Miracle-dz/UniFAR-FTUs huggingface dataset:
CONSTRAINING NEUTRINO COOLING USING THE HOT WHITE DWARF LUMINOSITY FUNCTION IN THE GLOBULAR CLUSTER 47 TUCANAE

We present Hubble Space Telescope observations of the upper part ( T eff > 10 4 ? > K) of the white dwarf cooling sequence in the globular cluster 47 Tucanae and measure a luminosity function of hot white dwarfs. Comparison with previous determinations from large-scale field surveys indicates that the previously determined plateau at high effective temperatures is likely a selection effect, as no such feature is seen in this sample. Comparison with theoretical models suggests that the current estimates of white dwarf neutrino emission (primarily by the plasmon channel) are accurate, and variations are restricted to no more than a factor of two globally, at 95% confidence. We use these constraints to place limits on various proposed exotic emission mechanisms, including a nonzero neutrino magnetic moment, formation of axions, and emission of Kaluza–Klein modes into extra dimensions.
Automated Brain Disease Classification using Transfer Learning based Deep Learning Models

classification is one of the most significant areas of medical imaging. Among different types of procedures, MRI is the most trusted one to detect brain diseases. Manual and semi-automated segmentations need highly experienced radiologists and much time to detect the problem. Recently, deep learning methods have taken attention due to their automation and self-learning techniques. To get a faster result, we have used different algorithms of Convolutional Neural Network (CNN) with the help of transfer learning for classification to detect diseases. This procedure is fully automated, needs less involvement of highly experienced radiologists, and does not take much time to provide the result. We have implemented six deep learning algorithms, which are InceptionV3, ResNet152V2, MobileNetV2, Resnet50, EfficientNetB0, and DenseNet201 on two brain tumor datasets (both individually and manually combined) and one Alzheimer’s dataset. Our first brain tumor dataset (total of 7,023 images-training 5,712, testing 1,311) has 99-100 percent training accuracy and 98-99 percent testing accuracy. Our second tumor dataset (total of 3,264 images-training 2,870, testing 394) has 100 percent training accuracy and 69-81 percent testing accuracy. The combined dataset (total of 10,000 images-training 8,000, testing 2,000) has 99-100 percent training accuracy and 98-99 percent testing accuracy. Alzheimer’s dataset (total of 6,400 images-training 5,121, testing 1,279, 4 classes of images) has 99-100 percent training accuracy and 71-78 percent testing accuracy. CNN models are renowned for showing the best accuracy in a limited dataset, which we have observed in our models.
Criteria and Guideline for Dyslexic Intervention Games

—The utilization of game-based interventions is growing as a result of technological advancements, and it has shown to be effective in the treatment of dyslexia and other medical conditions. Games are typically viewed as activities having the essential components of challenge, incentive, and reward. Games were originally created for pleasure, and they can make dyslexic teaching and learning more enjoyable and exciting. Although there are numerous applications available for treating dyslexic children, the inclusion of games and their standards in those applications has not yet been established. Therefore, there is a need for a standard design guideline to be formulated in establishing a guideline for designing and developing games specifically for dyslexic children. This article proposes a design guideline for dyslexic intervention games. Two methods have been employed which are interviews and systematic literature reviews (SLR) to discover the characteristics of dyslexic games. The first set of the criteria was developed through interviews with the stakeholders who are directly associated with dyslexic children. Scopus, the ACM digital library, EBSCO-host, Wiley, and Web of Science (WOS) are the five primary databases used in SLR. 50 articles out of the 551 that were early screened from the five primary databases are qualified to be studied based on the criteria. Only 23 publications could be selected for the study after further screening, which led to the creation of a second set of criteria. These two sets of criteria are thoroughly analyzed, combined, and formulated as a guideline which comprises of four main categories; device and platform, interface, game features, and gameplay. The guideline consists of guidance to be used for designing and developing Dyslexic therapy games with the purpose of assisting Dyslexic children to read. The guideline is believed to be beneficial to many parties especially the educational game developers, therapists, and educationist who are dealing with intervention for Dyslexic children. This study is aligned and significant to Sustainable Development Goals (SDG) three and four, Good Health and Well-being and Quality Education respectively.
Eur opean J ournal of Chem istry Evaluation of the effects of significant factors and interactions on the enrichment of arsenic and chromium by pipette tip solid phase extraction using novel P-ZrO 2 CeO 2 ZnO nanoparticles/alginate beads

The study seeks to determine the most significant factors affecting arsenic and chromium enrichment using novel P-ZrO 2 CeO 2 ZnO nanoparticles/alginate beads in order to minimize the total number of runs needed to successfully run the experiment. The effects of interactions between factors were also evaluated so that the optimum conditions which are not affected by the other factors are chosen for the experiments. The most significant factors on arsenic and chromium enrichment were screened for by using a half-factorial design, followed by the optimization of significant factors using the full-factorial design, and the interaction between factors was determined using ANOVA and interaction plots. The most significant factors for chromium recovery were sample volume, eluent flow rate, and sorbent dosage. For both chromium and arsenic recovery, interactions occurred between sample volume, dosage, and pH. The optimum conditions chosen for the experiment that gave favourable results for both metal ions were sample volume 5 mL, dosage 40 mg, pH = 7 and eluent flow rate 1 mL/min. This study showed that a preliminary screening step for the most significant factors for arsenic and chromium enrichment helps to reduce the number of total runs, and for the same experiment interactions between factors were present; hence, it is necessary to take this into account during the experimental design. hyperkeratosis, hyperpigmen- tation, cardiovascular disease, skin cancer, gangrene of limps,
Effect of Selenium on "Low T_3 Syndrome" inHepatic Failure Effect of Selenium on "Low T_3 Syndrome" inHepatic Failure

: Triiodothyronine occurs especially in 5’-monodeiodination of thyroxin in peripheral tissues. Deiodination of thyroxin mainly occurs in the liver. The enzyme which catalyzes this reaction is a seleno-enzyme. Deiodinase enzyme activity and the triiodothyronine level decrease in selenium deficiency. After the occurrence of chronic hepatic failure by carbon tetrachloride in rats, we gave sodium selenite to these rats. Then, we tried to evaluate the changes in thyroid hormone levels. Liver function tests, thyroxin and triiodothyronine levels, and hepatic 5’-deiodinase and glutathione peroxidase enzyme activities were measured. Triiodothyronine levels in the carbon tetrachloride group and carbon tetrachloride + selenium group were significantly lower than in the control group (P<0.01, P<0.05, respectively). In the carbon tetrachloride + selenium group, the level of triiodothyronine was higher than in the carbon tetrachloride group (P<0.05). Deiodination of thyroxin was impaired in hepatic failure. Selenium couldn’t prevent the inhibition of hepatic deiodination of thyroxin completely.
Attending to Visual Differences for Situated Language Generation in Changing Scenes

We investigate the problem of generating utter-001 ances from pairs of images showing a before 002 and an after state of a change in a visual scene. 003 We present a transformer model with differ-004 ence attention heads that learns to attend to vi-005 sual changes in consecutive images via a differ-006 ence key. We test our approach in instruction 007 generation, change captioning and difference 008 spotting and compare these tasks in terms of 009 their linguistic phenomena and reasoning abil-010 ities. Our model outperforms the state-of-the-011 art for instruction generation on the BLOCKS 012 and difference spotting on the Spot-the-diff 013 dataset and generates accurate referential and 014 compositional spatial expressions. Finally, we 015 identify linguistic phenomena that pose chal-016 lenges for generation in changing scenes. 017
WIND INSTRUMENTS IN SERBIAN PHRASEOLOGY а

Musical instruments are integral to our folklore and tradition, so much so that some even entered the phraseology of the Serbian language, shaping the image of the world expressed by it. The paper is aimed at examining idioms containing wind instruments as their component to determine what kind of linguistic image they depict. Examination of such material in contemporary Serbian language necessitated that its corpus be borrowed from The Phraseological Dictionary of the Serbian Language by Đorđe Otašević (2012), both due to its year of publication, and the author's intentions to examine the contemporary standard language. Reviewing the Dictionary , it was established that the following wind instruments occur as phraseological components: bagpipes, diple (type of bagpipe), duduk (double-reed woodwind instrument), the horn, svirala (pipe or flute), gourd and the fanfare. The semantic analysis of the idioms that contain the wind instruments mentioned above has established that the generation of the phraseological meaning results in a complete or partial desemanticization. In cases of complete desemanticization, the process of generating sound, i.e. playing these instruments, is transferred to the domain of human speech, thinking and actions. The process of partial desemanticization largely occurs in idioms with a comparative structure which are used to denote human traits, states or behaviors. In both cases, phraseologisms with negative meanings dominate. This may indicate that some of the functions of these wind instruments in our past have been negatively evaluated in the collective conscious from an ethical point of view, which indicates the need for new research. делимичне стање или понашање. И у првом и у дру-гом случају доминирају фразеологизми са негативним значењима. То може бити да у
Optimally Allocating Ambulances in Delhi using Mutation based Shuffled Frog Leaping Algorithm

This paper presents a reliable and competent evolutionary-based approach for improving the response time of Emergency Medical Service (EMS) by efficiently allocating ambulances at the base stations. As the prime objective of EMS is to save people's lives by providing them with timely assistance, thus increasing the chances of a person's survivability, this paper has undertaken the problem of ambulance allocation. The work has been implemented using the proposed mutation-based Shuffled Frog Leaping Algorithm (mSFLA) to provide an optimal allocation plan. The authors have altered the basic SFLA using the concept of mutation to improve the quality of the solution obtained and avoid being trapped in local optima. Considering a set of assumptions, the new algorithm has been applied for allocating 50 ambulances among 11 base stations in Southern Delhi. The working environment of EMS, which includes stochastic requests, travel time, and dynamic traffic conditions, has been considered to attain accurate results. The work has been implemented in the MATLAB simulation environment to find an optimized allocation plan with a minimum average response time. The authors have reduced the average response time by 12.23% with the proposed algorithm. The paper also compares mSFLA, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) for the stated problem. The algorithms are compared in terms of objective value (average response time), convergence rate, and constancy repeatability to conclude that mSFLA performs better than the other two algorithms. Keywords—Ambulance allocation; ambulance service; emergency medical service; shuffled frog leaping algorithm; mutation based shuffled frog leaping algorithm
Cognitive Artifacts and Their Virtues in Scientific Practice

Abstract One of the critical issues in the philosophy of science is to understand scientific knowledge. This paper proposes a novel approach to the study of reflection on science, called “cognitive metascience”. In particular, it offers a new understanding of scientific knowledge as constituted by various kinds of scientific representations, framed as cognitive artifacts. It introduces a novel functional taxonomy of cognitive artifacts prevalent in scientific practice, covering a huge diversity of their formats, vehicles, and functions. As a consequence, toolboxes, conceptual frameworks, theories, models, and individual hypotheses can be understood as artifacts supporting our cognitive performance. It is also shown that by empirically studying how artifacts function, we may discover hitherto undiscussed virtues and vices of these scientific representations. This paper relies on the use of language technology to analyze scientific discourse empirically, which allows us to uncover the metascientific views of researchers. This, in turn, can become part of normative considerations concerning virtues and vices of cognitive artifacts.
M5-branes in AdS$_4 \times Q^{1,1,1}$ spacetime

In this paper, we study the M5-brane configurations in AdS$_4 \times Q^{1,1,1}$ spacetime. We consider the configurations with an AdS$_2$ factor embedding into AdS$_4$, and manage to construct two solutions, which could be dual to line defects in the boundary gauge theory. Moreover we discuss their BPS nature and find that neither of them is supersymmetric. We show that the M5-brane with a R$_t$ or an AdS$_3$ factor found before is half-BPS.
Hypergraphs: Combinatorics of Finite Sets

1. General Concepts. Dual Hypergraphs. Degrees. Intersecting Families. The Coloured Edge Property and Chvatal's Conjecture. The Helly Property. Section of a Hypergraph and the Kruskal-Katona Theorem. Conformal Hypergraphs. Representative Graphs. 2. Transversal Sets and Matchings. Transversal Hypergraphs. The Coefficients r and r'. r-Critical Hypergraphs. The Konig Property. 3. Fractional Transversals. Fractional Transversal Number. Fractional Matching of a Graph. Fractional Transversal Number of a Regularisable Hypergraph. Greedy Transversal Number. Ryser's Conjecture. Transversal Number of Product Hypergraphs. 4. Colourings. Chromatic Number. Particular Kinds of Colourings. Uniform Colourings. Extremal Problems Related to the Chromatic Number. Good Edge-Colourings of a Complete Hypergraph. An Application to an Extremal Problem. Kneser's Problem. 5. Hypergraphs Generalising Bipartite Graphs. Hypergraphs without Odd Cycles. Unimodular Hypergraphs. Balanced Hypergraphs. Arboreal Hypergraphs. Normal Hypergraphs. Mengerian Hypergraphs. Paranormal Hypergraphs. Appendix: Matchings and Colourings in Matroids. References.
AUTOMORPHISMS OF C: A survey of the Andersén-Lempert theory

In this project, we study the automorphisms of C. We give a proof of the Global Andersén Lempert Theorem (Theorem 3.1) as well as the Local Andersén Lempert Theorem (Theorem 3.11). We illustrate the importance of these results by giving three geometric applications (Theorems 4.1, 4.10, and 4.18).
Machine Reading Comprehension: Generative or Extractive Reader?

While both extractive and generative readers 001 have been successfully applied to the Question 002 Answering (QA) task, little attention has been 003 paid toward the comparison of these two read-004 ers. Which reader performs better? What are 005 the reasons for the performance differences? 006 In this paper, we aim to answer these ques-007 tions in the setting of extractive QA tasks. We 008 design multiple transformer-based models and 009 different scenarios to systematically compare 010 these two readers. Our ﬁndings characterize 011 the difference of two readers and their pros 012 and cons, which can instruct the optimal se-013 lection of the two readers, and open up new 014 research avenues to improve each reader. Our 015 major ﬁndings are: 1) generative readers per-016 form better when the input context is long, 017 whereas extractive readers are better when the 018 context is short; 2) extractive readers general-019 ize better as compared to the generative ones 020 under out-of-domain settings, in both single-021 and multi-task learning scenarios. Our exper-022 iments also suggest that, although an encoder-023 only pre-trained language model (PrLM) is an 024 intuitive choice for extractive readers, the en-025 coder from encoder-decoder PrLM is a strong 026 alternative that performs competitively. 027
Transparent Distributed Investment in Digital Era Based on Blockchain Technology

In traditional indirect investment, in all methods we see a big problem called lack of transparency and lack of trust. Investors cannot find completely transparent data to compare funds and portfolios, and it is difficult to trust them. Blockchain technology and smart contracts can meet these challenges. They can create a safe environment for investors by creating trust-free funds, and blockchain technology ensures the transparency of traders' data. In this article, we try to take a step towards the future of investment by examining blockchain technology and protocols like Betoken, Cook and d HEDGE and comparing their performance.
Diagnostic Predictive Value of Tryptase, Serum Amyloid A and Lipoprotein-Associated Phospholipase A2 Biomarker Groups for Large Atherosclerotic Cerebral Infarction

Background There has been a gradual trend towards younger ageing of acute cerebral infarction in recent years. Atherosclerotic plaque rupture followed by dislodgement of emboli and resulting arterial embolism is an important mechanism for the development of acute cerebral infarction. Traditional independent risk factors for cerebral infarction have received attention from clinicians, but the risk factors for large artery atherosclerotic cerebral infarction are still unclear. Various blood biomarkers have an important role in the early diagnosis of large artery atherosclerotic cerebral infarction. Objective To assess the diagnostic predictive value of a group of biomarkers for large artery atherosclerotic cerebral infarction. Methods Lipoprotein-associated phospholipase A2 (LP-PLA2), trypsin-like protein (TPS), serum amyloid A (SAA), and supersensitive C-reactive protein (hs-CRP) levels were measured in the case group (30 cases) and control group (54 cases), respectively. Results The differences in the general data between the two groups were not statistically significant (P > 0.05). Logistic regression and ROC curve analysis showed that Lp-PLA2, TPS, and SAA were positively associated with the diagnosis of large atherosclerotic cerebral infarction (P < 0.05). The area under the ROC curve of the multivariate model for the biomarker group reached 0.995. Conclusion Biomarkers are closely associated with the occurrence of large atherosclerotic cerebral infarction and can be used as clinical adjuncts for diagnosis and assessment of prognosis.
Electromechanical power flowcharts in systems of electrical circuits

We present an original undergraduate level compilation for the physics of electromechanical systems with special attention to power flow. An approach based on energy considerations is presented that is specially suited to compute the mechanical and electrical actions of electromagnetic fields and to draw power flowcharts that clarify the path taken by energy in typical devices. The procedure guarantees energy conservation and provides a consistent way for auditing the power flow.
Perspectival Computational Thinking for Learning Physics: A Case Study of Collaborative Agent- Based Modeling

We examine the process through which computational thinking develops in a perspectival fashion as two middle school students collaborate with each other in order to develop computational models of two graphs of motion. We present an interaction analysis of the students' discourse and computational modeling, and analyze how they came to a joint understanding of the goal of the modeling activity. We show that this process involves bringing about coherence between multiple perspectives: the object in motion, the computational agent, the other student, and graphs of motion.
Performance Analysis of Deep Learning YOLO models for South Asian Regional Vehicle Recognition

— For years, humans have pondered the possibility of combining human and machine intelligence. The purpose of this research is to recognize vehicles from various media and while there are multiple models associated with this, there has not been enough testing and training of models when it comes to vehicle datasets that originate from countries like Bangladesh, India, etc. Our focus was to assimilate the largest dataset of vehicles exclusive to South Asia in addition to the more common universal vehicles and apply it to track and recognize these vehicles, even in motion. To develop this, we increased the class variations and quantity of the data. We trained different versions of the YOLOv5 model with our dataset to properly measure the degree of accuracy between the models in detecting the more unique vehicles. If vehicle detection and tracking are adopted and implemented in live traffic camera feeds, the information can be used to create smart traffic systems that can regulate congestion and routing by identifying and separating fast and slow-moving vehicles on the road. The comparison between the three different YOLOv5 models led to an analysis that indicates that the large variant of the YOLOv5 architecture outperforms the rest .