Miracle-dz/UniFAR-FTUs huggingface dataset:
Trait-Based Community Ecology of Phytoplankton

Trait-based approaches are increasingly used in ecology. Phytoplankton communities, with a rich history as model systems in community ecology, are ideally suited for applying and further developing these concepts. Here we summarize the essential components of trait-based approaches and review their historical and potential application to illuminating phytoplankton community ecology. Major ecological axes relevant to phytoplankton include light and nutrient acquisition and use, natural enemy interactions, morphological variation, temperature sensitivity, and modes of reproduction. Tradeoffs between these traits play key roles in determining community structure. Freshwater and marine environments may select for a different suite of traits owing to their different physical and chemical properties. We describe mathematical techniques for integrating traits into measures of growth and fitness and predicting how community structure varies along environmental gradients. Finally, we outline challenges and future directions for the application of trait-based approaches to phytoplankton ecology.
An Adaptive Gain Nonlinear Observer for State of Charge Estimation of Lithium-Ion Batteries in Electric Vehicles

The state of charge ( SOC ) is important for the safety and reliability of battery operation since it indicates the remaining capacity of a battery. However, it is difficult to get an accurate value of SOC , because the SOC cannot be directly measured by a sensor. In this paper, an adaptive gain nonlinear observer (AGNO) for SOC estimation of lithium-ion batteries (LIBs) in electric vehicles (EVs) is proposed. The second-order resistor–capacitor (2RC) equivalent circuit model is used to simulate the dynamic behaviors of a LIB, based on which the state equations are derived to design the AGNO for SOC estimation. The model parameters are identified using the exponential-function fitting method. The sixth-order polynomial function is used to describe the highly nonlinear relationship between the open circuit voltage ( OCV ) and the SOC . The convergence of the proposed AGNO is proved using the Lyapunov stability theory. Two typical driving cycles, including the New European Driving Cycle (NEDC) and Federal Urban Driving Schedule (FUDS) are adopted to evaluate the performance of the AGNO by comparing with the unscented Kalman filter (UKF) algorithm. The experimental results show that the AGNO has better performance than the UKF algorithm in terms of reducing the computation cost, improving the estimation accuracy and enhancing the convergence ability.
Intelligent Hybrid Man-Machine Translation Quality Estimation

Inferring evaluation scores based on human judgments is invaluable compared to using current evaluation metrics which are not suitable for real-time applications e.g. post-editing. However, these judgments are much more expensive to collect especially from expert translators, compared to evaluation based on indicators contrasting source and translation texts. This work introduces a novel approach for quality estimation by combining learnt confidence scores from a probabilistic inference model based on human judgments, with selective linguistic features-based scores, where the proposed inference model infers the credibility of given human ranks to solve the scarcity and inconsistency issues of human judgments. Experimental results, using challenging language-pairs, demonstrate improvement in correlation with human judgments over traditional evaluation metrics.
Using domain specific generated rules for automatic ontology population

This article proposes a process for automatic population of ontologies from text that applies natural language processing and information extraction techniques to acquire and classify ontology instances. The work is part of HERMES, an FCT/CAPES research project looking for techniques and tools for automating the process of ontology learning and population. Two experiments using a legal and a tourism corpora were conducted in order to evaluate it. The results indicate that our approach can extract and classify instances with high effectiveness with the additional advantage of domain independence.
Analytical approach of soft computing in big data issues

As big data computing is in emergence, therefore handling of large amount of data becoming a problematic day by day. Analyzing, visualizing, and managing this massive amount of data causing remarkable issues and challenges which are not even resolve through traditional technologies. Therefore it requires innovative technologies or methods to resolve issues and challenges. The main aim of this paper is to explore the effectiveness of combination of big data with soft computing to overcome the issues and challenges more efficiently and in less time. Here emphasis is given on three main soft computing techniques namely neural network, fuzzy logic and genetic for minimizing big data related problems. Research questions are also formed for this purpose in the present paper from 2004-2015 as primary study that will help the researchers in future in their related study.
Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery

High-Throughput (HT) SELEX combines SELEX (Systematic Evolution of Ligands by EXponential Enrichment), a method for aptamer discovery, with massively parallel sequencing technologies. This emerging technology provides data for a global analysis of the selection process and for simultaneous discovery of a large number of candidates but currently lacks dedicated computational approaches for their analysis. To close this gap, we developed novel in-silico methods to analyze HT-SELEX data and utilized them to study the emergence of polymerase errors during HT-SELEX. Rather than considering these errors as a nuisance, we demonstrated their utility for guiding aptamer discovery. Our approach builds on two main advancements in aptamer analysis: AptaMut—a novel technique allowing for the identification of polymerase errors conferring an improved binding affinity relative to the ‘parent’ sequence and AptaCluster—an aptamer clustering algorithm which is to our best knowledge, the only currently available tool capable of efficiently clustering entire aptamer pools. We applied these methods to an HT-SELEX experiment developing aptamers against Interleukin 10 receptor alpha chain (IL-10RA) and experimentally confirmed our predictions thus validating our computational methods.
The geographies of bullying in a secondary school context

This study, undertaken at a secondary school in the province of KwaZulu-Natal, sought to research bullying – a phenomenon seen globally as a major social problem that has a serious impact on the wellbeing of children and the youth. Participants were eight Grade 10 learners, 4 male and 4 female. The research tradition was a narrative inquiry as the aim was to foreground the participants’ stories of the places and spaces of bullying at the school. Data generation involved individual and focus group interviews. Data was analysed using thematic content analysis guided by theoretical concepts from New Childhood Studies and Children’s Geographies. The findings indicate that bullying is a serious problem at the school and has a negative impact on the wellbeing of children. Children emerged as social actors who were able to provide insight into the kinds of bullying they experienced and how they constructed ‘bullying’ as a phenomenon. The study was able to capture the reality of the children’s experiences of the complex power-laden spaces and places of bullying at the school. The study shows that bullying is situated in a context and an in-depth analysis of context is necessary to capture the intricacies of the phenomenon.Keywords: bullying; children’s geographies; narrative inquiry; new childhood studies; secondary school; South Africa
Network Router Resource Virtualisation

The Internet was created as a best effort service, however, there is now considerable interest in applications which transport time sensitive data across the network. This project looks into a novel network router architecture, which could improve the Quality of Service guarantees which can be provided to such flows. This router architecture makes use of virtual machine techniques, to assign an individual virtual routelet to each network flow requiring QoS guarantees. In order to evaluate the effectiveness of this virtual routelet architecture, a prototype router was created, and its performance was measured and compared with that of a standard router. The results suggest promise in the virtual routelet architecture, however, the overheads incurred by current virtual machine techniques prevent this architecture from outperforming a standard router. Evaluation of these results suggests a number of enhancements which could be made to virtual machine techniques in order to effectively support this virtual routelet architecture.
A low-latency, real-time-capable singing voice detection method with LSTM recurrent neural networks

Singing voice detection aims at identifying the regions in a music recording where at least one person sings. This is a challenging problem that cannot be solved without analysing the temporal evolution of the signal. Current state-of-the-art methods combine timbral with temporal characteristics, by summarising various feature values over time, e.g. by computing their variance. This leads to more contextual information, but also to increased latency, which is problematic if our goal is on-line, real-time singing voice detection. To overcome this problem and reduce the necessity to include context in the features themselves, we introduce a method that uses Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN). In experiments on several data sets, the resulting singing voice detector outperforms the state-of-the-art baselines in terms of accuracy, while at the same time drastically reducing latency and increasing the time resolution of the detector.
Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs.
Measuring the difficulty of text translation

This paper explores the impact of text complexity on translators’ subjective perception of translation difficulty and on their cognitive load. Twenty-six MA translation students from a UK university were asked to translate three English texts with different complexity into Chinese. Their eye movements were recorded by an eye-tracker, and their cognitive load was self-assessed with a Likert scale before translation and NASA-TLX scales after translation. The results show that: (i) the intrinsic complexity measured by readability, word frequency and non-literalness was in line with the results received from informants’ subjective assessment of translation difficulty; (ii) moderate and positive correlations existed between most items in the self-assessments and the indicator (fixation and saccade durations) obtained by the eye-tracking measurements; and (iii) the informants’ cognitive load as indicated by fixation and saccade durations (but not for pupil size) increased significantly in two of the three texts along with the increase in source text complexity.
Symmetry Analysis of Reversible Markov Chains

We show how to use subgroups of the symmetry group of a reversible Markov chain to give useful bounds on eigenvalues and their multiplicity. We supplement classical representation theoretic tools involving a group commuting with a self-adjoint operator with criteria for an eigenvector to descend to an orbit graph. As examples, we show that the Metropolis construction can dominate a max-degree construction by an arbitrary amount and that, in turn, the fastest mixing Markov chain can dominate the Metropolis construction by an arbitrary amount.
Psychiatric and Interpersonal Correlates of Suicide Ideation in Military Sexual Trauma Survivors: The National Health and Resilience in Veterans Study

Background Veterans who experience military sexual trauma are at increased risk for experiencing suicidal ideation, suicide attempt, and suicide. Yet few studies have attempted to discern factors that relate to suicidal ideation and suicide attempts among survivors of military sexual trauma. The present study aimed to identify psychiatric and interpersonal correlates of suicidal ideation (primary aim) and suicide attempt (secondary aim) among survivors of military sexual trauma. Methods This cross-sectional analysis included 115 veterans (56 females; mean age = 53.24) who participated in the National Health and Resilience in Veterans Study and reported experiencing military sexual trauma. Self-report measures assessed psychological distress, hazardous alcohol use, social support, loneliness, social acknowledgment following one’s worst trauma, suicidal ideation, and suicide attempts. Results Military sexual trauma survivors who reported more severe psychological distress (OR = 2.88), hazardous alcohol use (OR = 1.14), and perceived general disapproval from others (OR = 1.14) were significantly more likely to report experiencing suicidal ideation in the past two weeks. Hazardous alcohol use (OR = 1.19) and perceived general disapproval from others (OR = 1.36) were associated with being more likely to report attempting suicide in adulthood. Conclusions Addressing alcohol misuse, psychological distress, and perceived general disapproval from others in relation to one’s worst traumatic event is recommended when assessing and managing suicide risk among veterans who have experienced military sexual trauma. Findings also contribute to a growing literature highlighting the importance of understanding perceptions of the interpersonal response to trauma. Considering the cross-sectional design, longitudinal research is needed to further elucidate the roles of these constructs in predicting suicidal ideation and suicide attempt following military sexual trauma.
Concise Review: Methods and Cell Types Used to Generate Down Syndrome Induced Pluripotent Stem Cells

Down syndrome (DS, trisomy 21), is the most common viable chromosomal disorder, with an incidence of 1 in 800 live births. Its phenotypic characteristics include intellectual impairment and several other developmental abnormalities, for the majority of which the pathogenetic mechanisms remain unknown. Several models have been used to investigate the mechanisms by which the extra copy of chromosome 21 leads to the DS phenotype. In the last five years, several laboratories have been successful in reprogramming patient cells carrying the trisomy 21 anomaly into induced pluripotent stem cells, i.e., T21-iPSCs. In this review, we summarize the different T21-iPSCs that have been generated with a particular interest in the technical procedures and the somatic cell types used for the reprogramming.
Introduction to MPEG-7

How many times have you seen science fiction movies such as 2001: A Space Odyssey and thought, “Wow, we’re so far away from having any of the fancy gadgets depicted in these movies! ” In 2001, Hal, the talking computer intelligently navigates and retrieves information or runs complex operations instigated by spoken input. Or how about using an image-based query, say an image of the motorbike used by Arnold Schwartzenegger in the movie T2, to find images of similarly looking motorbikes. Dreams or reality? As more and more audiovisual information becomes available from many sources around the world, many people would like to use this information for various purposes. This challenging situation led to the need for a solution that quickly and efficiently searches for and/or filters various types of multimedia material that’s interesting to the user. For example, finding information by rich-spoken queries, hand-drawn images, and humming improves the user-friendliness of computer systems and finally addresses what most people have been expecting from computers. For professionals, a new generation of applications will enable high-quality information search and retrieval. For example, TV program producers can search with “laser-like precision” for occurrences of famous events or references to certain people, stored in thousands of hours of audiovisual records, in order to collect material for a program. This will reduce program production time and increase the quality of its content. MPEG-7 is a multimedia content description standard, (to be defined by September 2001), that addresses how humans expect to interact with computer systems, since it develops rich descriptions that reflect those expectations. This document gives an introductory overview of the MPEG-7 standard. More information about MPEG-7 can be found at the MPEG-7 website http://drogo.cselt. it/mpeg/ and the MPEG-7 Industry Focus Group website http://www.mpeg-7.com. These web pages contain links to a wealth of information about MPEG, including many publicly available documents, several lists of ‘Frequently Asked Questions’ and links to other MPEG-7 web pages.
Reliability Study of Coding Schemes for Wide-Area Distributed Storage Systems

Distributed storage systems comprise a large number of commodity hardware distributed across several data centers. Even in the presence of failures (permanent failures) the system should provide reliable storage. While replication has advantages because of its simplicity there exist coding techniques that provide adaptable reliability properties with an optimal redundancy ratio at the same time e.g. MDS (maximum distance separable) erasure codes. The coding and distribution scheme influences the prospective storage reliability. In this paper we present reliability models for erasure coding and replication techniques especially for their application in wide-area storage systems. Furthermore we utilize these models to quantify the reliability properties of concrete data storage scenarios.
Classifying Images of Classical Architectures: Chinese vs. European

Image classification is an important problem in computer vision. All existing image classification approaches tend to classify images of distinctly different objects. In this paper, we attempt to classify two similar image classes, Chinese and European classical architecture. First, Gabor filter is utilized to catch texture features of images. Then color histogram distance is adopted as a coefficient of image dissimilarity in a modified k-NN classifier. Images are segmented to regions, and all region texture features are combined into vectors by corresponding area proportion. We also studied the impact of image segmentation on classification by comparing two different segmentation al- gorithms. The experiment shows the new approach is effective in distinguishing images of Chinese and European classical architectures.
Projected changes in climatic suitability for Kinosternon turtles by 2050 and 2070

Abstract Chelonians are expected to be negatively impacted by climate change due to limited vagility and temperature‐dependent sex determination. However, few studies have examined how freshwater turtle distributions may shift under different climate change scenarios. We used a maximum entropy approach to model the distribution of five widespread North American Kinosternon species (K. baurii, K. flavescens, K. hirtipes, K. sonoriense, and K. subrubrum) under four climate change scenarios. We found that areas with suitable climatic conditions for K. baurii and K. hirtipes are expected to decline substantially during the 21st century. In contrast, the area with suitable climate for K. sonoriense will remain essentially unchanged, while areas suitable for K. flavescens and K. subrubrum are expected to substantially increase. The centroid for the distribution of four of the five species shifted northward, while the centroid for K. sonoriense shifted slightly southward. Overall, centroids shifted at a median rate of 37.5 km per decade across all scenarios. Given the limited dispersal ability of turtles, it appears unlikely that range shifts will occur rapidly enough to keep pace with climate change during the 21st century. The ability of chelonians to modify behavioral and physiological responses in response to unfavorable conditions may allow turtles to persist for a time in areas that have become increasingly unsuitable, but this plasticity will likely only delay local extinctions.
Lower Bounds and Separations on Extensions of Resolution

We work with an extension of Resolution, called Res(2), that allows clauses with conjunctions of two literals. In this system there are rules to introduce and eliminate such conjunctions. We prove that the pigeonhole principle PHP cn n requires exponential-size proofs in this system. As a consequence, Res(log) is exponentially more powerful than Res(2). Also we prove that Resolution cannot polynomially simulate Res(2), and that Res(2) does not have the feasible monotone interpolation theorem.
Repairing GUI Test Suites Using a Genetic Algorithm

Recent advances in automated functional testing of Graphical User Interfaces (GUIs) rely on deriving graph models that approximate all possible sequences of events that may be executed on the GUI, and then use the graphs to generate test cases (event sequences) that achieve a specified coverage goal. However, because these models are only approximations of the actual event flows, the generated test cases may suffer from problems of infeasibility, i.e., some events may not be available for execution causing the test case to terminate prematurely. In this paper we develop a method to automatically repair GUI test suites, generating new test cases that are feasible. We use a genetic algorithm to evolve new test cases that increase our test suite's coverage while avoiding infeasible sequences. We experiment with this algorithm on a set of synthetic programs containing different types of constraints and for test sequences of varying lengths. Our results suggest that we can generate new test cases to cover most of the feasible coverage and that the genetic algorithm outperforms a random algorithm trying to achieve the same goal in almost all cases.