Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin A and protein interrelationships in the milk-fed lamb

1. The mean liver retinol reserve (retinal + retinyl esters, expressed as retinol) of six newborn lambs was 21±8 μg. The mean value for ten suckled lambs, aged 5–7 days, was 2655±472 μg retinol per liver. 2. Three unsuckled lambs were fed ad lib. from birth for 28 days on a high-protein diet, based on lard and skim milk, without supplementary vitamin A. The diet provided sufficient vitamin A for normal growth, but insufficient to permit substantial liver reserves (43±8 μg retinol per liver). 3. Thirty-six suckled lambs aged 5–7 days were given either a low-or a high-protein diet for 21 days, with or without graded levels of retinyl acetate or βcarotene. There were no significant differences in the live-weight gain or in liver retinol reserves between the low-and highprotein dietary treatments, or between the supplemented and unsupplemented groups. 4. Twelve lambs were pair-fed on either a low-or a high-protein diet from birth for 21 days. Six lambs that were given a large supplement of retinyl palmitate on the 1st day of life had stored significantly less retinol in the liver at 21 days (P > 0.01) than six lambs given a somewhat smaller total amount of retinyl palmitate in small daily doses. Lambs given the high-protein diet had significantly greater liver retinol reserves (P > 0.01) than lambs given the low-protein diet, with both methods of supplementation. 5. Twelve lambs were pair-fed from birth on a high-protein diet for 2 or 6 days. Lambs that were given retinyl palmitate dissolved in either a low-or a high-protein diet on the 1st day of life had significantly lower liver retinol reserves some 24 h later (P > 0.01) than lambs given similar treatments on the 5th day of life. Liver retinol reserves were positively correlated with the protein concentration of the diet at the time of supplementation. 6. Eighteen lambs were pair-fed from birth with either a low- or a high-protein diet. Six pairs were given retinyl palmitate daily and three pairs were given the supplement 48 h before slaughter. The source of protein was casein. Eight out of nine lambs given the low-protein diet would have died had they not been slaughtered at between 8 and 11 days of age. The time of supplementation had no significant effect on liver retinol reserves, which were very low, regardless of the dietary protein concentration. Lambs given the high-protein diet retained a significantly greater proportion (P > 0.05) of the dietary retinyl palmitate than lambs given the low-protein diet.
Handling Big Data Stream Analytics using SAMOA Framework - A Practical Experience

Data analytics and machine learning has always been of great importance in almost every field especially in business decision making and strategy building, in healthcare domain, in text mining and pattern identification on the web, in meteorological department, etc. The daily exponential growth of data today has shifted the normal data analytics to new paradigm of Big Data Analytics and Big Data Machine Learning. We need tools to perform online data analysis on streaming data for achieving faster learning and faster response in data analytics as well as maintaining scalability in terms of huge volume of data. SAMOA (Scalable Advanced Massive Online Analysis) is a recent framework in this reference. This paper discusses the architecture of this SAMOA framework and its directory structure. Also it expresses a practical experience of configuring and deployment of the tool for handling massive online analysis on Big Data.
The Role of the Spouse in Early Retirement Decisions for Older Workers

This paper investigates the determinants of older workers' early retirement behavior in Denmark. Instead of considering dual retirement we recognize the importance of the spouse in the early retirement decision by assessing the effect of a rich number of spousal variables. Given the grouped nature of the data we set up a semi-parametric single risk grouped duration proportional hazard model accounting for right censoring and allows for time-varying covariates, a nonparametric baseline and unobserved heterogeneity. We find that spousal characteristics do influence the retirement decision and significant gender asymmetries also exist in the effects of spouse's characteristics.Classification-JEL: J26, C41.
“ Interaction Between Vesicular Arbuscular Mycorrhiza And Rhizobium With Special Reference To Cicer arietinum L And Phaseolus mungoL

The study was initiated to determine the influence of VAM fungi on a Rhizobiumlegume interaction. The pot experiment was conducted during rabbi season with seed of Cicer arietinum.L and Phaseolus mungo L. and Leonard-jar experiment was conducted for Phaseolus mungo L. The different inoculations of Rhizobium and Mycorrhiza were incorporated. During the period of experiment, samples were analysed for nodule numbers, dry weight of nodules, grain yields and percentage of Mycorrhizal colonization. The results revealed that dual inoculation of Rhizobium with VAM enhanced seed yield of chickpea and blackgram.
A Fuzzy Logic System for Seizure Onset Detection in Intracranial EEG

We present a multistage fuzzy rule-based algorithm for epileptic seizure onset detection. Amplitude, frequency, and entropy-based features were extracted from intracranial electroencephalogram (iEEG) recordings and considered as the inputs for a fuzzy system. These features extracted from multichannel iEEG signals were combined using fuzzy algorithms both in feature domain and in spatial domain. Fuzzy rules were derived based on experts' knowledge and reasoning. An adaptive fuzzy subsystem was used for combining characteristics features extracted from iEEG. For the spatial combination, three channels from epileptogenic zone and one from remote zone were considered into another fuzzy subsystem. Finally, a threshold procedure was applied to the fuzzy output derived from the final fuzzy subsystem. The method was evaluated on iEEG datasets selected from Freiburg Seizure Prediction EEG (FSPEEG) database. A total of 112.45 hours of intracranial EEG recordings was selected from 20 patients having 56 seizures was used for the system performance evaluation. The overall sensitivity of 95.8% with false detection rate of 0.26 per hour and average detection latency of 15.8 seconds was achieved.
L'intermédiation financière dans l'analyse macroéconomique: le défi de la crise

Dans cet article, nous presentons la modelisation du secteur financier dans la litterature des MEGIS. Ces maquettes de l'economie visent a quantifier l'impact sur les variables d'interet (inflation, prix des actifs, PIB, taux d'interet par exemple) de l'ensemble des interactions des agents economiques presents dans le modele. Cet accent sur l'equilibre general implique une modelisation lourde integrant non seulement le comportement de tous les agents, mais egalement l'impact de l'ensemble de ces comportements sur le prix de chaque marche modelise dans la maquette. Un economiste raisonnant en equilibre partiel ne s'interesserait qu'aux comportements individuels sans rechercher a quantifier l'impact des interactions individuelles sur l'economie. L'approche en equilibre general s'impose en particulier dans l'analyse de la crise recente au cours de laquelle les choix des agents economiques ont affecte les prix de marche, lesquels viennent, dans un effet retour, modifier les actions des agents.
Computational tests of a thermal cycling strategy to isolate more complex functional nucleic acid motifs from random sequence pools by in vitro selection

The dual information-function nature of nucleic acids has been exploited in the laboratory to isolate novel receptors and catalysts from random DNA and RNA sequences by cycles of in vitro selection and amplification. This strategy is particularly effective because, unlike polypeptides with random amino acid sequences, nucleic acids with random base sequences are often capable of stably folding into defined three-dimensional structures. However, the pervasive base-pairing potential of nucleic acids is also known to lead to kinetic traps in their folding landscapes. That is, the same DNA or RNA sequence can often adopt alternative base-paired structures that are local energy minima, and these folds may interconvert very slowly. We have used simulations with nucleic acid folding algorithms to evaluate the effect of misfolding on in vitro selection experiments. We demonstrate that kinetic traps can prevent the recovery of novel families of complex functional motifs by two mechanisms. First, misfolding can lead to the stochastic loss of unique sequences in the first round of selection. Second, frequent misfolding can reduce the average activity of multiple copies of a sequence to such an extent that it will be outcompeted after multiple rounds of selection. In these simulations, adding thermal cycling to sample multiple folds of one sequence during a selection for a self-modifying catalytic activity can improve the recovery of rare examples of more complex structures. Although newly isolated sequences may fold poorly, they can represent footholds in sequence space that can be improved to reliably fold after a few mutations. Thus, it is plausible that thermal cycling by day-night cycles or other mechanisms on the primordial earth may have been important for the evolution of the first RNA catalysts, and a fold sampling strategy might be used to search for more effective nucleic acid catalysts in the laboratory today.
Framewise Phone Classification Using Weighted Fuzzy Classification Rules

Our aim in this paper is to propose a rule-weight learning algorithm in fuzzy rule-based classifiers. The proposed algorithm is presented in two modes: first, all training examples are assumed to be equally important and the algorithm attempts to minimize the error-rate of the classifier on the training data by adjusting the weight of each fuzzy rule in the rule-base, and second, a weight is assigned to each training example as the cost of misclassification of it using the class distribution of its neighbors. Then, instead of minimizing the error-rate, the learning algorithm is modified to minimize the sum of costs for misclassified examples. Using six data sets from UCI-ML repository and the TIMIT speech corpus for frame wise phone classification, we show that our proposed algorithm considerably improves the prediction ability of the classifier.
Series connection of IGBTs in hard-switching applications

A new circuit topology is presented which makes possible and safe the series connection of devices in very high voltage switching applications. This circuit behaves like a flyback converter and assures the uniform distribution of the voltage among the devices of the series. Within the proposed topology the active devices are hard switched. By means of this circuit the performances of a single IGBT module rated at 3300 V-1200 A are compared with those ones of the series connection of two IGBT modules rated at 1700 V-1200 A. The comparison is performed on an experimental basis and shows that the on-state voltage drop of the series is about twice that one of the single module, but switching losses are much lower for the series connection. Consequently, the proposed topology makes convenient the use of the series connection of IGBTs modules for frequencies larger than 3 kHz whereas the single high voltage IGBT module remains advantageous for frequency lower than 2 kHz. In other words the paper demonstrates that the series connection of the IGBTs can be used to extend the trade-off between conduction and switching losses also to high voltage modules.
Growth Patterns of Two Types of Macro-Models: Limiting Behavior of One-and Two-Parameter Poisson-Dirichlet Models

This paper uses novel growth models composed of clusters of heterogeneous agents,and shows that limiting behavior of one-and two-parameter Poisson-Dirichlet models are qualitatively very different. As model sizes grow unboundedly, the coefficients of variations of extensive variables, such as the number of total clusters, and the numbers of clusters of specified sizes all approach zero in the one-parameter models, but not in the two-parameter models. In the calculations of the coefficients of variations Mittag-Le? er distributions arise naturally. We show that the distributions of the numbers of the clusters in the models havepower-lawbehavior.
Developing a Corporate Social Responsibility Index in the Philippines: An Assessment

Abstract Business response to societal obligations, either out of volition or by force of circumstances, is a long-standing practice in the Philippines. Interestingly, Filipino corporations tend to project their social obligations onto auxiliary associations. Filipino companies, for example, have long funneled their corporate social responsibility (CSR) resources into the Philippine Business for Social Progress (PBSP), a long-running non-profit group that absorbs the burden of social responsibility of member companies. In recent days, PBSP has developed an index for measuring social responsibility performance of its member companies. This article assesses this development.
The Quest for a Fundamental Algorithm in X-Ray Fluorescence Analysis and Calibration

The Fundamental Algorithm between concentration (C i ) and intensity (R i ) in X-ray fluorescence analysis is deduced from Sherman's equation without any approximation. Its explicit expression is thus theoretically exact and it cor- rects completely for all matrix effects on the intensity R i emitted by the analyte i in a given specimen. This powerful algo- rithm combines the practical flexibility of the influence coefficient concept and the theoretical exactness of the Funda- mental-Parameters method. In association with its innovative calibration procedure, the Fundamental Algorithm can be applied to the analysis of any sample type and offers maximum accuracy, limited only by the quality of sample prepara- tion and the standards used.
Using immersive video to evaluate future traveller information systems

An immersive video system that has been developed for the purpose of evaluating future traveller information system (F-TIS), in particular, F-TIS scenarios that rely on a pervasive computing infrastructure is presented. Immersive video uses multiple video streams captured from a first person perspective at key locations in a scenario. By dynamically reconstructing a user's visual and aural experiences, the immersive video system creates a lab-based framework that captures a number of contextual factors of real-world mobile information system use. Graphical user interfaces, displayed on a wearable display and a personal digital assistant, are used in the evaluation. Both the technical basis of the immersive video system and its application to the study of user perceptions and reactions to pervasive information services are presented.
ASEM: Mining Aspects and Sentiment of Events from Microblog

Microblogs contain the most up-to-date and abundant opinion information on current events. Aspect-based opinion mining is a good way to get a comprehensive summarization of events. The most popular aspect based opinion mining models are used in the field of product and service. However, existing models are not suitable for event mining. In this paper we propose a novel probabilistic generative model (ASEM) to simultaneously discover aspects and the specified opinions. ASEM incorporate a sequence labeling model(CRF) into a generative topic model. Additionally, we adopt a set of features for separating aspects and sentiments. Moreover, we novelly present a continuously learning model. It can utilize the knowledge of one event to learn another, and get a better performance. We use five real world events to do experiment. The experimental results show that ASEM extracts aspects and sentiments well, and ASEM outperforms other state-of-art models and the intuitive two-step method.
Volatile Metabolites of Pathogens: A Systematic Review

Ideally, invading bacteria are detected as early as possible in critically ill patients: the strain of morbific pathogens is identified rapidly, and antimicrobial sensitivity is known well before the start of new antimicrobial therapy. Bacteria have a distinct metabolism, part of which results in the production of bacteria-specific volatile organic compounds (VOCs), which might be used for diagnostic purposes. Volatile metabolites can be investigated directly in exhaled air, allowing for noninvasive monitoring. The aim of this review is to provide an overview of VOCs produced by the six most abundant and pathogenic bacteria in sepsis, including Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli. Such VOCs could be used as biological markers in the diagnostic approach of critically ill patients. A systematic review of existing literature revealed 31 articles. All six bacteria of interest produce isopentanol, formaldehyde, methyl mercaptan, and trimethylamine. Since humans do not produce these VOCs, they could serve as biological markers for presence of these pathogens. The following volatile biomarkers were found for identification of specific strains: isovaleric acid and 2-methyl-butanal for Staphylococcus aureus; 1-undecene, 2,4-dimethyl-1-heptane, 2-butanone, 4-methyl-quinazoline, hydrogen cyanide, and methyl thiocyanide for Pseudomonas aeruginosa; and methanol, pentanol, ethyl acetate, and indole for Escherichia coli. Notably, several factors that may effect VOC production were not controlled for, including used culture media, bacterial growth phase, and genomic variation within bacterial strains. In conclusion, VOCs produced by bacteria may serve as biological markers for their presence. Goal-targeted studies should be performed to identify potential sets of volatile biological markers and evaluate the diagnostic accuracy of these markers in critically ill patients.
Microsatellite Instability Generates Diversity in Brain and Sociobehavioral Traits

Repetitive microsatellites mutate at relatively high rates and may contribute to the rapid evolution of species-typical traits. We show that individual alleles of a repetitive polymorphic microsatellite in the 5′ region of the prairie vole vasopressin 1a receptor (avpr1a) gene modify gene expression in vitro. In vivo, we observe that this regulatory polymorphism predicts both individual differences in receptor distribution patterns and socio-behavioral traits. These data suggest that individual differences in gene expression patterns may be conferred via polymorphic microsatellites in the cis-regulatory regions of genes and may contribute to normal variation in behavioral traits.
The Evolution of Web Content and Search Engines

The Web grows at a fast pace and little is known about how new content is generated. The objective of this paper is to study the dynamics of content evolution in the Web, giv- ing answers to questions like: How much new content has evolved from the Web old content? How much of the Web content is biased by ranking algorithms of search engines? We used four snapshots of the Chilean Web containing doc- uments of all the Chilean primary domains, crawled in four distinct periods of time. If a page in a newer snapshot has content of a page in an older snapshot, we say that the source is a parent of the new page. Our hypothesis is that when pages have parents, in a portion of pages there was a query that related the parents and made possible the creation of the new page. Thus, part of the Web content is biased by the ranking function of search engines. We also deflne a ge- nealogical tree for the Web, where many pages are new and do not have parents and others have one or more parents. We present the Chilean Web genealogical tree and study its components. To the best of our knowledge this is the flrst paper that studies how old content is used to create new content, relating a search engine ranking algorithm with the creation of new pages.
Language and its two complex systems

Language has been a topic of great interest at least since the Greek philosophers. Clearly speech is one of the most sophisticated and complex of human capabilities and has remained a major puzzle through the centuries. Complex systems promise to provide analytical tools that will help break through some of the mystery. From this perspective, it appears that there are three complex systems relevant to speech. The first is natural selection, the slow influences on the gene pool of the species that give us whatever innate skills we need to learn at least one language. However, we will have nothing further to say about this issue here since the time scale involved is so long relative to human history. The remaining two complex systems are highly relevant. They are, first, the language itself, viewed here as a particular type of social institution, a set of cultural practices that present the language learner with a broad range of linguistic materials with which to communicate with others. This system clearly evolves as history and the cultural practices of the community change. It sometimes requires only a couple hundred years (a dozen or so generations) for a language to split into mutually incomprehensible dialects. The final complex system is the one that the individual speaker develops as he/she gradually becomes competent in the use of the language. This system begins before birth and continues to learn and adapt right up until death as the language environment of an individual changes. It involves controlling the many muscle systems of the vocal tract and respiratory system as well as specializations of the auditory system that customize it for hearing and understanding speech in the ambient language or languages.
Delivery Latency Trade-Offs of Heterogeneous Contents in Fog Radio Access Networks

A Fog Radio Access Network (F-RAN) is a cellular wireless system that enables content delivery via the caching of popular content at edge nodes (ENs) and cloud processing. The existing information-theoretic analyses of F-RAN systems, and special cases thereof, make the assumption that all requests should be guaranteed the same delivery latency, which results in identical latency for all files in the content library. In practice, however, contents may have heterogeneous timeliness requirements depending on the applications that operate on them. Given per-EN cache capacity constraint, there exists a fundamental trade-off among the delivery latencies of different users' requests, since contents that are allocated more cache space generally enjoy lower delivery latencies. For the case with two ENs and two users, the optimal latency trade-off is characterized in the high-SNR regime in terms of the Normalized Delivery Time (NDT) metric. The main results are illustrated by numerical examples.