Miracle-dz/UniFAR-FTUs huggingface dataset:
Current knowledge on biology, fishing and conservation of the blue shark (Prionace glauca)

The blue shark (Prionace glauca) is a large predator in marine ecosystems, figuring as the most common and abundant species in oceanic fisheries. For this reason, many studies on this species were conducted throughout its entire distribution range. However, no comparison has been made regarding the variability of the aspects addressed herein. Thus, the present study aims at analyzing the available information on P. glauca. This species constitutes between 85 and 90% of the total elasmobranchs caught by oceanic fisheries with pelagic longlines. Growth parameters reveal that individuals in the Atlantic Ocean show the highest asymptotic lengths when compared to those found in other oceans. Females present an average uterine fecundity of 30 embryos. Although it shows a diverse diet, it is mainly composed of teleost fish and cephalopods. Currently, the main threat to the species is commercial fishing, being listed in Brazil and worldwide, according to IUCN as Near Threatened. Regardless, information on crucial aspects, such as its population dynamics, are still scarce or unreliable for many areas. Despite the number of studies regarding its distribution, abundance, and biology, data for new stock assessments of P. glauca are still needed to improve the species’ management.
2. Farate-A-kjms-vol13no2

SONOGRAPHIC EVALUATION OF THE COMMON BILE DUCT SIZE IN NORMAL ADULTS AT UNIVERSITY OF MAIDUGURI TEACHING HOSPITAL, NIGERIA 1 Farate A, Umar UH, Ahmadu MS, Mustapha Z, Ahidjo A, Tahir A Department of Radiology, University of Maiduguri Teaching Hospital, Maiduguri, Borno State, Nigeria. Correspondences and reprint request to: Dr Abubakar Farate, Department of Radiology, University of Maiduguri Teaching Hospital, P. M. B. 1414 Maiduguri, Borno State, Nigeria. Email: Phone: +2348033581675 abu.farati@gmail.com Background: Despite ultrasound safety, affordability and its widespread use in evaluation of the diseases of biliary tree, paucity of literature on the sonographic measurements of the size of the normal adult common bile duct (CBD) in this environment exists. Objectives: To determine the normal adult diameter of the CBD in this environment using ultrasonography. Methods: This was a cross-sectional prospective study carried out at the University of Maiduguri Teaching Hospital between January to June, 2011. Results: There were 224(56%) females and 176(44%) males aged between18 and 87 years (Mean±SD, 36.88 ±16.97 years). The mean AP and transverse CBD diameters (±SD) were 3.68±0.82mm and 3.89±0.86mm, respectively. The average mean for the two measurements (± SD) was 3.78±0.84mm (range = 2.0 – 6.0 mm). The mean transverse diameter was slightly greater than AP diameter (p = 0.0004). The CBD diameter was strongly correlated with age (r = 2 0.798; p = 0.000; r = 0.629). The least squares regression slope of 0.039mm±0.001 (mean±SD) was obtained suggesting 0.039mm±0.001 increase in the CBD diameter per year. There was significant correlation between the CBD diameter with weight (r = 0.504; p = 0.000) and BMI (r = 0.454; p = 0.000). No significant difference between the mean CBD diameter in males and females (p= 0.084)was observed. Conclusion: The mean and range of CBD size in normal adult population were determined and significantly correlated with age, weight, and BMI. ORIGINAL ARTICLE Page 51 Kanem Journal of Medical Sciences 2019;13(2): 51-59
Adsorption and photochemical transformation of polycyclic aromatic hydrocarbons on atmospheric water films

Atmospheric water films affect the processing of chemicals in the atmosphere and have potential effects on human health and the environment. In this work, adsorption and photochemical transformations of gas-phase PAHs were studied in a flow-tube photo-reactor with a view to understanding the behavior of gas-phase PAHs occurring in thin water films such as those of aerosols and fog. Naphthalene and phenanthrene were chosen as model PAHs for this
Uric acid levels in Saudi females with type 2 diabetes mellitus

Background and Aim: Many studies have shown a relationship between hyperuricemia, metabolic syndrome (MetS), and cardiovascular disease. However, there is a dearth of studies identifying this relationship in those with type 2 diabetes mellitus (T2DM). Therefore, in the current study, we assessed the prevalence of hyperuricemia in Saudi females with T2DM and studied the correlation between risen serum uric acid levels and MetS. Methods and Results: We adopted an epidemiological, cross-sectional design. Participants were women aged ≥35 years old (n = 200) living in Al Madinah Al Munawarah city. Biochemical factors relevant to diabetes were measured. These included serum uric acid levels, glucose levels, HbA1c, and lipid profiles. In female T2DM patients, ANALYSIS 24(106), November December, 2020 Medical Science ISSN 2321–7359 EISSN 2321–7367
How do investor relations firms create value for their clients? Evidence from financial restatements

We examine whether investor relations (IR) firms create value by improving their clients’ communications. We find that IR clients experience higher restatement announcement returns than propensity-score matched control firms. Inconsistent with IR firms hyping for their clients, we do not observe return reversals in the post-restatement periods. The positive effect of IR is greater for clients with higher information asymmetry. Further investigations show that the valuation impact goes through both the expected cash flows and the discount rate. Overall, our findings suggest that IR professionals increase value for their clients by helping them communicate effectively during periods of crises, when communication is vital.
Perceptions of Auditor Conscientiousness and Fraud Detection

Fraud is expensive at both the societal and organiz ational level. One analysis concluded that the collective economic cost of fraud exceeds $650 billion each year (ACFE, 2006). The costs at the organizational level are more immediat and include the loss of reputation, a decline in market capitalization and even the dissolution o f the firm. Because of the extensive implicit and explicit costs of fraud, identifying ways to in crease the probability of fraud detection is of great interest to all stakeholders, but because the organization holds t he ul imate responsibility for any fraudulent behavior, it has the greatest mo tivation to detect fraud before it can adversely impact the financial statements. One way organizat ions can enhance the probability of detecting fraud in its nascent stage is by identifying, hirin g and utilizing internal auditors that are best suited for the task of fraud detection.
ABSORPTIVE CAPACITY AND INNOVATIVENESS IN TECHNOLOGICAL ENVIRONMENTS: AN ANALYSIS IN THE LIGHT OF THEORY

This paper presents an analysis in the form of a theoretical essay that approaches absorptive capacity as a promoter of organizational innovativeness in which all of the many different activities involved in knowledge management should be capable of promoting intraorganizational innovation. From this perspective, it is considered that absorptive capacity is related to market orientation and to the capacity to innovate. In other words, when an organizational environment has a greater degree of absorptive capacity, market-oriented behavior can stimulate innovative activities that will be valued and utilized by customers, thereby validating the whole process of knowledge transformation that is part of absorptive capacity (Lane & Lubatkin, 1998; Tsai, 2001; Yli-Renko, Autio & Sapienza, 2001; Zahra & George, 2002; Chao et al., 2011). Absorptive capacity is therefore the result of organizational management mechanisms that are capable of identifying new values for the organization. The concept synthesizes the process that starts with knowledge absorption and extends through to the exploitation of knowledge to generate innovation-oriented organizational capabilities, in a process of appropriation of external knowledge and its transformation into new knowledge.
Heat Transfer Model Performance in Simulation of Process Deviations

Performance of thermal process simulation software was tested for predicting internal product temperature and lethality. Responses were tested for process deviations on canned products with a wide range of heating characteristics for computer-based on-line control of retorts. Static and agitated processes were tested with products exhibiting heating rate factors (fh) ranging from 2 to 70 min. Cans were fitted with thermocouples and subjected to deviations of various types. Center temperature profiles and lethalities predicted by the model in response to dynamic retort temperatures were compared with those measured by thermocouples. Profiles agreed, and process lethalities calculated from predicted and measured profiles agreed ±10% with the model slightly underpredicting measured lethality.
The analysis of bud exudate of Populus x euramericana, and of propolis, by gas chromatography–mass spectrometry

Propolis and bud exudate of Populus x euramericana have been analysed by high-resolution gas chromatography–mass spectrometry; 104 compounds have been identified, including 26 not previously identified in propolis or bud exudate. The compounds identified in propolis are derived from three sources: plant exudate collected by bees, wax secreted by bees, and materials such as sugars, which are probably introduced accidentally either during propolis manufacture or during subsequent passage of bees over the propolis. Previous observations that bees use bud exudate from Populus as a primary source for propolis manufacture are confirmed.
Phenotype Risk Scores: moving beyond cases and controls to classify psychiatric disease in hospital-based biobanks.

Current phenotype classifiers for large biobanks with coupled electronic health records EHR and multi-omic data rely on ICD-10 codes for definition. However, ICD-10 codes are primarily designed for billing purposes, and may be insufficient for research. Nuanced phenotypes composed of a patients' experience in the EHR will allow us to create precision psychiatry to predict disease risk, severity, and trajectories in EHR and clinical populations. Here, we create a phenotype risk score (PheRS) for major depressive disorder (MDD) using 2,086 cases and 31,000 individuals from Mount Sinai's biobank BioMe. Rather than classifying individuals as 'cases' and 'controls', PheRS provide a whole-phenome estimate of each individual's likelihood of having a given complex trait. These quantitative scores substantially increase power in EHR analyses and may identify individuals with likely missing diagnoses (for example, those with large numbers of comorbid diagnoses and risk factors, but who lack explicit MDD diagnoses). Our approach applied ten-fold cross validation and elastic net regression to select comorbid ICD-10 codes for inclusion in our PheRS. We identified 158 ICD-10 codes significantly associated with Moderate MDD (F33.1). Phenotype Risk Score were significantly higher among individuals with ICD-10 MDD diagnoses compared to the rest of the population (Kolgorov-Smirnov p<2.2e-16), and were significantly correlated with MDD polygenic risk scores (R2>0.182). Accurate classifiers are imperative for identification of genetic associations with psychiatric disease; therefore, moving forward research should focus on algorithms that can better encompass a patient's phenome.
TCA cycle remodeling is associated with IL-1Î²-mediated proinflammatory eicosanoid signaling in humans with pulmonary tuberculosis

The metabolic signaling pathways that drive pathologic tissue inflammation and damage in humans with pulmonary tuberculosis (TB) are not well understood. Using combined methods in plasma high-resolution metabolomics, lipidomics and cytokine profiling from a multicohort study of humans with pulmonary TB disease, we discovered that IL-1{beta}-mediated inflammatory signaling was closely associated with TCA cycle remodeling, characterized by accumulation of TCA cycle intermediates such as succinate and decreased itaconate. This inflammatory metabolic network was particularly active in persons with multidrug-resistant (MDR)-TB after receiving 2 months of ineffective treatment and was only reversed after 1 year of appropriate anti-TB chemotherapy. Both succinate and IL-1{beta} were closely associated with increases in proinflammatory lipid signaling, including increases in the products of phospholipase A2, increased arachidonic acid formation, and metabolism of arachidonic acid to proinflammatory eicosanoids. Together, these results indicate that decreased itaconate and accumulation of succinate and other TCA cycle intermediates are important drivers of IL-1{beta}-mediated proinflammatory eicosanoid signaling in humans with pulmonary TB disease. Host-directed therapies that mitigate such metabolic reprograming may have potential to limit excessive pulmonary inflammation and tissue damage.
using CLICK BASED

 Abstract — Abstract - The growth of technology in the field of computer science & the popularity of information technology has changed the means of information exchange from letters to electronic messages. Security became a major concern with the advent of electronic messages as it led to higher possibilities of information attacks. One of the proposed solutions to this problem is the usage of passwords to protect the information. Password is a string of characters used for user authentication to prove identity or approval to gain access to a resource, which should be unknown to or kept secretive from unauthorized users. The most common types of passwords are Numeric Passcodes, Textual Passcodes or Alpha numeric Passcodes. These types of passwords are vulnerable to various kinds of attacks, such as eaves dropping, shoulder surfing, dictionary attack, spyware attack etc. This paper proposes a unique idea of
Skinfold Equations for Estimation of Body Fatness in Children and Youth I

I hoJy (arnes, as determined hI' three ,el',lr:lte ;'rproache,. (I) hody demlry (rom hyJrost;ltic weir,:hing an,1 (unctiol1al residu,d volulTle al"ne (PFD): (2} "ody den,,'y ;md w;Her (PFDW); (3) h"dy den"ry, ",;lter 'md hone mlner,,1 (PFD\VR). Bonc mineral W;1" estunated (rum radius :mel IIlna ll1ca'urement5 ! l"ing phot"n :1h,o[rti"ll1Cuy, ,In,1 t"t,d hody w:ner was ('<;(lIn,lIcd lISlng delll<'TlIllll oxide dilllrtlin. Nine ,kln(,,\d, ,",'ere taken ",id) a "l:lTrcndcn :! ( c:dil'cr. A 4 X 2 x 2 (;lcc"ri,d [,Ian \\':1' lI'l'd rCI'le'Cnllng (our 1n,Hllr,n1(1I1
Elevated HScore is Associated with Poor Clinical Outcomes in COVID-19, Even in the Absence of Secondary Hemophagocytic Lymphohistiocytosis.

Introduction: Patients with Coronavirus Disease 2019 (COVID-19) frequently experience a hyperinflammatory syndrome, that leads to unfavorable outcomes. This condition resembles Secondary Hemophagocytic Lymphohistiocytosis (sHLH) described in neoplastic, rheumatic and other infectious diseases. However, it has not been prospectively studied on these patients. A scoring system (HScore) has been validated for sHLH, and recently proposed to evaluate hyperinflammation in COVID-19. Methods: 143 patients aged [≥]18 years admitted because of COVID-19 were enrolled in a prospective, single-center, cohort study. HScore was calculated within the 72 hours since admission. The incidence of sHLH during hospitalization was evaluated. Additionally, the relationship between HScore [≥]130 points and either the requirement of mechanical ventilation or 60-days mortality was explored. Results: The median age of enrolled patients was 57 (21-100), and 63.6% were male. The median HScore was 96 (33-169). One patient was diagnosed with sHLH (incidence 0,7%), due to a HScore of 169. After adjusting for age, sex, comorbidities and obesity, HScore [≥]130 was independently associated with the composite clinical outcome (HR 2.13, p=0.022). Conclusion: sHLH is not frequent among COVID-19 patients. HScore can efficiently predict the risk for poor outcomes.
A Unified Paths Perspective for Pruning at Initialization

A number of recent approaches have been proposed for pruning neural network parameters at initialization with the goal of reducing the size and computational burden of models while minimally affecting their training dynamics and generalization performance. While each of these approaches have some amount of well-founded motivation, a rigorous analysis of the effect of these pruning methods on network training dynamics and their formal relationship to each other has thus far received little attention. Leveraging recent theoretical approximations provided by the Neural Tangent Kernel, we unify a number of popular approaches for pruning at initialization under a single path-centric framework. We introduce the Path Kernel as the data-independent factor in a decomposition of the Neural Tangent Kernel and show the global structure of the Path Kernel can be computed efficiently. This Path Kernel decomposition separates the architectural effects from the data-dependent effects within the Neural Tangent Kernel, providing a means to predict the convergence dynamics of a network from its architecture alone. We analyze the use of this structure in approximating training and generalization performance of networks in the absence of data across a number of initialization pruning approaches. Observing the relationship between input data and paths and the relationship between the Path Kernel and its natural norm, we additionally propose two augmentations of the SynFlow algorithm for pruning at initialization.
Synthesis of polymers in aqueous solutions: Esterification reaction of poly(methacrylic acid) with alkyl halides using DBU in aqueous solutions

A convenient esterification reaction of poly(methacrylic acid) (PMAA) with certain alkyl halides was performed using 1,8-diazabicyclo-[5.4. 0]-7-undecene (DBU) as a base in aqueous solution or in water. The esterification reaction of PMAA with propargyl bromide (PB) proceeded very smoothly and quantitatively at 30°C to give corresponding poly(propargyl methacrylate), although the rate of the reaction decreased with increasing water. The reaction of PMAA with benzyl bromide, o-nitrobenzyl bromide, and p-nitrobenzyl bromide gave corresponding poly(methacrylic ester) using DBU under suitable reaction conditions in water. The esterification reactions of PMAA with PB were carried out using certain organic bases such as triethylamine, 4(N,N-dimethylamino)pyridine and pyridine. Inorganic bases such as sodium carbonate, sodium hydroxide, potassium carbonate, and potassium hydroxide were also tried under the same conditions as with DBU. However, the degrees of estrification with all these bases was much lower than that with DBU. © 1996 John Wiley & Sons, Inc.
BE-RAN: Blockchain-enabled Open RAN with Decentralized Identity Management and Privacy-Preserving Communication

Radio Access Networks (RAN) tends to be more distributed in the 5G and beyond, in order to provide low latency and flexible on-demanding services. In this paper, Blockchain-enabled Radio Access Networks (BE-RAN) is proposed as a novel decentralized RAN architecture to facilitate enhanced security and privacy on identification and authentication. It can offer user-centric identity management for User Equipment (UE) and RAN elements, and enable mutual authentication to all entities while enabling on-demand point-to-point communication with accountable billing service add-on on public network. Also, a potential operating model with thorough decentralization of RAN is envisioned. The paper also proposed a distributed privacy-preserving P2P communication approach, as one of the core use cases for future mobile networks, is presented as an essential complement to the existing core network-based security and privacy management. The results show that BE-RAN significantly improves communication and computation overheads compared to the existing communication authentication protocols.
Compositional Cyber-Physical Systems Modeling

Assuring the correct behavior of cyber-physical systems requires significant modeling effort, particularly during early stages of the engineering and design process when a system is not yet available for testing or verification of proper behavior. A primary motivation for `getting things right' in these early design stages is that altering the design is significantly less costly and more effective than when hardware and software have already been developed. Engineering cyber-physical systems requires the construction of several different types of models, each representing a different view, which include stakeholder requirements, system behavior, and the system architecture. Furthermore, each of these models can be represented at different levels of abstraction. Formal reasoning has improved the precision and expanded the available types of analysis in assuring correctness of requirements, behaviors, and architectures. However, each is usually modeled in distinct formalisms and corresponding tools. Currently, this disparity means that a system designer must manually check that the different models are in agreement. Manually editing and checking models is error prone, time consuming, and sensitive to any changes in the design of the models themselves. Wiring diagrams and related theory provide a means for formally organizing these different but related modeling views, resulting in a compositional modeling language for cyber-physical systems. Such a categorical language can make concrete the relationship between different model views, thereby managing complexity, allowing hierarchical decomposition of system models, and formally proving consistency between models.
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups

Phase I clinical trials are designed to test the safety (non-toxicity) of drugs and find the maximum tolerated dose (MTD). This task becomes significantly more challenging when multiple-drug dose-combinations (DC) are involved, due to the inherent conflict between the exponentially increasing DC candidates and the limited patient budget. This paper proposes a novel Bayesian design, SDF-Bayes, for finding the MTD for drug combinations in the presence of safety constraints. Rather than the conventional principle of escalating or de-escalating the current dose of one drug (perhaps alternating between drugs), SDF-Bayes proceeds by cautious optimism: it chooses the next DC that, on the basis of current information, is most likely to be the MTD (optimism), subject to the constraint that it only chooses DCs that have a high probability of being safe (caution). We also propose an extension, SDF-Bayes-AR, that accounts for patient heterogeneity and enables heterogeneous patient recruitment. Extensive experiments based on both synthetic and real-world datasets demonstrate the advantages of SDF-Bayes over state of the art DC trial designs in terms of accuracy and safety.
LAIF: AI, Deep Learning for Germany Suetterlin Letter Recognition and Generation

One of the successful early implementation of deep learning AI technology was on letter recognition. With the recent breakthrough of artificial intelligence (AI) brings more solid technology for complex problems like handwritten letter recognition and even automatic generation of them. In this research, we proposed deep learning framework called Ludwig AI Framework(LAIF) for Germany Suetterlin letter recognition and generation. To recognize Suetterlin letter, we proposed deep convolutional neural network. Since lack of big amount of data to train for the deep models and huge cost to label existing hard copy of handwritten letters, we also introduce the methodology with deep generative adversarial network to generate handwritten letters as synthetic data. Main source code is in https://github.com/enkhtogtokh/LAIF repository.