Miracle-dz/UniFAR-FTUs huggingface dataset:
Carpal Tunnel Syndrome Effects on Grip Force Coordination

This study investigated the effects of carpal tunnel syndrome (CTS) on the coordination between grip force on and the force applied with a hand tool. A simulated tool device was developed to measure pinch grip force exerted on the tool and the force applied with the tool to a workpiece. Two measures of grip force coordination efficiency were calculated for seven subjects with diagnoses of carpal tunnel syndrome and seven controls. The dependent measures reflected subjects' abilities to (1) modulate grip force in parallel with the tool application force and (2) minimize the ratio of grip force to application force when dynamically applying forces with the tool. The parallel modulation of grip force with application force was 12% lower (p < 0.05) and the ratio of grip force to application force was 54% higher (p < 0.05) for the CTS group than for the controls. These results suggest that individuals with carpal tunnel syndrome lose some ability to efficiently coordinate grip force with tool application force.
Convex analysis of discrete-time uncertain H/sub infinity / control problems

Two classical problems involving discrete-time systems are analyzed. The first one concerns the quadratic stabilizability with uncertainties in convex bounded domains, which naturally covers the important class of interval matrices. In that problem, there is no need to introduce any kind of matching conditions, which is an important improvement compared with other results available in the literature. The second problem is defined by simply adding to the first problem some prespecified closed-loop transfer function H/sub infinity / norm bound. Assuming the state is available for feedback, the geometry of both problems is thoroughly analyzed. They turn out to be convex on the parameter space. <<ETX>>
Activity types for X-ray candidate AGN from SDSS

Abstract The Joint Catalogue of Hamburg ROSAT Sources (HRC/BHRC) is the result of merging of HRC and BHRC catalogs built on the basis of optical identifications of ROSAT BSC and ROSAT FSC. Altogether, 8132 sources are present. Based on this catalogue, we have compiled a sample of ROSAT AGN, including candidate ones. In this paper we classify candidate AGN (those that previously had not been spectroscopically classified) by their activity type. The sample contains 955 objects with count rate of photons CR>0.04 ct/s in the area with galactic latitudes |b|>30 and declinations δ>0, however only 217 objects have SDSS DR10 spectra. The classification led to the following results: 95 AGN, 71 absorption-line galaxies, 42 stars, and 9 unclassified objects.
Some mathematical models in quantum chemistry and uncertainty quantification

The contributions of this thesis work are two fold. The first part deals with the study of local defects in crystalline materials. Chapter 1 gives a brief overview of the main models used in quantum chemistry for electronic structure calculations. In Chapter 2, an exact variational model for the description of local defects in a periodic crystal in the framework of the Thomas-Fermi-von Weisz"acker theory is presented. It is justified by means of thermodynamic limit arguments. In particular, it is proved that the defects modeled within this theory are necessarily neutrally charged. Chapters 3 and 4 are concerned with the so-called spectral pollution phenomenon. Indeed, when an operator is discretized, spurious eigenvalues which do not belong to the spectrum of the initial operator may appear. In Chapter 3, we prove that standard Galerkin methods with finite elements discretization for the approximation of perturbed periodic Schrodinger operators are prone to spectral pollution. Besides, the eigenvectors associated with spurious eigenvalues can be characterized as surface states. It is possible to circumvent this problem by using augmented finite element spaces, constructed with the Wannier functions of the periodic unperturbed Schr"odinger operator. We also prove that the supercell method, which consists in imposing periodic boundary conditions on a large simulation domain containing the defect, does not produce spectral pollution. In Chapter 4, we give a priori error estimates for the supercell method. It is proved in particular that the rate of convergence of the method scales exponentiall with respect to the size of the supercell. The second part of this thesis is devoted to the study of greedy algorithms for the resolution of high-dimensional uncertainty quantification problems. Chapter 5 presents the most classical numerical methods used in the field of uncertainty quantification and an introduction to greedy algorithms. In Chapter 6, we prove that these algorithms can be applied to the minimization of strongly convex nonlinear energy functionals and that their convergence rate is exponential in the finite-dimensional case. We illustrate these results on obstacle problems with uncertainty via penalized formulations
Convergence of the Kähler–Ricci flow on Fano manifolds

Abstract In this article, we give an alternative proof for the convergence of the Kähler﻿–Ricci flow on a Fano manifold (M,﻿ J). The proof differs from the one in our previous paper [J. Amer. Math. Sci. 17 (2006), 675﻿–699]. Moreover, we generalize the main theorem given there to the case that (M,﻿ J) may not admit any Kähler–Einstein metrics.
Analysis of the Positive Effect of Short Video on the Audience

As a form of media practice, short videos are favored by users for their diverse content, strong visual impact, low production costs, fast dissemination, and easy sharing. In recent years, with the help of the development of network communication technology, short video platforms have rapidly grown into powerful communication media. Although short video, the rapidly developing new media, will inevitably have negative problems, it still brings quite positive effects to the development of society. This paper analyzes the positive effect of short videos on audiences from three perspectives: the improvement of short video audiences’ moral literacy, the improvement of public health, and the development of social culture, tourism and education.
Assessing the in vitro efficacy of biocontrol agents and oil cakes against basal rot of onion incited by Fusarium oxysporum f.sp. cepae

Onions are an important vegetable crop, which is infected by many soils and foliar pathogens. Among them, Fusarium Basal Rot (FBR) causes yield losses of up to 50 per cent in the field and 30 to 40 per cent during post - harvest storage of bulbs. For management of basal rot of onion, the efficacy of native antagonists such as six different Trichoderma sp. (T 1 - T 6 ), five different Bacillus sp. (B 1 - B 5 ) and five different oil cakes was assessed against the Fusarium oxysporum f.sp. cepae under in vitro condition. Among them, T 3 collected from Kulithalai recorded maximum virulence as well as dark green sporulation with conidia length of 2.68 – 3.25 and breadth of 2.54 - 3. 46µ. Among the tested isolates, In the case of B acillus sp. , isolate B 4 recorded the maximum inhibition zone (66.16%), followed by B. subtilis (B 5 ), which recorded a (59.03%) inhibition on the mycelial growth. Among the five different oil cakes, the filtrates of neem cake showed a maximum inhibition zone against F. oxysporum f.sp. cepae of 1.29 cm @ 15% concentration, followed by groundnut cake at 1.36 cm @ 30% concentration. Hence the different control measures, Trichoderma sp. showed critically acclaimed performance under in vitro than others. The combined application of Trichoderma sp , Bacillus sp and neem oilcake significantly inhibited the growth of basal rot of onion due to the presence of the antimicrobial property.
APPROXIMATE CONTROLLABILITY OF FRACTIONAL SEMI-LINEAR DELAY DIFFERENTIAL CONTROL SYSTEM WITH RANDOM IMPULSE

The approximate controllability of a class of fractional order semi-linear delay differential control systems with random impulse is investigated in this study under the natural premise that the linear system is approximately controllable. The existence and uniqueness of the mild solution to the above-mentioned system were determined by using Banach contraction principle. To demonstrate our analytical ﬁndings, we present an example.
Exploring Spurious Learning in Self-Supervised Representations

Recent empirical studies have found inductive biases in supervised learning toward simple features that may be spuriously correlated with the label, resulting in suboptimal performance on minority subgroups. Despite the growing popularity of methods which learn representations from unlabeled data, it is unclear how potential spurious features may be manifested in the learnt representations. In this work, we explore whether recent Self-Supervised Learning (SSL) methods would produce representations which exhibit similar behaviors under spurious correlation. First, we show that classical approaches in combating spurious correlations, such as dataset re-sampling during SSL, do not consistently lead to invariant representation. Second, we find that spurious information is represented disproportionately heavily in the later layers of the encoder. Motivated by these findings, we propose a method to remove spurious information from these representations during pretraining, by pruning or re-initializing later layers of the encoder. We find that our method produces representations which outperform the baseline on three datasets, without the need for group or label information during SSL.
Development of a New Lightweight Encryption Algorithm

—Due to the growing need to use devices with low hardware resources in everyday life, the likelihood of their susceptibility to various cyber-attacks increases. In this regard, one of the methods to ensure the security of information circulating in these devices is encryption. For devices with small hardware resources, the most applicable is low-resource (lightweight) cryptography. This article introduces a new lightweight encryption algorithm, ISL-LWS (Information Security Laboratory – lightweight system), designed to protect data on resource-constrained devices. The encryption algorithm is implemented in the C++ programming language. The paper presents the statistical properties of ciphertexts obtained using the developed algorithm. For the experimental testing for statistical security, the sets of statistical tests by NIST and D. Knuth were used. Separately, the ISL-LWS algorithm was tested for avalanche effect properties. The obtained results of statistical tests were compared with the Present and Speck modern lightweight algorithms. The study and comparative analysis of the speed of encryption and key generation of the three algorithms were carried out on the Arduino Uno R3 board.
ModHE: Modular Homomorphic Encryption Using Module Lattices: Potentials and Limitations

The promising field of homomorphic encryption enables functions to be evaluated on encrypted data and produce results for the same computations done on plaintexts. It, therefore, comes as no surprise that many ventures at constructing homomorphic encryption schemes have come into the limelight in recent years. Most popular are those that rely on the hard lattice problem, called the Ring Learning with Errors problem (RLWE). One major limitation of these homomorphic encryption schemes is that in order to securely increase the maximum multiplicative depth, they need to increase the polynomial-size (degree of the polynomial ring) thereby also ncreasing the complexity of the design. We aim to bridge this gap by proposing a homomorphic encryption (HE) scheme based on the Module Learning with Errors problem (MLWE), ModHE that allows us to break the big computations into smaller ones. Given the popularity of module lattice-based post-quantum schemes, it is an evidently interesting research endeavor to also formulate module lattice-based homomorphic encryption schemes. While our proposed scheme is general, as a case study, we port the well-known RLWE-based CKKS scheme to the MLWE setting. The module version of the scheme completely stops the polynomial-size blowups when aiming for a greater circuit depth. Additionally, it presents greater opportunities for designing flexible, reusable, and parallelizable hardware architecture. A hardware implementation is provided to support our claims. We also acknowledge that as we try to decrease the complexity of computations, the amount of computations (such as relinearizations) increases. We hope that the potential and limitations of using such a hardware-friendly scheme will spark further research.
Development of Zn–Mg–Ca Biodegradable Dual-Phase Alloys

In this paper, in order to achieve the development of a novel biodegradable dual-phase alloy in a Ca–Mg–Zn system, the establishment of the control strategy of degradation behavior of alloys composed of two phases was attempted by the control of alloy composition, constituent phases, and microstructure. By combining two phases with different dissolution behavior, biodegradable alloys are expected to exhibit multiple functions. For example, combining a suitable slow dissolving phase with a faster dissolving second phase may allow for dynamical concavities formation during immersion on the surface of the alloy, assisting the invasion and establishment of bone cells. Without the careful control of the microstructure, however, there is a risk that such dual-phase alloy rapidly collapses before the healing of the affected area. In this study, ten two-phase alloys consisting of various different phases were prepared and their degradation behaviors were examined. Consequently, it was found that by combining the IM3 and IM1 intermetallic phases with the compositions of Ca2Mg5Zn13 and Ca3Mg4.6Zn10. 4, the expected degradation behavior can be obtained.
Reinforcement Learning-based Aspect Term Extraction using Dilated Convolutions and Differential Equation Initialization

—Aspect term extraction is a crucial subtask in aspect-based sentiment analysis that aims to discover the aspect terms presented in a text. In this paper, a method for ATE is proposed that employs dilated convolution layers to extract feature vectors in parallel, which are then concatenated for classification downstream. Reinforcement learning is used to save the ATE model from imbalance classification, in which the training procedure is posed as a sequential decision-making process. The samples are the states; the network, and the agent; and the agent gets a more significant reward/penalty for correct/incorrect classification of the minority class compared with the majority class. The training phase, which typically employs gradient-based approaches, including back-propagation for the learning process, is tackled. Thus, it suffers from some drawbacks, including sensitivity to initialization. A novel differential equation (DE) approach that uses a clustering-based mutation operator to initiate the BP process is presented. Here, a winning cluster is identified for the current DE population, and a new updating strategy is used to generate candidate solutions. The BERT model is employed as word embedding, which can be included in a downstream task and fine-tuned as a model, while BERT can capture various linguistic properties. The proposed method is evaluated on two English datasets (Restaurant and Laptop) and has achieved outstanding results, surpassing other deep models (Restaurant: Precision 85.44%, F1-score 87.35%; Laptop: Precision 80.88%, F1-score 80.78%).
Effect of various pretreatment and temperature on chemical properties of sweet potato flour

In this study, sweet potato slices were pretreated with various pretreatments such as 0.1% w/v potassium metabisulfite (KMS), 1% w/v calcium chloride (CaCl 2 ), and blanching at 80 °C for 5 min. These pretreated slices were dried in a mechanical tray dryer at 50, 55, 60, and 65 °C at a constant drying air velocity of 2 m/s in the drying chamber. The dried samples were ground into the flour and subjected to various chemical analyses such as protein, starch, total sugar, total soluble solids, ash, fiber, and colour. According to results obtained, protein and starch content were found to decrease with an increase in drying temperatures. At 60 °C, the total sugar content was found to be highest for CaCl 2 pretreated samples. Total soluble solids (TSS) were found to increase with drying temperature and to be highest for CaCl 2 pretreated samples at 65°C. Ash content was found to be highest for CaCl 2 pretreated samples and decreases with drying temperature. The CaCl 2 pretreated sample was found to be best in terms of studied characteristics and can be used as an ingredient in food formulations.
Nondestructive Methods of Pathogen Detection: Importance of Mosquito Integrity in Studies of Disease Transmission and Control

Mosquitoes are vectors of many pathogens, including viruses, protozoans, and helminths, spreading these pathogens to humans as well as to wild and domestic animals. As the identification of species and the biological characterization of mosquito vectors are cornerstones for understanding patterns of disease transmission, and the design of control strategies, we conducted a literature review on the current use of noninvasive and nondestructive techniques for pathogen detection in mosquitoes, highlighting the importance of their taxonomic status and systematics, and some gaps in the knowledge of their vectorial capacity. Here, we summarized the alternative techniques for pathogen detection in mosquitoes based on both laboratory and field studies. Parasite infection and dissemination by mosquitoes can also be obtained via analyses of saliva- and excreta-based techniques or of the whole mosquito body, using a near-infrared spectrometry (NIRS) approach. Further research should be encouraged to seek strategies for detecting target pathogens while preserving mosquito morphology, especially in biodiversity hotspot regions, thus enabling the discovery of cryptic or new species, and the determination of more accurate taxonomic, parasitological, and epidemiological patterns.
Understanding the Concept of Uncertainty in Patients With Indolent Lymphoma

Review of the literature revealed that uncertainty is being managed in breast cancer survivors and patients with prostate cancer with watchful waiting or active surveillance. The chronic and incurable nature of indolent lymphoma, coupled with symptoms that are vague and transient, are possible sources of uncertainty in patients diagnosed with lymphoma. Nursing interventions should be aimed at assessing, educating, and supporting patients as they work toward a new view of life that incorporates uncertainty. Conclusions: Literature about the experience of patients diagnosed with lymphoma is lacking. The concept of uncertainty should be recog-nized by clinicians as an important aspect of living with indolent lymphoma because it is present throughout the disease trajectory and, if left untreated, can have a negative effect on patients’ overall quality of life. Implications for Nursing: Uncertainty should become an ongoing component of nursing assessment in patients diagnosed with lymphoma. Further research is needed to support the application of uncertainty theory to this patient population.
Krill Herd Algorithm for Live Virtual Machines Migration in Cloud Environments

—Green cloud computing is a modern approach that provides pay-per-use information and communication technologies with a minimal carbon footprint. Cloud computing enables users to access computing resources without the need for local servers or personal devices to operate applications. It allows businesses and developers to access infrastructure and hardware resources conveniently. Consequently, this results in a growing demand for data centers. It becomes crucial in maintaining economic and environmental sustainability as data centers use disproportionate energy. This points to sustainability and energy consumption as being important topics for research in cloud computing. This paper introduces a two-tiered VM placement algorithm. A queuing model is proposed at the first level to handle many VM requests. Models such as cloud simulation are easily implemented and validated using this model. It also provides an alternate method for allocating tasks to servers. Next, a multi-objective VM placement algorithm is proposed based on the Krill Herd (KH) algorithm. Basically, it maintains a balance between energy consumption and resource utilization.
Spatio-Temporal Features based Human Action Recognition using Convolutional Long Short-Term Deep Neural Network

—Recognition of human intention is crucial and challenging due to subtle motion patterns of a series of action evolutions. Understanding of human actions is the foundation of many applications, i.e., human robot interaction, smart video monitoring and autonomous driving etc. Existing deep learning methods use either spatial or temporal features during training. This research focuses on developing a lightweight method using both spatial and temporal features to predict human intention correctly. This research proposes Convolutional Long Short-Term Deep Network (CLSTDN) consists of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). CNN uses Inception-ResNet-v2 to classify object specific class categories by extracting spatial features and RNN uses Long Short-Term Memory (LSTM) for final prediction based on temporal features. Proposed method was validated on four challenging benchmark dataset, i.e., UCF Sports, UCF-11, KTH and UCF-50. Performance of the proposed method was evaluated using seven performance metrics, i.e., accuracy, precision, recall, f-measure, error rate, loss and confusion matrix. Proposed method showed better results comparing with existing research results. Proposed method is expected to encourage researchers to use in future for real time implications to predict human intentions more robustly.
Les systèmes de Pfaff, à cinq variables et les équations aux dérivées partielles du second ordre

© Gauthier-Villars (Éditions scientifiques et médicales Elsevier), 1910, tous droits réservés. L’accès aux archives de la revue « Annales scientifiques de l’É. N.S. » (http://www. elsevier.com/locate/ansens) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.