Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Identification of Arabidopsis Coiled-Coil Proteins and Establishment of the ARABI-COIL Database1

Increasing evidence demonstrates the importance of long coiled-coil proteins for the spatial organization of cellular processes. Although several protein classes with long coiled-coil domains have been studied in animals and yeast, our knowledge about plant long coiled-coil proteins is very limited. The repeat nature of the coiled-coil sequence motif often prevents the simple identification of homologs of animal coiled-coil proteins by generic sequence similarity searches. As a consequence, counterparts of many animal proteins with long coiled-coil domains, like lamins, golgins, or microtubule organization center components, have not been identified yet in plants. Here, all Arabidopsis proteins predicted to contain long stretches of coiled-coil domains were identified by applying the algorithm MultiCoil to a genome-wide screen. A searchable protein database, ARABI-COIL (http://www.coiled-coil.org/arabidopsis), was established that integrates information on number, size, and position of predicted coiled-coil domains with subcellular localization signals, transmembrane domains, and available functional annotations. ARABI-COIL serves as a tool to sort and browse Arabidopsis long coiled-coil proteins to facilitate the identification and selection of candidate proteins of potential interest for specific research areas. Using the database, candidate proteins were identified for Arabidopsis membrane-bound, nuclear, and organellar long coiled-coil proteins.
IMPROVING ACCELEROMETER BASED ACTIVITY RECOGNITION

This paper presents the findings of a research on how to improve activity recognition from data captured with chest mounted accelerometer. Several methods were applied to achieve this purpose, including: simple smoothing technique, hidden Markov models (HMM), extraction of frequency domain features, principal component analysis (PCA) and dynamic time warping (DTW). The paper describes each of the methods and presents the achieved results of our research. The results indicate that these techniques, used separately or in combination, can increase recognition accuracy.
Characterizing IPv4 anycast adoption and deployment

This paper provides a comprehensive picture of IP-layer anycast adoption in the current Internet. We carry on multiple IPv4 anycast censuses, relying on latency measurement from PlanetLab. Next, we leverage our novel technique for anycast detection, enumeration, and geolocation [17] to quantify anycast adoption in the Internet. Our technique is scalable and, unlike previous efforts that are bound to exploiting DNS, is protocol-agnostic. Our results show that major Internet companies (including tier-1 ISPs, over-the-top operators, Cloud providers and equipment vendors) use anycast: we find that a broad range of TCP services are offered over anycast, the most popular of which include HTTP and HTTPS by anycast CDNs that serve websites from the top-100k Alexa list. Additionally, we complement our characterization of IPv4 anycast with a description of the challenges we faced to collect and analyze large-scale delay measurements, and the lessons learned.
Divergence Estimation for Multidimensional Densities Via $k$-Nearest-Neighbor Distances

A new universal estimator of divergence is presented for multidimensional continuous densities based on k-nearest-neighbor (k-NN) distances. Assuming independent and identically distributed (i.i.d.) samples, the new estimator is proved to be asymptotically unbiased and mean-square consistent. In experiments with high-dimensional data, the k-NN approach generally exhibits faster convergence than previous algorithms. It is also shown that the speed of convergence of the k-NN method can be further improved by an adaptive choice of k.
Role of the ATP-Binding Cassette Transporter Abcg2 in the Phenotype and Function of Cardiac Side Population Cells

Recently, the side population (SP) phenotype has been introduced as a reliable marker to identify subpopulations of cells with stem/progenitor cell properties in various tissues. We and others have identified SP cells from postmitotic tissues, including adult myocardium, in which they have been suggested to contribute to cellular regeneration following injury. SP cells are identified and characterized by a unique efflux of Hoechst 33342 dye. Abcg2 belongs to the ATP-binding cassette (ABC) transporter superfamily and constitutes the molecular basis for the dye efflux, hence the SP phenotype, in hematopoietic stem cells. Although Abcg2 is also expressed in cardiac SP (cSP) cells, its role in regulating the SP phenotype and function of cSP cells is unknown. Herein, we demonstrate that regulation of the SP phenotype in cSP cells occurs in a dynamic, age-dependent fashion, with Abcg2 as the molecular determinant of the cSP phenotype in the neonatal heart and another ABC transporter, Mdr1, as the main contributor to the SP phenotype in the adult heart. Using loss- and gain-of-function experiments, we find that Abcg2 tightly regulates cell fate and function. Adult cSP cells isolated from mice with genetic ablation of Abcg2 exhibit blunted proliferation capacity and augmented cell death. Conversely, overexpression of Abcg2 is sufficient to enhance cell proliferation, although with a limitation of cardiomyogenic differentiation. In summary, for the first time, we reveal a functional role for Abcg2 in modulating the proliferation, differentiation, and survival of adult cSP cells that goes beyond its distinct role in Hoechst dye efflux.
Resistance exercise reduces liver fat and its mediators in non-alcoholic fatty liver disease independent of weight loss

Background Lifestyle interventions focusing on weight loss remain the cornerstone of non-alcoholic fatty liver disease (NAFLD) management. Despite this, the weight losses achieved in research trials are not easily replicated in the clinic and there is an urgent need for therapies independent of weight loss. Aerobic exercise is not well sustained and the effectiveness of the better tolerated resistance exercise upon liver lipid and mediators of liver lipid has not been assessed. Methods Sedentary adults with clinically defined NAFLD were assigned to 8 weeks of resistance exercise (n=11) or continued normal treatment (n=8). Results 8 weeks of resistance exercise elicited a 13% relative reduction in liver lipid (14.0±9.1 vs 12.2±9.0; p<0.05). Lipid oxidation (submaximal RQ ∆ −0.020±0.010 vs −0.004±0.003; p<0.05), glucose control (−12% vs +12% change AUC; p<0.01) and homeostasis model assessment insulin resistance (5.9±5.9 to 4.6±4.6 vs 4.7±2.1 to 5.1±2.5; p<0.05) were all improved. Resistance exercise had no effect on body weight, visceral adipose tissue volume, or whole body fat mass (p>0.05). Conclusion This is the first study to demonstrate that resistance exercise specifically improves NAFLD independent of any change in body weight. These data demonstrate that resistance exercise may provide benefit for the management for non-alcoholic fatty liver, and the long-term impact of this now requires evaluation.
The word entropy of natural languages

The average uncertainty associated with words is an information-theoretic concept at the heart of quantitative and computational linguistics. The entropy has been established as a measure of this average uncertainty - also called average information content. We here use parallel texts of 21 languages to establish the number of tokens at which word entropies converge to stable values. These convergence points are then used to select texts from a massively parallel corpus, and to estimate word entropies across more than 1000 languages. Our results help to establish quantitative language comparisons, to understand the performance of multilingual translation systems, and to normalize semantic similarity measures.
Relevant Anatomic and Morphological Measurements of the Rat Spine: Considerations for Rodent Models of Human Spine Trauma

Study Design. Basic science study measuring anatomical features of the cervical and lumbar spine in rat with normalized comparison with the human. Objective. The goal of this study is to comprehensively compare the rat and human cervical and lumbar spines to investigate whether the rat is an appropriate model for spine biomechanics investigations. Summary of Background Data. Animal models have been used for a long time to investigate the effects of trauma, degenerative changes, and mechanical loading on the structure and function of the spine. Comparative studies have reported some mechanical properties and/or anatomical dimensions of the spine to be similar between various species. However, those studies are largely limited to the lumbar spine, and a comprehensive comparison of the rat and human spines is lacking. Methods. Spines were harvested from male Holtzman rats (n = 5) and were scanned using micro– computed tomography and digitally rendered in 3 dimensions to quantify the spinal bony anatomy, including the lateral width and anteroposterior depth of the vertebra, vertebral body, and spinal canal, as well as the vertebral body and intervertebral disc heights. Normalized measurements of the vertebra, vertebral body, and spinal canal of the rat were computed and compared with corresponding measurements from the literature for the human in the cervical and lumbar spinal regions. Results. The vertebral dimensions of the rat spine vary more between spinal levels than in humans. Rat vertebrae are more slender than human vertebrae, but the width-to-depth axial aspect ratios are very similar in both species in both the cervical and lumbar regions, especially for the spinal canal. Conclusion. The similar spinal morphology in the axial plane between rats and humans supports using the rat spine as an appropriate surrogate for modeling axial and shear loading of the human spine. Level of Evidence: N/A
A statistical path loss model for medical implant communication channels

Knowledge of the propagation media is a key step toward a successful transceiver design. Such information is typically gathered by conducting physical experiments, measuring and processing the corresponding data to obtain channel characteristics. In case of medical implants, this could be extremely difficult, if not impossible. In this paper, an immersive visualization environment is presented, which is used as a scientific instrument that gives us the ability to observe RF propagation from medical implants inside a human body. This virtual environment allows for more natural interaction between experts with different backgrounds, such as engineering and medical sciences. Here, we show how this platform has been used to determine a statistical path loss model for medical implant communication systems.
Plasma Amino Acids and Incident Type 2 Diabetes in Patients With Coronary Artery Disease

OBJECTIVE Altered plasma amino acid levels have been implicated as markers of risk for incident type 2 diabetes; however, amino acids are also related to established diabetes risk factors. Therefore, potential for confounding and the impact from competing risks require evaluation. RESEARCH DESIGN AND METHODS We prospectively followed 2,519 individuals with coronary artery disease but without diabetes. Mixed Gaussian modeling identified potential for confounding. Confounding, defined as a change in effect estimate (≥10%), was investigated by comparing amino acid–incident diabetes risk in a Cox model containing age and sex with that in models adjusted for potential confounders (BMI, estimated glomerular filtration rate, HDL cholesterol, triacylglycerol, C-reactive protein), which were further adjusted for plasma glucose, competing risks, and multiple comparisons (false discovery rate = 0.05, Benjamini-Hochberg method). Finally, component-wise likelihood-based boosting analysis including amino acids and confounders was performed and adjusted for competing risks in order to identify an optimal submodel for predicting incident diabetes. RESULTS The mean age of the source population was 61.9 years; 72% were men. During a median follow-up of 10.3 years, 267 incident cases of diabetes were identified. In age- and sex-adjusted models, several amino acids, including the branched-chain amino acids, significantly predicted incident diabetes. Adjustment for confounders, however, attenuated associations. Further adjustment for glucose and multiple comparisons rendered only arginine significant (hazard ratio/1 SD 1.21 [95% CI 1.07–1.37]). The optimal submodel included arginine and asparagine. CONCLUSIONS Adjustment for relevant clinical factors attenuated the amino acid–incident diabetes risk. Although these findings do not preclude the potential pathogenic role of other amino acids, they suggest that plasma arginine is independently associated with incident diabetes. Both arginine and asparagine were identified in an optimal model for predicting new-onset type 2 diabetes.
TREC 2002 Video Track Experiments at MediaTeam Oulu and VTT

DW 0HGLD7HDP 2XOX DQG 977 0LND 5DXWLDLQHQ -DQL 3HQWWLOl 'PLWUL 9RURELHY . DL 1RSRQHQ 3HUWWL 9l\U\QHQ 0DWWL +RVLR (VD 0DWLQPLNNR 6DWX 0DUMD 0lNHOl -RKDQQHV 3HOWROD 7LPR 2MDOD DQG 7DSLR 6HSSlQHQ † MediaTeam Oulu P.O.BOX 4500, FIN-90014 University of Oulu, Finland {firstname.lastname@ee.oulu.fi} ‡ VTT Technical Research Centre of Finland P.O. Box 1100, Kaitoväylä 1, FIN-90571 Oulu, Finland {firstname.lastname@vtt.fi)
14 and younger: the sexual behavior of young adolescents. Summary.

The full report on which this summary is based contains seven papers based on six different data sets — three national and three local ones. These data were collected for different purposes in different years and places (school home) and using different interview techniques (self- and interviewer-administered). The surveys also used different methods of gathering data on youth aged 12-14 surveying 12- 13- and 14-year-olds at the same time; surveying a group of 12-year-olds and then following them over time as they turned 13 and 14; and surveying older teens about their experiences when age 14 and younger. These differences are important and care must be taken in pooling results or making comparisons across different data sets. For example a survey asking teens 15 and older about earlier experiences can in theory capture quite complete data on behavior occurring at ages 14 and younger. But surveys where youth are age 12-14 at the time of interview will necessarily miss some behavior that occurs in the 14th year of life but after the time of the interview unless a “life table” analytic approach is used as is the case for a few specific variables in the papers based on national data sets. These technical issues are taken up in detail in the individual papers. Nonetheless it is striking that on some of the most basic markers of sexual activity there is a high degree of uniformity — especially among the nationally representative data sets — and a surprisingly consistent picture emerges of sexual relationships and activity among very young teens. (excerpt)
Cluster Based Semantic Data Aggregation in VANETs

Recently, we are witnessing increased interest in the research of Vehicular Ad-hoc Networks (VANETs). Due to the peculiar characteristics of VANETs, such as high speed, the unstable communication link, and network partitioning, information transfer becomes inevitably challenging. The main communication challenges in vehicle to vehicle communication is scalability, predictability and reliability. With increasing number of vehicles in highway congestion scenarios, the congestion application need to disseminate large amount of information over multiple hops to the control center. This challenge can be solved by reducing the data load through clustering and data aggregation. In this paper, we propose cluster based semantic data aggregation (CBSDA) protocol that divide the road into different segments based on the cluster-ID and aggregate the data in each cluster. The aggregation scheme is a lossy aggregation with maximum precision. CBSDA scheme stores the data using a data structure that consists of super cluster, cluster and cluster member (CM) nodes. CBSDA is proposed to adaptively adjust the number of super cluster nodes. Moreover, the CBSDA scheme consists of weighted deviation scheme that decides which data to be fused for aggregation. Additionally, the aggregation level is controlled based on the density of vehicles and channel busy ratio (CBR). Simulation results show that the CBSDA using weighted deviation decision scheme is able to quickly reduce the channel congestion and improve the data precision even in congested traffic scenarios.
Automated generated collision-free time optimized robot movements in industrial environments based on rounding

This paper presents a new approach to optimized notion planning for industrial robot arms with six degrees of freedom in an online given 3D environment. The method is based on the A*-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly discrete configuration space. Collisions are detected in the Cartesian workspace by hierarchical distance computation based on the given CAD model. The collision-free result path is then optimized in execution time using rounding, a common command of every standard robot controller in the industry.
Constraint selection for topic-based MDI adaptation of language models

This paper presents an unsupervised topic-based language model adaptation method which specializes the standard minimum information discrimination approach by identifying and combining topic-specific features. By acquiring a topic terminology from a thematically coherent corpus, language model adaptation is restrained to the sole probability re-estimation of n-grams ending with some topic-specific words, keeping other probabilities untouched. Experiments are carried out on a large set of spoken documents about various topics. Results show significant perplexity and recognition improvements which outperform results of classical adaptation techniques. Index Terms: language model adaptation, topic terminology, minimum discrimination information, speech recognition
EFFECT OF SOME POWER SPECTRAL DENSITY ESTIMATION METHODS ON AUTOMATIC SLEEP STAGE SCORING USING ARTIFICIAL NEURAL NETWORKS

Sleep staging has an important role in diagnosing sleep disorders. It is usually done by a sleep expert through examining sleep Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG) signals of the patients and determining the stages of sleep in different time sections named as epochs. Manual sleep staging is preferred among the sleep experts but because it is rather tiring and time consuming task, automatic sleep stage scoring systems get popularity. In this study, we obtained EEG, EMG and EOG signals of four healthy people at sleep laboratory of Meram Medicine Faculty of Necmettin Erbakan University to use them in sleep staging and extracted 20 different features by using some power spectral density estimation methods which are: Fast Fourier Transform (FFT), Welch and Autoregressive (AR). We evaluated the effects of these methods on sleep staging through using ANN classifier. Comparison between these methods was done on each individual whose data were utilized separately from others. According to the results, the maximum test classification accuracy was reported as 79.72% by using of FFT method for subject1. Also, mean of test classification accuracies for all of subjects were obtained as 74.14%, 71,58 and 70.34% with use of FFT, Welch and AR, respectively.
Application of Carbon-Microsphere-Modified Electrodes for Electrochemistry of Hemoglobin and Electrocatalytic Sensing of Trichloroacetic Acid

By using the hydrothermal method, carbon microspheres (CMS) were fabricated and used for electrode modification. The characteristics of CMS were investigated using various techniques. The biocompatible sensing platform was built by immobilizing hemoglobin (Hb) on the micrometer-sized CMS-modified electrode with a layer of chitosan membrane. On the cyclic voltammogram, a couple of quasi-reversible cathodic and anodic peaks appeared, showing that direct electrochemistry of Hb with the working electrode was achieved. The catalytic reduction peak currents of the bioelectrode to trichloroacetic acid was established in the linear range of 2.0~70.0 mmol·L−1 accompanied by a detection limit of 0.30 mmol·L−1 (3σ). The modified electrode displayed favorable sensitivity, good reproducibility and stability, which suggests that CMS is promising for fabricating third-generation bioelectrochemical sensors.
Determination of the Static Voltage Stability Region of Distribution Systems with the Presence of Wind Power Generation

This paper presents a method to find the steady-state voltage stability region for each bus of a distribution power system, considering the presence of wind power generation. The maximum permissible load of each bus is calculated, so that it can operate with the voltage within the limits allowed by the power system utilities. The voltage stability region boundary is determined by plotting the P-Q curve of each load bus. All the combination of the P and Q values in this region is a stable and secure operating point. The methodology was applied on a simple two-bus power system and the results are very close to those obtained by using the analytical solution. The method is computationally efficient and it is suitable for online monitoring load bus bars of transmission and distribution power systems.
Phonetic labeling and segmentation of mixed-lingual prosody databases

An automatic system for segmenting speech signals used for the training of statistical prosody models is presented. Starting from a canonical transcription, the system simultaneously delivers an accurate phonetic segmentation and the matched phonetic transcription indicating pronunciation variants. Although the system is HMM-based, it uses only the speech signals of the prosody database which typically consists of a few hundred sentences with some 30 minutes total duration. Initial phone HMMs are generated with flat-start training using the canonical transcriptions of the sentences. Then iterative Viterbi search for best-matching pronunciation variants and HMM retraining is applied until convergence is attained.