Miracle-dz/UniFAR-FTUs huggingface dataset:
Character Recognition Method for Low-Contrast Images of Numerical Instruments

In this paper, a method of preprocessing to extract numbers from a low-contrast image of numerical instruments and recognition based on skeleton structural features is proposed. The approach is based on the grayscale dilation operation which can enhance the difference of targets with the background of the image and eliminate the adhesion between the target and the environment. After that, a skeleton algorithm is used to highlight the shape and topology of the target which makes the target number easier to be identified. Using HALCON to test, the result shows that the identification has a high accuracy rate.
Wideband CP Polarization and Pattern Reconfigurable Antennas

This paper gives an review of innovative wideband CP polarization and pattern reconfigurable antennas. First, two wideband CP reconfigurable antennas with the broadside radiation patterns are presented. One design was realized by four sequentially-rotated monopoles with an output reconfigurable feed network. Another design adopted L-probes fed square patch that reduced the profile to 0.1 λ0. Second, rather than producing the broadside radiation pattern, a wideband CP reconfigurable wheel-shaped antenna with the conical-beam pattern is introduced, which is intended for geostationary satellite applications. Third, in addition to the polarization reconfigurability, a wideband CP antenna with switchable broadside and conical-beam patterns is presented, which excites both TMn and $\mathbf{TM}_{21}$ modes on an annular slotted circular patch radiator. All the above CP polarization and pattern reconfigurable antennas are attractive for the emerging wireless communication systems, especially the satellite communication systems.
Renoprotective Effects of Antroquinonol in Rats with Nω-Nitro-l-Arginine Methyl Ester-Induced Hypertension

Endothelial dysfunction leads to elevation of blood pressure and vascular remodeling, which may result in tissue injuries. The aim of this study was to investigate the mechanisms and effects of antroquinonol on hypertension and related renal injuries. Rats were fed water containing 25 mg/kg/day Nω-nitro-l-arginine methyl ester (L-NAME) to induce hypertension, and a diet with or without antroquinonol (20 or 40 mg/kg/day) for a 9-week experiment. During the experimental period, antroquinonol reduced the elevation of systolic and diastolic blood pressure. At the end of the study, we found that the antroquinonol groups had lower serum creatinine, renal endothelin-1, angiotensin II, and malondialdehyde levels and arteriole thickening. We found that the 40 mg/kg/day antroquinonol group had lower renal nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activities, greater nuclear factor erythroid-2, and heme oxygenase-1 expressions. Moreover, we also found that antroquinonol decreased proinflammatory cytokine concentrations in the kidney by modulating the nuclear factor-κB pathway. These results suggest that antroquinonol may ameliorate hypertension and improve renal function by reducing oxidative stress and inflammation in rats with endothelial dysfunction.
Cyber Cascades Screening Considering the Impacts of False Data Injection Attacks

The attackers in smart grids can design false injection data attacks to intentionally cause branch overloaded tripping, which may trigger a cascading failure and thus impose substantial damages to the power grids. To address such risk, we in this paper propose an approach for screening out the most severe cascading failures triggered by potential data attacks. The proposed approach identifies these cascades and quantifies their impacts by assessing the data attacks induced branch overloads in a multistage model. The approach also includes a tool for handling the system separations during the spreading of a cascade. The simulations on the IEEE 118-bus system verify the proposed screening approaches and highlight the necessity of enhancing the defensive procedures for addressing such risk in smart grids.
Spatially-Coupled Codes for Channels with SNR Variation

In magnetic recording systems, consecutive sections experience different signal-to-noise ratios (SNRs). To perform error correction over these systems, one approach is to use an individual block code for each section. However, the performance over a section affected by a lower SNR is weaker compared to the performance over a section affected by a higher SNR. Spatially-coupled (SC) codes are a family of graph-based codes with capacity approaching performance and low latency decoding. An SC code is constructed by partitioning an underlying block code to several component matrices, and coupling copies of the component matrices together. The contribution of this paper is threefold. First, we present a new partitioning technique to efficiently construct SC codes with column weights 4 and 6. Second, we present an SC code construction for channels with SNR variation. Our SC code construction provides local error correction for each section by means of the underlying codes that cover one section each, and simultaneously, an added level of error correction by means of coupling among the underlying codes. Third, we introduce a low-complexity interleaving scheme specific to SC codes that further improves their performance over channels with SNR variation. Our simulation results show that our SC codes outperform individual block codes by more than one and two orders of magnitudes in the error floor region compared to the block codes with and without regular interleaving, respectively. This improvement is more pronounced by increasing the memory and column weight.
How to be a secure base: therapists’ attachment representations and their link to attunement in psychotherapy

ABSTRACT This paper investigates if therapists’ attachment classifications are linked to different types of therapists’ attunement in session. We present coding procedures and validation of the Therapist Attunement Scales (TASc), a transcript-based instrument that assesses attunement in therapy and that we hypothesized would be associated with therapists’ attachment classifications. Fifty therapists were administered the Adult Attachment Interview (AAI), and therapy sessions with each therapist were rated with the TASc. Therapists also completed the WAI-T to assess the therapeutic alliance and divergent validity of the TASc. Results indicate strong inter-rater reliability and stability across consecutive sessions of the TASc, as well as high convergent validity between one session rated with the TASc and the AAI rated independently (κ = .81). No significant associations were found with the WAI-T, which offers preliminary evidence of divergent validity of the TASc. These results suggest that therapists of different attachment classifications may attune to patients in distinct ways. These results also present the TASc as a valid measure of therapists’ attachment in psychotherapy and as a promising tool for training and supervision.
Associations of Physical Behaviours and Behavioural Reallocations with Markers of Metabolic Health: A Compositional Data Analysis

Standard statistical modelling has shown that the reallocation of sitting time to either standing or stepping may be beneficial for metabolic health. However, this overlooks the inherent dependency of time spent in all behaviours. The aim is to examine the associations between physical behaviours and markers of metabolic health (fasting glucose, fasting insulin, 2-h glucose, 2-h insulin, Homeostasis Model Assessment of Insulin Sensitivity (HOMA-IS), Matsuda Insulin Sensitivity Index (Matsuda-ISI) while quantifying the associations of reallocating time from one physical behaviour to another using compositional analysis. Objectively measured physical behaviour data were analysed (n = 435) using compositional analysis and compositional isotemporal substitutions to estimate the association of reallocating time from one behaviour to another in a population at high risk of type 2 diabetes mellitus (T2DM). Stepping time was associated with all markers of metabolic health relative to all other behaviours. Reallocating 30 min from sleep, sitting, or standing to stepping was associated with 5–6 fold lower 2-h glucose, 15–17 fold lower 2-h insulin, and higher insulin sensitivity (10–11 fold via HOMA-IS, 12–15 fold via Matsuda-ISI). Associations of reallocating time from any behaviour to stepping were maintained for 2-h glucose, 2-h insulin, and Matsuda-ISI after further adjusting for body mass index (BMI). Relocating time from stepping into sleep, sitting, or standing was associated with lower insulin sensitivity. Stepping time may be the most important behavioural composition when promoting improved metabolic health in adults at risk of T2DM.
On the Synthesis of Static Output Feedback Controllers for Guaranteed RMS Gain of Switched Systems with Arbitrary Switching

This paper addresses the problem of determining static output feedback controllers for ensuring desired upper bounds of the root mean square (RMS) gain of continuous-time switched linear systems with arbitrary switching. The problem is addressed by searching for a homogeneous rational Lyapunov function (HRLF) parameterized rationally by the sought controller, and by introducing a polynomial for quantifying the feasibility of the Lyapunov inequalities. It is shown that such a controller exists if and only if a condition built solving three convex optimization problems with linear matrix inequalities (LMIs) holds for polynomials of degree sufficiently large.
Relative State and Inertia Estimation of Unknown Tumbling Spacecraft by Stereo Vision

A novel algorithm is proposed to estimate the relative state, including position, attitude, linear velocity, angular velocity, and inertia parameters of an unknown tumbling spacecraft, by stereo vision. Feature points of the target are selected in situ, and their positions and velocities are estimated by the measurements of perspective projection and optical flow. Then, the relative attitude and angular velocity of the spacecraft are estimated by a unit quaternion method and least square method, respectively. After that, the relative position and translational velocity of the spacecraft, together with the relative positions of the detected feature points, are estimated simultaneously based on the relative translational motion model of the target by successive images. Finally, inertia parameters of the spacecraft are estimated by a quadratic optimization method based on angular momentum conservation subject to physical constraints. The performance of the newly proposed algorithm is verified by comparing with an existing case in the literature. Moreover, the performance is validated by Monte-Carlo simulations in different cases.
Exploring emotional expression recognition in aging adults using the Moving Window Technique

Adult aging is associated with difficulties in recognizing negative facial expressions such as fear and anger. However, happiness and disgust recognition is generally found to be less affected. Eye-tracking studies indicate that the diagnostic features of fearful and angry faces are situated in the upper regions of the face (the eyes), and for happy and disgusted faces in the lower regions (nose and mouth). These studies also indicate age-differences in visual scanning behavior, suggesting a role for attention in emotion recognition deficits in older adults. However, because facial features can be processed extrafoveally, and expression recognition occurs rapidly, eye-tracking has been questioned as a measure of attention during emotion recognition. In this study, the Moving Window Technique (MWT) was used as an alternative to the conventional eye-tracking technology. By restricting the visual field to a moveable window, this technique provides a more direct measure of attention. We found a strong bias to explore the mouth across both age groups. Relative to young adults, older adults focused less on the left eye, and marginally more on the mouth and nose. Despite these different exploration patterns, older adults were most impaired in recognition accuracy for disgusted expressions. Correlation analysis revealed that among older adults, more mouth exploration was associated with faster recognition of both disgusted and happy expressions. As a whole, these findings suggest that in aging there are both attentional differences and perceptual deficits contributing to less accurate emotion recognition.
Trust Region Policy Optimization for POMDPs

We propose Generalized Trust Region Policy Optimization (GTRPO), a policy gradient Reinforcement Learning (RL) algorithm for both Markov decision processes (MDP) and Partially Observable Markov Decision Processes (POMDP). Policy gradient is a class of model-free RL methods. Previous policy gradient methods are guaranteed to converge only when the underlying model is an MDP and the policy is run for an infinite horizon. We relax these assumptions to episodic settings and to partially observable models with memory-less policies. For the latter class, GTRPO uses a variant of the Q-function with only three consecutive observations for each policy updates, and hence, is computationally efficient. We theoretically show that the policy updates in GTRPO monotonically improve the expected cumulative return and hence, GTRPO has convergence guarantees.
Multi-Agent System for Renewable Based Microgrid Restoration

Power system restoration (PSR) is a very important procedure to ensure the consumer supply. In this paper, a decentralized multi-agent system (MAS) for dealing with the microgrid restoration procedure is proposed. In this method, each agent is associated with a consumer or microsource (MS) and these communicate with each other to reach a common decision. The agents solve a 0/1 knapsack problem to determine the best load connection sequence during the microgrid restoration procedure and then the proposed MAS is tested in one specific scenario where the microgrid is subjected to a blackout that occurred. This means that all the resources and loads are disconnected. This work is developed in Matlab/Simulink environment and the results show its feasibility and effectiveness in the microgrid restoration procedure.
Stiffness analysis and experimental validation of modular-type hybrid antagonistic tendon-driven joint systems

SUMMARY This paper proposes a new antagonistic tendon-driven joint (TDJ) that exhibits higher stiffness and larger travel range than conventional types of TDJs. A detailed mathematical analysis of the stiffness of the proposed TDJ is conducted and compared to other TDJs. The effect of the tendon length is taken into consideration to establish a more precise and realistic stiffness model of the proposed TDJ. Thereafter, two hardware prototypes of the proposed TDJ design, developed in the form of a packaged modular structure that integrates two TDJs, are introduced. Using these prototypes, the stiffness characteristics of the proposed TDJs are verified through experimentation. Additionally, experimental results on the stiffness behavior during the mimicked needle insertion tasks are provided. Results show that the proposed TDJs present much higher stiffness than conventional ones and thus give a potential benefit to precision manipulation.
Psychological stress and type 1 diabetes mellitus: what is the link?

ABSTRACT Introduction: Type 1 diabetes mellitus (T1DM) is a chronic disease characterized by the destruction of insulin-producing β-cells of the pancreas. The current paradigm in this disease’s etiopathogenesis points toward the interplay of genetic and environmental factors. Among the environmental variables, dietary factors, intestinal microbiota, toxins, and psychological stress have been implicated in disease onset. Areas covered: This review aims to investigate the relationship between psychological stress and T1DM by presenting evidence from epidemiological studies, animal models, and to provide the mechanism involved in this association. The literature search was conducted through PubMed to identify studies that investigate the connection between stress and T1DM. Experimental designs, such as case-control, and retrospective and prospective cohorts studies, were included. Expert commentary: A wide array of evidence, ranging from epidemiological to animal models, points toward the role of psychological stressors in T1DM pathogenesis. Various mechanisms have been proposed, including the hypothalamic-pituitary-adrenal (HPA) axis, influence of the nervous system on immune cells, and insulin resistance. Further research could investigate the gene-stress interactions to evaluate the risk of T1DM development.
Trimodal therapy for muscle-invasive bladder cancer

ABSTRACT Introduction: Radical cystectomy is the standard therapy for patients with muscle-invasive bladder cancer. Organ-preserving surgical procedures have been established as alternatives to radical surgery for localized malignancies in other anatomic sites. Trimodal therapy consisting of radiation therapy, chemotherapy, and either transurethral resection of the bladder or partial cystectomy is an effective treatment for selected patients with muscle-invasive bladder cancer that allows for preservation of the urinary bladder. Areas covered: This review provides an overview of the value of trimodal therapy in the treatment of muscle-invasive bladder cancer. Expert commentary: Prerequisites for trimodal therapy for bladder cancer include: good bladder function, unifocal cT2 urothelial carcinoma of the bladder, and absence of hydronephrosis. Careful selection of patients and accurate assessment of the anatomic extent of the tumor is important for patient safety. The basis for successful trimodal therapy is complete transurethral resection of the tumor, followed by radiation therapy with concurrent radiosensitizing chemotherapy. Cystoscopic controls and follow-up biopsies should be performed at completion of adjuvant therapy or shortly after induction of trimodal therapy to identify nonresponders for whom salvage radical cystectomy may be indicated.
Selección de la muestra

En este capitulo el Dr. Samiperi y colaboradores establecen los criterios metodologicos para definir el tamano de la muestra de estudio, los tipos de muestreo y sus caracteristicas. | REQUERIMIENTOS TECNICOS: | COSTO INVOLUCRADO: | COMPATIBILIDAD MOVILES: N/A | DISPONIBILIDAD DE INFORMACION DE ACCESIBILIDAD:
Simulation and Experimental Study on No-Load Loss Distributions of an IPM Motor Under the Conditions of Both Sinusoidal Supply and Converter Supply

In this paper, each component of the no-load loss of interior permanent magnet motors under the conditions of both sinusoidal supply and converter supply is investigated by the finite-element method and experimental method. The no-load loss is calculated at different rotation speeds, two different slot and pole combinations and different converter parameters. The wireless temperature sensor embedded in the interior rotor is used to test the temperature of the permanent magnet under no-load condition, and the permanent magnet loss is calculated according to the slope of the initial temperature–time curve. Then, the mechanical loss of the prototype is measured by dragging a nonmagnetic rotor. The total tested losses are subtracted from the copper loss, the mechanical loss, and the permanent magnet loss to obtain the test results of core loss, and the experimental results of each loss and permanent magnet temperature rise are compared with the corresponding calculated results to verify the correctness of the simulation results.
Gaussian Process Modeling of a Functional Output with Information from Boundary and Initial Conditions and Analytical Approximations

ABSTRACT A partial differential equation (PDE) models a physical quantity as a function of space and time. These models are often solved numerically with the finite element (FE) method and the computer output consists of values of the solution on a fine grid over the spatial and temporal domain. When the simulations are time-consuming, Gaussian process (GP) models can be used to approximate the relationship between the functional output and the computer inputs, which consists of boundary and initial conditions. The Dirichlet boundary and initial conditions give the functional output values on parts of the space-time domain boundary. Although this information can help improve prediction of the output, it has not been used to construct GP models. In addition, analytical solutions of the PDE derived by simplifying the PDE can often be obtained, which can help further improve performance of the GP model. This article proposes a Karhunen–Loève (KL) expansion-based GP model that satisfies the Dirichlet boundary and initial conditions almost surely, and effectively uses information from analytical approximations to the PDE solution. Real examples demonstrate the improved prediction performance achieved by using these sources of prior information. Supplementary materials for this article are available online.
Research of Image Main Objects Detection Algorithm Based on Deep Learning

Images have many objects in complex background. How to identify these objects and identify the main objects therein and understand the relationship between the main objects and other objects are the focus of this parper. There are many ways to object recognition, but most of them cannot mark the main objects of the image. In this paper, we use improved RCNN [1] network to detect and recognize multi-object in the image. Then we put forward the main objects scoring system to mark the image main objects. The experimental results show that the algorithm not only maintains the superiority of RCNN, but also detects the main objects of the image. We found that the image main objects were related to the size of candidate region and the rarity of objects.
Pre‐liver transplant renal dysfunction and association with post‐transplant end‐stage renal disease: A single‐center examination of updated UNOS recommendations

Simultaneous liver‐kidney allocation protocols allocate dual organs based on a sustained eGFR of 30 mL/min or less. A 2017‐UNOS update includes CKD3 as dual organ candidates but only when the listing eGFR is <30 mL/min while recommending a "safety net" for prioritized kidney listing post‐LT. We retrospectively reviewed adult LTs examine whether the UNOS proposal captured the LT population at highest risk for developing post‐LT ESRD. Among 290 LT recipients, 67 had pre‐LT CKD3, 141 had AKI, of whom 47 required dialysis (<4 weeks). During follow‐up, 25 (8.62%) developed ESRD, while 70 (24.1%) died. In adjusted Cox models, CKD3 had an independent association with post‐LT ESRD (adjusted HR 4.8; P = 0.001), independent of AKI. Interestingly, CKD3 with listing GFR >30 mL/min was still significantly associated with post‐LT ESRD. AKI was associated with reduced post‐LT survival (adjusted HR 1.9; P = 0.02), albeit only in the first‐year post‐LT. Severe AKI‐D was associated with post‐LT ESRD and mortality. The safety net would have captured only 60% of all post‐LT ESRD cases in our cohort. Pre‐LT CKD3 was associated with increased risk of post‐LT ESRD above the recommended cutoff for listing GFR. These findings, if generalizable in larger cohorts have important implications for dual organ allocation.