Miracle-dz/UniFAR-FTUs huggingface dataset:
An End-to-End Deep Reinforcement Learning Based Modular Task Allocation Framework for Autonomous Mobile Systems

—Intelligent decision-making systems that can solve task allocation problems are critical for multi-robot systems to conduct industrial applications in a collaborative and automated way, such as warehouse inspection using mobile robots, hydrographic surveying using unmanned surface vehicles, etc. This paper, therefore, aims to address the task allocation problem for multi-agent autonomous mobile systems to autonomously and intelligently allocate multiple tasks to a fleet of robots. Such a problem is normally regarded as an independent decision-making process decoupled from the following task planning for the member robots. To avoid the sub-optimal allocation caused by the decoupling, an end-to-end task allocation framework is proposed to tackle this combinatorial optimisation problem while taking the succeeding task planning into account during the optimisation process. The problem is formulated as a special variant of the multi-depot multiple travelling salesmen problem (mTSP). The proposed end-to-end task allocation framework employs deep reinforcement learning methods to replace the handcrafted heuristics used in previous works. The proposed framework features a modular design of the reinforcement learning agent which can be customised for various applications. Moreover, a real-robot implementation setup based on the Robot Operating System 2 is presented to fulfil the simulation-to-reality gap. A warehouse inspection mission is executed to validate the training outcome of the proposed framework. The framework has been cross-validated via both simulated and real-robot tests with various parameter settings, where adaptability and performance are well demonstrated. Note to Practitioners —This paper is motivated by the problem of dispatching a fleet of autonomous mobile robots to tackle a mission that can be resolved into multiple waypoint-following tasks. An end-to-end modular framework is proposed, making task allocation decisions based on the given waypoint information.
Survival dynamics of SMES supported by credit guarantee schemes: Insights from Morocco

The aim of this study is to assess the viability of SMEs that had benefited from bank loans backed by credit guarantee schemes. A quantitative approach has been adopted by the study. The sample comprised 398 Moroccan SMEs that had benefited from this type of financing, and the primary objective was to examine their survival over the ten years following the obtaining of these guarantees. Logistic regression was used to reflect several results. The results of the study highlight several factors influencing the probability of survival of these SMEs. Larger amounts of credit promote financial resilience and growth, thereby increasing the likelihood of business survival. Business profitability is a key factor in the likelihood of survival. Profitable businesses attract more investors and lenders, improving access to credit and increasing survival prospects. Contrary to some studies, high levels of debt do not appear to reduce the probability of survival. Similarly, repayment capacity showed no significant link with survival, suggesting the importance of other non-financial factors. Mature and well-considered management decision making is associated with a higher probability of survival. Well-thought-out decisions promote the long-term viability of businesses. Small SMEs also have a good chance of survival because of their rapid adaptability. A manager’s active participation in a company’s capital is linked to a higher probability of survival. This underlines the importance of the personal involvement of the manager and of solid governance.
DrSec: Flexible Distributed Representations for Efﬁcient Endpoint Security

—The increasing complexity of attacks has given rise to varied security applications tackling profound tasks, ranging from alert triage to attack reconstruction. Yet, security products, such as Endpoint Detection and Response, bring together applications that are developed in isolation, trigger many false positives, miss actual attacks, and produce limited labels useful in supervised learning schemes. To address these challenges, we propose DrSec —a system employing self-supervised learning to pre-train foundation language models (LMs) that ingest event-sequence data and emit distributed representations for processes. Once pre-trained, the LMs can be adapted to solve different downstream tasks with limited to no supervision, helping unify the currently fractured application ecosystem. We trained DrSec with two LM types on a real-world dataset containing ∼ 91M processes and ∼ 2.55B events, and tested it in three application domains. We found that DrSec enables accurate, unsupervised process identiﬁcation; outperforms leading methods on alert triage to reduce alert fatigue (e.g., 75.11% vs. ≤ 64.31% precision-recall area under curve); and accurately learns expert-developed rules, allowing tuning incident detectors to control false positives and negatives.
Siponimod Attenuates Neuronal Cell Death Triggered by Neuroinflammation via NFκB and Mitochondrial Pathways

Multiple sclerosis (MS) is the most common autoimmune demyelinating disease of the central nervous system (CNS), consisting of heterogeneous clinical courses varying from relapsing-remitting MS (RRMS), in which disability is linked to bouts of inflammation, to progressive disease such as primary progressive MS (PPMS) and secondary progressive MS (SPMS), in which neurological disability is thought to be linked to neurodegeneration. As a result, successful therapeutics for progressive MS likely need to have both anti-inflammatory and direct neuroprotective properties. The modulation of sphingosine-1-phosphate (S1P) receptors has been implicated in neuroprotection in preclinical animal models. Siponimod/BAF312, the first oral treatment approved for SPMS, may have direct neuroprotective benefits mediated by its activity as a selective (S1P receptor 1) S1P1 and (S1P receptor 5) S1P5 modulator. We showed that S1P1 was mainly present in cortical neurons in lesioned areas of the MS brain. To gain a better understanding of the neuroprotective effects of siponimod in MS, we used both rat neurons and human-induced pluripotent stem cell (iPSC)-derived neurons treated with the neuroinflammatory cytokine tumor necrosis factor-alpha (TNF-α). Cell survival/apoptotic assays using flow cytometry and IncuCyte live cell analyses showed that siponimod decreased TNF-α induced neuronal cell apoptosis in both rat and human iPSCs. Importantly, a transcriptomic analysis revealed that mitochondrial oxidative phosphorylation, NFκB and cytokine signaling pathways contributed to siponimod’s neuroprotective effects. Our data suggest that the neuroprotection of siponimod/BAF312 likely involves the relief of oxidative stress in neuronal cells. Further studies are needed to explore the molecular mechanisms of such interactions to determine the relationship between mitochondrial dysfunction and neuroinflammation/neurodegeneration.
BGRD-TransUNet: A Novel TransUNet-Based Model for Ultrasound Breast Lesion Segmentation

Breast UltraSound (BUS) imaging is a commonly used diagnostic tool in the field of counter fighting breast diseases, especially for early detection and diagnosis of breast cancer. Due to the inherent characteristics of ultrasound images such as blurry boundaries and diverse tumor morphologies, it is challenging for doctors to manually segment breast tumors. In recent years, the Convolutional Neural Network (CNN) technology has been widely applied to automatically segment BUS images. However, due to the inherent limitations of CNNs in capturing global contextual information, it is difficult to capture the full context. To address this issue, the paper proposes a novel BGRD-TransUNet model for breast lesion segmentation, based on TransUNet. The proposed model, first, replaces the original ResNet50 backbone network of TransUNet with DenseNet121 for initial feature extraction. Next, newly designed Residual Multi-Scale Feature Modules (RMSFMs) are employed to extract features from various layers of DenseNet121, thus capturing richer features within specific layers. Thirdly, a Boundary Guidance (BG) network is added to enhance the contour information of BUS images. Additionally, newly designed Boundary Attentional Feature Fusion Modules (BAFFMs) are used to integrate edge information and features extracted through RMSFMs. Finally, newly designed Parallel Channel and Spatial Attention Modules (PCSAMs) are used to refine feature extraction using channel and spatial attention. An extensive experimental testing performed on two public datasets demonstrates that the proposed BGRD-TransUNet model outperforms all state-of-the-art medical image segmentation models, participating in the experiments, according to all evaluation metrics used (except for few separate cases), including the two most important and widely used metrics in the field of medical image segmentation, namely the Intersection over Union (IoU) and Dice Similarity Coefficient (DSC). More specifically, on the BUSI dataset and dataset B, BGRD-TransUNet achieves IoU values of 76.77% and 86.61%, and DSC values of 85.08% and 92.47%, respectively, which are higher by 7.27 and 3.64, and 5.81 and 2.54 percentage points, than the corresponding values achieved by the baseline (TransUNet).
The Association of Glycated Hemoglobin and Lipid Profile with Peripheral Artery Disease in Metabolic Syndrome Patients from Northwestern Algeria

Glycated hemoglobin (HbA1c) was incorporated as an indicator of dysglycemia, as opposed to fasting glycaemia, for the purpose of classifying patients based on their vascular incidents. This choice was made due to HbA1c's robust correlation with vascular factors like pulse wave velocity, intima media thickness, and the albumin/creatinine ratio (ACR). However, the relationship between HbA1c and lipid profile in developing artery disease remain uncertain. We set out to investigate the association of HbA1c and lipid profile with peripheral artery diseases (PAD) in patients with metabolic syndrome (MetS) in north-western Algeria. Our cross sectional study was carried out during six months. The BMI was calculated as weight(kg)/height2(m2). Ankle-brachial index (ABI)<0.9 and angiography was used to diagnosed PAD and MetS was defined according NCEP-ATPIII criteria. Statistical test, involving correlations and linear regression, were employed to establish the link between HbA1c, fasting glycemia, lipid profile, and the occurrence of PAD in individuals with MetS. In a sample of 300 MetS patients, 53% were male. Positive associations were observed between HbA1c, fasting blood glucose (FBG) (r=0.753, p<0.001), and triglycerides (TG) (r=0.288, p<0.001), with a negative correlation seen with high-density lipoprotein (HDL) (r= -0.356, p<0.001). HbA1c exhibited no significant correlation with total cholesterol (TC) and low-density lipoprotein (LDL). Lipid ratios (LDL/HDL, TC/HDL, TG/HDL) were positively linked to HbA1c (r=0.232, r=0.332 and r=0.43, respectively). Linear regression affirmed these findings. HbA1c displayed positive ties with FBG and TG, while negatively correlated with HDL, showing independence from LDL and TC. Notably, all three lipid ratios showed significant associations with HbA1c
Retinal Ganglion Cell Function and Perfusion following Intraocular Pressure Reduction with Preservative-Free Latanoprost in Patients with Glaucoma and Ocular Hypertension

(1) Background: Given the global prevalence of glaucoma and the crucial role of intraocular pressure (IOP) reduction in the management of the disease, understanding the immediate effects on retinal structure and function is essential. (2) Methods: This study aimed to assess the effects of preservative-free latanoprost on morphological and functional parameters in treatment-naïve patients with ocular hypertension and open-angle glaucoma. (3) Results: This study showed a significant reduction in IOP by an average of 30.6% after treatment with preservative-free latanoprost. Despite the significant reduction in IOP, no statistically significant changes were observed in the electroretinogram (ERG) nor the optical coherence tomography/angiography (OCT/OCTA) parameters compared to baseline. An exploration of the correlation between IOP changes and various parameters revealed a significant association solely with the macular IPL/INL plexus vessel density (VD) measured with OCTA. (4) Conclusions: This finding suggests a possible association between IOP reduction and changes in the macular microcirculation and provides valuable insights into the differential effects of latanoprost. Acknowledging the study limitations, this study emphasizes the need for larger, longer-term investigations to comprehensively assess the sustained effects of preservative-free latanoprost on both IOP and retinal parameters. In addition, exploring systemic factors and conducting subgroup analyses could improve personalized approaches to glaucoma treatment.
Can an intervention increase access to higher education for disadvantaged students? Quasi-experimental

: Heterogeneity in the school education quality plays an important role for those who want to pursue a bachelor's degree in Peru since access to higher education is highly correlated with socioeconomic status. In that sense, an intervention for disadvantaged students took place for the first time in 2022 and was constrained to the assessment of a scholarship called “Beca 18”, the biggest scholarship that the public institution called PRONABEC addresses every year since 2012. The intervention included additional tools for a group of applicants: (i) full-time online classes for 2 to 4 months; (ii) an electronic device with an internet connection; and (iii) the admission exam payment fully covered up to 2 times. The objective of this thesis is to evaluate the effectiveness of this intervention in increasing the likelihood of the treated to access higher education through the 2022 “Beca 18” scholarship process. As the treatment was not randomly assigned, a control group was estimated using the Propensity Score Matching methodology based on individual characteristics. Results showed that there is no statistically significant effect of the intervention in the treated applicants and invite to re-evaluate its design and implementation.
UvA-DARE (Digital Academic Repository) Dynamical friction in gravitational atoms

Due to superradiant instabilities, clouds of ultralight bosons can spontaneously grow around rotating black holes, creating so-called “gravitational atoms”. In this work, we study their dynamical effects on binary systems. We first focus on open orbits, showing that the presence of a cloud can increase the cross section for the dynamical capture of a compact object by more than an order of magnitude. We then consider closed orbits and demonstrate that the backreaction of the cloud’s ionization on the orbital motion should be identified as dynamical friction. Finally, we study for the first time eccentric and inclined orbits. We find that, while ionization quickly circularizes the binary, it barely affects the inclination angle. These results enable a more realistic description of the dynamics of gravitational atoms in binaries and pave the way for dedicated searches with future gravitational wave detectors
Advanced Maternal Age: A Scoping Review about the Psychological Impact on Mothers, Infants, and Their Relationship

The mean age at childbirth in Europe has gradually increased, and it is now around 29 years of age. It has been shown that older maternal age is associated with problems of fertility; in fact, with increasing age, the chance of conceiving diminishes, and fetal and obstetric complications grow. Research has focused particularly on the biological risks associated with late pregnancy, both for the child and the woman. Less space has been dedicated to the potential psychological and relational benefits of motherhood at an advanced age. The aim of this review was to summarize the existing literature on this issue. Qualitative and quantitative studies were sourced from Pubmed, Science Direct, PsycINFO, and SciELO. The selected works highlight that advanced maternal age can be associated with some advantages for both mothers and their offspring in terms of physical healthcare, parenting styles, and child developmental outcomes. Specifically, the review suggests that older mothers have greater emotional maturity and feel more prepared for motherhood; also, advanced maternal age appears to exert a protective influence on children’s behavioral, social, and emotional functioning, compensating for the biological risks.
Study of highly sensitive C-reactive protein in type 2 diabetes mellitus and prediction of cardiovascular risk with glycemic status

Inflammation plays a vital role in accentuating the formation of atherosclerotic plaque in diabetes mellitus. So, the measurements of inflammatory markers provide a method of assessing cardiovascular risk. Among the inflammatory markers, highly sensitive C-reactive protein (hs-CRP) is used to detect the low-level inflammation when it is within the normal range. Also, hs-CRP measurement may be useful for assessment of the risk of complication in diabetes patients. So, the present study is conducted to measure plasma hs-CRP level in T2DM and to determine adequate glycaemic control reduces hs-CRP level. The objectives of this study were to correlate HbA1c and hs-CRP in T2DM and predict cardiovascular risk with glycaemic status.Methods: Authors took 50 diabetic patients. The investigation includes FBS, PPBS, hs-CRP and HbA1c. hs-CRP is measured by immunoturbidimetry method. The reports were collected and compared with normal reference range.Results: The correlation between hs-CRP levels and HbA1c level after six months show a significant relationship where mean HbA1c values on day 1 and after 6 months were 8.088±1.219 and 7.518±0.693 respectively. The hs-CRP values were 2.508±1.050 on day 1 and 2.15±0.927 after 6 months proving that better glycaemic controls decrease hs-CRP thereby decreasing cardiovascular risk.Conclusions: hs-CRP values are directly related to HbA1c and better glycaemic control reduces risk of CVD.
The Mathematics Enthusiast The Mathematics Enthusiast

: The level of the coherence of a concept image conveys how well the cognitive structure concerning the concept is organized. This study considers the relationship between deficiencies in the coherence of the concept image and erroneous conclusions in the case of differentiability. The study is based on an interview where the student made conclusions contradictory to the formal theory of mathematics. He used an erroneous method to study the differentiability of piecewise defined functions. This method became the key factor which maintained the internal coherence of the concept image. It made it possible to build a cognitive structure whose basis was erroneous.
Linking mid-scale distributive fluvial systems to drainage basin area: geomorphological and sedimentological evidence from the endorheic Gastre Basin, Argentina

Abstract The analysis of mid-scale distributive fluvial systems (DFS) provides an opportunity to study fluvial depositional patterns in sedimentary basins in a manner similar to megafans, but under the more homogeneous external conditions that control small alluvial fans from the source area to the depositional area. Four mid-scale Quaternary DFS and the areas of their drainage basins were analysed with the aim of understanding and predicting the mechanism and magnitude of fluvial fan deposition. These DFS were located in the Gastre Basin, Argentina, an endorheic basin that has evolved during the Quaternary under relatively uniform climatic and tectonic conditions. Using a geomorphological and sedimentological approach, the measured areas of the DFS were compared with the calculated areas using different regression equations for variables such as the drainage basin area and the drainage basin slope. The results suggest a moderate to high percentage of deviation in all cases, indicating that at an intermediate scale the size of the DFS is not solely a function of the size of the drainage basin. Adjacent DFS with similar depositional areas and catchment bedrock lithologies were linked with very different drainage basin areas and vice versa. This study suggests that the horizontal accommodation space, determined by the incision and distribution of previous deposits, and the drainage basin slope may also influence the size of mid-scale DFS.
Ubiquitous Access to Unified Messaging: A Study of Usability and the Use of Pervasive Computing

The advent of mobile devices and the wireless Internet is having a profound impact on the way people communicate, as well as on the user interaction paradigms used to access information that was traditionally accessible only through visual interfaces. Applications for mobile devices entail the integration of various data sources optimized for delivery to limited hardware resources and intermittently connected devices through wireless networks. Although telephone interfaces arise as one of the most prominent pervasive applications, they present interaction challenges such as the augmentation of speech recognition through natural language (NL) understanding and high-quality text-to-speech conversion. This article presents an experience in building an automated assistant that is natural to use and could become an alternative to a human assistant. The Mobile Assistant (MA) can read e-mail messages, book appointments, take phone messages, and provide access to personal-organizer information. Key components are.
Topic segmentation: algorithms and applications

Most documents are aboutmore than one subject, but the majority of natural language processing algorithms and information retrieval techniques implicitly assume that every document has just one topic. The work described herein is about clues which mark shifts to new topics, algorithms for identifying topic boundaries and the uses of such boundaries once identified. A number of topic shift indicators have been proposed in the literature. We review these features, suggest several new ones and test most of them in implemented topic segmentation algorithms. Hints about topic boundaries include repetitions of character sequences, patterns of word and word n-gram repetition, word frequency, the presence of cue words and phrases and the use of synonyms. The algorithms we present use cues singly or in combination to identify topic shifts in several kinds of documents. One algorithm tracks compression performance, which is an indicator of topic shift because selfsimilarity within topic segments should be greater than between-segment similarity. Another technique relies on word repetition and places boundaries by minimizing word repetitions across segment boundaries. A third method compares the performance of a language model with and without knowledge of the contents of preceding sentences to determine whether a topic shift has occurred. We use the output of this algorithm in a statistical model which incorporates synonymy, bigram repetition and other features for topic segmentation. We benchmark our algorithms and compare them to algorithms from the literature using concatenations of documents, and then perform further evaluation of our techniques using a collection of news broadcasts transcribed both by annotators and using a speech recognition system. We also test the effectiveness of our algorithms for identifying both chapter boundaries in works of literature and story boundaries in Spanish news broadcasts. We suggest ways to improve information retrieval, language modeling and various natural language processing algorithms by exploiting the topic segmentation. Disciplines Databases and Information Systems Comments University of Pennsylvania Institute for Research in Cognitive Science Technical Report No. IRCS-98-21. This thesis or dissertation is available at ScholarlyCommons: http://repository.upenn. edu/ircs_reports/66 TOPIC SEGMENTATION ALGORITHMS AND APPLICATIONS