Miracle-dz/UniFAR-FTUs huggingface dataset:
The Hypothesis of Unexplained Brain Damage and Learning Difficulties

Introduction: The term learning disabilities refers to a complex and multidimensional phenomenon that affects many thousands of students. Due to the rich symptomatology of learning difficulties and the increased differences between individuals, it has not been possible to analyze all cases exclusively from the perspective of the neuropsychological approach. Aim. The aim of this study was to present research conducted in the context of theories on the brain function of people with learning disabilities. Supporting the hypothesis of brain dysfunction. Methodology: Literature review was carried out in the web, which referred to researches on Special Learning Disabilities and the brain function associated with them. Results: Review of the literature highlighted key points of the relationship between learning difficulties and brain function. Brain dysfunction and the cognitive functions produced emerged as one of the key factors involved in learning disabilities. Many of the theories developed around the problems of children with learning disabilities have focused on specific areas of the brain that may be dysfunctional. Conclusions: The difficulty of locating obvious brain damage in individuals who have been characterized as dyslexic leads to the strengthening of the hypothesis of the existence of a slight or minimal brain damage that cannot be easily diagnosed and strengthens the hypothesis of an unexplained brain damage that could be heterogeneous groups of learning disabilities.
Video Streaming Solutions for Web-Based E-Learning Courses

The background of this work is the development of multimedia courses for an Internet-based master program in Business Informatics. This program is provided by a virtual organization. Delivering multimedia-based courses over the Internet is a challenging task. Low-cost multimedia technologies, in particular technologies for video production and delivery over the Internet, have just become available. Established rules and recommendations how to use those technologies effectively are still missing. In this paper an approach is discussed in which course material is divided into separate parts - one silent video file containing visual demonstrations, and another video with sound, with the instructor’s explanations. We discuss approaches to achieve synchronization among two separate videos streams. Based on Microsoft Windows Media technology this problem can be solved but the solution is not straight-forward. Problems encountered and the final solution to those problems are outlined.
SMOKE FROM WILDLAND FIRES

Biomass burning is a major contributor of toxic air pollutants, particulate matter (PM), and greenhouse gases, but unlike some anthropogenic sources, poorly quantified. On a global basis, the net effect on human health and impact on climate change has not been adequately determined. The temporal and spatial distribution of these emissions is very difficult to estimate and the interannual variability of smoke production can range by an order of magnitude or more. With the advent of sensors operating over a temporal scale of hours, progress in estimating smoke emissions should be advanced. Still, the exposure of people to smoke emissions on a regional scale will continue to be very difficult to quantify.
PREVALENCE OF SKIN TEARS IN INSTITUTIONALIZED OLDER ADULTS

Objective: To analyze the prevalence of skin tears and associated risk factors in institutionalized older adults. Method: cross-sectional and analytical study, conducted with 54 older adults from a long-term care institution in Teresina, Piauí, through interviews, physical examinations and medical records. Data were collected between August and September 2017. Descriptive and inferential analysis was performed, with student’s t-test applied to observe the difference of the means and the Odds Ratios in the association between the outcome and the independent variables. Results: mean age was 77.4 years, 63.0% men, 77.8% illiterate, 88.9% with comorbidities and 55.6% dependent for activities of daily living. The prevalence of lesions was 20.4%, mostly located in the lower limbs and of category 3, not statistically associated with any risk factor. Conclusion: there was a high prevalence of skin tears. It should be highlighted that these data help in the knowledge of the epidemiology of these injuries and in the planning of preventive measures. DESCRIPTORS: Older adult; Wounds and Injuries; Friction; Institutionalization; Prevalence. HOW TO REFERENCE THIS ARTICLE: Vieira CP de B, Araújo TME de, Silva Júnior FJG da, Rodrigues ASO, Galiza FT de. Prevalência de lesões por fricção em idosos institucionalizados. Cogitare enferm. [Internet]. 2019 [access “insert day, monh and year”]; 24. Available at: http://dx.doi. org/10.5380/ce.v24i0. 65078. 1Registered Nurse PhD in Nursing. Professor of Nursing of the Federal University of Piauí. Teresina, PI, Brazil. 2Registered Nurse. PhD in Collective Health Nursing. Professor of Nursing of the Federal University of Piauí. Teresina, PI, Brazil. 3Registered Nurse PhD in Nursing. Professor of Nursing of the Federal University of Piauí. Teresina, PI, Brazil. 4Registered Nurse. Master student in Technology and Innovation in Nursing. University of Fortaleza. Fortaleza, CE, Brazil. 5Registered Nurse. PhD in Clinical Health Care. Professor of Nursing of the Federal University of Piauí. Teresina, PI, Brazil. This work is licensed under a Creative Commons Attribution 4.0 International License. Chrystiany Plácido de Brito Vieira1, Telma Maria Evangelista de Araújo2, Fernando José Guedes da Silva Júnior3, Átila Sâmia Oliveira Rodrigues4, Francisca Tereza de Galiza5 dx.doi. org/10.5380/ce.v24i0. 65078 Cogitare enferm. 24: e65078, 2019
Impact of Foreign Direct Investment on Economic Growth of Nepal

This paper aims to investigate the impact of Foreign Direct Investment (FDI) on the economic growth of Nepal for the period 2008/09 to 2017/18 A.D. yearly data. It evaluated the Gross Domestic Product (GDP) performance and the trends of FDI and Gross Fix Capital Formation (GFCF) in Nepal. To demonstrate the relationship between Nepalese Gross Domestic Product (GDP) and Foreign Direct Investment (FDI) and Gross Fix Capital Formation (GFCF) Multiple-Regression-Model has been applied along with various econometrics techniques such as Unit-Root Test, Granger-Causality Test and Ordinary Least Square (OLS). GDP in this model is used as dependent variable whereas FDI and GFCF are measured as independent variables. According to the results, Unit Root Test indicated that all the variables included in the model were not stationary at level except FDI, whereas GDP and GFCF are stationary at first difference. The model is overall significant with the positive and significant relationship of GDP, FDI and GFCF. Result also indicate a good fit for the model with R2=86%. The Granger Causality Test revealed that there was no causality between the variables since all p-value obtained are more than 5%. Based on the empirical result of this paper, policy recommendation proposed that for Nepal to generate more foreign direct investment, hard work should be made at solving problems of government involvement in business; relative closed economy; corruption; weak public institutions; and poor external image, and political instability.
Designing AI Nudging for Social Good: New Healthcare Skills for Digital Personal Assistants

Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into making decisions and changing behaviours. This article discusses how these AI-driven systems pose particular ethical challenges with regards to nudging. To confront these issues, the value sensitive design (VSD) approach is adopted as a principled methodology that designers can adopt to design these systems to avoid harming and contribute to the social good. The AI for Social Good (AI4SG) factors are adopted as the norms constraining maleficence. In contrast, higher-order values specific to AI, such as those from the EU High-Level Expert Group on AI and the United Nations Sustainable Development Goals, are adopted as the values to be promoted as much as possible in design. The use case of Amazon Alexa's Healthcare Skills is used to illustrate this design approach. It provides an exemplar of how designers and engineers can begin to orientate their design programs of these technologies towards the social good.
A process model of management accounting change based on the contributions of institutional theory

Objective: This study aims to identify and discuss the core elements of the process of manage-ment accounting change in an organisation to serve as a theoretical framework and to explain the process of management accounting change as an outcome of the inter-relationship between exog-enous and endogenous factors. Method: This paper is based on a conceptual literature review of the institutional theory studies on management accounting change. Results: Institutional theory has been widely used to study management accounting change. The institutional literature on management accounting change is fragmented and disjointed though, providing an unstructured picture of the dynamics and outcomes of the process of management accounting change. This situation makes the task of explaining the complexity of management accounting change extremely difficult. In this paper, it is argued that the complexity of manage-ment accounting change comprises four key elements: (1) the internal and external pressures for change and the interplay between them; (2) the role of agency; (3) the idiosyncratic internal ele-ments; and (4) the process of institutionalisation. Contributions: Drawing on institutional theory and these four elements of management account-ing change, an integrated framework is developed to capture and examine the macro and micro level dynamics in management accounting change.
Preliminary study to determine phenotypic differences and sample size in Cacahuacintle corn

This study was carried out in spring-summer of 2016 in six communities of the municipality of Calimaya de Díaz González, State of Mexico to sample land of cooperating farmers and estimate phenotypic differences in plant and corn dimensions in the Cacahuacintle breed. In 30 plots, of one hectare each, distributed in the Municipal District, San Lorenzo Cuauhtenco, Santa María Nativitas, San Marcos de la Cruz, San Diego La Huerta and Zaragoza de Guadalupe, 50 plants and corn per producer were considered at random (almost 21 000 data). Simple statistics and values of n were calculated with two methodologies. With a principal component analysis, the relationship between producers, communities and variables was analyzed. The most outstanding results showed that there are important phenotypic differences in all characteristics. The values of n would allow sampling plots where Cacahuacintle is planted in that municipality, with method 1, only the population size should be known and a value assigned to the sampling error should be chosen. With the application of method 2 or other complementary techniques, fewer plants could be sampled than with method 1 but the arithmetic mean, standard deviation, standard error, coefficient of variation or proportions between two of these should be known. In the four quadrants of the biplot, at least three of the five cooperating farmers in each locality were grouped. There was a positive and significant correlation between the number of quality leaves for wrapping tamales (NHT) with the number of grains and rows of grain in the corn, this trend was also observed between the first and the length and diameter of the spine. Thus, NHT could be used as an indirect selection criterion to increase the size of the corn.
C OMPETITION BETWEEN ARM ’ S LENGTH AND RELATIONAL LENDERS : W HO WINS THE CONTEST ?

Using geo-coded data with precise location of bank branches and commercial borrowers we are able to study the effect of local bank competition on lending. We find that the impact of competition varies a great deal depending on the incumbent’s and the entrant’s lending technologies. The opening of a branch by a relational lender reduces the size of loans issued by both relational and arm’s length incumbents, while the opening of a branch by an arm’s length lender only reduces the size of loans granted by arm’s length incumbents. We believe relational lenders can use their soft information to retain their best borrowers. Knowing that, arm’s length lenders prefer to look elsewhere rather than getting a bite of the relational lender’s worse borrowers only. JEL Classification: D82, E50, G21, R51
OrderLight: Lightweight Memory-Ordering Primitive for Efficient Fine-Grained PIM Computations

Modern workloads such as neural networks, genomic analysis, and data analytics exhibit significant data-intensive phases (low compute to byte ratio) and, as such, stand to gain considerably by using processing-in-memory (PIM) solutions along with more traditional accelerators. While PIM has been researched extensively, the granularity of computation offload to PIM and the granularity of memory access arbitration between host and PIM, as well as their implications, have received relatively little attention. In this work, we first introduce a taxonomy to study the design space whilst considering these two aspects. Based on this taxonomy, we observe that much of PIM research to date has largely relied on coarse-grained approaches which, we argue, have steep costs (incompatibility with mainstream memory interfaces, prohibition of concurrent host accesses, and more). To this end, we believe that better support for fine-grained approaches is warranted in accelerators coupled with PIM-enabled memories. A key challenge in the adoption of fine-grained PIM approaches is enforcing memory ordering. We discuss how existing memory ordering primitives (fences) are not only insufficient but their large overheads render them impractical to support fine-grain computation offloads and arbitration. To address this challenge, we make the key observation that the core-centric nature of memory ordering is unnecessary for PIM computations. We propose a novel lightweight memory ordering primitive for PIM use cases, OrderLight, which moves away from core-centric ordering enforcement and considerably reduces the overheads of enforcing correctness. For a suite of key computations from machine learning, data analytics, and genomics, we demonstrate that OrderLight delivers 5.5 × to 8.5 × speedup over traditional fences.
Watering Frequency and Total Water Input Influence Wheat Growth, Soil Microbial Biomass and Nutrient Availability in a Silt Loam

ABSTRACT Two experiments with different watering regimes were conducted. In the first experiment, wheat was grown for four days at 50% of maximum water holding capacity (WHC), then 4-day cycles with three watering regimes were implemented, percentages refer to water lost over 4 days: in TW1 pots were watered on day 1 of each cycle adding 100%, TW2 pots were watered on day 1 and day 3 each time adding 50%, TW4, pots were watered daily, each time 25%. In the second experiment, the soil was rewetted to 50% WHC when soil water content reached 40, 30, 20 and 10% WHC. In the first experiment, shoot and root biomass were higher in 4TW than 1TW and 2TW, whereas microbial biomass carbon (MBC) in 2TW was higher than in 1TW and 4TW. In Experiment 2, shoot and root biomass and MBC decreased with soil water content at which the pots were watered. Watering treatments had a stronger effect on plant biomass than MBC.
Running head: PREDICTING SELF-HARM My Own Worst Enemy: Exploring Factors That Predict Self-Harm

Background/Objective: The aim of the current study was to examine factors that may be related yet independently predict self-harming behaviors. Method: Factors discussed include depression, rumination, self-criticism, and working memory. Results: The findings indicated that while there was a greater incidence of self-harming behaviors among those who demonstrated higher depressive symptoms, depression scores did not directly predict self-harm. A binary logistic regression found that the only factor that predicted the presence of self-harming behavior was a high level of self-criticism. Further, a Classification and Regression Tree found that the single strongest predictor of self-harming behavior was a belief that love needs to be continually earned from others. Conclusions: The findings have implications for improving the efficacy of interventions aimed at preventing self-harm. Treatments incorporating ways to reduce self-criticism, such as a focus on improving self-compassion with Compassionate Mind Training, may address underlying mechanisms that can trigger selfharm behavior.
An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.
Antibiotic Therapy for Children with Diarrhea in a Low-Resource Setting: A Syndromic Approach

Objective: To compare age and protein-energy malnutrition (PEM) – the predispositions – and fever and abnormal leukocyte count (ALC) – the SIRS criteria – in hospitalized children with and without diarrhea. Design: prospective case-control study. prospective case-control study; hemodynamically subjects and ALC in 59 patients with diarrhea and compared with 375 control patients without diarrhea. Odds ratios with con ﬁ dence intervals were determined; the chi-square test and binary logistic regression analysis were also performed. Main Outcome Measures: Associations of diarrhea with age, PEM, fever and ALC singly and various combinations of predispositions and SIRS parameters. Results: Infancy and ALC were signi ﬁ cantly associated with diarrhea. PEM or fever alone was not signi ﬁ cantly associated with diarrhea; however, the probability of developing diarrhea was signi ﬁ cantly higher when a combination of ALC and PEM was observed. The combination of infancy, PEM, and ALC carried a sensitivity of 81·36%; for other combinations, sensitivity varied between 70% and 80%. The combination of infancy and ALC had the lowest sensitivity (59·32%) but the best speci ﬁ city (61·07%). Conclusion: The association/presence of a combination of SIRS parameters (fever and ALC) and predispositions (infancy and PEM) in children with diarrhea may help in deciding whether antibiotic therapy should be initiated.
Productivity of two Mexican potato genotypes in perlite and aggregates in hydroponics and greenhouse

In order to determine the productive response of two Mexican potato genotypes in two substrates in the hydroponic cultivation system, three experiments were established with horticultural grade perlite and with the mixture of perlite with peat 1:1 v/v (aggregates), by what experiments were established in the autumn 2015, spring 2016 and summer 2016 cycles. With perlite, the Citlali variety and clone 99-39, produced on average 15.92 and 34.25 tubers per plant, respectively; in aggregates they produced 11.92 and 15.42 tubers per plant, respectively. Genotype 99-39 exceeded Citlali by up to 10.9 tubers per plant on average of the three crop cycles and produced 2.2 times more tubers in autumn than in spring, as well as 2.9 more tubers in autumn than in summer. Citlali produced 3.6 times more tubers in autumn than in summer and five times more in autumn than in spring. The most efficient substrate was horticultural grade perlite, clone 99-39 was more productive than the Citlali variety, the production of tubers in both genotypes was closely affected by the season of the year and the results will allow decisions on the management of the production of prebasic seed II in both genotypes.
First report of tetracycline-resistant Aeromonas veronii infection in Amur catfish (Silurus asotus) cultured in Korea

Mass mortality in commercially cultured Amur catfish (Silurus asotus), showing symptoms of dermal ulcerations, occurred on a private farm in Mar 2019 in Korea. β-hemolytic bacteria were isolated from the ulcers and kidneys of the fish and identified as Aeromonas veronii. The isolate was resistant to tetracycline and possessed cytotoxic heat-labile enterotoxin (aerolysin/ hemolysin). We investigated the genetic determinants associated with tetracycline resistance, and the isolate has been confirmed to simultaneously possess tetA and tetE genes. This is the first report on the occurrence of tetracycline-resistant A. veronii infection related to mass mortality in commercially cultured Amur catfish in Korea.
Examination of knowledge barriers in packaging industry using Interpretive Structural Modeling (ISM)

The efficient running of any packaging plant makes the organization successful. To achieve the efficiency of the packaging plant we must control and overcome the barriers which make the plant ineffective according to the optimum efficiency. Packaging plays an important role in all of the history of the modern manufacturing whether it is past or in the future. Today industries seek to improve their packaging capability in all the possible ways in order to improve their position in the sector. This paper focuses on packaging industry on the selection and analysis of the barriers which are responsible for inefficiency of the packaging plant. Organizations find difficulties in identifying the barriers which are responsible for the efficiency of the production. So, this requires in depth analysis in selecting the barriers, analyzing the barriers and ranked them according to the power they possess in the packaging industry. We have identified eight barriers which are responsible for the inefficiency of the packaging plant and ranked them according to the power they possess on the packaging industry. We have applied Interpretive Structural Modeling (ISM) on eight barriers for the analysis. This study focuses on relating each barrier depending on the dependence power and driving power they possess on other barriers. This result helps the organization in overcoming the barriers and increase the effectiveness and efficiency of the packaging plant.