Miracle-dz/UniFAR-FTUs huggingface dataset:
Myocardial Fatty Acid Metabolism: Independent Predictor of Left Ventricular Mass in Hypertensive Heart Disease

Abstract—The expression of myocardial fatty acid &bgr;-oxidation enzymes is downregulated at the gene transcriptional level in animal models of left ventricular hypertrophy and of heart failure. Humans with idiopathic dilated cardiomyopathy have decreased myocardial fatty acid oxidation. The extent to which molecular mechanisms, such as a reduction in myocardial fatty acid oxidation, regulate the cardiac hypertrophic response in humans in vivo is unknown. Positron emission tomography was used to measure myocardial blood flow, oxygen consumption, fatty acid utilization, and oxidation in two groups of patients: (1) hypertensive left ventricular hypertrophy (n=19; left ventricular mass, 211±39 g; left ventricular ejection fraction, 67±4%) and (2) left ventricular dysfunction (n=9; left ventricular mass, 210±36 g; left ventricular ejection fraction, 31±10%); these were compared with a normal control group (n=36; left ventricular mass, 139±25 g; left ventricular ejection fraction, 66±6%). Left ventricular mass showed significant correlation with gender, diastolic and systolic blood pressure, myocardial fatty acid uptake, utilization and oxidation, myocardial blood flow, body mass index, and left ventricular ejection fraction (all P <0.02). Independent predictors of increased left ventricular mass were male gender (r =0.38, P <0.001), myocardial fatty acid oxidation (r =−0.24, P <0.018), systolic blood pressure (r =0.41, P <0.001), and left ventricular ejection fraction (r =−0.29, P =0.005). Thus, myocardial fatty acid metabolism is an independent predictor of left ventricular mass in hypertension and in left ventricular dysfunction. The extent to which reduced myocardial fatty acid metabolism affects cardiovascular morbidity and mortality and whether pharmacologic modulation results in improved outcomes remains to be determined.
Effect of hypertension on low-density lipoprotein transport within a multi-layered arterial wall: modelling consistent with experiments

The influence of hypertension on low-density lipoproteins intake into the arterial wall is an important factor for understanding mechanisms of atherosclerosis. It has been experimentally observed that the increased pressure leads to the higher level of the LDL inside the wall. In this paper we attempt to construct a model of the LDL transport which reproduces quantitatively experimental outcomes. We supplement the well known four-layer arterial wall model to include two pressure induced effects: the compression of the intima tissue and the increase of the fraction of leaky junctions. We demonstrate that such model can reach the very good agreement with experimental data.
Novel communication services based on human body and environment interaction: applications inside trains and applications for handicapped people

We believe that near-field radio intra-body communications, wherein human body is used as the transmission medium, will be a very suitable solution for body area networks with many interesting applications towards a ubiquitous communication world. This paper presents some potential new applications of great usefulness for handicapped people. Moreover, we have also envisioned applications inside train coaches where the use of mobile phones is restricted in countries such as Japan. On the other hand, we present the system model designed to carry out these applications by using intra-body communications. Finally, in order to investigate the feasibility of this kind of communication, we analyze experimentally the characteristics of the intra-body propagation channels and we evaluate the performance of several digital modulation schemes
Classifying Pervasive Games: On Pervasive Computing and Mixed Reality

Pervasive Games have become popular in recent years. Their ambitious goal is to bring the computer into the world in order to augment existing games or to even come up with hitherto impossible or unthought-of forms of entertainment. This paper reflects on the various approaches to define what Pervasive Games consist of, how they relate to playing and games, and how different terms and views can be integrated. The paper contributes a unifying and integrating classification of the respective terms that relates different states of reality to the relevant dimensions and game elements.
A Unified Perspective on Advances of Independent Subspaces: Basic, Temporal, and Local Structures

A general framework of independent subspaces is presented, based on which a number of unsupervised learning topics have been summarized from a unified perspective, featured by different combinations of three basic ingredients. Moreover, advances on these topics are overviewed in three streams, with roadmaps sketched. One consists of studies on the second order independence featured principal component analysis (PCA) and factor analysis (FA), in adaptive and robust implementations as well as with duality and temporal extensions. The other consists of studies on the higher order independence featured independent component analysis (ICA), binary FA, and nonGaussian FA. The third is called mixture based learning that combines the above individual tasks, proportionally or competitively to fulfill a complicated task.
Analysis of Backpropagation using Biogeography Based Optimization

Biogeography Based Optimisation (BBO) is a population based evolutionary algorithm (EA) motivated by the migration mechanisms of ecosystems. BBO is a nature inspired technique. The idea was given by D.Simon in Dec.2008. Geographical areas that are well suited as residences for biological species are said to have a High Suitability Index (HSI). Features that are correlated with HSI include such factors as rainfall, diversity of vegetation, land area and temperatures. The variables that characterize the habitability are called Suitability Index Variables (SIVs). Habitats with a high HSI tend to have a large number of species, while those with a low HSI have small number of species. It is an example of natural process that can be modelled to solve general optimisation problems. In this paper, this nature inspired behaviour has been considered to optimise the neural network i.e Backpropagtion by BBO. The Backpropagation is a Neural Network. In this , the units are connected in a feed- forward fashion with input units fully connected to the units in the hidden layer and hidden units are fully connected t o the units in output layer. When a Backpropagation network is cycled , an input pattern is propagated forward to the output units through an intervening input-to-hidden and hidden-to-output weights. The idea behind this is that errors for the units of the hidden layer are determined by backpropagating the errors of the units of the output layer and analysis of the Backpropagation are done by BBO. The BBO searches the optimal or near optimal connection weights and threshold.
Medical distress prediction based on Classification Rule Discovery using ant-miner algorithm

Enormous data mining techniques were used for disease prediction among which only a few have employed feature selection. The prediction knowledge for disease diagnosis highly depends on the subjective knowledge of the experts. Developing a disease prediction model in time can help us to overcome the medical distress. In this paper, three feature selection strategies namely, HS, MS and TS are devised to obtain the valuable subset of relevant features for reducing the dimensionality of multiple attributes. This work proposed a modified ant-miner algorithm to extract the classification rules from the data. Three benchmarked datasets (Cleveland, Pima and Wisconsin) from the UCI machine learning repository were used to analyze effectiveness of the proposed model. The obtained results clearly shows that the modified ant-miner outperforms the other top data mining classification algorithms like the CN2, RBF, Adaboost and Bagging in terms of accuracy. Thus the proposed model is capable of producing good results with fewer features and serves as a suitable tool for eliciting and representing the expert's decision rules with an effective support for solving disease prediction problem.
The Pax gene family: Highlights from cephalopods

Pax genes play important roles in Metazoan development. Their evolution has been extensively studied but Lophotrochozoa are usually omitted. We addressed the question of Pax paralog diversity in Lophotrochozoa by a thorough review of available databases. The existence of six Pax families (Pax1/9, Pax2/5/8, Pax3/7, Pax4/6, Paxβ, PoxNeuro) was confirmed and the lophotrochozoan Paxβ subfamily was further characterized. Contrary to the pattern reported in chordates, the Pax2/5/8 family is devoid of homeodomain in Lophotrochozoa. Expression patterns of the three main pax classes (pax2/5/8, pax3/7, pax4/6) during Sepia officinalis development showed that Pax roles taken as ancestral and common in metazoans are modified in S. officinalis, most likely due to either the morphological specificities of cephalopods or to their direct development. Some expected expression patterns were missing (e.g. pax6 in the developing retina), and some expressions in unexpected tissues have been found (e.g. pax2/5/8 in dermal tissue and in gills). This study underlines the diversity and functional plasticity of Pax genes and illustrates the difficulty of using probable gene homology as strict indicator of homology between biological structures.
Monthly variation in human semen quality in male partners of infertile women in the tropics.

The aim of the study was to determine whether there were significant 'seasonal' variations in the rhythm of sperm parameters (i.e. semen volume and sperm density) of men who reside in the tropics. A total of 7656 semen analysis results from the department of obstetrics and gynaecology of a tertiary general hospital was analysed. These samples were obtained as part of an initial screening for male partners of couples with problems trying to conceive who were attending a fertility clinic from 1991 to 1995. The subjects' mean semen volume and sperm density of 2.9 ml and 26.9x10(6)/ml respectively were within the World Health Organization reference values. There were no significant month-to-month variations in the adjusted (for age of subject, year of test and technologist who performed the analysis by analysis of co-variance, ANCOVA) mean semen volume and sperm density over the 5 year period. Variations in semen volume and density observed in the temperate climates are not seen in this study, which was conducted in subjects staying in the tropics. This observation may be related to relative constant temperature and hours of light exposure among men who reside in the tropics. As this study is, so far, published data from only one country, Singapore, it may not truly reflect the actual situation for individuals who are residing in the tropics.
A New Technique for Jointly Optimizing Gate Sizing and Supply Voltage in Ultra-Low Energy Circuits

Mobile applications with battery lifetimes on the order of thousands of days have placed stringent energy requirements on circuits. In this paper, we propose a new energy optimization technique for ultra-low energy circuits operating in the sub threshold regime. Our technique uses simultaneous gate sizing and supply voltage scaling to reduce energy. We demonstrate the effectiveness of our technique on benchmark circuits and offer insight on the roles of the timing distribution and wire capacitance in determining the achievable energy reductions
Education and income

The effects of education on income are comprehensively surveyed in five papers. The topics of education and economic growth, returns to education, farmer education and farm efficiency, education and urban poverty, and education and income distribution in developing countries are examined. Among the specific subjects discussed are different approaches for assessing the contribution of education to income growth, the impact of increasing the stock of educated manpower in developing countries, private and social rates of return to different levels of education, and the effects of education upon labor force participation. The lack of data for microanalysis, particularly in the urban area, is highlighted and it is noted that advances in the economics of education will come from careful empirical work at the micro level through special purpose investigations, censuses, and household surveys.
New Paleocene skeletons and the relationship of plesiadapiforms to crown-clade primates

Plesiadapiforms are central to studies of the origin and evolution of primates and other euarchontan mammals (tree shrews and flying lemurs). We report results from a comprehensive cladistic analysis using cranial, postcranial, and dental evidence including data from recently discovered Paleocene plesiadapiform skeletons (Ignacius clarkforkensis sp. nov.; Dryomomys szalayi, gen. et sp. nov.), and the most plesiomorphic extant tree shrew, Ptilocercus lowii. Our results, based on the fossil record, unambiguously place plesiadapiforms with Euprimates and indicate that the divergence of Primates (sensu lato) from other euarchontans likely occurred before or just after the Cretaceous/Tertiary boundary (65 Mya), notably later than logistical model and molecular estimates. Anatomical features associated with specialized pedal grasping (including a nail on the hallux) and a petrosal bulla likely evolved in the common ancestor of Plesiadapoidea and Euprimates (Euprimateformes) by 62 Mya in either Asia or North America. Our results are consistent with those from recent molecular analyses that group Dermoptera with Scandentia. We find no evidence to support the hypothesis that any plesiadapiforms were mitten-gliders or closely related to Dermoptera.
Transient expression of Mnb / Dyrk 1 A couples cell cycle exit and neuronal differentiation of neuronal precursors in the vertebrate CNS by inducing p 27 KIP 1 expression and suppressing NOTCH signaling

The decision of a neural precursor to stop dividing and begin its terminal differentiation at the correct place, and at the right time, is a critical step in the generation of cell diversity in the nervous system. Here, we show that the Down’s syndrome candidate Mnb/Dyrk1A gene is transiently expressed in prospective neurons of vertebrate CNS neuroepithelia. The gain of function (GoF) of Mnb/Dyrk1A induced proliferation arrest. Conversely, its loss of function (LoF) caused over proliferation and cell death. We found that MNB/DYRK1A is both necessary and sufficient to up regulate at transcriptional level the expression of the cyclin-dependent kinase inhibitor p27KIP1 in the embryonic chick spinal cord and mouse telencephalon, supporting a regulatory role in cell cycle exit of vertebrate CNS neurons. All these actions required the MNB/DYRK1A kinase activity. We also observed that MNB/DYRK1A is coexpressed with the NOTCH ligand Delta-1 in single neuronal precursors. Furthermore, we found that MNB/DYRK1A suppressed NOTCH signaling, counteracted the pro-proliferative action of the NOTCH intracellular domain (NICD), stimulated Delta1 expression, and it was required for the neuronal differentiation induced by the decrease in NOTCH signaling. Nevertheless, although Mnb/Dyrk1A GoF led to extensive withdrawal of neuronal precursors from the cell cycle, it was insufficient to elicit their differentiation. Remarkably, a transient (ON/OFF) Mnb/Dyrk1A GoF efficiently induced neuronal differentiation. We propose that the transient expression of MNB/DYRK1A in neuronal precursors acts as a binary switch, coupling the end of proliferation and the initiation of neuronal differentiation by upregulating p27KIP1 expression and suppressing NOTCH signaling.
A Genomic Distance Based on MUM Indicates Discontinuity between Most Bacterial Species and Genera

ABSTRACT The fundamental unit of biological diversity is the species. However, a remarkable extent of intraspecies diversity in bacteria was discovered by genome sequencing, and it reveals the need to develop clear criteria to group strains within a species. Two main types of analyses used to quantify intraspecies variation at the genome level are the average nucleotide identity (ANI), which detects the DNA conservation of the core genome, and the DNA content, which calculates the proportion of DNA shared by two genomes. Both estimates are based on BLAST alignments for the definition of DNA sequences common to the genome pair. Interestingly, however, results using these methods on intraspecies pairs are not well correlated. This prompted us to develop a genomic-distance index taking into account both criteria of diversity, which are based on DNA maximal unique matches (MUM) shared by two genomes. The values, called MUMi, for MUM index, correlate better with the ANI than with the DNA content. Moreover, the MUMi groups strains in a way that is congruent with routinely used multilocus sequence-typing trees, as well as with ANI-based trees. We used the MUMi to determine the relatedness of all available genome pairs at the species and genus levels. Our analysis reveals a certain consistency in the current notion of bacterial species, in that the bulk of intraspecies and intragenus values are clearly separable. It also confirms that some species are much more diverse than most. As the MUMi is fast to calculate, it offers the possibility of measuring genome distances on the whole database of available genomes.
Non-soya legume-based therapeutic lifestyle change diet reduces inflammatory status in diabetic patients: a randomised cross-over clinical trial

The present randomised cross-over clinical trial investigated the effects of two intervention diets (non-soya legume-based therapeutic lifestyle change (TLC) diet v. isoenergetic legume-free TLC diet) on inflammatory biomarkers among type 2 diabetic patients. A group of thirty-one participants (twenty-four women and seven men; weight 74·5 (sd 7·0) kg; age 58·1 (sd 6·0) years) were randomly assigned to one of the two following intervention diets for 8 weeks: legume-free TLC diet or non-soya legume-based TLC diet. The latter diet was the same as the legume-free TLC diet, except that two servings of red meat were replaced with different types of cooked non-soya legumes such as lentils, chickpeas, peas and beans over a period of 3 d per week. The intervention period was followed by a washout period of 4 weeks, after which the groups followed the alternate treatment for 8 weeks. Concentrations of inflammatory markers were measured at baseline and after the intervention periods. Compared with the legume-free TLC diet, the non-soya legume-based TLC diet significantly decreased high-sensitivity C-reactive protein, IL-6 and TNF-α in overweight diabetic patients. The replacement of two servings of red meat by non-soya legumes in the isoenergetic TLC diet for a period of 3 d per week reduced the plasma concentrations of inflammatory markers among overweight diabetic patients, independent of weight change.
Fault Classification in P 2 P Semantic Mapping

An alternative to global ontology use in the semantic interoperability among heterogeneous information sources is the reaching of a consensus among distributed ontologies using local mapping and translation exchange. We investigate the construction of a flexible consensus system from distributed ontoliges in a peer-to-peer (P2P) network. We believe that such a flexible consensus system requires a semantic query processing with a fault-tolerance capability. Fault-tolerance capability refers to the ability to differentiate between permanent and non-permanent mapping faults. As first step in building such a flexible consensus system, this work provides a classification along the temporal dimension for the different types of faults that could arise in the context of semantic mapping in a P2P network.
The Relative Activation of Associations Modulates Interference between Elementally Trained Cues

Abstract Matute and Pineno (1998a) showed evidence of interference between elementally trained cues and suggested that this effect occurs when the interfering association is more strongly activated than the target association at the time of testing. The present experiments tested directly the role of the relative activation of the associations in the effect of interference between elementally trained cues. In three human experiments we manipulated the relative activation of the interfering and target associations in three different ways: (a) introducing a retention interval between training of the interfering association and the test trial (Experiment 1); (b) training the target and the interfering associations in a single phase, instead of training them in separate phases (Experiment 2); and (c) introducing, just before testing, a novel cue which, like the retention interval used in Experiment 1, had the purpose of separating the interfering trials from the test trial (Experiment 3). All three manipulations led to an enhancement of responding to the target association at testing, suggesting that they were effective in preventing the interfering association from being the most strongly activated one at the time of testing. Taken together, these results add further evidence on how the relative activation of associations modulates interference between elementally trained cues.
Automatic Document Classification Temporally Robust

p, li { white-space: pre-wrap; } The widespread use of the Internet has increased the amount of information being stored on and accessed through the Web. This information is frequently organized as textual documents and is the main target of search engines and other retrieval tools, which have to classify documents, among other tasks. Automatic Document Classification (ADC) associates documents to semantically meaningful categories, and usually employs a supervised learning strategy, where we first build a classification model using pre-classified documents, and then use the model to classify new documents. One major challenge in building classifiers is dealing with the temporal evolution of the characteristics of the documents and the classes to which they belong. However, most of the current techniques for ADC do not consider this evolution while building and using the models. Previous studies show that the performance of classifiers may be affected by three different temporal effects (class distribution, term distribution and class similarity). In this paper, we propose a new approach that aims to minimize the impact of temporal effects through a Temporal Adjustment Factor , in order to devise temporally robust classifiers based on traditional ones (Rocchio and KNN). Experimental results obtained using two real and large textual collections point to significant gains up to 11% of the temporal-aware versions of the classifiers over their traditional counterparts, and up to 4% compared to SVM (with a significantly lower runtime).
On an Iteration Method for Solving a Class of Nonlinear Matrix Equations

This paper treats a set of equations of the form $X+A^{\star}{\cal F}(X)A =Q$, where ${\cal F}$ maps positive definite matrices either into positive definite matrices or into negative definite matrices, and satisfies some monotonicity property. Here A is arbitrary and Q is a positive definite matrix. It is shown that under some conditions an iteration method converges to a positive definite solution. An estimate for the rate of convergence is given under additional conditions, and some numerical results are given. Special cases are considered, which cover also particular cases of the discrete algebraic Riccati equation.