Miracle-dz/UniFAR-FTUs huggingface dataset:
The formation of black holes derived from X-ray binaries

This Thesis revolves around the topic of black holes (BHs) in X-ray binaries (XRBs). The trigger of this work was to understand how stellar-mass BHs form, a question which we tackled both with theoretical as well as observational studies. The formation mechanism of BHs is an unsolved problem in high-energy astrophysics, in particular when it comes to the amount of mass ejected at formation and to how large is the velocity BHs acquire at birth (the so-called natal kick), if they acquire a velocity at all. One way of tackling these uncertainties is to perform physically-motivated simulations of the core-collapse supernova, which is computationally challenging. Another way is to study the birth and evolution of XRBs hosting a BH accreting from a stellar companion, which is the method we use in this Thesis. On the theoretical side, we combine an approach typical of binary population synthesis calculations with a more detailed approach which solves for the binary evolution of each source. When possible, we describe the different evolutionary paths of the binary via analytical calculations and time-scale arguments. On the observational side, we combine the techniques of optical spectroscopy and photometry, with the goal of increasing the sample of Galactic BHs
Disjoint Paths in Densely Embedded Graphs (Preprint)

Abstract : We consider the following maximum disjoint paths problem (MDPP). We are given a large network, and pairs of nodes that wish to communicate over paths through the network -- the goal is to simultaneously connect as many of these pairs as possible in such a way that no two communication paths share an edge in the network. This classical problem has been brought into focus recently in papers discussing applications to routing in high-speed networks, where the current lack of understanding of the MDPP is an obstacle to the design of practical heuristics. We consider the class of densely embedded, nearly-Eulerian graphs, which includes the two-dimensional mesh and many other planar and locally planar interconnection networks. We obtain a constant-factor approximation algorithm for the maximum disjoint paths problem for this class of graphs; this improves on an O(log n)-approximation for the special case of the two-dimensional mesh due to Aumann-Rabani and the authors. For networks that are not explicitly required to be high-capacity, this is the first constant-factor approximation for the MDPP in any class of graphs other than trees. We also consider the MDPP in the on-line setting, relevant to applications in which connection requests arrive over time and must be processed immediately. Here we obtain an asymptotically optimal O(log )-competitive on-line algorithm for the same class of graphs; this improves on an O(log n log log n)-competitive algorithm for the special case of the mesh due to Awerbuch, Gawlick, Leighton, and Rabani.
The secondary metabolites profiling of the phytopathogenic fungus Sclerotinia Sclerotiorum

Sclerotinia sclerotiorum is a necrotrophic plant pathogen causing more than 60 different disease symptoms in approximately 400 plants globally. Hence, due to this distinctive characteristic, S. sclerotiorum has been the subject of various research to comprehend its pathogenicity mechanism, including virulent genes, proteins, and metabolites. Likewise, the genomic annotation of S. sclerotiorum uncovered its remarkable potential for producing secondary metabolites, of which genome mining has additionally prompted the disclosure of these uncharacterized metabolic pathways, which might aid the pathogenicity process. To comprehend the secondary metabolites secreted by S. sclerotiorum that might be involved in its pathogenicity, a secondary metabolite-level investigation of this plant pathogen was performed. Profiling and characterizing these secondary metabolites produced during in vitro germination would increase the current knowledge of this pathogen. In this study, S. sclerotiorum secondary metabolites profile examination was conducted, utilizing the Ultra-High Resolution Qq-Time-Of-Flight mass spectrometer (UHR-QqTOF). Proficient data analysis and verification with the genomic pathways of S. sclerotiorum gave an unequivocal metabolome profile of this pathogen. Two hundred and thirty secondary metabolites were identified in all three biological replicates, and their bodily functions were identified.
Initial growth performance and establishment problem of dragon fruit under aonla based multistoried production system

A field experiment was conducted at the aonla based multistoried agroforestry research field of Bangabandhu Sheikh Mujibur Rahman Agricultural University from June, 2018 to July, 2019 to know the growth performance of dragon fruit and its establishment problems under multistoried tree orchard. The upper storied component of multistoried was aonla tree, carambola and lemon were used as middle storied components, while dragon fruit was the test crop grown as lower storied component. The experiment was laid out in a two-factor randomized complete block design with three replications. Factor A: Production systems (T1: aonla + carambola + lemon + dragon fruit, T2: aonla + dragon fruit, and T3: dragon fruit as sole). Factor B: Two dragon fruit genotypes i.e. red fleshed dragon fruit (V1), and white fleshed dragon fruit (V2). The result indicated that the higher plant height and the maximum number of branches were produced by the red-fleshed dragon fruit than white-fleshed dragon fruit irrespective of production systems. Upper storied plant aonla received 100% PAR but the average amount of light availability for lower storied dragon fruit in the whole growing season was 70.71% (807.51 µmm-2s-1), middle storied carambola and lemon received 77.11% (880.60 µmm-2s-1) and 65.19% (744.47 µmm-2s-1) PAR, respectively. The study found a negative linear relationship between the plant height of dragon fruit and PAR. Only basal rot disease was observed as establishment problem. The maximum disease infestation occurred (37.50%) in multistoried system compared to the sole cropping system (6.94%) and Fusarium oxysporum was identified as causal organism. SAARC J. Agric. , 21(1): 39-51 (2023)
DomainFeat: Learning Local Features With Domain Adaptation

Accurate and efficient keypoint detection and description is a fundamental step in various computer vision tasks. In this paper, we extract robust descriptors and detect accurate keypoints by learning local Features with Domain adaptation (DomainFeat). Specifically, our Domainfeat includes image-level domain invariance supervision, pixel-level domain consistency supervision, Pixel-Adaptive keypoint Detection(PA-Det), and cross-domain dataset with domain stable point supervision. First, we introduce the image-level domain invariance supervision to make the high-level feature distributions from different domains close by fusing domain-invariant representations in the decoder. Furthermore, to compensate for the inconsistency between descriptors corresponding to the keypoints at the pixel level, we propose the pixel-level domain consistency supervision. Then we present the Pixel-Adaptive keypoint Detection to efficiently detect accurate keypoints, which can improve accuracy by enhancing the local consistency of heatmaps. Finally, we propose an efficient approach to construct data and supervision labels in diverse domains, which can tackle complex application scenarios. With these novel modules and supervision methods, our DomainFeat can make feature detectors more accurate and descriptors more robust. Extensive experiments confirm that Domainfeat achieves state-of-the-art performance on benchmarks such as Aachen-Day-Night localization, HPatches image matching, and the challenging DNIM dataset.
The MOND External Field Effect on Dwarf Spheroidal Galaxies

THE MOND EXTERNAL FIELD EFFECT ON DWARF SPHEROIDAL GALAXIES by Benjamin David Blankartz MOdified Newtonian Dynamics, or MOND, is an alternative to the dark matter paradigm which can be used to explain the missing mass problem. The External Field Effect(EFE) is a feature unique to MOND that has no counterpart in the dark matter paradigm. The EFE comes about when a gravitationally bound system is under the influence of an external gravitational field. We embed three Milky Way satellites, Fornax, Leo I and Crater II, as well as one Andromeda satellite, Andromeda XIX, in an external field produced by their host galaxy. We then model these systems kinetically. The velocity dispersion profiles are calculated statistically and then compared to observational data; acceleration profiles of each system are also presented. Fornax and Leo I show good agreement with observations in their velocity dispersion. We also examine structural similarities of the acceleration plots. THE MOND EXTERNAL FIELD EFFECT ON DWARF SPHEROIDAL GALAXIES
Pain Reduction and Posture Alignment Improvement in Older Adults with Chronic Low Back Pain: A Novel Approach Using Spinal Thermal Massage Bed and Calf Pneumatic Cell Compression

Background Chronic low back pain (CLBP) significantly affects the well-being of older adults, leading to diminished quality of life and heightened stress. Existing treatments have limited effectiveness and potential side effects. This study aimed to explore an integrative approach, employing a combination of spinal thermal massage bed (STMB) and intermittent pneumatic calf compression, as an alternative strategy for managing CLBP, improving body posture, reducing stress, and enhancing quality of life. Material/Methods Twenty-three participants aged 65–80 years completed a 4-week intervention involving eight sessions (2 per week) with the STMB device. Outcome measures included pain level assessed by the visual analog scale, trunk and pelvic tilting angles indicating spine curvature, stress level of the autonomic nervous system, Oswestry Disability Index, and EuroQol five-dimensions QoL questionnaire. Results The study revealed significant reductions in pain intensity between baseline and mid-term scores (p=0.002) and between baseline and post-test scores (p=0.001). Moreover, notable improvements were observed in trunk and pelvic tilting angles (p<0.001) and stress scores between baseline and mid-term scores (p=0.037) and between baseline and post-test scores (p=0.019). However, no significant changes were observed in disability level or QoL. Participants expressed high satisfaction with the intervention, and no serious side effects were reported. Conclusions This study provides compelling evidence supporting the safety and efficacy of combining STMB with intermittent pneumatic calf compression in reducing pain intensity and stress levels and improving trunk and pelvic tilting angles. Clinical trial number: KCT0008212.
Generating Series and Performance Bounds for Convolutional Codes - Part 1: Transmission on Memoryless Channels

Performance bounds for convolutional codes over memoryless channels are commonly measured using the distance weight enumerator (cid:1)(cid:1)(cid:2)(cid:3)(cid:4)(cid:2) , also referred to as the generating series or the transfer function , of the code. In particular, bounds to the bit error probability are computed using the ﬁrst few terms of the series expansion of (cid:1)(cid:5) (cid:1)(cid:1)(cid:2)(cid:3)(cid:4)(cid:2)(cid:6)(cid:5)(cid:2)(cid:2) (cid:1)(cid:1)(cid:2) . In this paper we present an efﬁcient algebraic method to obtain this truncated series. We also propose a iterative procedure to compute the truncated (cid:1)(cid:1)(cid:2)(cid:3)(cid:4)(cid:2) that discards, at each step, all paths with Hamming weight higher than a given order.
Homozygous deep intronic variant in SNX14 cause autosomal recessive Spinocerebellar ataxia 20: a case report

Autosomal recessive spinocerebellar ataxia type 20, SCAR20 (MIM: 616354) is a rare syndromic form of hereditary ataxias. It characterized by the presence of progressive ataxia, intellectual developmental disorder, autism and dysmorphic features. The disease caused by biallelic variants in SNX14 gene that lead to loss of protein function. Typically, these variants result in the formation of a premature stop codon, a shift in the reading frame or a variant in canonical splicing sites, as well as gross rearrangements. Here we present the first case of a deep intronic variant c.462-589A>G in SNX14 identified in two sisters with SCAR20 from a consanguineous family. This variant resulted in the inclusion of a pseudo-exon 82 nucleotides long and the formation of a premature stop codon, leading to the production of a truncated protein (NP_722523.1:p.Asp155Valfs*8). Following an extensive diagnostic search, the diagnosis was confirmed using trio whole genome sequencing. This case contributes to expanding the spectrum of potential genetic variants associated with SCAR20.
A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis

Bearings are fundamental mechanical components in rotary machines (engines, gearboxes, generators, radars, turbines, etc.) that have been identified as one of the primary causes of failure in these machines. This makes bearing fault diagnosis (detection, classification, and prognosis) an economic very relevant topic, as well as a technically challenging one as evaluated by the extensive research literature on the subject. This paper employs a systematic methodology to identify, summarize, analyze, and interpret the primary literature on fuzzy formalisms for bearing fault diagnosis from 2000 to 2017 (March). The main contribution is an updated, unbiased, and (to a higher extend) repeatable search, review, and analysis (summary, classification, and critique) of the available approaches resorting to fuzzy formalisms in this trendy topic. A discussion on a new promising future research direction is provided. A comprehensive list of references is also included.
Many Valued Generalised Quantifiers for Natural Language in the DisCoCat Model

DisCoCat refers to the Categorical compositional distributional model of natural language, which combines the statistical vector space models of words with the compositional logic-based models of grammar. It is fair to say that despite existing work on incorporating notions of entailment, quantification, and coordination in this setting, a uniform modelling of logical operations is still an open problem. In this report, we take a step towards an answer. We show how one can generalise our previous DisCoCat model of generalised quantifiers from category of sets and relations to category of sets and many valued rations. As a result, we get a fuzzy version of these quantifiers. Our aim is to extend this model to all other logical connectives and develop a fuzzy logic for DisCoCat. The main contributions are showing that category of many valued relations is compact closed, defining appropriate bialgebra structures over it, and demonstrating how one can compute within this setting many valued meanings for quantified sentences.
A systematic review of social media communication with respect to fashion brands

Social media communication is an important way to visualize the observation of fashion brands in the context of cost and benefit analysis of the paradigm of the fashion market on social media sites. In the context of the definition of the 21st century is a synonym for globalization in the perspective of new liberal economics. In these consequences, social media communication sharpens the direction and dimension of fashion brands among customers because it creates the concept of digital economics and replaces the traditional approach of the fashion markets. In these consequences, the present paper examines the systematic review of the role of social media communication with respect to fashion brands with a study design of an analytical framework. The findings of the study show that India is an emerging market for fashion brands due to its new liberal economics in the aspect of social media communication, but there are lots of challenges emerged in the society of India regarding the adoption of fashion mode in lifestyle. Therefore, it may be managed through the positive role of social media communication in the traditional market of India.
Vismodegib — a chance for improvement of quality of life in patients with locally advanced basal cell carcinoma — a case report

Basal cell carcinoma (BCC) is the most common non-melanocytic skin cancer. Therapeutic strategies available so far include: surgical resection, radiotherapy, or — in the case of low risk of recurrence — superficial application of drugs like 5-fluorouracil or imiquimod. The frequent localisation of BCC is eye bulb area, often with deep penetration into the tissues. Standard therapies in this area may lead to blindness. The Hedgehog (HH) pathway is a key point in BCC development. For patients with advanced BCC, not suitable for surgical resection or radiotherapy, oral small-molecule drug inhibitors of this pathway are the new therapeutic option. Here we present a case of a patient with locally advanced skin BCC localised on the face, sinuses, and eye-socket region. Wide excision with the right eye bulb resection was performed. Eight months after the treatment the patient developed regional recurrence. Due to the advanced stage of the disease the patient was disqualified from further surgical resection. Use of radiotherapy was associated with high risk of blindness of the left eye. The patient was treated with vismodegib and developed a complete response. Moreover, we avoided blindness after radiotherapy. Also, the patient’s symptoms due to locally spreading cancer resolved. The patient has been receiving HH inhibitor without any progression in imaging tests for 20 months.
VEGF Mediates Tumor Growth and Metastasis by Affecting the Expression of E-Cadherin and N-Cadherin Promoting Epithelial to Mesenchymal Transition in Gastric Cancer

Background: Gastric cancer (GC) is the fifth leading cancer in the world, and there is a high mortality rate in China. Exploring the relationship between the prognosis of GC and the expression of related genes is helpful to further understand the common characteristics of the occurrence and development of GC and provide a new method for the identification of early GC, so as to provide the best therapeutic targets. Methods: Vascular endothelial growth factor (VEGF) and markers of epithelial-mesenchymal transition (EMT) were investigated immunohistochemically using tumor samples obtained from 196 GC tissues and adjacent tumor tissues. The correlation of the expression level with histopathologic features and survival was investigated. Results: Here, we show that VEGF and EMT markers expression were significantly correlated with depth of tumor invasion and GC stage (P < .05), degree of differentiation and lymph node metastasis (P < .001). We found that the rate of VEGF positivity in GC tissues was 52.05%, which was significantly higher than that in adjacent cancer tissues (16.84%). In GC, the association between VEGF and E-cadherin was negative (r = −0.188, P < .05), whereas VEGF and N-cadherin were positively correlated (r = 0.214, P < .05). Furthermore, the Kaplan-Meier analysis and a Cox regression model were used to analyze the effect of VEGF and EMT marker expression on the survival of the patients. We found that the overall survival of GC patients was correlated with VEGF (P < .001), N-cadherin (P < .001), E-cadherin (P = .002) expression, and some histopathologic features. Conclusions: Vascular endothelial growth factor and EMT markers exist side by side and play a part together in the development of GC, which provides new ideas for evaluating the prognosis of GC and researching targeted drugs.
Centralized and Collaborative RL-Based Resource Allocation in Virtualized Dynamic Fog Computing

Fog computing (FC) emerged as a new paradigm enabling the deployment of new Internet of Things (IoT) applications. Fog infrastructure is composed of heterogeneous nodes characterized by a complex distribution, mobility, and sporadic resource availability. Hence, resource coordination for continuous Quality-of-Service (QoS) satisfaction becomes challenging, and accurate resource tracking is needed for flawless servicing. In this context, we investigate and propose online resource allocation solutions. The main objective is to maximize the number of satisfied users within a predefined latency requirement. Hence, we model the FC environment as a Markov Decision Process, and then, we formulate the optimization problem. Due to the problem’s NP-hardness, we leverage the reinforcement learning (RL) tool to develop resource allocation schemes. First, a centralized method where a smart fog controller possesses a global awareness of the FC environment is proposed. Next, a more practical and collaborative solution is presented, where each RL-enabled agent manages a group of fog nodes and their resources in order to satisfy computing requests. Based on real-world mobility data sets, simulation results illustrate the high efficiency of the proposed solutions with a preference for the collaborative approach. The superiority of our proposed solutions over state-of-the-art methods is also illustrated.
Early illicit drug use and the age of onset of homelessness

We investigate the effect of taking up daily use of cannabis on the onset of homelessness by using Australian data. We use a bivariate simultaneous mixed proportional hazard model to address potential biases due to common unobservable factors and reverse causality. We find that taking up daily use of cannabis substantially increases the probability of transitioning into homelessness for young men but not young women. In contrast, the onset of homelessness increases the probability of taking up daily use of cannabis for young women but not for young men. In a trivariate extension we find that the use of other illicit drugs at least weekly has no additional effect on transitions into homelessness for either gender but there is a large if imprecisely estimated effect of onset of homelessness on taking up weekly use of such drugs for young women.
Neurochemical Basis of Inter-Organ Crosstalk in Health and Obesity: Focus on the Hypothalamus and the Brainstem

Precise neural regulation is required for maintenance of energy homeostasis. Essential to this are the hypothalamic and brainstem nuclei which are located adjacent and supra-adjacent to the circumventricular organs. They comprise multiple distinct neuronal populations which receive inputs not only from other brain regions, but also from circulating signals such as hormones, nutrients, metabolites and postprandial signals. Hence, they are ideally placed to exert a multi-tier control over metabolism. The neuronal sub-populations present in these key metabolically relevant nuclei regulate various facets of energy balance which includes appetite/satiety control, substrate utilization by peripheral organs and glucose homeostasis. In situations of heightened energy demand or excess, they maintain energy homeostasis by restoring the balance between energy intake and expenditure. While research on the metabolic role of the central nervous system has progressed rapidly, the neural circuitry and molecular mechanisms involved in regulating distinct metabolic functions have only gained traction in the last few decades. The focus of this review is to provide an updated summary of the mechanisms by which the various neuronal subpopulations, mainly located in the hypothalamus and the brainstem, regulate key metabolic functions.