Miracle-dz/UniFAR-FTUs huggingface dataset:
A Co-Association Network Analysis of the Genetic Determination of Pig Conformation, Growth and Fatness

Background Several QTLs have been identified for major economically relevant traits in livestock, such as growth and meat quality, revealing the complex genetic architecture of these traits. The use of network approaches considering the interactions of multiple molecules and traits provides useful insights into the molecular underpinnings of complex traits. Here, a network based methodology, named Association Weight Matrix, was applied to study gene interactions and pathways affecting pig conformation, growth and fatness traits. Results The co-association network analysis underpinned three transcription factors, PPARγ, ELF1, and PRDM16 involved in mesoderm tissue differentiation. Fifty-four genes in the network belonged to growth-related ontologies and 46 of them were common with a similar study for growth in cattle supporting our results. The functional analysis uncovered the lipid metabolism and the corticotrophin and gonadotrophin release hormone pathways among the most important pathways influencing these traits. Our results suggest that the genes and pathways here identified are important determining either the total body weight of the animal and the fat content. For instance, a switch in the mesoderm tissue differentiation may determinate the age-related preferred pathways being in the puberty stage those related with the miogenic and osteogenic lineages; on the contrary, in the maturity stage cells may be more prone to the adipocyte fate. Hence, our results demonstrate that an integrative genomic co-association analysis is a powerful approach for identifying new connections and interactions among genes. Conclusions This work provides insights about pathways and key regulators which may be important determining the animal growth, conformation and body proportions and fatness traits. Molecular information concerning genes and pathways here described may be crucial for the improvement of genetic breeding programs applied to pork meat production.
An Information Extraction Method for Multiple Data Sources

a method of information extraction for multiple data sources or for various kinds of datasets like Internet web pages. Generally, because many different writing styles or vo- cabularies exist among different kinds of data, the accuracy of information extraction using various kinds of datasets is not better than that using a single kind of data. Our method divides the data by clustering and learns extraction rules to increase accuracy even if we use various kinds of datasets. In our ex- periment, we applied our method to a NTCIR8 Technical Trend Map Creation subtask that uses two kinds of data, patents and technical papers, and obtained the better precision than normal information extraction method.
Elsevier Editorial System(tm) for Neurobiology of Aging Manuscript Draft Neurobiology of Aging Focal Posterior Cingulate Atrophy in Incipient Alzheimer's Disease

Severe posterior cingulate cortex hypometabolism is a feature of incipient, sporadic Alzheimer's disease (AD). The aim was to test the hypothesis that this region is focally atrophic in very early disease by studying AD patients at the mild cognitive impairment (MCI) stage, and, if so, to determine whether the amount of atrophy was comparable to that of the hippocampus. Twenty-four patients meeting criteria for amnestic MCI, who all subsequently progressed to fulfil AD criteria, and 28 age-matched controls, were imaged with volumetric MRI. Four regions of interest were manually traced in each hemisphere: two posterior cingulate regions (BA 23 and BA 29/30), the hippocampus (as a positive control) and the anterior cingulate (as a negative control). BA 23 and BA 29/30 were both significantly atrophic and this atrophy was comparable to that found in the hippocampus, in the absence of anterior cingulate cortex atrophy. Contrary to previous reports, there was no evidence that posterior cingulate atrophy is specifically associated with early-onset AD. The results indicate that posterior cingulate cortex atrophy is present from the earliest clinical stage of sporadic AD and that this region is as vulnerable to neurodegeneration as the hippocampus.
Small Changes in Climate Can Profoundly Alter the Dynamics and Ecosystem Services of Tropical Crater Lakes

African tropical lakes provide vital ecosystem services including food and water to some of the fastest growing human populations, yet they are among the most understudied ecosystems in the world. The consequences of climate change and other stressors on the tropical lakes of Africa have been informed by long-term analyses, but these studies have largely focused on the massive Great Rift Valley lakes. Our objective was to evaluate how recent climate change has altered the functioning and services of smaller tropical lakes, which are far more abundant on the landscape. Based on a paired analysis of 20 years of high-resolution water column data and a paleolimnological record from a small crater lake in western Uganda, we present evidence that even a modest warming of the air (∼0.9°C increase over 20 years) and changes in the timing and intensity of rainfall can have significant consequences on the dynamics of this common tropical lake type. For example, we observed a significant nonlinear increase (R2adj = 0.23, e.d.f. = 7, p<0.0001) in thermal stability over the past 20 years. This resulted in the expansion of anoxic waters and consequent deterioration of fish habitat and appears to have abated primary production; processes that may impair ecosystem services for a vulnerable human population. This study on a system representative of small tropical crater lakes highlights the far-reaching effects of global climatic change on tropical waters. Increased research efforts into tropical aquatic ecosystem health and the development of sound management practices are necessary in order to strengthen adaptive capabilities in tropical regions.
Map building with ultrasonic sensors of indoor environments using neural networks

Map building and position estimation are basic tasks in mobile robot navigation with path planning. A method to generate a global map of the vehicle work environment using ultrasonic sensors is developed in this paper. Depending on the physical properties of the walls that form the room where the robot is navigating, sonar sensors show different behaviours. A neural network is utilized to interpret the range readings of ultrasonic sensors in the different environments. A local map composed of squared cells is formed through the neural network that gives the occupancy probabilities for each cell. Finally, a global map is built achieving integration of different views of the environment using Bayes' rule. Results of the method implementation in the construction in a specular environment as well as in rough wall environments are shown in this paper.
Design and Development of Heart Rate Monitoring Device with Reduction of Motion Artefact using 3-axis Accelerometer

There are various non-invasive heart rate monitoring devices available for monitoring & diagnosis of the patient. It has been observed that the final values of the device are altered by the motion. This paper overcome the problems related with variations in the health parameters due to the motion of the object by developing a viable device to catch human critical physiological parameters like heart rate. The configuration of this heart rate checking device was focused around an automatic noise cancellation system utilizing 3-axis MEMS accelerometer to recover signals ruined by body development which is the principle source of motion artefacts.
Effects of dexamethasone on the infectivity of Trypanosoma vivax Y486 and the haematological changes in Nigerian domestic chickens (Gallus gallus domesticus)

ADEDAPO, A. A. , A. B. SABA, O. A. DINA, G. M. A. OLADEJO: Effects of dexamethasone on the infectivity of Trypanosoma vivax Y486 and the haematological changes in Nigerian domestic chickens (Gallus gallus domesticus). Vet. arhiv 74, 371- 381, 2004. ABSTRACT The study was carried out to investigate how the infectivity of Trypanosoma vivax Y486 could be affected by steroid administration to Nigerian domestic chickens and to observe the haematological and serum biochemistry changes in these chickens infected with Trypanosoma vivax Y486. Results showed that T. vivax Y486 does affect the haematological parameters of Nigerian domestic chickens (Gallus gallus domesticus) as there may be development of anaemia as in large animals. However, there was no patent parasitaemia. In addition, steroid administration when applied at high doses did affect the haematological parameters of the local chickens. It thus showed that serial passaging of T. vivax Y486 can result in infectivity of the Nigerian domestic chickens with trypanosomosis.
Impact of search results on user queries

In this paper, we experimentally study how web searchers select the keywords to describe their information needs and specifically we investigate whether query keyword selections are influenced by the results the users reviewed for a previous search. For our study, we determine two types of searches: (i) those in which users define their queries without any external influence and which we call tightly-focused and (ii) those in which users define their queries under some external influence and which we call loosely-focused. Based on the analysis of the user querying trends and web visits on the query results, we propose a model that tries to capture the results' influence on the specification of the subsequent user queries. The application of our model on a search trace of 19,250 queries issued to Google by 18 users over a period of two months reveals that in overall search results influence the specification of 12.79% of the web queries.
Disambiguation of medline abstracts using topic models

Topic models are an established technique for generating information about the subjects discussed in collections of documents. Latent Dirichlet Allocation (LDA) is a widely applied topic model. The topic models generated by LDA consist of sets of terms associated with each topic and these are used to provide context for a Word Sense Disambiguation (WSD) system. It is found that using this context leads to a statistically significant improvement in the performance of a graph-based WSD system when applied to a standard evaluation resource.
Collaborative Filtering using Weighted BiPartite Graph Projection

We implement a personal recommendation system on the Yelp Dataset Challenge dataset using the same novel network-based-inference collaborative filtering algorithm that was proposed by [2] and originally created by [1]. By representing our Yelp dataset using a weighted bipartite graph where edges from user to business are weighted by rating, we pose the recommendation problem as graph projection. More specifically we follow a network based resource allocation process to produce similarity measures (which can both be thought of as weights in a bipartite graph projection) between every pair of users and every pair of businesses, which are then used to produce predicted ratings and recommendations. We evaluate the performance of this system with respect to popular competing ways of creating recommendation systems using different non-network based approaches to collaborative filtering. We then attempt to experiment and improve upon the algorithm by relying on properties of the Yelp dataset and then evaluate the results of these experiments.
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic

We study the problem of learning probabilistic models for permutations, where the order between highly ranked items in the observed permutations is more reliable (i.e., consistent in different rankings) than the order between lower ranked items, a typical phenomena observed in many applications such as web search results and product ranking. We introduce and study a variant of the Mallows model where the distribution is a function of the widely used Average-Precision (AP) Correlation statistic, instead of the standard Kendall’s tau distance. We present a generative model for constructing samples from this distribution and prove useful properties of that distribution. Using these properties we develop an efficient algorithm that provably computes an asymptotically unbiased estimate of the center permutation, and a faster algorithm that learns with high probability the hidden central permutation for a wide range of the parameters of the model. We complement our theoretical analysis with extensive experiments showing that unsupervised methods based on our model can precisely identify ground-truth clusters of rankings in real-world data. In particular, when compared to the Kendall’s tau based methods, our methods are less affected by noise in low-rank items.
An unsupervised object-level image segmentation method based on foreground and background priors

Conventional unsupervised image segmentation methods return many superpixels or object parts and thus tend to over-segmentation. In this paper, we present a novel post-processing approach for unsupervised object-level image segmentation (UnOLIS). Starting with the results of any conventional unsupervised segmentation method, we first combine a global region-based saliency and a robust background feature to cluster the pre-segmented regions into foreground and background. We then design a region growing process, encoded with several object priors, to generate a high quality foreground object segmentation. In parallel, we group the background regions into different stuffs by clustering. We test our method on the Berkeley Segmentation Dataset (BSDS500). Our approach significantly improves conventional unsupervised segmentation methods and achieves almost comparable results as the state-of-the-art supervised image segmentation methods.
Attitudes, stress, and satisfaction of staff who care for residents with dementia.

PURPOSE Considering the increasing proportion of residents in long-term care who have dementia, and the important influence that direct care providers have on resident quality of life, this study explores the dementia-related attitudes of residential care/assisted living (RC/AL) and nursing home staff, as well as their work stress and satisfaction. DESIGN AND METHODS Data were derived from interviews with 154 direct care providers from 31 RC/AL facilities and 10 nursing homes who participated in the Collaborative Studies of Long-Term Care. RESULTS Stress was more often reported by care providers who had been working for 1 to 2 years (compared with longer); in addition, those who had been working for 1 to 2 years were more likely to espouse hopeful or person-centered attitudes than those who had been working for a longer period of time. Also, a person-centered attitude related to satisfaction, and perceived competence in providing dementia care was consistently associated with dementia-sensitive attitudes and job satisfaction. IMPLICATIONS Attending to the welfare and ongoing training of workers who have demonstrated job commitment may lessen their tendency to become jaded over time or seek job opportunities elsewhere. Further, the attitudes the staff hold related to dementia and the training they receive to provide dementia care are important for their own well-being.
A Novel CMKLR1 Small Molecule Antagonist Suppresses CNS Autoimmune Inflammatory Disease

Therapies that target leukocyte trafficking pathways can reduce disease activity and improve clinical outcomes in multiple sclerosis (MS). Experimental autoimmune encephalomyelitis (EAE) is a widely studied animal model that shares many clinical and histological features with MS. Chemokine-like receptor-1 (CMKLR1) is a chemoattractant receptor that is expressed by key effector cells in EAE and MS, including macrophages, subsets of dendritic cells, natural killer cells and microglia. We previously showed that CMKLR1-deficient (CMKLR1 KO) mice develop less severe clinical and histological EAE than wild-type mice. In this study, we sought to identify CMKLR1 inhibitors that would pharmaceutically recapitulate the CMKLR1 KO phenotype in EAE. We identified 2-(α-naphthoyl) ethyltrimethylammonium iodide (α-NETA) as a CMKLR1 small molecule antagonist that inhibits chemerin-stimulated β-arrestin2 association with CMKLR1, as well as chemerin-triggered CMKLR1+ cell migration. α-NETA significantly delayed the onset of EAE induced in C57BL/6 mice by both active immunization with myelin oligodendrocyte glycoprotein peptide 35-55 and by adoptive transfer of encephalitogenic T cells. In addition, α-NETA treatment significantly reduced mononuclear cell infiltrates within the CNS. This study provides additional proof-of-concept data that targeting CMKLR1:chemerin interactions may be beneficial in preventing or treating MS.
Device-to-device mobile data offloading for music streaming

Device-to-device communication (also referred to as opportunistic networking) is considered a feasible means for offloading mobile data traffic. Due to the sporadic nature of contact opportunities, applications in the domain of device-to-device communication are assumed to be delay-tolerant, with content delivery deadlines being in the order of hours. However, predictions suggest that by 2020 more than 75% of the traffic volumes at mobile operators will be generated by multimedia contents which is often seen as data served in real-time. In this paper we explore how the concept of opportunistic networking can be used for dissemination of real-time streaming contents for users in urban environments without degrading quality of experience. We first present a general framework for offloading multimedia data that is organized in terms of playlists, and we then investigate the performance of the framework in realistic urban environments using the music streaming service Spotify as a use-case. Our results show that it is feasible to use opportunistic device-to-device communication in the context of music streaming. We demonstrate that the system performance is insensitive to a number of parameters such as playlist length distribution, and initial content availability distribution, however it exhibits sensitivity towards the amount of requested data and the node density.
A new behavioural model for performance evaluation of common mode chokes

A behavioural model for performance evaluation of a common mode choke (CMC) is proposed: the topology and methods used to model the different properties of the CMC are presented. It combines an accurate model of the complex permeability, of the saturation, of leakage inductances and of parasitic capacitances. Inputs needed from the designer are measured values of currents, voltages and impedance of the actual system, and parameters available in literature and/or from manufacturers for the modelled CMC. The behavioural model is essential in simulation of EMI effects.
Hierarchical Approach for Multiscale Support Vector Regression

Support vector regression (SVR) is based on a linear combination of displaced replicas of the same function, called a kernel. When the function to be approximated is nonstationary, the single kernel approach may be ineffective, as it is not able to follow the variations in the frequency content in the different regions of the input space. The hierarchical support vector regression (HSVR) model presented here aims to provide a good solution also in these cases. HSVR consists of a set of hierarchical layers, each containing a standard SVR with Gaussian kernel at a given scale. Decreasing the scale layer by layer, details are incorporated inside the regression function. HSVR has been widely applied to noisy synthetic and real datasets and it has shown the ability in denoising the original data, obtaining an effective multiscale reconstruction of better quality than that obtained by standard SVR. Results also compare favorably with multikernel approaches. Furthermore, tuning the SVR configuration parameters is strongly simplified in the HSVR model.
Case Study: Distance-Based Image Retrieval in the MoBIoS DBMS

Similarity search leveraging distance-based index structures is increasingly being used for complex data types. It has been shown that for high dimensional uniform vectors with similarity norms, any clustering and partitioning index method is outperformed by sequential scan. However, intrinsic clustering of real data usually leads to low intrinsic dimensionality. MoBIoS (the molecular biological information system) is a next generation database management system comprising distance-based indices. Owing to its generality, we have built, evaluated and optimized a prototype of a distance-based image retrieval system. We show that under a metric distance function, image data is intrinsically low dimensional. We investigate the performance of three distance-based index structures (M-tree, RBT-index, and MVP-index), and, to optimize the construction of MVP-indexes, develop new heuristics that seek centers as pivots and partition the data according to its intrinsic clustering. Last, we show the SQL extension to embody distance-based image retrieval in MoBIoS
Assessing GARCH model's predictive ability from Traders' Point of View ∗ (Preliminary Version)

This paper shows that, even if volatility is accurately predicted by correctly specified GARCH models, however such predictions are not very useful for traders when the conditional volatility does not vary "enough" over time, being therefore quite close to the unconditional one. It is shown that a low R 2 in the Mincer-Zarnowitz regression implies flat (although correctly predicted) volatility, and therefore leads to extremely poor performances of GARCH based investment strategies. Conversely, a high R 2
Nitrous Oxide Sedation and Bispectral Index

Objectives To determine whether bispectral analysis (BIS) changes during nitrous oxide (N2O) sedation in anxious children undergoing extraction of primary teeth. Methods In this prospective study 45, ASA physical status I children, aged between 7 to 12 years and scheduled for primary teeth extraction under N2O/O2 sedation are included. At baseline (T0) and during the sedation procedure (T1-6); BIS levels, Ramsay Sedation Scores (RSS), oxygen saturation (Sp02), and heart rate (HR) were recorded at one-minute intervals. Forty percent N2O in O2 was given by a nasal hood, and N2O concentration was enhanced to 60% in a two-minute period. Paired measurements of BIS levels with Observer’s Assessment of Alertness and Sedation (OAA/S) scores were obtained during sedation procedure. Results Since 5 patients refused application of the nasal hood, a total 40 of the original 45 subjects completed the study. Mean age and weight of the children were 9.5 ± 1.4 years and 23.7 ± 9.7 kg, respectively. Nitrous oxide inhalation produced no changes in BIS levels despite a sedation level in OAA/S scores were observed at 40–60% N2O concentrations. Conclusions BIS values do not change during N2O/O2 sedation and the BIS monitor is not appropriate to evaluate the depth of sedation provided by N2O/O2 during primary teeth extraction in children.