Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial enteric pathogens and serum interleukin-6 levels in children with acute diarrhea

Background Acute diarrhea is currently one of the major causes of morbidity and mortality in developing countries. A wide range of enteric pathogens, including bacteria, is responsible for the pathogenesis of acute infectious diarrhea. Recent studies have shown an increase in acute phase proteins, such as serum interleukin-6 (IL-6) levels, in patients with acute bacterial gastroenteritis. Thus, IL-6 may be a useful marker to differentiate bacterial from non-bacterial enteric pathogens. Objective To assess for a correlation between bacterial enteric pathogens and serum IL-6 levels in children with acute diarrhea. Methods We conducted a cross-sectional study from November 2013 to March 2014 in two hospitals in Manado. Subjects were children aged 1-5 years with acute diarrhea and good nutritional status. Subjects’ provided stool samples for bacterial culture and microscopic examination, as well as blood specimens for serum IL-6 measurements. Data was analyzed by linear regression and Pearson’s correlation tests for a correlation between bacterial enteric pathogens and serum IL-6 levels. Results In children with acute diarrhea, those with bacterial enteric pathogens had significantly higher mean serum IL-6 than those with non-bacterial enteric pathogens (r = 0.938; P < 0.001). Conclusion Serum IL-6 levels are significantly more elevated in children with acute diarrhea and bacterial enteric pathogens. Therefore, serum IL-6 may be a useful marker for early identification of bacterial gastroenteritis in children aged 1-5 years. [Paediatr Indones. 2016;56:144-8. ].
Fuzzy model estimation of the risk factors impact on the target of promotion of the software product

ABSTRACT This article studies the application of fuzzy logic to the risk analysis of a new software product development and marketing in specific case of a small size IT company. Identification and analysis of external and internal risk factors show that this type of business activity could be evaluated as high-risk enterprise. So, the purpose of the paper is to develop robust method to evaluate probability of occurrence of major risk events and their impact on the company financial health. The fuzzy logic is used to estimate degrees of threat of each relevant risk factor due to lack of reliable statistical data. The novelty of proposed approach is the inclusion into the model the risk event time.
CAGE Screening at Emergency Department with Trauma Patients

Due to the great evidence between accidents trauma assisted in the emergency department (ED) and the involvement of patients with alcohol, the goal of this work is characterize violence and trauma patients treated in two regional hospitals in a rural area, using the CAGE questionnaires and other questionings. A cross-sectional cohort study was carried out from August 2014 and December 2015, on weekends. 85 individuals, who showed clinical characteristics of alcohol intoxication, were submitted to a socio-demographic and CAGE questionnaires. The data analysis was carried out using the Statistical Package for the Social Sciences SPSS 20.0. The 73.5% of the individuals were male, 83% non-white, 61.5% with less than 6 years of formal education, and 57% of men and 68% of women were single. The main sectors of occupation were agriculture (25%), trade and services (27%), followed by students (12%) and only 1.2% of them were unemployed. The vast majority of traumas were caused by motorcycles (80%), followed by car accidents (7%). The results obtained with the CAGE questionnaire was surprising since 38.2% of the interviewees scored two or more points, of those, 10.7% answered affirmatively three or more questions, which indicates a severe risk of alcohol consumption. Data obtained in our study suggest a strong association between traumas and alcohol use. The alarming number of males, motorcyclists, with low educational and socioeconomic levels, should be taken into account in order to improve public healthcare policies and trauma assistance practices in the ED.
Biphenyl structure and its impact on the macromolecular structure of lignin: A critical review

Abstract Biphenyl linkage is the second most abundant linkage in softwood lignin; the β-O-4′ linkage being the most abundant linkage. That about 20–28% of monolignols are linked by biphenyl linkage has been demonstrated by UV spectroscopy, permanganate oxidation, 13C NMR, and thioacidolysis followed by 31P NMR. Most, if not all, of the biphenyl structures in softwood lignin are etherified, indicating that biphenyl structures are formed while monolignols are being transported to the lignifying zone during lignin biosynthesis. Along with 4-O-5′ (∼3/100 C9 units), β-6′/α-6′ (∼3/100 C9) and noncyclic α-O-4′ structures (4/100 C9), biphenyl structures are the major branching points of lignin structure. Thus, at least one out of every three C9 units in softwood lignin are branching units. This fact indicates that softwood lignin is most likely a network polymer. Many alkyl-aryl ether bonds are cleaved during ball milling for the isolation of Milled Wood Lignin (MWL), but the number of branching points remains the same. Therefore, softwood milled wood lignin, with a number average DP of 20, exists most likely as at least a highly branched polymer and unlikely as a linear polymer. Harwood lignin has less biphenyl structures (∼9%), but has more 4-O-5′ (∼7%), noncyclic α-O-4′ (6%) and similar β-6′/α-6′ (∼2%) linkages as compared with softwood lignin. Thus, only one out of every four C9 units is a branching point, indicating that hardwood lignin is most likely a highly branched polymer. Hardwood MWL is most likely a branched polymer, but one cannot rule out the chance of finding a few linear oligomers in MWL. One potential branching point is not considered in the above discussion. The lignin-carbohydrate complexes are also branching points in lignin. The number of LCC linkages in native lignin cannot be determined precisely.
Integrating Reservoir Dynamics, Crustal Stress, and Geophysical Observations of the Laguna del Maule Magmatic System by FEM Models and Data Assimilation

The Laguna del Maule volcanic field is a large rhyolitic magmatic system in the Chilean Andes, which has exhibited frequent eruptions during the past 20 ka. Rapid surface uplift (>20 cm/year) has been observed since 2007 accompanied by localized earthquake swarms and microgravity changes, indicating the inflating magma reservoir may interact with a preexisting weak zone (i.e., Troncoso fault). In this investigation, we model the magma reservoir by data assimilation with Interferometric Synthetic Aperture Radar data. The reservoir geometry is comparable to the magma body inferred by seismic tomography, magnetotelluric, and gravity studies. The models also suggest that a weak zone, which has little effect on surface displacement, is important as a fluid transport channel to promote earthquakes and microgravity changes. In particular, concentrated dilatancy within the weak zone facilitates the microfracture formation during reservoir inflation. High‐pressure fluid can inject into the weak zone from the magma reservoir to trigger earthquakes and further migrate upward to create positive gravity changes by occupying unsaturated storages. The pore pressure will then decrease, halting the seismicity swarm until the next cycle. This “hydrofracturing” process may release some accumulated stress along the magma reservoir delaying an eventual eruption in turn. Besides, the resultant models are propagated forward in time to evaluate potential stress trajectories for future unrest.
Epidemiology of Brucellosis in Northern Saudi Arabia

A regional survey was carried out in 1989 to assess the prevalence of brucellosis in the northern region of Saudi Arabia. A sample size of 3152 was subjected to clinical and laboratory evaluation. The study revealed that the prevalence of brucellosis was 1.6%. The prevalence increases by age and is higher in rural areas and low socioeconomic classes. There are eight risk factors associated with having brucellosis. These are drinking raw milk, consumption of milk products, keeping livestock, milking the livestock, animal contact, cutting raw meat, handling parturient animals, and contact with placental membranes
Use of rhizosphere microorganisms for bioremediation of oil contaminated soils

Microbial soil remediation is one of the most promising methods for soil cleaning from oil and oil products. In order to search for promising oil destructors from the rhizosphere of plants growing in oil-polluted soils, bacteria that effectively destroy oil within a short time and belong to the genera Rhodococcus and Acinetobacter have been determined. Their ability to survive and decompose oil at its high and extremely high concentrations as well as at low positive temperatures has been shown. Microbial decomposition of oil model compounds (naphthalene, anthracene and phenanthrene) has been studied. All the studied strains have been established to be able to utilize these compounds with the formation of a group of metabolites, among which phthalic, gentisic and protocatechuic acids have been identified. The model compounds decrease ranged from 30 to 70% within 10 days.
Interprofessional Collaboration Across the Treatment Process in Music Therapy

The purpose of this study was to identify common protocols for music therapists who utilize interprofessional collaboration (IC) in the workplace. Participants were all BoardCertified Music Therapists (N = 595). The research sought to determine: 1.What is the profile of the music therapists that are currently utilizing IC in practice? ; 2.How is IC utilized across the treatment process in music therapy practice? ; and 3.What is the perception of IC among music therapists? Results revealed that the majority of participants are newer music therapists, who primarily collaborate with Occupational, Speech and Physical therapists and mainly utilize collaboration in the Treatment Planning and Treatment Implementation phases of the treatment process. Implications for practice, educational standards and standardized protocols are discussed.
A Molecular Assessment of the Taxonomy of Iranian Sylvia Warblers (Aves; Sylviidae)

The largest genus in the Sylviidae family is Sylvia, which is the archetype for warblers. It contains up to 28 species that are distributed in the Old World. Here, we study Iranian Sylvia using cytochrome c oxidase subunit 1 (cox1) and cytochrome b (cytb) mitochondrial markers to identify them and place them in a phylogenetic context using all available GenBank samples of sufficient length. Bayesian trees for both cytb and cox1 mitochondrial markers are compatible. Previous results suggesting that the Sylvia curruca complex is separated into two major clades with high support are corroborated, as our results show two main clades, one that includes Sylvia atricapilla and Sylvia borin plus Pseudoalcippe atriceps and Lioptilus nigricapillus, and the remainder of the Sylvia species in the other one. Our study did not support the geographical groups: The West-Mediterranean group, the Central-Mediterranean group, and the East-Mediterranean or the African-European species, the African-Asian species, and the Mediterranean species inferred on molecular evidenced by previous studies. Sylvia cantillans is divided into three clades, corroborating previous studies. All Iranian samples were conclusively identified to species level, and none of them give rise to any further taxonomic inquiry.
Entrusting decisions to the public service pension fund: An integrated predictive model with additive network DEA approach

Abstract A critical issue for ensuring long-term sustainability of pension funds is how the Public Service Pension Fund Management Board (PSPFMB) makes entrusting decisions to choose investment trust corporations (ITCs). To design a more comprehensive performance measure, this study uses the additive network data envelopment analysis (DEA) approach to measure efficiency scores of 34 ITCs, including operating performance, equity fund performance, and bond fund performance. We further propose a method to effectively forecast the future efficiency scores of each ITC by using a trend analysis technique. Our mechanism for ITC evaluation helps improve the deficiency of old decision-making processes that merely look at ITCs’ past performances. Our proposed approach offers a theoretical contribution to the additive DEA literature by through its practicality and by integrating measurement and prediction procedures. For a practical implication with additive network DEA, we provide a more feasible method for selecting ITCs that will run the Public Service Pension Fund.
Portfolio optimization for an P2P investor on Zonky

This thesis analyzes the Czech peer-to-peer lending platform Zonky. The goal was to find the optimal portfolio for a risk-averse investor investing in Zonky loans. For this purpose, the Modern portfolio theory from Markowitz was used. Based on the provided loan book containing information about loans which Zonky has provided since its foundation we examined the statistical properties of the individual risk categories represented by the interest rate charged. The optimization was done using the Excel Solver tool assuming that the loan categories are uncorrelated as well as considering the correlation we found using the variancecovariance matrix. For both cases, the portfolio minimizing the standard deviation as well as the portfolio which maximizes the Sharpe ratio was found. Generally, both types of portfolios were comprised mainly of loans with lower interest rate. According to our results, it seems that such loans offer better relationship between risk and return compared to categories which are riskier. Also, we showed that the platform’s recovery rate has a significant impact on the performance of the loan categories especially of those which are among the riskiest. Furthermore, we demonstrated that the correlation between individual risk categories should not be ignored when a portfolio analysis is done.
Updated Morphological Descriptions of the Larval Stage of Urophycis (Family: Phycidae) from the Northeast United States Continental Shelf

Including early life history data in assessments can improve fisheries management by increasing our knowledge of stock structure, spawning habitat, and population trends. The identification of fish larvae to species is a necessary step in using early life history data toward this goal. Three species of hakes from the genus Urophycis are common on the northeast United States continental shelf: U. chuss or Red Hake, U. regia or Spotted Hake, and U. tenuis or White Hake. Unfortunately, identification of larval Urophycis has long been only possible at the genus level. Larvae of Urophycis (n = 277) collected in a subset of ethanol-preserved samples were identified genetically through sequencing of the cytochrome oxidase I gene and were used to update morphological descriptions with characters that separate these three species at the larval stage. Sequencing occurred in two stages: the first (n = 88) to develop a set of known-identity larvae to define species-specific traits, the second (n = 189) to test morphological identification based on the traits described in this study. We describe a combination of the location of dorsal and ventral pigment, head pigment, lower jaw pigment, and the timing of development of the pectoral fins to distinguish the larvae of these three species at sizes <6 mm. Using molecular techniques to improve morphological identifications is a powerful and efficient way to obtain the species-level data needed for assessments and management.
A clinico-epidemiological study of hypopigmented and depigmented lesions in children and adolescent age group in Hadoti region (South East Rajasthan)

Background: Hypopigmentory and depigmented lesions are common among children and adolescent group. The parents are very much concerned about the condition and they seek dermatologist advice without fail. Aims and Objectives: To evaluate the Epidemiology and clinical characteristics of Hypopigmented and Depigmented Lesion in patients of Children and Adolescent age group in Hadoti region in Rajasthan. Materials and Methods: The study was conducted for the period one year from April 2015 to March 2016. This planned study is to be undertaken in children age 0-19 yr with hypopigmented and depigmented lesions irrespective of sex. Results: The most common disorder was Pityriasis alba, seen in 27.33%, followed by Pityriasis versicolor in 21%, Vitiligo 19.33%, Post inflammatory hypopigmentation in 14%, Primary disorders of hypopigmentation in 13%, Hansen's disease in 1.33%, and miscellaneous conditions in 4% of the cases. Conclusion: The most common hypopigmentary disorders are seen in our study is Pityriasis alba and other causes of hypopigmentary and depigmentory disorders are in decreasing order are Pityriasis versicolor, Vitiligo, Postinflammatory hypopigmentation, Primary causes of hypopigmentation and less common are Leprosy.
Discovering the Importance of Mesoscale Cloud Organization Through Unsupervised Classification

The representation of shallow trade wind convective clouds in climate models dominates the uncertainty in climate sensitivity estimates. In particular the radiative impact of cloud spatial organization is poorly understood. This work presents the first unsupervised neural network model which autonomously discovers cloud organization regimes in satellite images. Trained on 10,000 GOES‐16 satellite images (tropical Atlantic and boreal winter) the regimes found are shown to exist in a hierarchy of organizational scales, with sub‐clusters having distinct radiative properties. The model requires no time‐consuming and subjective hand‐labeled data based on predefined structures allowing for objective study of very large data sets. The model enables the study of environmental conditions in different organizational regimes and in transitions between regimes and objective comparisons of model behavior with observations through cloud structures emerging in both. These abilities enable the discovery of previously unknown physical relationships in cloud processes, enabling better representation of clouds in weather and climate simulations.
Mutual Fund Bets on Market Power

Processing qualitative information about a firm's product market competition matters for professional investors. Consistent with a superior understanding of a firm's market power, fund managers who overweight companies with the fewest competitors (monopolies) outperform their peers. An exogenous shock to a firm's competitive position around the 9/11 terrorist attacks supports this finding. Managers who place larger bets on monopolies pursue more long-term investment strategies, select superior innovators, and more actively avoid competition within their portfolio. These findings suggest that skilled managers exploit hardto-process information about a firm's competitive environment when picking stocks.
Cost-sensitive ranking: Evolving data analytics in power systems and risk management

This thesis develops Cost-Sensitive Ranking, Supervised Learning to directly minimize costs and risks from real industrial resource deployment policies, supported by two case studies with the power utility BC Hydro: Cost-Sensitive Learning to Rank and Risk Clearance. Our first solution is motivated to guide resource deployment within the top-k highest predicted impact events in sets of possible threats/items. For example, British Columbia storms can result in hundred thousands of customers losing power with global yearly storm outage losses exceeding billions of dollars. To prevent the most costly power outages before a storm, BC Hydro could apply data analytics models to recommend the top-k highest damage areas so they can act in these areas given their limited response resources. Though Regression could return the top-k highest predicted outage damage areas, Regression’s emphasis on numeric prediction accuracy even on “low damage events” can compromise the ranking and thus the resulting preventative actions. Similarly, existing ranking solutions in Learning to Rank focus on web page search domains with vastly different priorities than deploying preventative resources as shown in our extensive studies. We thus define Cost-Sensitive Learning to Rank, a ranking problem of directly maximizing a company’s cost-saving resulting from a ranking model; our suite of Cost-Sensitive Adaptions adapt most existing ranking models to this new problem, achieving up to 20% more cost-saving than competitors for identifying forest fires, crimes, quality assurance, and outages. While outage prevention was limited by available resources, our second problem is limited by ensuring regulatory standards while minimizing expensive costs. For example, BC Hydro’s asset management for toxic electrical transformers must balance the cost of identification, breaking $100,000s of equipment to test for contaminated oil, with the risk of leaving a hazard unidentified, an unlikely toxic transformer leak’s health and environmental damage. Because of the extreme difficulty in estimating health/environmental risks as a dollar value, company decision-making is instead guided by the “clearance threshold”, a maximum acceptable probability of toxicity in unknown outcome transformers. Such “under threshold” transformers are within safety guidelines and are cleared from expensive tests. Other domains, such as regulations on maximum tolerable risk of device failures, rely on similar clearance thresholds to guide recalls or other actions. We therefore develop data analytics via clearance thresholds: Categorical Risk Clearance, to clear many future low-risk items
Evaluation of the association between lifestyle risk factors for myopia development and the prevalence of nearsightedness among young adults

: Aim: The aim of the study was to evaluate the association between lifestyle risk factors for myopia development and the prevalence of nearsightedness among young adults. Materials and Methods: The analysis included 1608 students of Cracow universities. An original questionnaire was distributed to the participants through the Internet or as a paper version. Respondents answered questions about their refractive defects, average time spent per day on: reading, using electronic devices, doing- sports and staying outdoors in daylight. We also asked them about taking care of good lighting conditions, and taking breaks during visual work at close range. Results: Our study shows the prevalence rate of vision defects, with myopia as the dominating one among Cracow’s students (63%). Our study showed an association between higher myopia prevalence and longer time spent on near work. More time spent outdoors in daylight, physical activity, and taking breaks during close work were associated with a lower frequency of nearsightedness. Conclusion: There is a connection between some lifestyle behaviors and a higher prevalence of myopia. The development and progression of nearsightedness is a common occurrence among young adults.