity.
Study on Student Attendance System Based on Face Recognition

Student attendance is not only an important indicator for the school to inspect students’ achievements, but also an objective evaluation of teachers’ teaching quality. In the system, we use PyCharm as the development platform, design the system interface through QT Designer (QT5), use PyQt5 library to write the function of interface controls, use MySQL as the database, and use OpenCV face recognition algorithm to recognize, thus realizing an attendance system based on face recognition. The system is divided into two parts: attendance and face recognition. Through the test, the number and quality of members can be monitored in real-time. The traditional attendance method of manual statistical management is abandoned, and the method in this paper provides a scientific basis for the implementation of the campus attendance system.
Research on the influence of pilot workload on local route path planning of helicopters in low-altitude penetration

Targeting the problem of high pilot workload caused by trajectory planning of low altitude penetration, this paper proposed a trajectory planning method considering the pilot workload. Firstly, by decomposing the three-dimensional trajectory into horizontal and vertical directions, the trajectory tree method based on the dynamic programming technique is used for horizontal trajectory planning, and the comprehensive slope-curvature limitation method is used for altitude trajectory planning. Then, a method was proposed to quantify the control inputs and pilot workload based on trajectory tracking simulation. The pilot workload cost, together with flight altitude cost and route length cost, was added to the local planning of a reference trajectory. To solve the problem of dimension explosion in trajectory tree search, a segmented optimal route tree algorithm is proposed. Finally, the simulation results show that the proposed method can effectively consider the pilot workload in trajectory planning, which is helpful to improve the flight ability of the planning trajectory and reduce the pilot workload at the same time.
Geometry-limited diffusion

This paper addresses the problem of image segmentation and suggests that a number of interesting visual features can be specified as the boundaries of segments. It proposes a segmentation strategy that utilizes the local homogeneity of local image structure. Stable differential measurements are made via a variable-conductance diffusion process, sometimes called anisotropic diffusion. Anisotropic diffusion has been shown to preserve important image structure while reducing unwanted noise. A multi-scale approach to variable-conductance diffusion is described. This technique combines information at a range of scales and provides a means of obtaining precise boundaries of "large-scale" objects in the presence of noise. These ideas generalize to incorporate multi-valued images and higher-order geometric structure. The result is a framework for constructing image segmentations based on the homogeneity of a set of descriptors. When applied to local image geometry, this method offers a means of breaking images into geometric patches that have interesting visual features as boundaries. Several examples of this framework are presented. While the diffusion of intensity provides a means of detecting edges, the diffusion of first-order information produces ridges and valleys. A combination of first- and second-order information provides a means of detecting the "middles" as well as the edges of objects. A proof of the geometric invariance under orthogonal group transformations is given. These same methods generalize to include systems of frequency-sensitive diffusion processes. These systems are useful for characterizing patches based on texture. An empirical investigation of these nonlinear diffusion processes shows they are stable in the presence of noise and offer distinct advantages over conventional linear smoothing. This analysis derives from a novel method for evaluating low-level computer-vision algorithms. The method uses ensembles of stochastically generated images to compute a set of statistical metrics which quantify the accuracy and reliability of a process. This evaluation offers a means of comparing different algorithms and exploring the space of free parameters associated with a single algorithm.
Primary Prevention of Cardiovascular Disease at Community Clinics in the State of Sao Paulo, Brazil: Results from the Epidemiological Information Study of Communities

Background: Primary prevention of cardiovascular disease (CVD) remains a major challenge, especially in communities of low- and middle-income countries with poor medical assistance influenced by distinct local, financial, infrastructural, and resource-related factors. Objective: This a community-based study aimed to determine the proportion and prevalence of uncontrolled cardiovascular risk factors (CRF) in Brazilian communities. Methods: The EPICO study was an observational, cross-sectional, and community clinic-based study. Subjects were living in Brazilian communities and were of both sexes and ≥18 years old, without a history of a stroke or myocardial infarction but presenting at least one of the following cardiovascular risk factors: hypertension, diabetes mellitus and hypercholesterolemia. The study was carried out in Brazil, including 322 basic health units (BHU) in 32 cities. Results: A total of 7,724 subjects with at least one CRF were evaluated, and one clinical visit was performed. Mean age was 59.2 years-old (53.7% were >60 years old). A total of 66.7% were women. Of the total, 96.2% had hypertension, 78.8% had diabetes mellitus type II, 71.1% had dyslipidemia, and 76.6% of patients were overweight/obese. Controlled hypertension (defined by <130/80 mmHg or <140/90 mmHg) was observed in 34.9% and 55.5% patients among respective criteria, the rates of controlled blood glucose in patients taking antidiabetic medications was 29.5%, and among those with documented dyslipidemia who received any lipid-lowering medication, only 13.9% had LDL-c on target. For patients presenting three CRF less than 1.9% had LDL-c < 100 mg/dL once their BP and blood glucose were on target. High education level as associated with blood pressure (BP) target of less than 130 / 80mm Hg. The glucose and LDL-c levels on target were associated with the presence of hypertension and diabetes mellitus. Conclusion: In Brazilian community clinics, regarding most patients in primary prevention, the CRF such as BP, blood glucose, and lipid levels are poorly controlled, with a majority of patients not achieving guidelines/recommendations.
Experimental study of induced transparency or absorption and slow or fast light using orthogonally polarized whispering gallery modes of a single microresonator

Induced transparency and absorption effects are observed in the throughput of a hollow bottle microresonator using either mode coupling or superposition of two coresonant orthogonally polarized whispering gallery modes of very different quality factors (Q). The first method is based on intracavity cross polarization coupling when either the TE mode or the TM mode is driven, resulting in coupled mode induced transparency (CMIT) and coupled mode induced absorption (CMIA). The second method is based on superposition of the throughputs when the two modes are simultaneously driven by input light linearly polarized at an angle of 45° with respect to the TE-TM basis of the resonator, and throughput of the same polarization is detected. In this way, superposition can be created even in the absence of cross polarization coupling. The observations using the second method are referred to as coresonant polarization induced transparency and absorption (CPIT, CPIA). Coresonance between the TE and TM modes can be obtained by strain tuning. The above behaviors are analogous to electromagnetically induced transparency and absorption (EIT, EIA), and enable slow light and fast light, i.e., the delay or advancement of an incident resonant pulse. Experimental results representative of several different types of behavior are presented here. Induced transparency is seen to be accompanied by pulse delay, whereas induced absorption can be accompanied by pulse advancement or delay. The results are analyzed and explained by simple analytical modeling and by comparison to the output of a more detailed numerical model describing these effects.
Hydromagnetic Equilibria and their Evolution in Neutron Stars

Abstract The strongest known magnetic fields are found in neutron stars. I briefly discuss how they are inferred from observations, as well as the evidence for their time-evolution. I go on to show how these extremely strong fields are actually weak in terms of their effects on the stellar structure. This is also the case for magnetic stars on the upper main sequence and magnetic white dwarfs, which have similar total magnetic fluxes, perhaps pointing to an evolutionary connection. I suggest that a stable hydromagnetic equilibrium (containing a poloidal and a toroidal field component) could be established soon after the birth of the neutron star, aided by the strong compositional stratification of neutron star matter, and this state is slowly eroded by non-ideal magnetohydrodynamic processes such as beta decays and ambipolar diffusion in the core of the star and Hall drift and breaking of the solid in its crust. Over sufficiently long time scales, the fluid in the neutron star core will behave as if it were barotropic, because, depending on temperature and magnetic field strength, beta decays will keep adjusting the composition to the chemical equilibrium state, or ambipolar diffusion will decouple the charged component from the neutrons. Therefore, the still open question regarding stable hydromagnetic equilibria in barotropic fluids will become relevant for the evolution, at least for magnetar fields, which are likely too strong to be stabilized by the solid crust.
Enhanced damping-based anti-swing control method for underactuated overhead cranes

In this study, a novel enhanced anti-swing control method is proposed for underactuated overhead crane systems, which shows superior anti-swing control performance than most existing control methods. In particular, to increase the anti-swing control performance of overhead crane systems, an improved damping anti-swing signal is investigated based on a swing-related storage function. Subsequently, based on the anti-swing signal, a constructive Lyapunov function candidate is introduced and a new non-linear anti-swing control method is proposed straightforwardly, and the equilibrium point of the overall closed-loop system is proven to be asymptotically stable by Lyapunov techniques and LaSalle's invariance theorem. Some experimental results are provided to demonstrate the feasibility and effectiveness of the proposed control method. In addition, to illustrate the superior control performance of the proposed method, a comparison study between the designed control method and the existing control methods is provided as well.
Comparison between two Three-Dimensional Edge Operators applied in a 3D Navigation Approach

This paper will compare two 3D surface detection and normal estimation operators applied on a rough voxel database. These approaches can be applied as virtual endoscopy for the exploriation of 3D medical image volumes. The data context will be first explained, the two methodologies will be then described and evaluated on a 3D model data.
Clinical, humanistic and economic outcomes, including experiencing of patient safety events, associated with admitting patients to single rooms compared with shared accommodation for acute hospital admissions: a systematic review and narrative synthesis

Objectives Assess the impact of single rooms versus multioccupancy accommodation on inpatient healthcare outcomes and processes. Design Systematic review and narrative synthesis. Data sources Medline, Embase, Google Scholar and the National Institute for Health and Care Excellence website up to 17 February 2022. Eligibility criteria Eligible papers assessed the effect on inpatients staying in hospital of being assigned to a either a single room or shared accommodation, except where that assignment was for a direct clinical reason like preventing infection spread. Data extraction and synthesis Data were extracted and synthesised narratively, according to the methods of Campbell et al. Results Of 4861 citations initially identified, 145 were judged to be relevant to this review. Five main method types were reported. All studies had methodological issues that potentially biased the results by not adjusting for confounding factors that are likely to have contributed to the outcomes. Ninety-two papers compared clinical outcomes for patients in single rooms versus shared accommodation. No clearly consistent conclusions could be drawn about overall benefits of single rooms. Single rooms were most likely to be associated with a small overall clinical benefit for the most severely ill patients, especially neonates in intensive care. Patients who preferred single rooms tended to do so for privacy and for reduced disturbances. By contrast, some groups were more likely to prefer shared accommodation to avoid loneliness. Greater costs associated with building single rooms were small and likely to be recouped over time by other efficiencies. Conclusions The lack of difference between inpatient accommodation types in a large number of studies suggests that there would be little effect on clinical outcomes, particularly in routine care. Patients in intensive care areas are most likely to benefit from single rooms. Most patients preferred single rooms for privacy and some preferred shared accommodation for avoiding loneliness. PROSPERO registration number CRD42022311689.
Field angle dependent resonant dynamics of artificial spin ice lattices

Artificial spin ice structures which are networks of coupled nanomagnets arranged on different lattices that exhibit a number of interesting phenomena are promising for future information processing. We report reconfigurable microwave properties in artificial spin ice structures with three different lattice symmetries namely square, kagome, and triangle. Magnetization dynamics are systematically investigated using field angle dependent ferromagnetic resonance spectroscopy. Two distinct ferromagnetic resonance modes are observed in square spin ice structures in contrast with the three well-separated modes in kagome and triangular spin ice structures that are spatially localized at the center of the individual nanomagnets. A simple rotation of the sample placed in magnetic field results in the merging and splitting of the modes due to the different orientations of the nanomagnets with respect to the applied magnetic field. Magnetostatic interactions are found to shift the mode positions after comparing the microwave responses from the array of nanomagnets with control simulations with isolated nanomagnets. Moreover, the extent of the mode splitting has been studied by varying the thickness of the lattice structures. The results have potential implications for microwave filter-type applications which can be operated for a wide range of frequencies with ease of tunability.
Problems in Ramsey theory, probabilistic combinatorics and extremal graph theory

In this dissertation, we treat several problems in Ramsey theory, probabilistic combinatorics and extremal graph theory. We begin with the Ramsey theoretic problem of finding exactly m-coloured graphs. For which natural numbers m ∈ N are we guaranteed to find an m-coloured complete subgraph in any edge colouring of the complete graph on N? We resolve this question completely and prove, answering a question of Stacey and Weidl [104], that whenever we colour N(2) with infinitely many colours, we are guaranteed to find an ( n 2 ) -coloured complete subgraph for each n ∈ N. In addition, we also demonstrate that given a colouring of N(2) with k colours, there are at least √ 2k distinct values m ∈ [k] for which an infinite m-coloured complete subgraph exists. Finally, we also prove that given a colouring of N(2) with k colours and m ∈ [k], we can always find an infinite m-coloured complete subgraph for some m ∈ [k] such that |m− m| ≤ √ m/2. Next, we give some results in probabilistic combinatorics. First, we investigate the stability of the Erdős–Ko–Rado Theorem. For natural numbers n, r ∈ N with n ≥ r, the Kneser graph K(n, r) is the graph on the family of r-element subsets of {1, . , n} in which two sets are adjacent if and only if they are disjoint. Delete the edges of K(n, r) with some probability, independently of each other: is the independence number of this random graph equal to the independence number of the Kneser graph itself? We shall answer this question affirmatively as long as r/n is bounded away from 1/2, even when the probability of retaining an edge of the Kneser graph is quite small; we also prove a much more precise result when r = o(n1/3). We then study a geometric bootstrap percolation model on the three dimensional grid [n]3 called line percolation. In line percolation with infection parameter r, infection spreads from a subset A ⊂ [n]3 of initially infected lattice points as follows: if there is an axis parallel line L with r or more infected lattice points on it, then every lattice point of [n]3 on L gets infected and we repeat this until the infection can no longer spread. Our main result is the determination the critical density of initially infected points at which percolation (infection of the entire grid) becomes likely. Finally, we present two results in extremal graph theory. First, we consider a graph partitioning problem. For a graph G, let f(G) be the largest integer k such that there are two vertex-disjoint subgraphs of G, each on k vertices, inducing the same number of edges. We prove that f(G) ≥ n/2 − o(n) for every graph G on n vertices, settling a conjecture of Caro and Yuster [36]. Finally, we study the problem of cops and robbers on the grid where the robber is allowed to move faster than the cops. We prove that when the speed of the robber is a sufficiently large constant, the number of cops needed to catch the robber on an n×n grid is exp(Ω(log n/ log log n)).
Predicting Seasonal Influenza Hospitalizations Using an Ensemble Super Learner: A Simulation Study

Abstract Accurate forecasts can inform response to outbreaks. Most efforts in influenza forecasting have focused on predicting influenza-like activity, with fewer on influenza-related hospitalizations. We conducted a simulation study to evaluate a super learner’s predictions of 3 seasonal measures of influenza hospitalizations in the United States: peak hospitalization rate, peak hospitalization week, and cumulative hospitalization rate. We trained an ensemble machine learning algorithm on 15,000 simulated hospitalization curves and generated weekly predictions. We compared the performance of the ensemble (weighted combination of predictions from multiple prediction algorithms), the best-performing individual prediction algorithm, and a naive prediction (median of a simulated outcome distribution). Ensemble predictions performed similarly to the naive predictions early in the season but consistently improved as the season progressed for all prediction targets. The best-performing prediction algorithm in each week typically had similar predictive accuracy compared with the ensemble, but the specific prediction algorithm selected varied by week. An ensemble super learner improved predictions of influenza-related hospitalizations, relative to a naive prediction. Future work should examine the super learner’s performance using additional empirical data on influenza-related predictors (e.g., influenza-like illness). The algorithm should also be tailored to produce prospective probabilistic forecasts of selected prediction targets.