Miracle-dz/UniFAR-FTUs huggingface dataset:
Humans parasitized by the hard tick Ixodes ricinus are seropositive to Midichloria mitochondrii: is Midichloria a novel pathogen, or just a marker of tick bite?

Abstract Midichloria mitochondrii is an intracellular bacterium found in the hard tick Ixodes ricinus. In this arthropod, M. mitochondrii is observed in the oocytes and in other cells of the ovary, where the symbiont is present in the cell cytoplasm and inside the mitochondria. No studies have so far investigated whether M. mitochondrii is present in the salivary glands of the tick and whether it is transmitted to vertebrates during the tick blood meal. To address the above issues, we developed a recombinant antigen of M. mitochondrii (to screen human sera) and antibodies against this antigen (for the staining of the symbiont). Using these reagents we show that (i) M. mitochondrii is present in the salivary glands of I. ricinus and that (ii) seropositivity against M. mitochondrii is highly prevalent in humans parasitized by I. ricinus (58%), while it is very low in healthy individuals (1·2%). These results provide evidence that M. mitochondrii is released with the tick saliva and raise the possibility that M. mitochondrii is infectious to vertebrates. Besides this, our study indicates that M. mitochondrii should be regarded as a package of antigens inoculated into the human host during the tick bite. This implies that the immunology of the response toward the saliva of I. ricinus is to be reconsidered on the basis of potential effects of M. mitochondrii and poses the basis for the development of novel markers for investigating the exposure of humans and animals to this tick species.
Social Performance Cues Induce Behavioral Flexibility in Humans

Behavioral flexibility allows individuals to react to environmental changes, but changing established behavior carries costs, with unknown benefits. Individuals may thus modify their behavioral flexibility according to the prevailing circumstances. Social information provided by the performance level of others provides one possible cue to assess the potential benefits of changing behavior, since out-performance in similar circumstances indicates that novel behaviors (innovations) are potentially useful. We demonstrate that social performance cues, in the form of previous players’ scores in a problem-solving computer game, influence behavioral flexibility. Participants viewed only performance indicators, not the innovative behavior of others. While performance cues (high, low, or no scores) had little effect on innovation discovery rates, participants that viewed high scores increased their utilization of innovations, allowing them to exploit the virtual environment more effectively than players viewing low or no scores. Perceived conspecific performance can thus shape human decisions to adopt novel traits, even when the traits employed cannot be copied. This simple mechanism, social performance feedback, could be a driver of both the facultative adoption of innovations and cumulative cultural evolution, processes critical to human success.
Quick test method for evaluating the delamination tendency of glass packaging

The invention relates to a rapid test procedure for evaluating the delamination in glass packaging, in particular for the pharmaceutical sector, comprising the steps of: Step (1): subjecting the glass packaging an atmosphere of water vapor to form a corrosion zone; and subsequently performing a further step selected from step (2a), the step (2b) or step (2c), comprising Step (2a): visualizing the corrosion zone using a light microscope; Step (2b): visualizing the corrosion zone by staining and subsequent inspection; or Step (2c): elution of glass components in ultrapure water and quantifying the leached glass components. There is provided a rapid test method available that provides a statement as easily, reliably and in a relatively short period of time, whether a glass packaging shows a tendency to delamination or not.
Comorbidity and Sex-Related Differences in Mortality in Oxygen-Dependent Chronic Obstructive Pulmonary Disease

Background It is not known why survival differs between men and women in oxygen-dependent chronic obstructive pulmonary disease (COPD). The present study evaluates differences in comorbidity between men and women, and tests the hypothesis that comorbidity contributes to sex-related differences in mortality in oxygen-dependent COPD. Methods National prospective study of patients aged 50 years or older, starting long-term oxygen therapy (LTOT) for COPD in Sweden between 1992 and 2008. Comorbidities were obtained from the Swedish Hospital Discharge Register. Sex-related differences in comorbidity were estimated using logistic regression, adjusting for age, smoking status and year of inclusion. The effect of comorbidity on overall mortality and the interaction between comorbidity and sex were evaluated using Cox regression, adjusting for age, sex, PaO2 breathing air, FEV1, smoking history and year of inclusion. Results In total, 8,712 patients (55% women) were included and 6,729 patients died during the study period. No patient was lost to follow-up. Compared with women, men had significantly more arrhythmia, cancer, ischemic heart disease and renal failure, and less hypertension, mental disorders, osteoporosis and rheumatoid arthritis (P<0.05 for all odds ratios). Comorbidity was an independent predictor of mortality, and the effect was similar for the sexes. Women had lower mortality, which remained unchanged even after adjusting for comorbidity; hazard ratio 0.73 (95% confidence interval, 0.68–0.77; P<0.001). Conclusions Comorbidity is different in men and women, but does not explain the sex-related difference in mortality in oxygen-dependent COPD.
Innovative strategies for intelligent robot industry in Korea

In the 21st century, the robot is rapidly emerging in the general public. In particular, the intelligent robot will play important roles in the future by strengthening the global competitiveness. In this paper, strategies to improve the utilization of the intelligent robot were investigated using a Structural Equation Model (SEM). The relation among various factors that have a potential influence on robot utilization is explored. According to the results of our study, the current government policies are not effective on revitalization of the robot industry, mainly due to excessive policies implemented simultaneously by the Korean government. However, a Robot Utilization Expectation Index of 75.86 indicates that many people expect a robot as useful in their daily life. These results are expected to contribute to stimulating the robot industry in Korea.
Differential expression of multiple exo‐cellobiohydrolase I‐like genes in the lignin‐degrading fungus Phanerochaete chrysosporium

The genome of Phanerochaete chrysosporium strain ME446 contains multiple, non‐allelic, cellobiohydrolase I (CSHI)‐like sequences, at least two of which are expressed in a cellulose‐dependent manner. Each of the expressed genes contains two identically positioned introns within its coding region. The lengths and sequences of these introns are different and one is not excised from all transcripts, raising the possibility that subtly different protein products may be expressed from a common gene. Introns are also present upstream of both genes but these differ in number and position, as well as sequence and length. Endoglucanase‐like sequences could not be identified and it is suggested that variant CBHI‐like proteins may provide endoglucanase activity in this fungus.
Large-scale MIMO detection design and FPGA implementations using SOR method

In this paper, we propose a very large scale integration design method for a large-scale multiple-input multiple-output detection algorithm. Our design uses a modified version of the Successive Over Relaxation (SOR) method, which substantially reduces the highly computational complexity of data detection and achieves the near-optimal performance. We use a reconfigurable Processing Elements Array (PEA) to compute matrix-vector or matrix-matrix in SOR Method, which reduces the complexity of linear data detection. Then we implement our design on Xilinx Virtex-7 FPGA and the experimental results show that SOR method has a superior performance over conventional methods.
Power converter topologies with energy recovery and grid power limitation for inductive load applications

This work investigates a grid interface for power supplies used in particle accelerators for cycling loads such as large electromagnets. Two topologies are discussed integrating magnetic energy recovery. For each topology, the associated energy management strategies are examined with the objective to control the grid current profile. A model is established for each of the proposed solutions and the simulation results are presented. A critical review of the investigated energy management solutions is attempted.
Impact of Radio Resource Allocation and Pulse Shaping on Papr of SC-FDMA Signals

Single carrier frequency division multiple access (SC- FDMA) is a strong candidate for uplink transmissions in the 3G long term evolution (LTE) standard. SC-FDMA is a multiple access scheme that uses DFT spreading prior to OFDM modulation to map the signal from each user to a subset of the available subcarriers. SC-FDMA has a significantly lower peak-to-average power ratio (PAPR) compared to OFDM/OFDMA. This greatly improves its RF power amplifier efficiency and also the mean power output from a battery driven mobile terminal. In this paper, the impact of radio resource allocation and pulse shaping on the PAPR of SC-FDMA signals are investigated, especially for localized FDMA (LFDMA) signals. It is shown that distributed FDMA (DFDMA) signals with raised cosine filtering experience reduced PAPR as a increases. However, for LFDMA signals the PAPR increases with increasing alpha and further varies according to the allocated resource unit.
On Unsupervised Nearest-neighbor Regression and Robust Loss Functions

In many scientific disciplines structures in high-dimensional data have to be detected, e.g., in stellar spectra, in genome data, or in face recognition tasks. We present an approach to non-linear dimensionality reduction based on fitting nearest neighbor regression to the unsupervised regression framework for learning of lowdimensional manifolds. The problem of optimizing latent neighborhoods is difficult to solve, but the UNN formulation allows an efficient strategy of iteratively embedding latent points to fixed neighborhood topologies. The choice of an appropriate loss function is relevant, in particular for noisy, and high-dimensional data spaces. We extend unsupervised nearest neighbor (UNN) regression by the e-insensitive loss, which allows to ignore residuals under a threshold defined by e. In the experimental part of this paper we test the influence of e on the final data space reconstruction error, and present a visualization of UNN embeddings on test data sets.
A Novel Reinforcement Model of Birdsong Vocalization Learning

Songbirds learn to imitate a tutor song through auditory and motor learning. We have developed a theoretical framework for song learning that accounts for response properties of neurons that have been observed in many of the nuclei that are involved in song learning. Specifically, we suggest that the anterior forebrain pathway, which is not needed for song production in the adult but is essential for song acquisition, provides synaptic perturbations and adaptive evaluations for syllable vocalization learning. A computer model based on reinforcement learning was constructed that could replicate a real zebra finch song with 90% accuracy based on a spectrographic measure. The second generation of the birdsong model replicated the tutor song with 96% accuracy.
Visual hulls from single uncalibrated snapshots using two planar mirrors

Two mirrors are used to create five views of an object: a view onto the object, two reflections and two reflections of reflections. The five views are captured in a single snapshot. Epipolar geometry of the object’s five silhouettes is determined directly from the image without knowing the poses of the camera or the mirrors. The epipolar geometry provides constraints on the pose of each silhouette, allowing the pose of each silhouette to be computed in a common reference frame using only the silhouette outlines. Once the pose associated with each silhouette has been computed, a five-view visual hull of the object can be computed from the five silhouettes. By capturing several images of a rigid object in different poses, sets of five silhouettes can be combined into a single silhouette set in which the pose of each silhouette is known in a common reference frame. This allows visual hulls of an arbitrary number of views to be computed if more than one image is used. The method is applied to an ornamental cat, and experimental results are shown.
An Operator Approach to Tangent Vector Field Processing

In this paper, we introduce a novel coordinate‐free method for manipulating and analyzing vector fields on discrete surfaces. Unlike the commonly used representations of a vector field as an assignment of vectors to the faces of the mesh, or as real values on edges, we argue that vector fields can also be naturally viewed as operators whose domain and range are functions defined on the mesh. Although this point of view is common in differential geometry it has so far not been adopted in geometry processing applications. We recall the theoretical properties of vector fields represented as operators, and show that composition of vector fields with other functional operators is natural in this setup. This leads to the characterization of vector field properties through commutativity with other operators such as the Laplace‐Beltrami and symmetry operators, as well as to a straight‐forward definition of differential properties such as the Lie derivative. Finally, we demonstrate a range of applications, such as Killing vector field design, symmetric vector field estimation and joint design on multiple surfaces.
Interrater and Intrarater Reliability of the Functional Movement Screen

Abstract Smith, CA, Chimera, NJ, Wright, NJ, and Warren, M. Interrater and intrarater reliability of the functional movement screen. J Strength Cond Res 27(4): 982–987, 2013—The purpose of this study was to investigate interrater and intrarater reliability of the Functional Movement Screen (FMS) with real-time administration with raters of different educational background and experience. The FMS was assessed with real-time administration in healthy injury-free men and women and included a certified FMS rater for comparison with other raters. A relatively new tool, the FMS, was developed to screen 7 individual movement patterns to classify subjects' injury risk. Previous reliability studies have been published with only one investigating intrarater reliability. These studies had limitations in study design and clinical applicability such as the use of only video to rate or the use of raters without comparison to a certified FMS rater. Raters (n = 4) with varying degrees of FMS experience and educational levels underwent a 2-hour FMS training session. Subjects (n = 19) were rated during 2 sessions, 1 week apart, using standard FMS protocol and equipment. Interrater reliability was good for session 1 (intraclass correlation coefficient [ICC] = 0.89) and for session 2 (ICC = 0.87). The individual FMS movements showed hurdle step as the least reliable (ICC = 0.30 for session 1 and 0.35 for session 2), whereas the most reliable was shoulder mobility (ICC = 0.98 for session 1 and 0.96 for session 2). Intrarater reliability was good for all raters (ICC = 0.81–0.91), with similar ICC regardless of education or previous experience with FMS. The results showed that the FMS could be consistently scored by people with varying degrees of experience with the FMS after a 2-hour training session. Intrarater reliability was not increased with FMS certification.
Value Profiling and Optimization

Variables and instructions that have invariant or predictable values at run-time, but cannot be identified as such using compiler analysis, can benefit from value-based compiler optimizations. Value-based optimizations include all optimizations based on a predictable value or range of values for a variable or instruction at run-time. These include constant propagation, code specialization, optimizations assuming the value predictability of an instruction, continuous optimization, and partial evaluation. This paper explores the value behavior found from profiling load instructions and memory locations. We compare the value predictability and invariant behavior of instructions (registers) and variables (memory locations) found from value profiling across different inputs. We use the value profiles to perform codespecialization for a couple of programs, showing that value profiles can be used to reduce a program’s execution time up to 21%. The ability to accurately and efficiently generate value profiles is also examined using convergent profiling and random sampling.
Growth Hormone Responses to Provocative Tests in Children with Short Stature

Growth hormone deficiency (GHD) is defined as a serum peak GH concentration <10 ng/mL with provocation as tested by a combination of at least two separate tests. The aim of this study was to compare two standard tests, insulin and levodopa (L-dopa), with a primary focus on specificity and accuracy. Clinical data were collected retrospectively from a review of 120 children who visited the pediatric endocrine clinic at Chonnam National University Hospital for the evaluation of short stature between January 2006 and April 2014. Subjects underwent GH provocation tests with insulin and L-dopa. Blood samples were obtained at 0, 15, 30, 45, 60, 90, and 120 min after administration, and GH levels were measured. In the insulin test, serial glucose levels were also checked, closely monitoring hypoglycemia. A total of 83 children (69.2%) were diagnosed with GHD and 37 children (30.8%) were diagnosed with idiopathic short stature (ISS). Peak GH levels were achieved an average of 45 min after the administration of insulin and L-dopa for both groups. The specificity and accuracy were 78.4% and 93.6% for the insulin test and 29.7% and 79.2% for L-dopa test, respectively. In the ISS group, the cumulative frequency of a GH cutoff value of >10 ng/mL at 120 min was 75.6% after insulin stimulation compared with 35.1% after L-dopa stimulation. Considering these results, we recommend performing the insulin test first to exclude ISS and then the L-dopa test for the diagnosis of GHD. This way, ISS patients are diagnosed after a single test, thus reducing hospital days and the burden of undergoing two serial tests.
WhyNot: debugging failed queries in large knowledge bases

When a query to a knowledge-based system fails and returns "unknown", users are confronted with a problem: Is relevant knowledge missing or incorrect? Is there a problem with the inference engine? Was the query ill-conceived? Finding the culprit in a large and complex knowledge base can be a hard and laborious task for knowledge engineers and might be impossible for non-expert users. To support such situations we developed a new tool called "WhyNot" as part of the PowerLoom knowledge representation and reasoning system. To debug a failed query, WhyNot tries to generate a small set of <i>plausible partial proofs</i> that can guide the user to what knowledge might have been missing, or where the system might have failed to make a relevant inference. A first version of the system has been deployed to help debug queries to a version of the Cyc knowledge base containing over 1,000,000 facts and over 35,000 rules.
Whole Exome Sequencing for Identification of Potential Causal Variants for Diffuse Cutaneous Systemic Sclerosis

Quality filters applied were Variant Quality Score Recalibration tranche sensitivity ,99.00, read depth . 10, and genotyping quality in phred scale . 20. MAF 5 minor allele frequency in the 1000 Genomes European (phase I) population or in the ESP6500 European American population. Variants enriched in patients with dcSSc and in those with ILD (red boxes) were those that satisfied the criteria described in the case–control gene burden analysis (see Patients and Methods). Pathway analysis was performed using g:Profiler (http://biit.cs.ut.ee/gprofiler). IDENTIFICATION OF POTENTIAL dcSSc CAUSAL VARIANTS WITH WES 2259
An acoustic distance measure for automatic cross-language phoneme mapping

This paper explores an automated approach to mapping one phoneme set to another, based on the acoustic distances of the individual phonemes. The main goal of this investigation is to automate the technique for creating initial/baseline acoustic models for a new language. Using this technique, it would be possible to rapidly build speech recognition systems for a variety of languages. A subsidiary objective of this investigation is to compare different acoustic distance measures and to assess their ability to quantify the acoustic similarity between phonemes. The distance measures that were considered for this investigation are the Kullback-Leibler measure, the Bhattacharyya distance metric, the Mahalanobis measure, the Euclidean measure, the L2 metric and the Jeffreys-Matusita distance. Both the TIMIT and SUN Speech corpora were used. It was found that by selecting an appropriate distance measure, an automated procedure to map phonemes from a source language (English) to a target language (Afrikaans) can be applied, with recognition results comparable to a manual mapping process undertaken by a phonetic expert.
Towards an Adaptive Multi-Power-Source Datacenter

Big data and cloud computing are accelerating the capacity growth of datacenters all over the world. Their energy costs and environmental issues have pushed datacenter operators to explore and integrate alternative energy sources, such as various renewable energy supplies and energy storage devices. Designing datacenters powered by multi-power supplies in the smart grid environment is becoming a promising trend in the next few decades. However, gracefully provisioning various power sources and efficiently manage them in datacenter is a significant challenge. In this paper, we explore an unconventional fine-grained power distribution architecture for multi-source powered datacenters. We thoroughly investigate how to deliver and manage multiple power sources from the power generation plant outside of the datacenter to datacenter inside. We then propose a novel Power Switch Network (PSN) for datacenters. PSN is a reconfigurable multi-power-source distribution architecture which enables datacenter to distribute various power sources with a fine-grained manner. Moreover, a tailored machine learning based power sources management framework is proposed for PSN to dynamically select different power sources and optimize user-demanded performance metrics. Compared with the conventional single-switch system, evaluation results show that PSN could improve solar energy utilization by 39.6%, reduce utility power cost by 11.1% and improve workload performance by 33.8%, meanwhile enhancing battery lifetime by 9.3%. We expect that our work could provide valuable guidelines for the emerging multi-power-source datacenter to improve their efficiency, sustainability and economy.