Miracle-dz/UniFAR-FTUs huggingface dataset:
Common polymorphisms in 5‐lipoxygenase and 12‐lipoxygenase genes and the risk of incident, sporadic colorectal adenoma

Lipoxygenases (LOX) are major enzymes that metabolize arachidonic acid to hydroxyl‐eicosatetraenoic acids and leukotrienes, which have been implicated in inflammation and colorectal cancer risk. Polymorphisms in LOX genes may influence their function and/or expression and, thus, may modify the risk for colorectal adenoma. The authors investigated the associations of 3 polymorphisms (2 in 5‐LOX, −1708 guanine→adenine and 21 cytosine→thymine; and 1 in 12‐LOX, arginine 261 glutamine [Arg261Gln]) in LOX genes with the risk of colorectal adenoma and also explored possible interactions of these polymorphisms with several inflammation‐pathway or arachidonic acid metabolism‐pathway related factors with the risk of colorectal adenoma.
The transcriptional coactivator PGC-1α mediates exercise-induced angiogenesis in skeletal muscle

Peripheral arterial disease (PAD) affects 5 million people in the US and is the primary cause of limb amputations. Exercise remains the single best intervention for PAD, in part thought to be mediated by increases in capillary density. How exercise triggers angiogenesis is not known. PPARγ coactivator (PGC)-1α is a potent transcriptional co-activator that regulates oxidative metabolism in a variety of tissues. We show here that PGC-1α mediates exercise-induced angiogenesis. Voluntary exercise induced robust angiogenesis in mouse skeletal muscle. Mice lacking PGC-1α in skeletal muscle failed to increase capillary density in response to exercise. Exercise strongly induced expression of PGC-1α from an alternate promoter. The induction of PGC-1α depended on β-adrenergic signaling. β-adrenergic stimulation also induced a broad program of angiogenic factors, including vascular endothelial growth factor (VEGF). This induction required PGC-1α. The orphan nuclear receptor ERRα mediated the induction of VEGF by PGC-1α, and mice lacking ERRα also failed to increase vascular density after exercise. These data demonstrate that β-adrenergic stimulation of a PGC-1α/ERRα/VEGF axis mediates exercise-induced angiogenesis in skeletal muscle.
Multidrug-resistant tuberculosis: Treatment outcome in Denmark, 1992–2007

Abstract A retrospective nationwide study including all culture-verified multidrug-resistant (MDR) tuberculosis (TB) cases was performed in Denmark. The aim was to examine the long-term treatment outcome of MDR-TB, to assess if MDR-TB transmission occurs, and to evaluate a rapid mutation analysis detecting rifampin and isoniazid resistance in this cohort. Clinical data were obtained from patient records. A restriction fragment length polymorphism genotype database of all TB cases was compared for identical strains indicating active transmission. Twenty-nine cases of MDR-TB were identified and the incidence was low at 0.5%. Acquired MDR-TB and active transmission was rare. Mutations in rifampin (rpoB) and isoniazid (katG, inhA) genes correctly determined resistance in 100% and 82% of all isolates tested, respectively. Initial treatment success was 89% for 27 MDR-TB patients with available outcome data. Initially 3 patients defaulted; no deaths were reported. Including successfully re-treated default patients and censoring patients who spent <2 y in the cohort, long-term treatment success was achieved for all 26 patients (mean follow-up 8.9 y). MDR-TB has a good prognosis in the high-income, low TB burden country of Denmark. Continued surveillance and rapid detection of resistance mutations directly in smear-positive patients may improve the standard of MDR-TB care.
Fine-grained vehicle recognition using hierarchical fine-tuning strategy for Urban Surveillance Videos

The Fine-grained Vehicle recognition is easily affected by small visual changes. The existing recognition methods have less robustness to these conditions (such as illumination, weather changes, etc.) and the accuracy of vehicle recognition in complex environments cannot achieve a satisfying result. In this paper, a high-accuracy fine-grained vehicle recognition method using Convolutional Neural Network for urban surveillance videos is proposed. Differing from the conventional CNN based methods, which usually obtain a single classification model, the proposed method combines Pre-training and hierarchical fine-tuning to obtain different classification model that can adapt to the change of illumination conditions. In the recognition phase, the input image is evaluated firstly using the proposed image quality assessment method. Then, the classification model is selected adaptively according to the results of quality evaluation and used for recognition. To test our method, we use a publicly vehicle recognition dataset for Urban Surveillance Videos provide by Yang. Experimental results show that the accuracy of the proposed method is up to 98.89%, which is 0.5% higher than Yang's method.
Smartwatch-aided handheld augmented reality

We demonstrate a novel method for interaction of humans with real objects in their surrounding combining Visual Search and Augmented Reality (AR). This method is based on utilizing a smartwatch tethered to a smartphone, and it is designed to provide a more user-friendly experience compared to approaches based only on a handheld device, such as a smartphone or a tablet computer. The smartwatch has a built-in camera, which enables scanning objects without the need to take the smartphone out of the pocket. An image captured by the watch is sent wirelessly to the phone that performs Visual Search and subsequently informs the smartwatch whether digital information related to the object is available or not. As described in our ISMAR 2014 poster [6], we distinguish between three cases. If no information is available or the object recognition failed, the user is notified accordingly. If there is digital information available that can be presented using the smartwatch display and/or audio output, it is presented there. The third case is that the recognized object has digital information related to it, which would be beneficial to see in an Augmented Reality view spatially registered with the object in real-time. Then the smartwatch informs the user that this option exists and encourages using the smartphone to experience the Augmented Reality view. Thereby, the user only needs to take the phone out of the pocket in case Augmented Reality content is available, and when the content is of interest for the user.
Resting heart rate and risk of type 2 diabetes in women.

BACKGROUND Resting heart rate has been shown to predict risk of cardiovascular disease; its association with diabetes remains unclear, particularly in non-Western populations. METHODS We evaluated the association between resting heart rate and risk of type 2 diabetes in the Shanghai Women's Health Study, a population-based prospective cohort study. The analysis included 47 571 Chinese women with no prior history of diabetes, cancer, cardiovascular disease or thyroid dysfunction at the time when resting heart rate was measured. Incident diabetes was ascertained through biennial in-person interviews. RESULTS During a mean follow-up of 4.9 years, 849 women developed type 2 diabetes. For heart rate categories of < or =68, 69-72, 73-76, 77-80 and >80 beats/min, the incidence rates of diabetes per 1000 person-years were 2.91, 3.31, 3.71, 4.16 and 5.34, respectively. The multivariable-adjusted hazard ratios (HRs) [95% confidence intervals (CIs)] for diabetes across increasing heart rate categories were 1, 1.21 (0.99-1.47), 1.30 (1.05-1.62), 1.37 (1.12-1.69) and 1.60 (1.28-2.00), respectively. Further analyses of the joint effects of heart rate with body mass index (BMI), waist-hip ratio (WHR) and blood pressure (BP) showed increased risk of diabetes with increasing heart rate in all categories of BMI, WHR or BP. The combinations of the highest heart rate category with highest BMI, WHR or BP category were associated with the highest HRs, ranging from 4.81 to 6.34. CONCLUSIONS A high resting heart rate is independently associated with an increased risk of type 2 diabetes in women. The combinations of high heart rate with high BMI, WHR or BP level are associated with a substantially increased risk.
Development of a flexible public lighting system

This paper presents the development of a flexible public lighting system which aims to monitor and control electronic ballasts. The system consists of dimmable electronic ballast for high pressure sodium lamps (HPS) with power meter, and a control board with 2.4 GHz digital radios based on the IEEE 802.15. 4 (ZigBee) protocol, and data transmission module using SMS. The system has bidirectional communication between the central control and the master units using SMS messaging. Further, the master units send and receive information to and from the slave units via ZigBee modules and coordinates with the central controller the operation of each lamp in their region. This system can measure and report power and energy consumption to a central controller, and to dim, turn on and turn off the lamps individually, controlling the power consumption of the illumination system.
Partitioned-SLM Scheme with Low Complexity for PAPR Reduction of OFDM Signals

In this paper, we propose P-SLM (partitioned-selective mapping) scheme with low complexity for PAPR (peak-to-average power ratio) reduction of OFDM (orthogonal frequency division multiplexing) signals. In the proposed scheme, a symbol sequence in frequency domain is partitioned into several sub-blocks, and each sub-block is multiplied by different phase sequences whose length and number are shorter and smaller than those used in the conventional SLM. Then, among statistically independent sequences in time domain generated after the IFFT (inverse fast Fourier transform) for the phase rotated sub-blocks, the sub-block combination with the lowest PAPR is selected and transmitted. Simulation results reveal that the proposed P-SLM scheme can remarkably reduce the number of IFFT calculation and multiplication than the conventional SLM without loss of PAPR reduction performance
Research on fusion method for indoor positioning system based on sensors and WLAN technology

In order to improve the quality of the RSS (Received Signal Strength) during the offline phase, a Mixture Gaussian Calibration Model(MGCM) is proposed by us, and a Time Latency Calibration Model(TLCM) is proposed to address the time latency effect during the online phase for a fast moving object. Firstly, MGCM is applied to the collected RSS data to precisely extract the less noised RSS. Then a feed forward neural network is trained to build a model between RSS and physical location. Finally, TLCM is applied during the online phase. The experimental results indicate that MGCM and TLCM reduce error compared to traditional positioning method respectively, which demonstrate the advantages of the proposed algorithms.
Numerical analysis of characteristic modes on the chassis of mobile phones

This paper explores the application of the concept of characteristic modes on the chassis of a mobile phone to purposeful design of its radiation characteristics. Focus is on the resonant chassis modes which dominate the overall radiation properties. Modal radiation quality factors are derived from characteristic mode eigenvalues. Antenna ¿ chassis coupling, previously only considered in terms of equivalent circuits, is discussed from a field theoretic point of view. A numerical approach for characteristic mode analysis is presented which is an eigenmode solver extension to the well known NEC2 code. Numerical results are given for wire grid models of a bar-type and a folder-type phone chassis.
The effects of silver, silicon-containing apatite towards bacteria and cell responses

An integrated approach is proposed to incorporate silicon and silver into hydroxyapatite (HA) to enhance the biological response and reduce implant-related infection in bone substitutes. This study examined the responses of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria to silver, silicon-containing apatite (Ag,Si-HA). Scanning electron microscopy images revealed significant reduction in adherence of S. aureus and E. coli bacteria on Ag,Si-HA as compared to HA. The antibacterial property of Ag,Si-HA was shown from a 7-log reduction of S. aureus population in the test solution and on the sample's surface as compared to HA at day 7. Rapid inhibition of the adherent bacteria suggested that the antibacterial action of Ag incorporated in Ag,Si-HA could be attributed to the Ag+ ions on the crystal surface rather than the released Ag+ ions. Presence of Ag may influence the biological response of HA and as such, the long-term interaction between human adipose-derived mesenchymal stem cells and Ag,Si-HA was evaluated in-vitro. An alamarBlue™ assay showed higher cell proliferation for Ag,Si-HA as compared to HA from day 3 onwards. Immunofluorescence staining revealed well-spread actin cytoskeletons on Ag,Si-HA. In addition, signs of extracellular matrix secretion and biomineralization were observed on Ag,Si-HA at day 14 onwards. Results demonstrated enhanced bone differentiation on Ag,Si-HA, as indicated by a higher level of protein expressions (type 1 collagen and osteocalcin) from day 14 to 21. Therefore, the incorporation of Ag and Si complement each other by endowing HA with antibacterial property, and concurrently promoting biological performance of the cells.
Protection of the Retina from Ischemia-Reperfusion Injury by L-Carnitine in Guinea Pigs

Purpose To investigate the efficacy of L-carnitine in preventing retinal injury followed by ischemia-reperfusion. Methods The eyes of 34 guinea pigs were used in this experiment. The guinea pigs were divided into two groups: the first group (n= 17) was given L-carnitine intraperitoneally (500mg/kg) and second group (n=17) received the same dose of saline solution. Under general anesthesia, peritomy was performed. Retro-orbital tissues were ligated for 90 minutes and ischemia was induced, followed by 4 hours of reperfusion. One of the enucleated eye was stained with hematoxylin and eosin (H&E) and retinal thicknesses were evaluated. Thiobarbituric acid reactive substances (TBARS) levels were determined in the retina of the other eye. Results Mean TBARS levels in retinal tissue were found lower in L-carnitine group (2.77 ± 0.55 μM) than in the control group (6.57 ± 1.19 μM), (p<0.01). On the other hand, mean retinal thickness was found to be increased in the control group (47.47 ± 5.62 μm) when compared to the L-carnitine group (26.52 ± 4.65 μm), (p<0.01). In correlation analysis, significantly positive relationships were found between retinal TBARS level and retinal thickness both in the control and L-carnitine groups (r=0.981, p<0.01 and r= 0.967, p<0.01 respectively). Conclusions. L-carnitine is effective in preventing retinal injury followed by ischemia-reperfusion.
Structure in solution of a four‐helix lipid binding protein

Because of the low solubility of lipids in water, intercellular and intracellular pathways of lipid transfer are necessary, e.g., for membrane formation. The mechanism by which lipids in vivo are transported from their site of biogenesis (endoplasmatic reticulum and the chloroplasts) to their place of action is unknown. Several small plant proteins with the ability to mediate transfer of radiolabeled phospholipids in vitro from liposomal donor membranes to mitochondrial and chloroplast acceptor membranes have been isolated, and a protein with this ability, the nonspecific lipid transfer protein (nsLTP) isolated from barley seeds (bLTP), has been studied here. The structure and the protein lipid interactions of lipid transfer proteins are relevant for the understanding of their function, and here we present the three‐dimensional structure in solution of bLTP as determined by NMR spectroscopy. The 1H NMR spectrum of the 91‐residue protein was assigned for more than 97% of the protein 1H atoms, and the structure was calculated on the basis of 813 distance restraints from 1H‐1H nuclear Overhauser effects, four disulfide bond restraints, from dihedral angle restraints for 66 ø‐angles, 61 χ1 angles, and 2 χ2 angles, and from 31 sets of hydrogen bond restraints. The solution structure of bLTP consists of four well‐defined α‐helices A‐D (A, Cys 3‐Gly 19; B, Gly 25‐Ala 38; C, Arg 44‐Gly 57; D, Leu 63‐Cys 73), separated by three short loops that are less well defined and concluded by a well defined C‐terminal peptide segment with no observable regular secondary structure. For the 17 structures that are used to represent the solution structure of bLTP, the RMS deviation to an average structure is 0.63 Å 0.04 Å for backbone atoms and 0.93 Å± 0.06 Å for all heavy atoms. The secondary structure elements and their locations in the sequence resemble those of nsLTP from two other plant species, wheat and maize, whose structures were previously determined (Gincel E et al, 1995, Eur J Biochem 226:413–422; Shin DH et al, 1995, Structure 3:189–199). In bLTP, the residues analogous to those in maize nsLTP that constitute the palmitate binding site are forming a similar hydrophobic cavity and a potential acyl group binding site. Analysis of the solution structure of bLTP and bLTP in complex with a ligand might provide information on the conformational changes in the protein upon ligand binding and subsequently provide information on the mode of ligand uptake and release. In this work, we hope to establish a foundation for further work of determining the solution structure of bLTP in complex with palmitoyl coenzyme A, which is a suitable ligand, and subsequently to outline the mode of ligand binding.
HTMVS: Visualizing hierarchical topics and their evolution

Topic model has been an active research area for many years, it can be used for discovering latent semantics and finding hidden knowledge in unstructured data corpus. In this paper, we investigated the problems in visualizing hierarchical topic and their evolution. The contribution of this paper is threefold, first we explore the static visualization of hierarchical topics using the `nested circle' layout, and then in order to present the topic evolution over time, we extended a hierarchical topic model and employ topic transformation visualizations to track the arising, splitting and disappearing of certain topics under the dynamic topical hierarchy. Finally, a Hierarchical Topic Model Visualization System (HTMVS) is designed to take advantage of both static and dynamic hierarchical topic visualization.
Determining Term on Text Document Clustering using Algorithm of Enhanced Confix Stripping Stemming

In a term based clustering technique with the vector space model, the issue of high dimensional vector space due to the number of words used always appears. This causes the clustering performance drops because the distance among the points tends to have the same value. The reduction of dimension by decreasing the number of words can be done by stemming. Stemming was used as term selection to reduce the many terms generated on preprocessing. The utilization of algorithm of enhance confix stripping stemmer reduced the terms that must be processed of 199.358 terms resulted from 108 text documents, became 5.476 terms result of the stemming. This reduction would speed up the process and saved the storage media. The evaluation by utilizing clustering was done using confusion matrix. The accuracy of experiment increased. General Terms Information Retrieval, Text Mining, K-Means
Tetracycline Resistance in Group A Streptococci: Emergence on a Global Scale and Influence on Multiple-Drug Resistance

ABSTRACT A global sample of group A streptococci (GAS) revealed ≥80 separate acquisitions of tetracycline resistance. Of 244 clones, 38 and 25% displayed resistance to tetracycline and erythromycin, respectively; a relatively high proportion (15%) were resistant to both classes of drugs. tet(M) displayed a highly significant association with erm(B).
Knowledge extraction from medical literature using Recurrent Neural Networks

The problem of extracting knowledge relationships from unstructured text has proved a challenge for NLP. We focus on extracting relationship information between drugs targeting bacteria from medical literature. Deep learning techniques have proved most fruitful of late in learning relationships from NLP tasks. We use a recurrent neural network architecture (LSTM) and use this to train on labeled sentences to decide whether a given relationship exists
Fault-Tolerant Matrix Converter Motor Drives With Fault Detection of Open Switch Faults

This paper describes a novel fault-tolerant matrix converter motor drive system which requires an appropriate control strategy and the application of an effective fault detection technique. Two types of fault-tolerant matrix converter, a direct matrix converter and an indirect matrix converter, are proposed for a permanent magnet synchronous motor drive against open-circuit faults in safety-critical applications. A fault-tolerant control strategy is developed in order to maintain the continuous operation of the drive system with satisfactory performance. A high-speed fault detection strategy for detecting and identifying the faulty open-circuited switches located in the fault-tolerant four-phase direct matrix converter is also proposed. Simulation and experimental results are shown to demonstrate the effectiveness of the proposed fault-tolerant matrix converters and the developed fault detection strategy applied to the motor drive system under faulty operating conditions.
Genomics Analyser: A Big Data Framework for Analysing Genomics Data

Abstract Genomics data is unstructured and mostly stored on hard disks. It is both technically and culturally residing in big data domain due to the challenges of volume, velocity and variety. Huge volumes of data are generated from diverse sources in different formats and at a high frequency. Appropriate data models are required to accommodate these data formats for analysing and producing required results with a quick response time. Genomics data can be analysed for a variety of purposes. Existing genomics data analysis pipelines are disk I/O intensive and focus on optimizing data processing for individual analysis tasks. Intensive disk I/O operations and focus on optimizing individual analysis tasks are the biggest bottleneck of existing genomics analysis pipelines. Making any updates in genomics data require reading the whole data set again. In this paper, we present a genomics data analysis framework that addresses both the issues of existing genomics analysis pipelines. It reads unstructured genomics data from sources, transforms it in a structured format and stores this data into a NoSQL database. In this way, genomics data can be queried like any other data and an update in the genomics data does not require reading the whole data set. The framework also presents an efficient analysis pipeline for analysing the genomics data for a variety of purposes like genotype clustering, gene expression microarrays, chromosome variations or gene linkage analysis. A case study of genotype clustering is presented to demonstrate and evaluate the effectiveness of the presented framework. Our results show that the framework improves overall performance of the genomics data analysis pipeline by 49% from existing genomics data analysis pipelines. Furthermore, our approach is robust and is able sustain high performance with high system workloads.