Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Quantum Effect for Nano-confined Substance Ultrafast Flow

Many researchers, however, found that the flow of both liquid and gas through nanoscale pores is one to even seven orders of magnitude faster than that would be predicted from the classic Newton’s mechanic theories, such as the Hagen-Poiseuille equation, the Bernoulli’s principle, the Knudsen theory. Here, for the first time, we propose a possible explanation for the ultra-fast flow of substance through the nano-confined pores based on the Wave-Particle Dualism. Since the mass of the substance is a constant, the velocity of the substance in the nanopores is very important. The molecule behaves like a particle above the critical velocity, while could reduce its velocity to the critical value in the nanopores, which, then, behaves like the wave inducing the tunneling transfer. The critical velocities in 18 different study cases from the literatures have been calculated. The role of quantum effect for ultrafast flow could possibly provide new ideas for studying the nature of the physiological processes with the ion and molecule channels, which are the backbones for the biology, and possibly promote the development of new method for energy conversion, desalination of sea water and even for information systems.
Verifiable Credential Proof Generation and Verification Model for Decentralized SSI-Based Credit Scoring Data

SUMMARY The continuous development of the mobile computing environment has led to the emergence of ﬁntech to enable convenient ﬁnan-cial transactions in this environment. Previously proposed ﬁnancial identity services mostly adopted centralized servers that are prone to single-point-of-failure problems and performance bottlenecks. Blockchain-based self-sovereign identity (SSI), which emerged to address this problem, is a technology that solves centralized problems and allows decentralized iden-tiﬁcation. However, the veriﬁable credential (VC), a unit of SSI data trans-actions, guarantees unlimited right to erasure for self-sovereignty. This does not suit the speciﬁcity of the ﬁnancial transaction network, which requires the restriction of the right to erasure for credit evaluation. This paper proposes a model for VC generation and revocation veriﬁcation for credit scoring data. The proposed model includes double zero knowledge - succinct non-interactive argument of knowledge (zk-SNARK) proof in the VC generation process between the holder and the issuer. In addition, cross-revocation veriﬁcation takes place between the holder and the veriﬁer. As a result, the proposed model builds a trust platform among the holder, issuer, and veriﬁer while maintaining the decentralized SSI attributes and focusing on the VC life cycle. The model also improves the way in which credit evaluation data are processed as VCs by granting opt-in and the special right to erasure.
Impacts of Low-Carbon Fuel Standards in Transportation on the Electricity Market

Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market dimension. In this paper, an Electricity Market Model with Electric Vehicles (EMMEV) was developed, exploiting an agent-based model that analyzes how carbon reduction policy in transportation may increase the number of Electric Vehicles and how that would influence electricity price. Agents are Energy Service Providers (ESCOs) which can distribute fuels and their objective is to maximize their profit. In this paper, the EMMEV is used to analyze the impacts of the Low-Carbon Fuel Standard (LCFS), a performance-based policy instrument, on electricity prices and EV sales volume. The agents in EMMEV are regulated parties in LCFS should meet a certain Carbon Intensity (CI) target for their distributed fuel. In case they cannot meet the target, they should buy credits to compensate for their shortfall and if they exceed it, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price, as a result of implementing the LCFS and increasing number of EVs, has increased between 2% and 3% depending on banking strategy.
A review and meta-analysis of machine intelligence approaches for mental health issues and depression detection

Cases of mental health issues are increasing continuously and have sped up due to COVID-19. There are high chances of developing mental health issues such as depression, anxiety, schizophrenia, and dementia after 2–3 months of COVID-19 diagnosis. In this paper, a review and meta-analysis of machine intelligence approaches—namely, machine learning, deep learning (deep learning with hybrid boosting), and machine vision methods—for mental health issues and depression detection were presented. Meta-analysis was performed in four parts. The first part focused on the publication trends, criteria for inclusion and exclusion, and the current methodological scenario. The second part was intended for the methods and their advantages and limitations. It covered mental health issues and depression detection techniques along with the challenges. The third part focused on the discussion and applicability of datasets. The fourth part focused on the complete analysis and discussion along with suggestive measures;moreover, it covered the overall analysis, including the methodological impact, result impact, current trends, and some suggestions based on the limitations and challenges. © The Authors.
The Uncontrolled Web: Measuring Security Governance on the Web

SUMMARY While websites are becoming more and more complex daily, the di ﬃ culty of managing them is also increasing. It is important to conduct regular maintenance against these complex websites to strengthen their security and improve their cyber resilience. However, misconﬁgura-tions and vulnerabilities are still being discovered on some pages of web-sites and cyberattacks against them are never-ending. In this paper, we take the novel approach of applying the concept of security governance to web-sites; and, as part of this, measuring the consistency of software settings and versions used on these websites. More precisely, we analyze multiple web pages with the same domain name and identify di ﬀ erences in the security settings of HTTP headers and versions of software among them. After analyzing over 8,000 websites of popular global organizations, our measurement results show that over half of the tested websites exhibit differences. For example, we found websites running on a web server whose version changes depending on access and using a JavaScript library with di ﬀ erent versions across over half of the tested pages. We identify the cause of such governance failures and propose improvement plans.
Uso de modelo multicritério não compensatório para a priorização de localizações para uma nova filial de uma empresa de combustíveis

A localização é um dos fatores estratégicos para as empresas, visto que impacta na sua cadeia de fornecedores, seus custos operacionais, proximidade aos clientes e oportunidades de expansão. Considerando estes aspectos, propomos neste estudo um modelo de apoio a decisão multicritério para priorização de cidades adequadas para a implantação de uma nova filial baseado no método não compensatório ELECTRE III. O artigo apresenta a temática de expansão de mercado e alguns artigos que propõem a solução de problemas de localização. Também é tratado a descrição da estrutura axiomática do método utilizado e discutido sobre o método de elicitação de pesos Direct Rating. O estudo de caso consistiu na análise das cidades mais adequadas da região de planejamento do Vale do Jaguaribe – CE para a introdução de mais uma filial de uma empresa que comercializa combustíveis, no qual o modelo foi composto por 15 alternativas, 6 critérios de avaliação e os parâmetros do método multicritério. O modelo forneceu uma ordem parcial, dando suporte ao problema de decisão e direcionando os gestores sobre a priorização das cidades na etapa de busca por terrenos processos de negociação.
Discovery of a 3 s Spinning Neutron Star in a 4.15 hr Orbit in the Brightest Hard X-Ray Source in M31

We report the discovery with XMM-Newton of 3 s X-ray pulsations from 3XMM J004232.1+411314, a dipping source that dominates the hard X-ray emission of M31. This finding unambiguously assesses the neutron star (NS) nature of the compact object. We also measured an orbital period of 4.15 hr and a projected semi-axis at aX sin i = 0.6 lt-s, which implies a low-mass companion of about 0.2–0.3 M⊙ assuming an NS of 1.5 M⊙ and an orbital inclination i = 60°–80°. The barycentric orbit-corrected pulse period decreased by ∼28 ms in about 16 year, corresponding to an average spin-up rate of s s−1; pulse period variations, probably caused by X-ray luminosity changes, were observed on shorter timescales. We identify two possible extreme scenarios for the source: a mildly magnetic NS with Bp ≃ few × 1010 G if the pulsar is far from its equilibrium period Peq and the disk is truncated at the value of the Alfvén radius corresponding to the observed luminosity, and a relatively young, highly magnetic NS with Beq ≃ 2 × 1013 G if spinning close to Peq and the disk is truncated close to the co-rotation surface.
Essential Thrombocytosis and Hepatocellular Carcinoma: A Mechanistic Challenge

Thrombocytosis has been reported in 8.2% of patients with Hepatocellular carcinoma [HCC] and has been attributed to increased Thrombopoietin [TPO] production by the tumor. We present a case of a 68-year-old male with a history of Hepatitis C and ethanol abuse presented with complaints of headache and chills. Imaging studies revealed a large mass in the liver [right lobe] suggesting an HCC of fibrolamellar type. His platelet count [PC] was 965 K/mcL. The serum AFP [Alpha feto protein] concentration was >51,800 ng/ml. There was no evidence of metastatic disease and the patient was started on Capecitabine and radiation therapy targeting the liver mass. Lung metastasis became evident and Sorafenib was added. His PCs and AFP concentrations however continued decreasing to 306 K/mcL and 460.7 ng/ml respectively. His PC then increased to a peak of 1.32 million/mcL 10 months later. The molecular workup done at our reference lab was positive for CALR [Calreticulin] mutation. The patient was started on Hydroxyurea and his PC decreased to 323 K/mcL at the time of writing. His AFP has remained stable. This case illuminates the complicated relationship between HCC and thrombocytosis. The therapy directed against the HCC did decrease PC and AFP concentration in our case. The second wave of thrombocytosis led to the discovery of CALR mutation, and the patient was diagnosed with Essential Thrombocytosis [ET]. Treatment with Hydroxyurea again decreased the PC while AFP concentration was increased but stable. Thrombopoietin levels have remained stable for the patient after treatment with Hydroxyurea. NA Although the question of which mechanism(or possibly both) was at work in this case cannot be resolved definitely, two points are worth noting. The first is that- the assumption that the thrombocytosis was related to the HCC delayed testing for mutations associated with Essential Thrombocytosis. The second is that the TPO assay that may have yielded useful information in sorting out the alternatives was not ordered early enough before starting hydroxyurea.
Effects of a High Voltage Line on a Biological Tissue

: Living tissues are highly heterogeneous, with very specific properties; and in order to determine the interactions between electromagnetic fields generated by different sources to which we are exposed, it is imperative to be able to calculate the induced electromagnetic currents and to find out the resulting reactions. To apprehend the field nuisance on people’s health, this paper highlights some of these effects from a simulation study of biological tissues (muscle sample) subjected to the electromagnetic field created by a 440 kV HV line. Induced currents in these tissues and their effects on blood microcirculation will be emphasized.
High-throughput preprocessing pipeline for resting-state fMRI

Resting-state functional magnetic resonance imaging (fMRI) examines functional connectivity between brain regions by measuring spontaneous fluctuation of blood-oxygen-level dependent (BOLD) signal while subjects are at rest. Recent studies have revealed that neurodegenerative diseases are associated with abnormalities in resting-state functional connectivity. This thesis work aimed to develop a high-throughput preprocessing pipeline for minimizing spatial and temporal artifacts in resting-state fMRI data. The building blocks and cluster computing capabilities of the pipeline are discussed in detail. In an effort to validate this pipeline, a seed-based analysis was performed on preprocessed data using 3 seeds placed in the posterior cingulate cortex (PCC), supplementary motor area (SMA) and inferior parietal sulcus (IPS). These 3 seeds represent the core components of the default mode network (DMN) and task-positive network (TPN), two of the most commonly examined resting-state networks. Consistent with literature, results indicate that activity in the PCC is functionally correlated to regions of the DMN and anti-correlated to regions of the TPN, whereas activities in the SMA and IPS are functionally correlated to regions of the TPN and anti-correlated to regions of the DMN. These functional connectivity patterns were consistent across scans on both group-level and subject-level. This preprocessing pipeline will support researchers and clinical collaborators of Medical Image Analysis Lab (MIAL) in their analysis of resting-state functional connectivity.
DNA Barcoding for Identification and Detection of Species

Identification is a very important part of the taxonomy. Since a species represents the basic unit of biological classification, identifying species is important to understand the systematics and the precise phylogenetic position of particular species. In recent years, species identification and delimitation have seen major improvements because of the incorporation of DNA sequence data. This review provides a comprehensive list of commonly employed nuclear and chloroplast regions used for the barcoding of plants.
Fast Model-based Protein Homology Discovery without Alignment

The need for quick gene categorization tools is growing as more genomes are sequenced. To evaluate a newly sequenced genome, the genes must first be identified and translated into amino acid sequences, which are then categorized into structural or functional classes. Protein homology detection using sequence alignment algorithms is the most effective way for protein categorization. Discriminative approaches such as support vector machines (SVMs) and position-specific scoring matrices (PSSM) derived from PSI-BLAST have recently been used to improve alignment algorithms. However, if a fresh sequence is being aligned, alignment algorithms take time. must be compared to a large number of previously published sequences — the same is true for SVMs. Building a PSSM for the PSSM is even more time-consuming than a fresh order It would take roughly 25 hours to implement the best-performing approaches to classify the sequences on today's computers. Describing a novel genome (20, 000 genes) as belonging to one single organism. There are hundreds of classes to choose from, though. Another flaw with alignment algorithms is that they do not construct a model of the positive class, instead of measuring the mutual distance between sequences or profiles. Only multiple alignments and hidden Markov models are common classification approaches for creating a positive class model, but they have poor classification performance. A model's advantage is that it may be evaluated for chemical features that are shared by all members of the class to get fresh insights into protein function and structure. We used LSTM to solve a well-known remote protein homology detection benchmark, in which a protein must be categorized as a member of the SCOP superfamily. LSTM achieves state-of-the-art classification performance while being significantly faster than other algorithms with similar classification performance. LSTM is five orders of magnitude quicker than the quickest SVM-based approaches and two orders of magnitude faster than methods that perform somewhat better in classification (which, however, have lower classification performance than LSTM). We applied LSTM to PROSITE classes and analyzed the derived patterns to test the modeling capabilities of the algorithm. Because it does not require established similarity metrics like BLOSUM or PAM matrices, LSTM is complementary to alignment-based techniques. The PROSITE motif was retrieved by LSTM in 8 out of 15 classes. In the remaining seven examples, alternative motifs are developed that, on average, outperform the PROSITE motifs in categorization.
Examining migration factors among generative college graduates: Strategic implications for people attraction, retention, and leadership transfer efforts

ABSTRACT Out-migration of college-educated young adults – a phenomenon that continues to plague rural community vitality – affects not just population size, but also has larger implications for leadership transfer due to impending Baby Boomer retirements. To help community leaders and policy makers simultaneously address forthcoming local leadership transfers as well as young adult attraction and retention efforts, community development scholars and practitioners will benefit from understanding young adults who think and act as “community builders” when choosing their living community after college – the focus of the current descriptive study. Both economic (i.e. available job opportunities) and non-economic (i.e. leadership opportunities) factors were identified as most important to migration decisions with “opportunities to make a difference” and “obtain work-life balance” emerging as highly important community choice factors. These results highlight strategic implications for people attraction, retention, and leadership transfer efforts.
Changes in the Names of Polish Investment Funds vs. Fund Flows

The set divided into positive changes (the new name suggested a new investment style for the fund), neutral and negative (fund names were not linked the investment policy). The third criterion were the types of funds (there were four groups of changes: for equity, mixed equity, debt and money market funds). In order determine the impact of changes in fund names on fund flows, there were used differences in average fund flows before and after changes. For detailed results, a second method was used – event analysis. Based on the results of the study, it can be concluded that changes in fund names have an impact on the size of fund flows even within a period of up to twelve months. The largest inflow of capitals to funds was demonstrated for positive changes, especially in the period from four to nine months after the change. In turn, the largest outflow of capital for negative changes was noted mainly in the period from seven to twelve months.
The M2Mix System

This paper introduces notions of semantics modiﬁer and on-standard semantics of programming languages. The universal resolving algorithm and neighborhood analyzer are considered as examples of semantics modiﬁers. The precise deﬁnition of semantics modiﬁer and non-standard semantics is given and illustrated with additional examples. Finally it is shown that programming tools for eﬀective implementation of non-standard semantics – non-standard interpreters, non-standard compilers – can be obtained using a powerful specializer (e
Screening for Student Subjective Wellbeing: An Analog Evaluation of Broad and Targeted Models

This brief report presents a secondary analysis of responses to the Student Subjective Wellbeing Questionnaire (SSWQ) with a sample of urban middle-schoolers. Relative classification validity evidence was evaluated for two screening models derived from responses to the SSWQ: one based on the Overall Wellbeing Scale (OWS) and the other based solely on the Academic Efficacy Subscale (AES). Results from Bayesian t-tests, using several school-reported outcomes as dependent variables, indicated evidence in favor of classification validity for both the OWS and AES screening models. Yet findings also show that the evidence for the AES model was stronger than that for the OWS model. Implications for future research and practice are discussed.
APLICAÇÃO COMBINADA DO VALUE-FOCUSED THINKING E DO FITRADEOFF: UM ESTUDO DE CASO EM UMA EMPRESA DO SETOR TÊXTIL DO AGRESTE PERNAMBUCANO

A cada dia, decisões necessitam ser tomadas nas mais variadas organizações. Neste contexto, as mesmas podem impactar na gestão e nos resultados empresariais. Porto outro lado, neste enquadramento, estruturar problemas e tomar decisões assertivas enquadram-se como tarefas complexas e que demandam certo tempo. Desta maneira, este artigo possui como objetivo principal aplicar o Value-Focused Thinking (VFT) e o método FITradeoff de ordenação, com o propóstio de facilitar o processo decisório da organização estudada, além de direcionar as implementações de melhorias. Assim sendo, com a estruturação concebida pelo VFT, o modelo foi construído com cinco critérios e dezoito alterantivas. Posto isto, foi possível ordenar as alternativas prioritárias com o método multicritério utilizado, recomendando as ações que busquem a evolução deste objeto de estudo.
STUDY ON SOME HEMATOLOGICAL AND BLOOD BIOCHEMICAL PARAMETERS OF NEWLY INTRODUCED LAYER BREEDS DEPENDING ON THE LAYING PERIOD

PURPOSE: To compare some major hematological and biochemical blood parameters of 3 newly introduced poultry breeds – Australorp, Marans and Araucana, during different stages of their egg-laying period. METHODS: Five blood parameters were investigated: hematocrit, hemoglobin, glucose, total protein and total cholesterol. A hundred blood samples were tested, collected at three laying stages – beginning, middle and end. RESULTS: Statistically significant differences in the hemoglobin levels by sexes were established: in Marans breed (males – between 8.38 and 13.45; females – between 7.30 and 9.02 g*dl-1) and Araucana (males – between 9.17 and 13.65; females – between 9.08 and 9.40 g*dl-1). The hematocrit levels in the males (from 23.16% in Marans to 40.88% in Australorp) were significantly higher than the levels in the females (from 23.72% in Marans to 30.48% in Australorp). The blood glucose test of the cocks (from 32.07 in Marans to 40.88 mmol*l-1 in Australorp) showed higher levels compared to the female (from 23.72 in Marans to 30.48 mmol*l-1 in Australorp). The total protein content in the layers’ blood (between 5.97 in Araucana and 8.73 g*dl-1 in Marans) was higher compared to cocks. The total cholesterol levels were, as follows: males – from 2.05 in Araucana to 3.49 mmol*l-1 in Australorp; females – from 1.92 in Australorp to 6.57 3.49 mmol*l-1 in Araucana. CONCLUSIONS: The variations in the investigated parameters in the blood are a result of the simultaneous effect of several factors - breed genetic differences, differences in egg-laying effort and degree of adaptation.