Miracle-dz/UniFAR-FTUs huggingface dataset:
Abrupt shifts in African savanna tree cover along a climatic gradient

Aim To describe patterns of tree cover in savannas over a climatic gradient and a range of spatial scales and test if there are identifiable climate-related mean structures, if tree cover always increases with water availability and if there is a continuous trend or a stepwise trend in tree cover. Location Central Tropical Africa. Methods We compared a new analysis of satellite tree cover data with botanical, phytogeographical and environmental data. Results Along the climatic transect, six vegetation structures were distinguished according to their average tree cover, which can co-occur as mosaics. The resulting abrupt shifts in tree cover were not correlated to any shifts in either environmental variables or in tree species distributions. Mainconclusions Astrongcontrastappearsbetweenfine-scalevariabilityintree cover and coarse-scale structural states that are stable over several degrees of latitude. While climate parameters and species pools display a continuous evolution along the climatic gradient, these stable structural states have discontinuous transitions, resulting in regions containing mosaics of alternative stable states. Soils appear to have little effect inside the climatic stable state domains but a strong action on the location of the transitions. This indicates that savannas are patch dynamics systems, prone to feedbacks stabilizing their coarse-scale structure over wide ranges of environmental conditions.
Bioprocess Engineering Issues That Would Be Faced in Producing a DNA Vaccine at up to 100 m3 Fermentation Scale for an Influenza Pandemic

The risk of a pandemic with a virulent form of influenza is acknowledged by the World Health Organization (WHO) and other agencies. Current vaccine production facilities would be unable to meet the global requirement for vaccine. As a possible supplement a DNA vaccine may be appropriate, and bioprocess engineering factors bearing on the use of existing biopharmaceutical and antibiotics plants to produce it are described. This approach addresses the uncertainty of timing of a pandemic that precludes purpose‐built facilities. The strengths and weaknesses of alternative downstream processing routes are analyzed, and several gaps in public domain information are addressed. The conclusion is that such processing would be challenging but feasible.
A brief introduction to probabilistic machine learning with neuroscientific relations

My aim of this article is to summarize in a concise way what I consider the most important ideas of modern machine learning. I start with some general comments of organizational mechanisms, and will then focus on unsupervised, supervised and reinforcement learning. Another aim of this introductory review is the focus on relating different approaches in machine learning such as SVM and Bayesian networks, or reinforcement learning and temporal supervised learning. Some examples of relations to brain processing are included such as synaptic plasticity and models of the Basal Ganglia. I also provide Matlab examples for each of the three main learning paradigms with programs available at www.cs.dal.ca/∼tt/repository/MLintro2012. 1 Evolution, Development and Learning Development and learning are both important ingredients for the success of natural organisms, and applying those concepts to artificial systems might hold the key to new breakthroughs in science and technology. This article is an introduction to machine learning with examples of its relation to neuroscientific findings. There has been much progress in this area, specifically by realizing the importance of representing uncertainties and the corresponding usefulness of a probabilistic framework. 1.1 Organizational mechanisms Before focusing on the main learning paradigms that are dominating much of our recent thinking in machine learning, I would like to start by outlining briefly some Thomas Trappenberg Dalhousie University, Halifax Canada, e-mail: tt@cs.dal.ca
Online forum post opinion classification based on tree conditional random fields model

There is a major defect when using the traditional topic-opinion model for post opinion classifications in an online forum discussion. The accuracy of the classification based on the topic-opinion model highly depends on the observable topic-opinion features aiming at the subject, while a large number of posts do not have such features in a forum. Therefore, for the most part, the accuracy is less than 78%. To solve this problem, we propose a new method to identify post opinions based on the Tree Conditional Random Fields (T-CRFs) model. First, we select the topic-opinion features of the posts and associated opinion features between posts to construct the T-CRFs model, and then we use the T-CRFs model to label the opinions of the tree-structured posts under the same topic iteratively to reach a maximum joint probability. To reduce the training cost, we design a simplified tree diagram module and some feature templates. Experimental results suggest the proposed method costs less training time and improves the accuracy by 11%.
A Fully Stabilized Combined Field Formulation for Coupled Fluid-Structure Interactions

We present a fully coupled three dimensional formulation based on arbitrary Lagrangian-Eulerian (ALE) approach with exact interface tracking for nonlinear fluid-structure interactions. This formulation is second order accurate in time and stable for very low mass ratios of O(10). The proposed formulation is an extension of the combined field with explicit interface (CFEI) presented in [1, 2] for two-dimensional framework. The CFEI is a monolithic nonlinear coupled fluid-structure formulation with explicit/implicit time integration. In the CFEI formulation the fluid-structure interface is explicitly determined at the start of each time step. This enables decoupling of ALE mesh from the remaining variables (structural velocity, fluid velocity and pressure) and consequently requires an explicit treatment of convective velocity. Hence, the CFEI formulation needs to solve the system of linear equations only once per time step. Additionally, the combined field formulation [2] absorbs the traction and velocity continuity equations into its weak form resulting in lesser number of linear equations per time step.
Experimental Research on Treatment of Injured Facial Nerves Induced by Hepatocyte Growth Factor Mediated by Ultrasound-Targeted Microbubble Destruction

AbstractThe purpose of our study was to explore the regeneration effect of the ultrasound (US)–targeted microbubble destruction–mediated eukaryotic coexpression vector (pIRES2–enhanced green fluorescent protein [EGFP]/hepatocyte growth factor [HGF]) with EGFP and HGF gene system on facial nerve injury in rats. Forty rats were randomly divided into 4 groups after the models of facial nerve injury were established: A, phosphate-buffered saline (PBS) group; B, HGF and microbubble (HGF + MB) group; C, HGF and US (HGF + US) group; and D, HGF + US + microbubble (HGF + MB/US) group. Gene and protein levels of HGF were detected by quantitative real-time reverse transcriptase–polymerase chain reaction and Western blot, respectively. The expression of pEGFP in facial nerve trunks was examined by laser scanning confocal microscope; HGF gene and protein expression were significantly higher in D group compared with those of the other groups (P < 0.05). The expression of pEGFP was the strongest in D group (P < 0.05). These data indicate that US-targeted microbubble destruction effectively transfects the HGF gene into target tissues and has a significant effect on an injured facial nerve, thus providing a new strategy for gene therapy in facial nerve injury.
Potential of Genomic Breeding Program in Iranian Native Chickens

Development of genomic selection can be a new strategy in breeding of native chicken. The main aim of this study was to evaluate application of a genomic selection program in Iranian native chickens from economic and genetic points of view. In this study, two scenarios including conventional scenario with 3360 and 3380 animals and genomic scenario were compared using ZPLAN+ software. The traits in the selection index were egg number, body weight, mean weight of egg and age at sexual maturity. In genomic scenario different reference population size were considered. In this scenario the genomic information from cocks (800 cocks were genotyped) was added to available information in conventional scenario based on selection index method. The generation interval was 14.5 months for all conventional and genomic scenarios. In comparison of scenarios, genetic gain and the economic profit increased by increasing reference population size in genomic scenario (€126.88-€147.45 with 80 cocks) and (€140.20 to €160.77 with 60 cocks) per animal unit. The reliability of selection index was 0.33 for cocks in conventional scenario. The reliabilities of genomic scenarios were 0.61-0.84 for 80 selected cocks and 0.66-0.87 for 60 selected cocks and that were high in comparison to conventional scenario. This study showed that genomic selection can increase the genetic improvement rate of native chickens. However, the costs of genomic scenarios were higher than conventional scenario, but genomic information increased accuracy of selection and genetic gain in breeding goals traits.
Biomarkers as predictors of outcome after cardiac arrest

Cardiac arrest (CA) is a major health and economic problem. Management of patients resuscitated from CA is challenging for clinicians, and the mortality rate of those who achieve return of spontaneous circulation remains high. Hypoxic brain injury, cardiovascular abnormalities and systemic ischemia/reperfusion response characterize the so-called ‘postcardiac arrest syndrome’, which could lead to multiple organ failure and poor outcome after CA. The magnitude of these disorders differs in individual patients, mainly based on the cause and duration of CA and on the severity of the ischemic episode. Prognostication of outcome after CA is of importance because it could help physicians on triage decisions and readdress the overall management. A number of factors are thought to influence the prognosis of patients after CA, but due to the heterogeneity of CA population and scenarios no single factor has been identified as a reliable predictor of outcome and the timing and optimal approach to prognostication is still controversial. Biomarkers represent a growing area of interest in this field, as they may provide clinicians with early information on the severity of organ dysfunction to make a decision on clinical strategies and prognosticate outcome. In this article, the authors will focus on cardiac, neurological and inflammatory biomarkers as potential predictors of outcome after CA.
Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders

Online Mendelian Inheritance in Man (OMIM) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support research and education in human genomics and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (www.ncbi.nlm.nih.gov/omim) is now distributed electronically by the National Center for Biotechnology Information (NCBI), where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, approved gene nomenclature, and the highly detailed mapviewer, as well as patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.
A new wide-band beam current monitor with active-passive circuit

In this article, a new wide-band beam current monitor is presented which uses an active-passive circuit to improve the low frequency response of the system without impairing the high frequency response. Theoretical analysis and experimental results show that through appropriately choosing the operational amplifier parameters the active-passive current transformer can be used for the measurement of both macro-pulses and mini-pulses. The operational amplifier AD847 is used in the active-passive current transformer. Some measurement results are given.
The Impact of the Service Innovativeness on Perceived Overall Service Quality, Customer Loyalty and Perceived Customer Value in Shopping Sites

Associated with the change of life style, due to reasons such as time constraints, information access, and alternatives comparison easiness, consumers prefer directed shopping on the internet. Shopping is done along with the initiation by the internet, in the scope of study such as web site service innovativeness, perceived overall service quality, customer loyalty, and perceived customer value. What are the effects of service innovativeness on perceived overall service quality, customer loyalty and perceived customer value? In order to answer this question, theoretical and empirical research is structured. From a holistic point of view the results suggest the positive effect of service innovativeness on perceived overall service quality, customer loyalty, and perceived customer value. Website service innovativeness influences behavioural intentions such as perceived overall service quality, customer loyalty, and perceived customer value. Following the examination of the results, the present article discussed the implications for practice and future research.
Autism Spectrum Disorders in Children With a History of Infantile Spasms: A Population-Based Study

The objective of this article is to describe autistic spectrum disorders in children diagnosed with infantile spasms in the first year of life. The source of data was the records of all 3 pediatric departments in Iceland. Twenty children born between 1981 and 1998 who had infantile spasms were invited to participate. When appropriate, the parents of these children were asked to complete the Social Communication Questionnaire. Children scoring 10 points or higher on the questionnaire were selected for further examination using the Autism Diagnostic Interview− Revised and either the Autism Diagnostic Observation Schedule or the Childhood Autism Rating Scale. All participants were given appropriate cognitive tests or measures of adaptive behavior. The parents of 17 children (10 boys, 7 girls) agreed to participate in the study. Age at assessment ranged from 5 to 19 years with a mean age of 11 years and 6 months. Fourteen children had at least one neurodevelopmental disorder. Six (6/17), or 35.3%, were diagnosed with autism spectrum disorder (3 boys, 3 girls), five of these had a history of symptomatic infantile spasms, and four were profoundly mentally retarded (IQ/DQ<20). If the diagnosis of autism spectrum disorder was restricted to children with a developmental age of 24 months or more (3 cases), the prevalence was 17.6%. The estimates found in this study exceed the estimated prevalence of autism spectrum disorder in the general population.
Factors influencing the investors’ intention to adopt Takaful (Islamic insurance) products

Purpose The research paper is an effort to find out the behavior of Pakistani individuals toward usage of Takaful insurance. This paper aims to identify the factors, which influence investors’ intention toward the adoption of Takaful. Islamic finance is growing rapidly in the international market, especially in Islamic countries. Pakistan is an Islamic country, where the majority of the population is Muslim. Therefore, there is a great potential for Takaful exists in the country. Design/methodology/approach Both explanatory and descriptive research designs used for the research framework. The theory of planned behavior is the base theory and the model incorporates several factors such as relative advantage, compatibility, social influence, awareness and religiosity that may influence the adoption of Takaful. The primary data collected through the distribution of self-administered survey-based questionnaire, containing 23 items scaled at a five-point Likert scale. The non-probability snowball sampling and judgmental sampling techniques are used due to the scarce of Takaful users. The sample consists of 345 individuals (127 Takaful users and 218 non-users) living in the three main cities, namely, Karachi, Lahore and Islamabad. The data are further analyzed and interpreted with IBM SPSS 21. The results are evaluated using descriptive statistics, reliability, confirmatory factor analysis, correlation and binary logistic regression models. Findings The research findings reveal that factors such as relative advantage, compatibility, social influence, awareness and religiosity have a significant impact on the behavioral intention of Takaful amongst a depicted sample of Pakistani people. Similarly, Takaful has great potential in the Pakistani market, but due to lack of awareness, Takaful share is far behind than conventional insurance. It is further suggested that Takaful operators must devise some policies and plan to spread awareness about Takaful and come up with more innovative products. Practical implications The Takaful operators must devise plans to aware people about Islamic insurance. The study provides implication to Takaful management; Takaful users; and more importantly, the regularity authorities to operate and successfully conduct Takaful applications. Further, they should advance Takaful operations and produce more innovative products. The study focuses on some factors while there are plenty of others, which should be studied accordingly. For future researchers and students, there is a great potential of other techniques and measures, which can be further used for analysis of Takaful business. Originality/value This research is a first attempt to trace out the behavior of Pakistani people about Takaful, using the above discussed factors. The behavioral intention is studied using users and non-users combination, which is never done before in the current setting.
Detection and Recognition of Myanmar Traffic Signs from Video

The efficient traffic sign detection and recognition (TSDR) is an important and challenging task for intelligent transportation systems. Traffic signs are an essential part of a Driver Assistance System (DAS) that automatically alerts and informs the driver of the traffic signs ahead. They are designed to be easily seen and understood. This paper describes a software application for the automatic detection and recognition of Myanmar traffic signs from a video sequence. The proposed system accomplishes two main modules: traffic sign detection and recognition. Before traffic signs are detected, color information, mainly red, yellow and blue, contained on the video is analyzed. In traffic sign detection module, there are three steps: 1) RGB to HSL conversion, 2) color filtering to extract color and 3) shape detection by using Harris corner detector. Traffic sign recognition module consists of three steps: 1) grayscale conversion, 2) edge detection with Sobel edge detector and 3) classification with template matching. The output of the system is audio. The proposed system can operate under a range of different lighting conditions at an average speed of 30 frames per second and is accurate even at high vehicle speeds. The experiment results show that the overall recognition rate of the proposed algorithm is 94%. It is proved that the proposed method is robust, effective and accurate to recognize the traffic signs. It is implemented with C# programming language.
The effect of ocular hypertension caused by red cells on the rate of formation of aqueous humor.

fluid in one eye and 1S5 I-albumin in the other. In the eyes with red cells the intraocular pressure was about 9 mm. Hg higher than in the controls. The rate of outflow of anterior chamber fluid in the red cell eye minus that in the control eye was divided by the difference in intraocular pressure. The ratio, representing the reduction in rate of outflow per millimeter of Hg pressure difference, was about the same in the two species, and the over-all average value for the suppressibility of the rate of aqueous humor formation was 0.060 ± 0.013 fil per minute per millimeter Hg. In 10 eyes receiving red cells but with the intraocular pressure adjusted to the same level as in the control eyes by means of a reservoir, the rate of aqueous humor formation toas 1.33 ± 0.08 fil per minute. In the control eyes it was 1.20 ± 0.07 fil per minute. The difference, 0.13 ± 0.05 fil per minute, was probably signiflcant, P < 0.05. If an alloivance is made for the somewhat doubtful tendency of the red cells per se to enhance the rate of formation of aqueous humor, in the pressure region investigated, the average suppressibility of the rate of aqueous humor formation becomes 0.07 fil per minute per millimeter Hg. The results indicate that there are large variations in the suppressibility of the rate of aqueous humor formation from one animal to another and that it may vary also in the individual eye.
Performance comparison of six Data mining models for soft churn customer prediction in Telecom

Due to a high competition in the market, the telecom operators are affected by churn, therefore it is very important for them to identify which users are likely to leave them and switch to the competition telecom company. This research uses data on behaviour of the users from telecom systems that serve to identify patterns in behaviours and thereby recognize the churn. Creating new definition of prepaid soft churn based on multiple conditions is valuable contribution of this paper. At preparing data, a selection of useful attributes was made using the Principal Component Analysis (PCA). The normalization of the attribute values has also been made in order to obtain a proper balance of the influence of all the attributes. Common problem with telecom churn prediction data is imbalance, taking into account the target variable. Such a case is also in the data used in this paper, where the percentage of churners is 12%. Comparison of undersampling and oversampling was performed as a method for resolving the data imbalance problem. Data sets with undersampling and oversasmpling have been used to train the decision tree, logistic regression and neural network algorithms and therefore six prediction models for detecting the churn of the Prepaid users in the telecom were created in this paper. Performance analysis and comparison of the six developed Data mining models was also performed.
Comparative systems of assessment of illness or disability for the purposes of adult social welfare payments, First Report (Final) (Incapacity for Work)

This is the first report of the study of comparative systems of assessment of illness or disability for the purposes of adult ‘incapacity’ social welfare payments. The purpose of the research is to examine systems for medical/disability assessment and review used in other comparable jurisdictions for assessing entitlement to social welfare illness and disability payments, and to draw key learning for the Irish system.