Miracle-dz/UniFAR-FTUs huggingface dataset:
Formation of features based on computational topology methods

The use of traditional methods of algebraic topology to obtain information about the shape of an object is associated with the problem of forming a small amount of information, namely, Betti numbers and Euler characteristics. The central tool for topological data analysis is the persistent homology method, which summarizes the geometric and topological information in the data using persistent diagrams and barcodes. Based on persistent homology methods, topological data can be analyzed to obtain information about the shape of an object. The construction of persistent barcodes and persistent diagrams in computational topology does not allow one to construct a Hilbert space with a scalar product. The possibility of applying the methods of topological data analysis is based on mapping persistent diagrams into a Hilbert space; one of the ways of such mapping is a method of constructing a persistence landscape. It has an advantage of being reversible, so it does not lose any information and has persistence properties. The paper considers mathematical models and functions for representing persistence landscape objects based on the persistent homology method. Methods for converting persistent barcodes and persistent diagrams into persistence landscape functions are considered. Associated with persistence landscape functions is a persistence landscape kernel that forms a mapping into a Hilbert space with a dot product. A formula is proposed for determining a distance between the persistence landscapes, which allows the distance between images of objects to be found. The persistence landscape functions map persistent diagrams into a Hilbert space. Examples of determining the distance between images based on the construction of persistence landscape functions for these images are given. Representations of topological characteristics in various models of computational topology are considered. Results for one-parameter persistence modules are extended onto multi-parameter persistence modules.
Intergenerational analysis of cash waqf behavior: lessons learned from Indonesia

Purpose The proponents of cash waqf speak highly about its huge potential for mobilizing the third sector of the economy to fund the socio-economic development agenda. However, the under-collection issue has been characterizing the cash waqf movement globally. This study aims to examine how understanding the distinct cash waqf donating behavior across different generations has the potential to address the problem. Design/methodology/approach This study extends the theory of planned behavior by adding religiosity and knowledge variables into the standard model, using the partial least square structural equation modeling. A survey is conducted on 684 respondents representing the main provinces in Indonesia and four major generations (Baby Boomers [BB], Generations X, Y and Z). Findings Religiosity, Knowledge, Attitude, Subjective Norms and Perceived Behavioral Control directly or indirectly affect cash waqf intention. The effect is contingent on the characteristics of generations. Research limitations/implications This study covers only the Indonesian case with limited coverage of the more heterogeneous provinces in the country. The sample distribution for BB can also be enlarged. Practical implications Cash waqf institutions (government and private) should apply the dynamic segmenting strategy, where the diversification of the promotion, marketing, awareness and approaches are contingent on the different characteristics of each generation. Originality/value To the best of the authors’ knowledge, this is the first study evaluating the intergenerational determinants of Intention toward cash waqf, particularly in Indonesia.
Sur l'établissement des équations de l'hydrodynamique des fluides relativistes dissipatifs. I. — L'équation de Boltzmann relativiste

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A new type of chaotic generator

A new type of chaotic generator is studied by constructing a three_segment piec ewise_linear odd function with variable breakpoint α. The characteristic of the chaotic generator presented is that when the breakpoint α varies in th e range of 0<α≤1, there is a route to chaos through period_doubling bifurcations, and the doubl e_ layer single spiral, single_layer single spiral, double_layer double spiral and single_layer double spiral chaotic attractors can be generated. In particular, the double-layer single spiral and double-layer double spiral are found in our circuit experiment for the first time so far as we know. The b ifurca tion diagram, Lyap unov exponents λ_1,λ_2,λ_3, maximal Lyapunov exponent λ_maxand the spectrum of the single_layer double spiral and double-layer double spiral are also investigated. The associated electronic circuit is designed and the experimental result is given, which is ver ified by computer simulation and circuit experiment.
The Sustainable Rural Industrial Development under Entrepreneurship and Deep Learning from Digital Empowerment

This paper aims to realize the planning of resource utilization and development of rural industries endowed by digitalization under entrepreneurship. First, the global classic practical experience of digitizing rural industries is studied, and the development model of existing rural industries is captured from the perspective of entrepreneurship. Second, the influencing factors of rural industrial development are extracted, the structure of resource development is analyzed, and a Neural Network (NN) model of industrial development aiming at expected per capita annual income is established. In addition, a Genetic Algorithm (GA) is introduced to learn the weights of influencing factors in the model. The structure of the NN is determined through extensive experiments. Finally, conclusions are drawn through the simulation and experiment of NN and GA. Tourism, infrastructure, and transportation planning have weights of 7.79, 5.6, and 6.4, respectively, and these three sectors should be vigorously developed. In the future, the weight values of these factors can be used for reference, and the development of various aspects can be refined. This paper clarifies the core of industrial development in rural revitalization based on the perspective of entrepreneurship. The problem of how to realize the optimal utilization of resources is solved scientifically and rationally through the mathematical model. The introduction of deep learning algorithm models provides data support for resource allocation and industrial planning in the process of digital empowerment of traditional rural industries, which is of great value and significance for exploring digital models for rural industry development.
IL-22-Activated MUC13 Impacts on Colonic Barrier Function through JAK1/STAT3, SNAI1/ZEB1 and ROCK2/MAPK Signaling

Overexpression of the transmembrane mucin MUC13, as seen in inflammatory bowel diseases (IBD), could potentially impact barrier function. This study aimed to explore how inflammation-induced MUC13 disrupts epithelial barrier integrity by affecting junctional protein expression in IBD, thereby also considering the involvement of MUC1. RNA sequencing and permeability assays were performed using LS513 cells transfected with MUC1 and MUC13 siRNA and subsequently stimulated with IL-22. In vivo intestinal permeability and MUC13-related signaling pathways affecting barrier function were investigated in acute and chronic DSS-induced colitis wildtype and Muc13−/− mice. Finally, the expression of MUC13, its regulators and other barrier mediators were studied in IBD and control patients. Mucin knockdown in intestinal epithelial cells affected gene expression of several barrier mediators in the presence/absence of inflammation. IL-22-induced MUC13 expression impacted barrier function by modulating the JAK1/STAT3, SNAI1/ZEB1 and ROCK2/MAPK signaling pathways, with a cooperating role for MUC1. In response to DSS, MUC13 was protective during the acute phase whereas it caused more harm upon chronic colitis. The pathways accounting for the MUC13-mediated barrier dysfunction were also altered upon inflammation in IBD patients. These novel findings indicate an active role for aberrant MUC13 signaling inducing intestinal barrier dysfunction upon inflammation with MUC1 as collaborating partner.
Towards Safe Robotic Agricultural Applications: Safe Navigation System Design for a Robotic Grass-Mowing Application through the Risk Management Method

Safe navigation is a key objective for autonomous applications, particularly those involving mobile tasks, to avoid dangerous situations and prevent harm to humans. However, the integration of a risk management process is not yet mandatory in robotics development. Ensuring safety using mobile robots is critical for many real-world applications, especially those in which contact with the robot could result in fatal consequences, such as agricultural environments where a mobile device with an industrial cutter is used for grass-mowing. In this paper, we propose an explicit integration of a risk management process into the design of the software for an autonomous grass mower, with the aim of enhancing safety. Our approach is tested and validated in simulated scenarios that assess the effectiveness of different custom safety functionalities in terms of collision prevention, execution time, and the number of required human interventions.
An Innovative Undergraduate Medical Curriculum Using Entrustable Professional Activities

The need to educate medical professionals in changing medical organizations has led to a revision of the Radboudumc's undergraduate medical curriculum. Entrustable professional activities (EPAs) were used as a learning tool to support participation and encourage feedback-seeking behavior, in order to offer students the best opportunities for growth. This paper describes the development of the Radboudumc's EPA-based Master's curriculum and how EPAs can facilitate continuity in learning in the clerkships. Four guiding principles were used to create a curriculum that offers possibilities for the students’ development: (1) working with EPAs, (2) establishing entrustment, (3) providing continuity in learning, and (4) organizing smooth transitions. The new curriculum was designed with the implementation of EPAs and an e-portfolio, based on these 4 principles. The authors found that the revised curriculum corresponds to daily practice in clerkships. Students used their e-portfolios throughout all clerkships, which stimulates feedback-seeking behavior. Moreover, EPAs promote continuity in learning while rotating clerkships every 1 to 2 months. This might encourage curriculum developers to use EPAs when aiming for greater continuity in the development of students. Future research needs to focus on the effect of EPAs on transitions across clerkships in order to further improve the undergraduate medical curriculum.
Performance Modeling of an NR-U and WiFi Coexistence System Using the NR-U Category-4 LBT Procedure and 802.11e EDCA Mechanism in the Presence of Hidden Nodes

This article studies the performance modeling of an NR-U and WiFi coexistence system using the NR-U category-4 listen-before-talk (LBT) procedure and 802.11e enhanced distributed channel access (EDCA) mechanism in the presence of hidden nodes. 3-D Markov models are first developed to describe the NR-U category-4 LBT procedure for a priority-<inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> queue of an NR-U gNB and the 802.11e EDCA mechanism for an AC-<inline-formula> <tex-math notation="LaTeX">${q}$ </tex-math></inline-formula> queue of a WiFi AP, taking into account the effects of hidden nodes and the transmission of different-priority data. Based on the Markov models, theoretical models are derived for analyzing the mean throughput of a priority-<inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> queue in an NR-U gNB and that of an AC-<inline-formula> <tex-math notation="LaTeX">${q}$ </tex-math></inline-formula> queue in a WiFi AP as well as the mean transmission delay of an NR-U priority-<inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> data packet and that of a WiFi AC-<inline-formula> <tex-math notation="LaTeX">${q}$ </tex-math></inline-formula> data packet. The derived theoretical performance models are validated through simulation results. Based on the performance models, the impacts of major system parameters on the system performance are investigated, including the density of NR-U gNBs, the sensing distance and channel transmission rate of an NR-U gNB, and the data packet arrival rate at an NR-U gNB.
Invariants intégraux pour l'indexation d'images omnidirectionnelles

The present study proposes an innovative approach to mobile robot’s localization using omnidirectionnal image indexation. The localization is qualitative and the robot has to determine the room it is situating in. Indexation is completed thanks to integral invariants computed on omnidirectionnal images. Our method starts from the Haar integral to which we include a model of the omnidirectionnal sensor. The integral approach allows us to cope simply with the sensor geometry and with the robot’s movements to compute the invariant. The robustness of this invariant to the movements of the robot in a given room is improved when compared to an histogram based method.
Deep Learning-Based Speech Specific Source Localization by Using Binaural and Monaural Microphone Arrays in Hearing Aids

A deep learning-based method is proposed for jointly detecting and localizing speech sources in a complex acoustic scene by using microphones of a hearing aid. Motivated by the human auditory system, peripheral preprocessing is applied on the microphone signals to obtain auditory subband signals that serve as input to the proposed deep neural network for detecting and localizing speech sources. In the proposed neural network, a combination of residual and dense aggregation learning is utilized rather than the conventional residual learning to preserve and reuse the spatial representations at the output layers. This process is performed to improve the gradient flow in deeper layers, in the training stage. The learning curves show that the proposed residual-dense aggregation mapping do improve the speed and accuracy of the convergence. The proposed model shows good performance in joint speech source detection and localization using a binaural microphone array (i.e., three channels at each side) but also using a monaural microphone array (i.e., four channels at the right side) despite of the short distances between the microphones. The proposed methods also outperform neural networks that are directly using STFT components of the binaural or monaural microphone arrays. In addition, the proposed models extended with learnable peripheral processing show slightly improved in detection and localization scores compared to the proposed models using the plain auditory subband signals, in both the binaural and monaural microphone arrays but only so, when the learnable peripheral processing is initialized with parameters stemming from human peripheral processing.
Studies in Resource Allocation Processes.

One of the central questions of economics relates to the coordination of individual units within a large organization to achieve the central objectives of that organization. This book examines the problems involved in allocating resources in an economic system where decision-making is decentralized into the hands of individuals and individual enterprises. The decisions made by these economic agents must be coordinated because the input decisions of some must eventually equal the output decisions of others. Coordination arises naturally out of the mathematical theory of optimization but there is still the question of how it can be achieved in practice with dispersed knowledge. The essays here explore the many facets of this problem. Nine papers are grouped under the title 'Economies with a single maximand'. They include papers on static and dynamic optimization, decentralization within firms, and nonconvexities in optimizing problems. Fourteen papers are concerned with 'Economies with multiple objectives'. Among the topics covered here are stability of competitive equilibrium, stability in oligopology, and dynamic shortages. The final part of the book includes three papers on informational efficiency and informationally decentralized systems. Leonid Hurwitcz is the Nobel Prize Winner 2007 for The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, along with colleagues Eric Maskin and Roger Myerson, for his work on the effectiveness of markets.
Effect of Regular Electrotherapy on Spinal Flexibility and Pain Sensitivity in Patients with Chronic Non-Specific Neck Pain and Low Back Pain: A Randomized Controlled Double-Blinded Pilot Trial

Background and Objectives: Chronic neck pain and low back pain are common conditions in high-income countries leading to social and medical problems such as invalidity and decreased quality of life. The aim of this study was to investigate the effect of supra-threshold electrotherapy on pain level, subjective feeling of disability, and spinal mobility in patients with chronic pain in the spinal cord. Materials and Methods: 11 men and 24 women with a mean age of 49 years were randomly divided into three groups: group 1, “therapy”: supra-threshold electrotherapy was applied on the whole back after electrical calibration; group 2, “control”: electrical calibration without successive electrotherapy; group 3, “control of control”: no stimulation. Sessions were performed once a week and six times in total, each lasting 30 min. The numeric pain rating scale (NRS), cervical and lumbar range of motion (ROM), as well as disability in daily live were investigated before and after the sessions using questionnaires (Neck Disability Index, Roland Morris Questionnaire, Short-form Mc Gill Pain Questionnaire (SF-MPQ)). Results: Spinal mobility improved significantly in the lumbar anteflexion (baseline mean, 20.34 ± SD 1.46; post session mean, 21.43 ± SD 1.95; p = 0.003) and retroflexion (baseline mean, 13.68 ± SD 1.46; post session mean, 12.05 ± SD 1.37; p = 0.006) in the group receiving electrotherapy. Pain levels measured by the NRS and disability-questionnaire scores did not differ significantly before and after treatment in any of the groups. Conclusions: Our data indicate that regular supra-threshold electrotherapy for six times has a positive effect on lumbar flexibility in chronic neck pain and low back pain patients, whereas pain sensation or subjective feeling of disability remained unchanged.
L-Shape-Model-Based Vehicle Tracking With Joint Kinematic and Geometric Estimation Using Lidar

In this article, the problem of tracking vehicles using lidar sensors mounted on an ego-vehicle is addressed. Due to line-of-sight limitations, the back (or front) of a vehicle as seen by the lidar on the ego-vehicle behind (or ahead of) it is often modeled as L-shaped. In this article, an L-shape-based vehicle tracking algorithm with joint kinematic and geometric estimation is presented. By feeding back tracking results to L-shape fitting, an L-shape detection method that is robust to outliers is proposed. In the L-shape tracker currently available in the literature, the kinematic and geometric states of the L-shape model are separately estimated and maintained. However, the kinematic and geometric states are not independent since the orientation of a vehicle influences its velocity. Also, the dependence between the kinematic and the geometric states is caused by anchor-point (the closest point on the vehicle being tracked) switching, which is required during changes in the relative position between vehicles. To address this limitation, the proposed L-shape tracker exploits this dependence and estimates the kinematic and geometric states jointly. The proposed L-shape-model-based tracking algorithm is evaluated and compared with the original algorithm using the real traffic data from the KITTI datasets. The results demonstrate the superiority of the proposed algorithm over the original algorithm in terms of L-shape detection and tracking accuracies.
Influence of Crosslinking Methods on Biomimetically Mineralized Collagen Matrices for Bone-like Biomaterials

To assist in bone defect repair, ideal bone regeneration scaffolds should exhibit good osteoconductivity and osteoinductivity, but for load-bearing applications, they should also have mechanical properties that emulate those of native bone. The use of biomimetic processing methods for the mineralization of collagen fibrils has resulted in interpenetrating composites that mimic the nanostructure of native bone; however, closely matching the mechanical properties of bone on a larger scale is something that is still yet to be achieved. In this study, four different collagen crosslinking methods (EDC-NHS, quercetin, methacrylated collagen, and riboflavin) are compared and combined with biomimetic mineralization via the polymer-induced liquid-precursor (PILP) process, to obtain bone-like collagen-hydroxyapatite composites. Densified fibrillar collagen scaffolds were fabricated, crosslinked, and biomimetically mineralized using the PILP process, and the effect of each crosslinking method on the degree of mineralization, tensile strength, and modulus of the mineralized scaffolds were analyzed and compared. Improved modulus and tensile strength values were obtained using EDC-NHS and riboflavin crosslinking methods, while quercetin and methacrylated collagen resulted in little to no increase in mechanical properties. Decreased mineral contents appear to be necessary for retaining tensile strength, suggesting that mineral content should be kept below a percolation threshold to optimize properties of these interpenetrating nanocomposites. This work supports the premise that a combination of collagen crosslinking and biomimetic mineralization methods may provide solutions for fabricating robust bone-like composites on a larger scale.
Assessment of Hydration, Nutritional Status and Arterial Stiffness in Hypertensive Chronic Kidney Disease Patients

The aim of this cross-sectional study was to determine the body fluid volume in patients diagnosed with both chronic kidney disease (CKD) and arterial hypertension (AH), and to investigate the relationship between fluid overload (FO), nutritional status and arterial stiffness in this specific patient population. A total of 169 participants with CKD and AH were enrolled in the study, and data on general parameters, comorbidities, medication use, and laboratory parameters were collected. Body composition was assessed with a Tanita MC 780 device, and data on the central and peripheral systolic and diastolic blood pressure, as well as pulse wave velocity (PWV) and the augmentation index (AIx) were collected with an IEM Mobil-O-Graph 24 h ambulatory blood pressure monitor, which was based on oscillometry. The Mediterranean Diet Serving Score (MDSS) questionnaire was used to determine the adherence to the Mediterranean diet (MeDi). Our results showed that the significant positive predictors of hydration status were the use of diuretics and oral hypoglycemic agents, whereas the negative predictors were female sex, higher body mass index level and use of two or more antihypertensives in the form of a single-pill combination. We also found differences in blood pressure and arterial stiffness parameters in relation to volume status, along with differences based on the presence of diabetes mellitus (DM). In conclusion, these results call for a higher awareness of volume status in the care of CKD patients with AH, especially in those with diabetes mellitus.