Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble of Autoencoders for Anomaly Detection in Biomedical Data: A Narrative Review

In the context of biomedical data, an anomaly could refer to a rare or new type of disease, an aberration from normal behavior, or an unexpected observation requiring immediate attention. The detection of anomalies in biomedical data has a direct impact on the health and safety of individuals. However, anomalous events are rare, diverse, and infrequent. Often, the collection of anomalous data may involve significant loss of human life and healthcare costs. Therefore, traditional supervised machine and deep learning algorithms may not be directly applicable to such problems. Biomedical data are often collected in the form of images, electronic health records, and time series. Typically, an autoencoder (AE) or its corresponding variant is trained on normal data, and an anomaly is identified as a significant deviation from these data based on reconstruction error or other metrics. An Ensemble of AEs (EoAEs) can serve as a robust approach for anomaly detection in biomedical data by combining diverse and accurate views of normal data. An EoAE can provide superior detection to a single encoder; however, its performance can depend on various factors, including the diversity of the created data, the accuracy of the individual AEs, and the combination of their outcomes. Herein, we perform a comprehensive narrative literature review on the use of EoAEs when using different types of biomedical data. Such an ensemble provides a promising approach for anomaly detection in biomedical data, offering the potential for performance improvement by leveraging the strengths of diverse AEs. However, several challenges remain, such as the need for data specification and determination of the optimal number of AEs in the ensemble. By addressing these challenges, researchers can enhance the effectiveness of EoAEs for anomaly detection in various types of biomedical data. Furthermore, through this review, we highlight the significance of evaluating and comparing the performance of an EoAE with that of single AEs by establishing agreed-upon evaluation metrics and investigating normalization techniques for anomaly scores. We conclude the review by presenting challenges and open questions in the field with for future research.
Comparison of Mechanical Properties of Steam-Free and Steam-Based Specimens Made of Expanded Polypropylene Beads

Reducing the CO2 emissions of plastic parts is crucial in terms of sustainable product and process designs. Approaches include the use of recycled materials and reducing the energy demands of processes through more efficient technologies. In this context, this study shows the potential of the steam-free processing of particle foam beads into thin-walled moulded parts. Expanded polypropylene (EPP) particle foam beads have been processed in both a steam-free and steam-based process. For this purpose, specimens with different part densities and thicknesses were produced, the mechanical properties were investigated, and the surface quality was discussed. Specimens made of EPP with a part thickness of 5 to 20 mm and part densities of 60 to 185 g/L were produced steam-free. Lower part thicknesses and higher densities increase the mechanical properties. As the density increased, the homogeneity of the surfaces of the steam-free specimens also increased. In comparison, specimens with a thickness of 10 mm and part densities of 35 to 90 g/L were produced on a steam-based process. The results of the mechanical test were compared with those of the steam-free specimens. The steam-based specimens showed higher mechanical properties for the same density.
A Simultaneous Wireless Information and Power Transfer-Based Multi-Hop Uneven Clustering Routing Protocol for EH-Cognitive Radio Sensor Networks

Clustering protocols and simultaneous wireless information and power transfer (SWIPT) technology can solve the issue of imbalanced energy consumption among nodes in energy harvesting-cognitive radio sensor networks (EH-CRSNs). However, dynamic energy changes caused by EH/SWIPT and dynamic spectrum availability prevent existing clustering routing protocols from fully leveraging the advantages of EH and SWIPT. Therefore, a multi-hop uneven clustering routing protocol is proposed for EH-CRSNs utilizing SWIPT technology in this paper. Specifically, an EH-based energy state function is proposed to accurately track the dynamic energy variations in nodes. Utilizing this function, dynamic spectrum availability, neighbor count, and other information are integrated to design the criteria for selecting high-quality cluster heads (CHs) and relays, thereby facilitating effective data transfer to the sink. Intra-cluster and inter-cluster SWIPT mechanisms are incorporated to allow for the immediate energy replenishment for CHs or relays with insufficient energy while transmitting data, thereby preventing data transmission failures due to energy depletion. An energy status control mechanism is introduced to avoid the energy waste caused by excessive activation of the SWIPT mechanism. Simulation results indicate that the proposed protocol markedly improves the balance of energy consumption among nodes and enhances network surveillance capabilities when compared to existing clustering routing protocols.
Nanoencapsulated Curcumin Mitigates Liver Injury and Drug-Metabolizing Enzymes Induction in Diclofenac-Treated Mice

Curcumin (CUR) is a natural product with known anti-inflammatory, antioxidant, and hepatoprotective properties. The aim of this study was to formulate CUR into a polymeric nanoparticle (NP) formulation and examine its potential hepatoprotective activity in an animal model of diclofenac (DIC)-induced hepatotoxicity. CUR was loaded into polymeric NPs composed of poly(ethylene glycol)-polycaprolactone (PEG–PCL). The optimal CUR NPs were evaluated against DIC-induced hepatotoxicity in mice, by studying the histopathological changes and gene expression of drug-metabolizing cyp450 (cyp2c29 and cyp2d9) and ugt (ugt2b1) genes in the livers of the animals. The optimal NPs were around 67 nm in diameter with more than 80% loading efficiency and sustained release. Histological findings of mice livers revealed that CUR NPs exhibited a superior hepatoprotective effect compared to free CUR, and both groups reduced DIC-mediated liver tissue injury. While treatment with DIC alone or with CUR and CUR NPs had no effect on cyp2c29 gene expression, cyp2d9 and ugt2b1 genes were upregulated in the DIC-treated group, and this effect was reversed by CUR both as a free drug and as CUR NPs. Our findings present a promising application for nanoencapsulated CUR in the treatment of nonsteroidal anti-inflammatory drugs-induced liver injury and the associated dysregulation in the expression of hepatic drug-metabolizing enzymes.
Constrained Weighted Least-Squares Algorithms for 3-D AOA-Based Hybrid Localization

Source localization with time-of-arrival (TOA), time-difference-of-arrival (TDOA), time-delay (TD), received-signal-strength (RSS), or angle-of-arrival (AOA) measurements from several spatially distributed sensors is commonly used in practice. Existing analysis of the Cram $\acute{\text{e}}$ r-Rao lower bounds (CRLB) shows that a hybrid of two or more independent kinds of measurement has a lower CRLB than one individual type of measurement. This paper develops a unified constrained weighted-least squares (CWLS) algorithm for five types of hybrid localization systems: AOA and TOA (AOA/TOA), AOA and TDOA (AOA/TDOA), AOA and TD (AOA/TD), AOA and RSS (AOA/RSS), AOA, TOA, and RSS (AOA/TOA/RSS). These formulated CWLS problems only have one quadratic constraint, which can be effectively solved by the Lagrange multiplier method and root-finding algorithm. Extensive simulation results show that the proposed CWLS algorithms are superior to state-of-the-art algorithms and reach the CRLB.
Bid Landscape Forecasting and Cold Start Problem With Transformers

In Real-Time Bidding, advertisers aim to optimally bid within a limited budget constraint. Effective bidding strategies require bid landscape forecasting to predict the probability distribution of market price for each advertisement auction. This distribution has a complicated form with many peaks. Moreover, all probabilities of bids depend on each other. Most existing solutions mainly focus on learning a parameterized model based on some heuristic assumptions of distribution forms. In this paper, we propose a Transformer model that takes into account dependencies between bids improving the bid landscape forecasting. We also increase the quality of model prediction on the advertisement cold start for the cases of insufficient data. Our experiments on two real-world industrial datasets prove that the proposed model statistically significantly outperforms the state-of-the-art solutions both in terms of ANLP metrics by 8.75% and ROC-AUC by 1.1%. In addition, we show the industrial applicability of our approach.
European Node of the Urban Application Center for KOMPSAT-1/2 derived products

The well established scientific and technological collaboration between the Korean Aerospace Research Institute (KARI) and the Austrian Research Centers - Seibersdorf research (ARCS) triggered the idea for the joint development of an Urban Application Center, targeting the needs of the urban planning and urban monitoring domain of governmental and other non-profit organizations. Data from the Very-High-Resolution Multi-Spectral-Camera mounted on KOMPSAT-2 misson (operated by KARI) will provide the major input to a semi-automated processing chain, delivering geocoded and thematic products. As a first step the thematic information extracted from the satellite data will use a classification scheme based on 6 classes. The European Regional Node, located in ARCS, of the Urban Application Center will provide coverage of larger cities in Europe, Africa and the Near East. To access the Urban Application Center for searching the catalog, presenting and selecting the results and later to access the available data at the Urban Application Center a WebMapServer (WMS) has been implemented. The OpenSource WMS of the University of Minnesota, which already provides a WebFeatureServer (WFS) and soon will provide a WebCoverageServer (WCS), together with the spatial enabled PostGIS/PostgreSQL database was chosen and extended to the special needs of the intended services provided by the Urban Application Center.
A Map Matching Algorithm for GPS Tracking Data

Map matching GPS floating car tracking data is different from that for traditional navigation system according to the specific application.With the consideration that GPS floating car tracking data provide a global moving trend,using drive constraints in city road networks,this paper proposed a novel map matching method based on road connectivity under geometric topology and traffic control constraints as well as the similarity between the curve of trajectory and the outline of road paths.This algorithm can obtain good map matching results and was validated through experiments,and finally can support the further analysis and application of GPS floating car data.
Student-teachers’ Emotion Regulation in Speaking

Several scholars in education have asserted that emotions play a significant role in motivation to learn. On the side of self-regulated learning theory, it is believed that a learner would succeed more if he owned fully constructed self-regulation in learning. This research aims to describe the student-teachers’ academic emotions, specifically in speaking, and later to elaborate on their tendency to regulate it. The researcher applied mixed methods in this study. The data was obtained through questionnaires and in-depth interviews. Supporting theory used to gain the description of the student-teacher state of academic emotion is the theory proposed by Pekrun et al. (2002). The result showed that the student-teachers tend to perceive negative emotions about their ability to speak. However, they managed to use a cognitive reappraisal strategy to modify their academic emotion in both stages of preparation and mastering speaking. Meanwhile, they tend to use expressive suppression to manage their academic emotion in performing speaking. Moreover, the implications and implementation of emotion regulation in the East Nusa Tenggara context as a part of the researcher’s reflection are also discussed.
On-Axis Optical Trapping with Vortex Beams: The Role of the Multipolar Decomposition

Optical trapping is a well-established, decades old technology with applications in several fields of research. The most common scenario deals with particles that tend to be centered on the brightest part of the optical trap. Consequently, the optical forces keep the particle away from the dark zones of the beam. However, this is not the case when a focused doughnut-shaped beam generates on-axis trapping. In this system, the particle is centered on the intensity minima of the laser beam and the bright annular part lies on the periphery of the particle. Researchers have shown great interest in this phenomenon due to its advantage of reducing light interaction with trapped particles and the intriguing increase in the trapping strength. This work presents experimental and theoretical results that extend the analysis of on-axis trapping with light vortex beams. Specifically, in our experiments, we trap micron-sized spherical silica (SiO2) particles in water and we measure, through the power spectrum density method, the trap stiffness constant κ generated by vortex beams with different topological charge orders. The optical forces are calculated from the exact solutions of the electromagnetic fields provided by the generalized Lorentz–Mie theory. We show a remarkable agreement between the theoretical prediction and the experimental measurements of κ. Moreover, our numerical model gives us information about the electromagnetic fields inside the particle, offering valuable insights into the influence of the electromagnetic fields present in the vortex beam trapping scenario.
An Individual Prosthesis Control Method with Human Subjective Choices

An intelligent lower-limb prosthesis can provide walking support and convenience for lower-limb amputees. Trajectory planning of prosthesis joints plays an important role in the intelligent prosthetic control system, which directly determines the performance and helps improve comfort when wearing the prosthesis. Due to the differences in physiology and walking habits, humans have their own walking mode that requires the prosthesis to consider the individual’s demands when planning the prosthesis joint trajectories. The human is an integral part of the control loop, whose subjective feeling is important feedback information, as humans can evaluate many indicators that are difficult to quantify and model. In this study, trajectories were built using the phase variable method by normalizing the gait curve to a unified range. The deviations between the optimal trajectory and current were represented using Fourier series expansion. A gait dataset that contains multi-subject kinematics data is used in the experiments to prove the feasibility and effectiveness of this method. In the experiments, we optimized the subjects’ gait trajectories from an average to an individual gait trajectory. By using the individual trajectory planning algorithm, the average gait trajectory can be effectively optimized into a personalized trajectory, which is beneficial for improving walking comfort and safety and bringing the prosthesis closer to intelligence.
Predicting distributions of estuarine associated fish and invertebrates in Southeast Alaska

Estuaries in Southeast Alaska provide habitat for juveniles and adults of several commercial fish and invertebrate species; however, because of the area’s size and challenging environment, very little is known about the spatial structure and distribution of estuarine species in relation to the biotic and abiotic environment. This study uses advanced machine learning algorithms (random forest and multivariate random forest) and landscape and seascape-scale environmental variables to develop predictive models of species occurrence and community composition within Southeast Alaskanestuaries. Species data were obtained from trawl and seine sampling in 49 estuaries throughout the study area. Environmental data were compiled and extracted from existing spatial datasets. Individual models for species occurrence were validated using independent data from seine surveys in 88 estuaries. Prediction accuracy for individual species models ranged from 94% to 63%, with 76% of the fish species models and 72% of the invertebrate models having a predictive accuracy of 70% or better. The models elucidated complex species-habitat relationships that can be used to identify habitat protection priorities and to guide future research. The multivariate models demonstrated that community composition was strongly related to regional patterns of precipitation and tidal energy, as well as to local abundance of intertidal habitat and vegetation. The models provide insight into how changes in species abundance are influenced by both environmental variation and the co-occurrence of other species. Taxonomic diversity in the region was high (74%) and functional diversity was relatively low (23%). Functional diversity was not linearly correlated to species richness, indicating that the number of species in the estuary was not a good predictor of functional diversity or redundancy. Functional redundancy differed across estuary clusters, suggesting that some estuaries have a greater potential for loss of functional diversity with species removal than others.
Fault Tolerance Exploration and SDN Implementation for de Bruijn Topology based on betweenness Coefficient

This article considers the method of analyze potentially vulnerable places during development of topology for fault-tolerant systems based on using betweenness coefficient. Parameters of different topological organizations using De Bruijn code transformation are observed. This method, assessing the risk for possible faults, is proposed for other topological organizations that are analyzed for their fault tolerance and to predict the consequences of simultaneous faults on more significant fragments of this topology.
Unilateral Approach Bilateral Microdecompression for Degenerative Lumbar Spinal Stenosis

Objective: Degenerative lumbar spinal stenosis is a frequent cause of back and leg pain in elderly patients. Degenerative spinal stenosis may be due to inter-vertebral disk bulging, joint facet hypertrophy, thickening of the ligamentum flavum, and spondylolisthesis. The aim of this study is to investigate the results of unilateral approach bilateral microdecompression for degenerative lumbar spinal stenosis patients. Materials and Methods: We observed 78 patients who have back and/or leg pain with neurogenic claudication. The patients were scored by visual analog scale (VAS), oswestry disability index (ODI) score, and walking distance (WD). The surgical technique used in all stenotic levels was unilateral approach bilateral microdecompression. All patients were questioned and examined before surgery, post-operative 2 nd year. Results: Thirty-nine males and 39 females total of 78 patients with the mean age of 64.3±7.2 were investigated. There was no statistically significance according to gender and age. Pre-operative mean VAS, ODI and WD values were 8.9±1.1, 65±17.20, 42±21.30 and post-operative 2 nd year values were 1.2±0.23, 17±1.91, 1800±617.13. All three parameters were found statistically significant when compared between pre-operative and post-operative values (p<0.05). Conclusion: The results of the unilateral approach bilateral microdecompression for treating lumbar spinal stenosis are satisfying because you can achieve sufficient decompression with minimal invasive technique without dissecting and damaging the opposite side tissues.
Climatic Water Balance of Annapurna, Langtang and Khumbu regions of Nepal Himalaya

For the protection of the environment, climatic water balance studies play key role. This study attempts to assess the potential water availability at the Annapurna, Langtang and Khumbu regions of Nepal Himalaya. Potential evapotranspitration (PET) is calculated by CROPWAT 8 with the help of maximum and minimum temperature, relative humidity, wind speed and sunshine hour. The climatic water balance of water bodies is calculated on the basis of Thornthwait procedure. These calculations help to examine annual water surplus (WS) and water deficit (WD) periods. Potential water surplus at three selected station is calculated by above techniques after averaging the data of time period from 1987 to 2008. The main aim of this study is to compare the obtained result from the climatic water balance for the selected sites of the Nepal Himalaya region. This study will provide climatic water balance information of the given area which will be useful for sustainable management of water resources in local and small area of the Nepal Himalaya. Journal of Hydrology and Meteorology, Vol. 8(1) p.47-57
The Identiﬁcation of Polyphenolic Compounds and the Determination of Antioxidant Activity in Extracts and Infusions of Peppermint, Lemon Balm and Lavender

: Bioactive compounds are molecules that may have therapeutic potential with inﬂuence on oxidative stress, pro-inﬂammatory state and metabolic disorders. Herbs are recognized as a signiﬁcant source of natural antioxidants. The aim of this study was to determine the antioxidant properties of peppermint ( Mentha piperita L.), lemon balm ( Melissa ofﬁcinalis L.) and lavender ( Lavandula angustifolia Mill.). Fresh plant materials were harvested and obtained from the Experimental Station of Agriculture University in Krak ó w, Poland. Proximate analysis (protein, fat, ash and dry matter) was performed on herbs. Total polyphenol content and polyphenol proﬁle antioxidant activity (ABTS and FRAP methods) were measured in an extract prepared with deionized distilled hot water (infusion), 70% methanol or 70% methanol acidiﬁed with formic acid. It was found that the water extract of peppermint had the highest polyphenol content and antioxidant activity measured by the FRAP method. The highest antioxidant activity measured with the ABTS method was in methanolic lemon balm extract. The highest amount of total phenolic compound was determined in the water extract of peppermint. The water and acidiﬁed methanol extract of peppermint contained a higher amount of naringin, rutin, hesperidin and rosmarinic acid. Evaluated plants can be used as natural antioxidants instead of synthetic antioxidants in the food and pharmaceutical industries.
Génomique fonctionnelle du gène modA essentiel à l'infection pulmonaire chronique chez Pseudomonas aeruginosa

v Table des matières . vii Liste des tableaux . xi Liste des figures . xiii Remerciements . xvii Avant-propos . xix Introduction . 1 1.1 L’organisme modèle Pseudomonas aeruginosa. 1 1.1.1 Caractéristiques . 1 1.1.2 P. aeruginosa et la fibrose kystique . 1 1.1.3 La génomique de P. aeruginosa . 6 1.1.4 Les facteurs de virulence . 7 1.1.5 La régulation de la virulence . 11 1.1. 6 Le biofilm . 16 1.1. 7 Les adaptations lors de l’infection chronique . 24 1.1. 8 Un métabolisme respiratoire diversifié . 27 1.2 La mutagénèse transpositionnelle par étiquette signature . 30 1.2. 1 Le concept de la STM . 30 1.2. 2 Les étapes principales de la STM . 30 1.3 Le gène modA . 32 1.3. 1 Le molybdate . 32 1.3. 2 Le transport du molybdate . 33 1.3. 3 L’homéostasie du molybdène . 34 1.3. 4 Les mutations mod . 37 1.4 L’étude de l’expression génique par séquençage à haut débit . 38 1.4. 1 Le séquençage de nouvelle génération . 38 1.4. 2 Le séquençage de nouvelle génération appliqué aux transcriptomes . 38 1.5 Mise en situation du projet de recherche . 41 1.5. 1 Problématique . 41 1.5. 2 Hypothèses et objectifs . 41 Chapitre 2 . 43 Le transporteur à molybdate ModABC est essentiel à l’infection pulmonaire chronique, la croissance anaérobie et la formation du biofilm chez Pseudomonas aeruginosa . 43