Miracle-dz/UniFAR-FTUs huggingface dataset:
Soft Tactile Sensor With Multimodal Data Processing for Texture Recognition

In this letter, a soft tactile device with an alternative design approach is presented in tasks of texture recognition using multimodal data processing. This device integrates multiple layers and sensing elements in a soft device. The top layer is covered with a flexible piezoresistive material. The bottom layer is comprised of a soft case and a seven-axis chip within capable of measuring acceleration, angular velocity, and pressure data. The soft tactile sensor is validated with texture recognition tasks using data collected from five textures slid on the sensor with a robotic arm. These experiments are key to validate and characterize the sensor design by analyzing both individual and combined piezoresistive, accelerometer, and angular velocity signals with Bayesian methods. The results show that the recognition accuracy achieved by the sensor is related to the type and combination of data modalities. The highest accuracy achieved is 99.43% by combining piezoresistive and accelerometer data, while the lowest accuracy of 90.12% is obtained with angular velocity data alone. Overall, this work shows that the proposed multimodal soft tactile sensor can improve the performance of recognition tasks by the systematic use of multimodal data.
Isotope Detection in Microwave-Assisted Laser-Induced Plasma

Isotope detection and identification is paramount in many fields of science and industry, such as in the fusion and fission energy sector, in medicine and material science, and in archeology. Isotopic information provides fundamental insight into the research questions related to these fields, as well as insight into product quality and operational safety. However, isotope identification with established mass-spectrometric methods is laborious and requires laboratory conditions. In this work, microwave-assisted laser-induced breakdown spectroscopy (MW-LIBS) is introduced for isotope detection and identification utilizing radical and molecular emission. The approach is demonstrated with stable B and Cl isotopes in solids and H isotopes in liquid using emissions from BO and BO2, CaCl, and OH molecules, respectively. MW-LIBS utilizes the extended emissive plasma lifetime and molecular-emission signal-integration times up to 900 μs to enable the use of low (~4 mJ) ablation energy without compromising signal intensity and, consequently, sensitivity. On the other hand, long plasma lifetime gives time for molecular formation. Increase in signal intensity towards the late microwave-assisted plasma was prominent in BO2 and OH emission intensities. As MW-LIBS is online-capable and requires minimal sample preparation, it is an interesting option for isotope detection in various applications.
Relationship between Participation in Daily Life Activities and Physical Activity in Stroke Survivors: A Protocol for a Systematic Review and Meta-Analysis

Stroke survivors undertake low levels of physical activity and participation in daily life activities, but the correlation between these two domains still carries some degree of uncertainty. This systematic review and meta-analyses-based data synthesis will aim to describe and estimate the relationship between participation in daily life activities and physical activity in stroke survivors. Six databases (MEDLINE/PubMed, Web of Science, Scopus, PEDro, SPORTDiscus, and Rehabilitation & Sport Medicine Source) will be searched. Studies assessing participation alongside physical activity levels in adult stroke survivors in English or Spanish will be included. The study selection, assessment of the risk of bias, and data extraction will be conducted independently by two investigators. If available, correlation values between physical activity and participation outcomes will be extracted. The Hedges–Olkin method will be used for pooling correlation values between participation and physical activity measures. Subgroup analyses will be performed according to the time elapsed since the stroke (i.e., ≤6 months and >6 months). This will be the first systematic review with a meta-analysis to provide information on the relationship between physical activity and participation in stroke survivors. Findings are likely to inform the design of health prevention protocols and the development of healthy behavior change interventions.
Ischemic strokes in COVID-19: risk factors, obesity paradox, and distinction between trigger and causal association

Background and purpose Stroke has been described as a COVID-19 complication. However, its occurrence rate, risk factors, and causal relationships are still not well established. Methods We describe the characteristics of confirmed COVID-19-related strokes among all cases of COVID-19 hospitalized in our health network, from November 1, 2020 to April 30, 2021. Risk factor analysis has been conducted for ischemic stroke (IS), which represents 92% of all confirmed cases of Covid-19-related strokes, and a “causal attribution to infection” classification is provided. Results In all, 62/4105 hospitalized COVID-19 patients had an acute stroke (1.51%). Severe COVID-19 (OR 2.27—CI 1.06–4.77; p = 0.032), atrial fibrillation (OR 3.65—CI 1.63–7.98; p = 0.001), and ischemic heart disease (OR 4.590—CI 1.714–12.137; p = 0.002) proved to be independent risk factors for IS, while obesity was a protective factor (OR 0.90—CI 0.82–0.97; p = 0.012). COVID-19 had a causal role in 32.1% of IS cases, was a relevant cofactor in 28.6% of cases of IS, and was a possible trigger in 39.3% of events. Conclusion Our stroke occurrence rate is consistent with other population-based reports (range 0.34–2.7%). Prespecified peculiar clinical and radiological features allow the distinction between “IS caused by COVID-19” and “IS triggered by COVID-19. ” Clinical history of vascular diseases and risk factors is crucial in determining the risk of IS in patients with COVID-19. However, the protective effect of a BMI > 30 kg/m2 seems to suggest an obesity paradox.
How to perform and write a systematic review and meta-analysis

a systematic review and meta-analysis is considered beneficial when selecting a review methodology that is suitable for a specific research purpose. This paper provides a comprehensive summary of the key points to consider for systematic reviews and meta-analyses to ensure the utility of publications. It covers an overall conceptual understanding, reporting guidelines, and methodological procedures
Implicações no cuidado de um familiar doente: mulheres negras cuidadoras

Introdução: As desvantagens ligadas ao gênero feminino são visualizadas em diversos aspectos da vida, mediante ao patriarcado. É possível compreender que, no caso de mulheres negras, estas se encontram desfavorecidas frente as estruturas sociais, atravessadas por condicionantes de classe, raça e gênero. Além disso, é visto que, em diversos casos, as cuidadoras mulheres, sobretudo, mulheres negras, não escolhem de forma voluntária este papel dentro da conjuntura familiar. Objetivo: Identificar as implicações do cuidado ao familiar adoecido realizado por mulheres negras cuidadoras considerando suas condições socioculturais. Metodologia: Este trabalho é uma revisão integrativa, cuja busca no banco de dados foi realizada em dezembro de 2020, onde 3 resultados foram encontrados na base de dados Web of Science, 48 na base de dados PubMed e 29 na base de dados LILACS. Depois de ler os resumos dos 80 artigos e aplicar os critérios de exclusão, 7 artigos foram selecionados para leitura completa. Finalmente, 4 artigos foram incluídos para análise. Resultados: Apenas um estudo abordou exclusivamente mulheres, e a maioria eram afro-americanos. Dados indicam que, dentro de uma comunidade quilombola, o cuidado com a saúde é repassado do mais velho para o mais novo, como símbolo de respeito aos saberes ancestrais. Além disso, ficou evidente que cuidadores afro-americanos de pessoas com demência precisam de informações de qualidade sobre cuidados e autocuidado, necessitando de recursos em sua comunidade. Conclusão: É possível notar as desigualdades de acordo com as construções históricas, políticas e culturais causadas, para diferenciar homens e mulheres no cuidado familiar. Havendo uma necessidade de debates que tenham como enfoque a população negra, principalmente as cuidadoras, visando estratégias para reduzir sua sobrecarga para cuidar de familiares em adoecimento.
An Approximate Deep Hole Algorithm Based on Dual HKZ-Bases of Lattices

The Covering Radius Problem (CRP) is an important lattice problem. Computing the covering radius of a lattice is a classic problem in the geometry of numbers. In 2004, Micciancio [1] showed that finding collision of some hash function can be reduced to approximate Covering Radius Problem of lattice. Guruswami, Micciancio, and Regev [2] initiated the study for computation complexity of the CRP, and showed that lies in AM, lies in . Peikert[3] showed that lies in coNP in the norm for . The first hardness result of CRP was presented by Haviv and Regev, they obtained there exists some constant such that the problem is -hard in the norm for any suffintly large value of p [4]. In 2013, Micciancio and Voulgaris[5] gave a deterministic time algorithm to solve all the important lattice problems in NP including the Shortest Vector Problem (SVP) [6]and the Closest Vector Problem (CVP). Then, using a randomized polynomial time reduction from CVP to CRP in [2], can be approximately solved in single exponential time. Using the algorithm for Voronoi cell in [5], we can compute the exact value of the covering radius by enumerating all the vertices of the Voronoi cell and selecting the longest. In 2015, Haviv[7] proposed the Remote Set Problem (RSP) on lattices and proved that the relations between the covering radius and the nth successive minimum in norms for .
Deep Learning-Based Recognition of Periodontitis and Dental Caries in Dental X-ray Images

Dental X-ray images are important and useful for dentists to diagnose dental diseases. Utilizing deep learning in dental X-ray images can help dentists quickly and accurately identify common dental diseases such as periodontitis and dental caries. This paper applies image processing and deep learning technologies to dental X-ray images to propose a simultaneous recognition method for periodontitis and dental caries. The single-tooth X-ray image is detected by the YOLOv7 object detection technique and cropped from the periapical X-ray image. Then, it is processed through contrast-limited adaptive histogram equalization to enhance the local contrast, and bilateral filtering to eliminate noise while preserving the edge. The deep learning architecture for classification comprises a pre-trained EfficientNet-B0 and fully connected layers that output two labels by the sigmoid activation function for the classification task. The average precision of tooth detection using YOLOv7 is 97.1%. For the recognition of periodontitis, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve is 98.67%, and the AUC of the precision-recall (PR) curve is 98.38%. For the recognition of dental caries, the AUC of the ROC curve is 98.31%, and the AUC of the PR curve is 97.55%. Different from the conventional deep learning-based methods for a single disease such as periodontitis or dental caries, the proposed approach can provide the recognition of both periodontitis and dental caries simultaneously. This recognition method presents good performance in the identification of periodontitis and dental caries, thus facilitating dental diagnosis.
New Perspectives of Symmetry Conferred by q-Hermite-Hadamard Type Integral Inequalities

The main goal of this work is to provide quantum parametrized Hermite-Hadamard like type integral inequalities for functions whose second quantum derivatives in absolute values follow different type of convexities. A new quantum integral identity is derived for twice quantum differentiable functions, which is used as a key element in our demonstrations along with several basic inequalities such as: power mean inequality, and Holder’s inequality. The symmetry of the Hermite-Hadamard type inequalities is stressed by the different types of convexities. Several special cases of the parameter are chosen to illustrate the investigated results. Four examples are presented.
A New Class of Scaling Matrices for Scaled Trust Region Algorithms

A new class of affine scaling matrices for the interior point Newton-type methods is considered to solve the nonlinear systems with simple bounds. We review the essential properties of a scaling matrix and consider several well-known scaling matrices proposed in the literature. We define a new scaling matrix that is the convex combination of these matrices. The proposed scaling matrix inherits those interesting properties of the individual matrices and satisfies all the desired requirements. The numerical experiments demonstrate the superiority of the new scaling matrix in solving several important test problems.
Contact-aided invariant extended Kalman filtering for robot state estimation

Legged robots require knowledge of pose and velocity in order to maintain stability and execute walking paths. Current solutions either rely on vision data, which is susceptible to environmental and lighting conditions, or fusion of kinematic and contact data with measurements from an inertial measurement unit (IMU). In this work, we develop a contact-aided invariant extended Kalman filter (InEKF) using the theory of Lie groups and invariant observer design. This filter combines contact-inertial dynamics with forward kinematic corrections to estimate pose and velocity along with all current contact points. We show that the error dynamics follows a log-linear autonomous differential equation with several important consequences: (a) the observable state variables can be rendered convergent with a domain of attraction that is independent of the system’s trajectory; (b) unlike the standard EKF, neither the linearized error dynamics nor the linearized observation model depend on the current state estimate, which (c) leads to improved convergence properties and (d) a local observability matrix that is consistent with the underlying nonlinear system. Furthermore, we demonstrate how to include IMU biases, add/remove contacts, and formulate both world-centric and robo-centric versions. We compare the convergence of the proposed InEKF with the commonly used quaternion-based extended Kalman filter (EKF) through both simulations and experiments on a Cassie-series bipedal robot. Filter accuracy is analyzed using motion capture, while a LiDAR mapping experiment provides a practical use case. Overall, the developed contact-aided InEKF provides better performance in comparison with the quaternion-based EKF as a result of exploiting symmetries present in system.
A renormalized modified normalized burn ratio (RMNBR) index for detecting mature rubber plantations with Landsat-8 OLI in Xishuangbanna, China

ABSTRACT A novel phenology-based algorithm, namely the Landsat-derived renormalized modified normalized burn ratio (RMNBR) index, was developed with Xishuangbanna in southern China, also the second-largest national base of natural rubber production. The RMNBR algorithm included two key steps, namely the modification of NBR (or MNBR) by normalizing near infrared (NIR) and two short-wave infrared (SWIR 1/2) bands of Landsat-8 Operational Land Imager (OLI) and, the re-normalization of MNBR between two critical phenological stages of rubber plantations, i.e. defoliation and foliation. It highlighted the temporal differences of surface reflectance of three non-visible bands (i.e. NIR, SWIR 1 and SWIR 2) in canopy density and moisture content of rubber plantations from defoliation to formation during the dry season. Then, the RMNBR was used to identify mature rubber plantations (pixels) in 2018, by combining two auxiliary masks of Landsat-based forest of the same year and topographically-suitable area of rubber trees cultivation. This makes the discrimination of mature rubber plantation straightforward as it only needs to distinguish mature rubber plantations (RMNBR < 0) from other land cover types (RMNBR > 0) within the two critical periods. The phenology-based RMNBR algorithm greatly enriches the remotely-sensed approaches for rubber plantations mapping at the regional scale.
A Simulation and Graph Theoretical Analysis of Certain Properties of Spectral Null Codebooks

: The spectral shaping technique and the design of codes providing nulls at rational sub-multiples of the symbol frequency, as the case with spectral null (SN) codes, have enhanced digital signaling over communication channels as digital mass recorders and metallic cables. The study of the special structure of these codes helps in investigating and analyzing certain of their properties which have been proved and emphasized from a mathematical perspective using graph theory. The cardinality of spectral null codebooks reﬂects the rate of spectral null codes and therefore the amount of transmitted information data. The rate of these codes can also play a role in their error correction capability. The paper presents in different ways the special structure of spectral null codebooks and analyze better their properties. A possible link between these codes and other error correcting codes as the case of Low Density Parity Check (LDPC) is presented and discussed in this paper.
Exaggerated myocardial torsion may contribute to dynamic left ventricular outflow tract obstruction in hypertrophic cardiomyopathy

Abstract Aims Dynamic left ventricular (LV) outflow tract obstruction (LVOTO) is associated with symptoms and increased risk of developing heart failure in hypertrophic cardiomyopathy (HCM). The association of LVOTO and LV twist mechanics has not been well studied in HCM. The aim of the study was to compare the pattern of LV twist in patients with HCM associated with asymmetrical septal hypertrophy with and without LVOTO. Methods and results Echocardiography (including speckle tracking) was performed in 212 patients with HCM, divided according to the absence (n = 130) or presence (n = 82) of LVOTO (defined as peak pressure gradient ≥30 mmHg either at rest and/or with Valsalva manoeuvre). Patients with LVOTO were older, had smaller LV dimensions, a higher LV ejection fraction (LVEF), a longer anterior mitral valve leaflet length, and a higher early transmitral pulsed wave to septal tissue Doppler velocity ratio (E/E′). A univariate analysis showed that peak twist was significantly higher in patients with LVOTO compared with patients without LVOTO (19.7 ± 7.3 vs. 15.7 ± 6.0, P = 0.00015). Peak twist was similarly enhanced in patients with LVOTO, manifesting only during Valsalva (19.2 ± 5.6, P = 0.007) and patients with resting LVOTO (19.9 ± 8.0, P = 0.00004) compared with patients without LVOTO (15.7 ± 6.0). A stepwise forward logistic regression analysis showed that LVEF, LV end-systolic dimension indexed to body surface area, anterior mitral valve leaflet length, E/E′, and peak twist were all independently associated with LVOTO. Conclusion This study demonstrates that increased peak LV twist is independently associated with LVOTO in patients with HCM. Peak twist was similarly exaggerated in patients with only latent LVOTO, suggesting that it may play a contributory role to LVOTO in HCM.
Face anti-spoofing based on ASFF and LBP self-supervision branch

Since the tremendous advancement of face recognition technology, how to detect real human faces from images has gradually captured the attention of researchers. To address the problem that most face anti-spoofing approaches ignore context information and local information about faces, this paper proposes a face anti-spoofing algorithm that fuses multi-scale features and texture features of images. On the one hand, we extract multi-scale features using adaptively spatial feature fusion (ASFF) and polarized self-attention (PSA) mechanism. On the other hand, local binary patterns (LBP) is used to form an auxiliary self-supervision branch to extract image texture difference information. As a final step, end-to-end live detection is achieved by balancing the difference between two different loss functions based on homoscedastic uncertainty. The EER of the presented method is 0.81% and 1.26% on CASIA-FASD and MSU-MFSD, respectively, and the ACER is only 1.64% and 2.07%±1.05% on the second and third protocols of Oulu_NPU, which indicates the validity of the method.
Boundary-Aware Multiscale Learning Perception for Remote Sensing Image Segmentation

For remote sensing image segmentation, the boundaries of objects are difficult to distinguish, which is ignored by most methods. Therefore, it is challenging how to excavate and recover the boundaries of objects accurately. In this article, we propose a boundary-aware multiscale network (BMNet) to solve this problem. The key components of BMNet include the scale attention module (SAM) and boundary guidance module (BGM). Specifically, the SAM is proposed to guide the refinement of multiscale features in a context-aware way. It enhances the discriminability of multiscale features by establishing contextual dependencies, which enables the refinement of the prediction of objects. Then, the BGM is proposed to enable networks to distinguish the boundary of objects. It uses manifold information of features to generate BG maps and forces the network to focus more on the boundary of objects. The effectiveness of the proposed BMNet is demonstrated on two public remote sensing datasets: ISPRS 2-D semantic labeling Potsdam dataset and Vaihingen dataset, where BMNet achieves better segmentation than prevalent methods. Finally, the experimental results indicate that BMNet can produce sharper boundaries of objects to reconstruct more detailed segmentation results.
Saturation of single toroidal number Alfvén modes

The results of numerical simulations are presented to illustrate the saturation mechanism of a single toroidal number Alfvén mode, driven unstable, in a tokamak plasma, by the resonant interaction with energetic ions. The effects of equilibrium geometry non-uniformities and finite mode radial width on the wave-particle nonlinear dynamics are discussed. Saturation occurs as the fast-ion density flattening produced by the radial flux associated to the resonant particles captured in the potential well of the Alfvén wave extends over the whole region where mode-particle power exchange can take place. The occurrence of two different saturation regimes is shown. In the first regime, dubbed resonance detuning, that region is limited by the resonance radial width (that is, the width of the region where the fast-ion resonance frequency matches the mode frequency). In the second regime, called radial decoupling, the power exchange region is limited by the mode radial width. In the former regime, the mode saturation amplitude scales quadratically with the growth rate; in the latter, it scales linearly. The occurrence of one or the other regime can be predicted on the basis of linear dynamics: in particular, the radial profile of the fast-ion resonance frequency and the mode structure. Here, we discuss how such properties can depend on the considered toroidal number and compare simulation results with the predictions obtained from a simplified nonlinear pendulum model.