Miracle-dz/UniFAR-FTUs huggingface dataset:
Etude des transferts thermo-convectifs dans un canal semi-ouvert : Application aux façades type double-peau

Notre investigation porte sur la simulation numerique des echanges thermo-convectifs dans un canal vertical ouvert a flux impose. Cette etude rentre dans le cadre des recherches sur le rafraichissement passif des composants PV integres au bâtiment. A cet effet, un code numerique en Differences Finies est utilise pour resoudre les equations de Navier-Stokes et simuler la convection naturelle dans un canal. Ce probleme reste difficile a resoudre parce que l'ecriture des conditions aux limites d'entree et de sortie reste un probleme ouvert. Notre travail consiste d'abord en etude des differentes conditions aux limites pour le benchmark numerique AMETH. Les travaux realises ont permis de faire un premier choix sur les conditions aux limites. L'etude s'oriente ensuite sur la qualification et la quantification numeriques et experimentales pour deux fluides : l'air (convection-rayonnement) et l'eau (convection pure). Les resultats numeriques/experimentaux ont ete compares et les discordances ont ete analysees. Plusieurs aspects phenomenologiques (rayonnement entre surfaces, variation des proprietes thermo-physiques, variation du nombre de Prandtl) ont ete abordes afin de caracteriser leurs influences respectives sur l'ecoulement et le transfert thermique. Enfin, dans le but d'apporter des elements de reponses sur les conditions aux limites dynamiques, nous avons simule la convection naturelle d'un canal dans une cavite et tente une modelisation.
Backpacking a dwa pokolenia turystów – wstęp do badań nad definicją

Backpacking and two generations of tourists – introduction to research theory Background. Backpacking is a relatively new type of travelling (its existence dates back to the 90s of the 20th century). According to the indications of foreign researchers of the issue, it has evolved from drifting, and according to Polish theorists – from tramping. From the very beginning, backpacking has been identified with a generation of young people, mostly students, who have temporary resources or employment status and are not conditioned with family responsibilities. The definition of this alternative mode of travelling was established on the basis of research and analysis of canon characteristics of backpackers. Material and methods. Some essential features relevant only to backpacking are classified in the paper. However, backpacking is changing together with the changing generations. Therefore, the research presents reflections on backpacking definitions formulated by two generations of tourists (backpackers youth: aged 18–25 years, and seniors: aged 60–75 years). The study should be treated as a survey, supporting the diagnosis of the problem and preparing the ground for research on a wider scale. A questionnaire survey was conducted among 100 people aged between the so-called young backpackers (50 respondents) and senior backpackers (50 respondents). The technique of a diagnostic questionnaire was used. conclusion. The results obtained allowed to establish backpacker definitional characteristics, as perceived in the context of the travelling experience of two generations of travellers. key words: travelling, seniors, students, alternative tourism, the definitions of backpacking słowa kluczowe: podróże, seniorzy, młodzież ucząca się, turystyka alternatywna, definicje backpackingu ROZPRAWY NAUKOWE Akademii Wychowania Fizycznego we Wrocławiu
Surface-Based Functional Alterations in Early-Onset and Late-Onset Parkinson’s Disease: A Multi-Modal MRI Study

This study used a surface-based method to investigate brain functional alteration patterns in early-onset Parkinson’s disease (EOPD) and late-onset Parkinson’s disease (LOPD) to provide more reliable imaging indicators for the assessment of the two subtypes. A total of 58 patients with Parkinson’s disease were divided into two groups according to age at onset: EOPD (≤50 years; 16 males and 15 females) and LOPD (>50 years; 17 males and 10 females) groups. Two control groups were recruited from the community: young adults (YC; ≤50 years; 8 males and 19 females) and older adults (OC; >50 years; 12 males and 10 females). No significant differences were observed between the EOPD and YC groups or the LOPD and OC groups in terms of age, sex, education, and MMSE scores (p > 0.05). No statistically significant differences were observed between the EOPD and LOPD groups in terms of education, H-Y scale, UPDRS score, or HAMD score (p > 0.05). Data preprocessing and surface-based regional homogeneity (2D-ReHo) calculations were subsequently performed using the MATLAB-based DPABIsurf software. The EOPD group showed decreased 2D-ReHo values in the left premotor area and right dorsal stream visual cortex, along with increased 2D-ReHo values in the left dorsolateral prefrontal cortex. In patients with LOPD, 2D-ReHo values were decreased in bilateral somatosensory and motor areas and the right paracentral lobular and mid-cingulate. The imaging characterization of surface-based regional changes may serve useful as monitoring indicators and will help to better understand the mechanisms underlying divergent clinical presentations.
An Improved Three-Level Neutral Point Clamped Converter System With Full-Voltage Balancing Capability for Bipolar Low-Voltage DC Grid

Bipolar low-voltage dc grids are an emerging and promising solution for power distribution. As a natural candidate for the distribution converter, the three-level neutral-point-clamped (3L-NPC) converter has inherent but limited capability in balancing the dc voltages during asymmetrical operation. This article begins by investigating the voltage balancing limits of the conventional 3L-NPC in detail. To overcome the identified limitations, an improved 3L-NPC converter system with a zigzag transformer and a neutral line is proposed. With the designed control strategy, the proposed converter system can provide full bipolar voltage balancing capability without extra devices or penalties on component ratings. The effectiveness and advantages of the proposed scheme are verified by simulation and experimental results.
The structure of the south?central Taiwan thrust belt

The Taiwan thrust belt is generally thought to develop above a shallow, through-going basal detachment confined to within the sedimentary cover of the Eurasian continental margin. A number of data sets, however, such as surface geology, earthquake hypocentre, and seismic tomography data among others, suggest that crustal levels below the interpreted location of the detachment are also currently being involved in the deformation. In this thesis, new surface geology data were combined with several available geophysical data sets to find a model for the structure of the south-central part of the thrust belt that takes into account deformation taking place at depth. Results of this thesis indicate that beneath the internal Hsuehshan and Central ranges the structural development of the south-central Taiwan thrust belt is controlled by steeply dipping and deep-penetrating faults that are currently inverting pre-existing basement faults inherited from the Eurasian continental margin. Basement rocks are uplifted along these faults to form a basement culmination in the interior of the thrust belt. Beneath the more external Coastal Plain and Western Foothills, however, most of the deformation appears to be taking place near the basement-cover interface, which is acting as an extensive level of detachment and still preserves the extensional geometry inherited from the Eurasian margin.
Financial Distress Classification Using Feedforward Neural Network Based on Altman and Ohlson Financial Ratios

The ever-changing economy requires companies to anticipate future conditions in order to avoid financial distress, a continuous decline in financial conditions. The research focused on comparing Altman and Ohlson’s financial ratio in classifying financial distress on Property and Real Estate companies using the Feedforward Neural Network. The data used is the financial report data of 19 Property and Real Estate companies listed on the Indonesian Stock Exchange in 2016-2022, with the initial status of financial conditions based on earnings per share. (EPS). The study also used the Synthetic Minority Oversampling Technique (SMOTE) method to address class imbalances. The best financial ratio is selected based on accuracy values and Area Under Curve (AUC). Altman’s financial ratio with the FFNN model architecture (5-2-1) with a balance of 60:40 yields an accuracy of 84.62% and an AUC of 0.8325. The Ohlson Financial ratio with the 60:40 data balancing process and the FFNN model architecture (9-4-1) yields an accuracy of 93.27% and an AUC of 0.9045. Thus, in predicting financial distress in companies in the Property and Real Estate sector, Ohlson’s financial ratio with the predictor variables Corporate Size (SIZE), Total Liabilities to Total Assets (TLTA), Working Capital to Total Acts (WCTA), Current Liability to Current Asset (CLCA), OENEG, Net Income to total assets (NITA), Cash Flows Operating to Total Responsibilities (CFOTL), Net Revenue (INTWO), and Net Incoming Change (CHIN) yielded the best results. This best ratio can be used as a consideration in using alternative financial ratio to classify financial distress.
Optimization Algorithm to Reduce Training Time for Deep Learning Computer Vision Algorithms Using Large Image Datasets With Tiny Objects

The optimization of convolutional neural networks (CNN) generally refers to the improvement of the inference process, making it as fast and precise as possible. While inference time is an essential factor in using these networks in real time, the training of CNNs using very large datasets can be costly in terms of time and computing power. This study proposes a technique to reduce the training time by an average of 75% without altering the results of CNN training with an algorithm which partitions the dataset and discards superfluous objects (targets). This algorithm is a tool that pre-processes the original dataset, generating a smaller and more condensed dataset to be used for network training. The effectiveness of this tool depends on the type of dataset used for training the CNN and is particularly effective with sequential images (video), large images and images with tiny targets generally from drones or traffic surveillance cameras (but applicable to any other type of image which meets the requirements). The tool can be parameterized to meet the characteristics of the initial dataset.
Detecting Spammers on Social Networks

Social media is an online platform, one person can make social relations with the other persons easily via social platform (Facebook, twitter, LinkedIn). Nowadays in social media platform peoples are sharing their personal information’s, habits, carrier interest, activities to their friends. Various information is propagating through online social networks including both the positive and negative. Online information sharing is becoming ubiquitous every day. In this paper, naïve Bayes algorithm is used to detect the wrong information for example the online rumors, and it is also used to work out the distinguish and predictive problems. And Naïve Bayes algorithm is also used for text classification, spam filtering, hybrid recommender system and collaborative filtering.
Memory Optimization in RNN-Based Full Waveform Inversion Using Boundary Saving Wavefield Reconstruction

In wave equation modeling, wavefields propagating over time can be regarded as feedforward in a recurrent neural network (RNN). Therefore, the seismic inversion problem based on partial differential wave equations can be addressed using automatic differentiation in the state-of-the-art deep learning frameworks, eliminating the need for explicit backpropagating the residual wavefield. However, one challenge that arises in the context of automatic differentiation is the significant memory usage due to the necessity of storing the hidden states of the RNN (i.e., wavefields in seismic modeling) during forward computation for constructing the computational graph and computing the derivatives during backpropagation. This memory overhead can become a bottleneck, particularly when dealing with large-scale inversion problems. To mitigate this issue, we propose an effective boundary-saving strategy that allows for the reconstruction of the computational graph during the backpropagation process. Instead of storing all the intermediate wavefields at each time step, we selectively save the necessary information at the boundaries, thereby significantly reducing the memory footprint. This approach enables us to maintain the convenience and efficiency of automatic differentiation computations while minimizing the memory requirements. Both 2-D and 3-D numerical experiments validate the accurate reconstruction of wavefields with minimal loss in precision, while the computational graph is simultaneously reconstructed. Consequently, the gradients can also be calculated correctly by automatic differentiation with minimal CPU/graphics processing unit (GPU) memory occupation.
Relanguaging translingual writing in a Khayelitshan primary school

ABSTRACT Linguistic heterogeneity and fluidity – prominently captured in the notion of ‘translanguaging’– are starting to be seen as normative and natural. In turn, homogeneity and fixity, instantiated for example in standard languages, are becoming the ‘odd-ones-out. ’ I challenge the dichotomy between linguistic fluidity (languaging) and fixity (named languages), in a situated conceptual account of translingual writing practices in English classrooms in a Khayelitshan primary school. These spaces fold the linguistic fluidity typical of South African townships, and the fixity of two standard languages, into one complex spatial repertoire. Operationalizing this spatial perspective, I suggest that students are constantly engaged in relanguaging, recursively sorting out the classroom repertoire according to the various linguistic norms enfolded in the space, and of bringing together linguistic resources in various combinations. Relanguaging systematically unsettles the dichotomy between fluid languaging and fix institutional language norms retained in dominant conceptualizations of translanguaging. This way it opens up new conceptual and analytical perspectives with possible pedagogical implication for writing instruction and testing. Standard English could, for example, be assessed beyond its own confines, using writing tasks that can make visible increasingly sophisticated linguistic sorting skills as students.
Nonlinear Filter-Based Adaptive Output-Feedback Control for Uncertain Fractional-Order Nonlinear Systems with Unknown External Disturbance

This study is devoted to a nonlinear filter-based adaptive fuzzy output-feedback control scheme for uncertain fractional-order (FO) nonlinear systems with unknown external disturbance. Fuzzy logic systems (FLSs) are applied to estimate unknown nonlinear dynamics, and a new FO fuzzy state observer based on a nonlinear disturbance observer is established for simultaneously estimating the unmeasurable states and mixed disturbance. Then, with the aid of auxiliary functions, a novel FO nonlinear filter is given to approximately replace the virtual control functions, together with the corresponding fractional derivative, which not only erases the inherent complexity explosion problem under the framework of backstepping, but also completely compensates for the effects of the boundary errors induced by the constructed filters compared to the previous FO linear filter method. Under certain assumptions, and in line with the FO stability criterion, the stability of the controlled system is ensured. An FO Chua–Hartley simulation study is presented to verify the validity of the proposed method.
The structural transformation of territories and the climate governance of an urban area: The mediating role of human capital in adaptation processes

This article forms a crucial part of an economic essay exploring the dynamics of territorial climate governance and its potential impact on the structural transformation of Agadir, a vibrant city. In this context, the role of human capital is also examined while considering the theoretical nuances and empirical analysis tools. The central question drives this study: "to what extent can territorial climate governance contribute to the structural transformation of Agadir, and how does human capital mediate this process? ". To tackle this question, we adopted an abductive reasoning approach and aligned our methodology with a post-positivist paradigm. By meticulously aligning theory with observed reality, we formulated a hypothetical model that interconnects the trio of climate governance, structural transformation, and human capital in the context of Agadir. This model was put to the test with data collected from 416 stakeholders involved in the management of territorial affairs in the city. The findings reveal compelling evidence of significant contributions and correlations among the concepts studied. However, our results also highlight the necessity of recognizing and involving new actors to strengthen Agadir's climate governance mechanisms. In conclusion, our research sheds light on the crucial role of territorial climate governance and human capital in driving the structural transformation of Agadir. By providing a novel perspective on this topic, our study underscores the need for inclusive and proactive engagement of various stakeholders to bolster climate governance measures in the city, paving the way for sustainable development and growth.
Lexical Access Restrictions after the Age of 80

Background: During the fourth age (80+ years), cognitive difficulties increase. Although language seems to resist the advancement of age, an older person without pathological developments in cognition may exhibit deficits in lexical access. This study examines the restrictions on lexical access in people aged 80 and older in word recognition and retrieval modalities through four lexical tasks. Method: The effect of aging on response time and accuracy was measured using recognition (lexical decision/naming/priming) and retrieval (picture naming) tasks. A fourth age group (>80) and two third age groups (60–69/70–79) were compared according to lexical access modality and type of task employed through linear regression models. Results: People aged 80 and older exhibit a strong lexical access constraint, as they are slower and less accurate in recognizing and retrieving words than both third age groups. These restrictions are more profound for the word retrieval modality, especially in the picture naming task. Conclusion: Impaired fluid intelligence and internode transmission deficits during advanced aging could further reduce the ability to recognize and/or retrieve words, having an impact on access speed and accuracy. Furthermore, the idea that crystallized intelligence could strengthen the accuracy of lexical access during aging is supported, specifically in word recognition modality.
Insights into Photo/Electrocatalysts for the Degradation of Per- and Polyfluoroalkyl Substances (PFAS) by Advanced Oxidation Processes

Per- and polyfluoroalkyl substances (PFASs) are an emerging group of persistent organic pollutants in aquatic environments with high levels of toxicity and bioaccumulation. The risks posed by PFASs to the environment and health have attracted increasing attention. To remove them from water, advanced oxidation processes (AOPs), with the merits of high efficiency and low cost, are mainly used. Photo/electrocatalytic heterogeneous AOPs, with the assistance of nanostructured catalysts and external energy in the form of light/electricity, have emerged as one of the most powerful techniques, overcoming the difficulty associated with defluorination and achieving the effective and complete degradation of PFASs in water. The structures of photo/electrocatalysts play a critical role in the production of reactive oxygen species, the electron transfer process, and the degradation pathway and its efficiency. Herein, to elucidate the structure–performance relationship, a review of photo/electrocatalysts for the enhanced degradation of PFASs in heterogeneous AOPs, organized according to their composition and nanostructure design, is provided. This review article is mainly focused on (1) the mechanisms and pathways of PFAS degradation by heterogeneous photo/electrocatalytic AOPs, and (2) the structural designs and modifications of photo/electrocatalysts for the enhanced degradation of PFASs by heterogeneous AOPs. Finally, the challenges and prospects for future research into photo/electrocatalysts of heterogeneous AOPs in the field of PFAS remediation are discussed.
Twisting-Based Finite-Time Consensus for Euler–Lagrange Systems With an Event-Triggered Strategy

In this paper, a twisting-based consensus algorithm is put forward to deal with the event-triggered finite-time consensus for networked Lagrangian systems with directed graphs. First, a fully distributed event-triggered finite-time protocol is considered, for which we can show that each agent can achieve the consensus after a settling time. In order to remove the requirement of continuous monitoring, a pull-based triggering mechanism is employed. Simultaneously, the Zeno-behavior can be excluded under a finite-time dynamic condition. Then, due to the advantages of non-chattering behaviors and finite-time convergence, a twisting-based consensus algorithm based on homogeneous techniques is developed to drive the Euler–Lagrange systems to the consensus value in a settling time. By means of Pólya's theorem and Sum of Squares tools, a polynomial Lyapunov function is constructed to verify our criteria. At last, we give a numerical example for 2-DOF prototype manipulators to verify the validity of the theoretical results.
A New Chapter in the Management of Hypertrophic Cardiomyopathy: Cardiac Myosin Inhibitors

In the recent years, there has been a significant breakthrough in the treatment of hypertrophic cardiomyopathy. New precision molecules have been developed and successfully applied in clinical trials. A new class of orally available allosteric inhibitors reduces heart muscle hypercontractility, the core molecular defect of the disease, by selectively inhibiting cardiac beta-myosin. Based on the results obtained with the first two agents developed to date, mavacamten and aficamten, their use is safe and is associated with rapid and unprecedented improvement in quality of life and functional capacity in patients with left ventricular outflow tract obstruction, comparable to an optimal surgical result. This review provides an overview of the latest and most important studies that led to the approval of mavacamten by the U.S. Food and Drug Administration, and the clinical development of aficamten.