Miracle-dz/UniFAR-FTUs huggingface dataset:
The complete mitochondrial genome and molecular phylogeny of Lueyang black-bone chicken

ABSTRACT 1. The objectives of the current study were to investigate the mitochondrial genome and molecular phylogeny of Lueyang black-bone chicken, and provide molecule base to preserve and explore the specific chicken strain. 2. Based on sequencing and clustering, the complete mitochondrial DNA map and sequences of Lueyang black-bone chicken were revealed, and two phylogenetic trees of Lueyang black-bone chickens based on D-loop sequences and the mitochondrial genome were constructed. 3. The results showed that the complete mitochondrial genome of Lueyang black-bone chickens is 16,784bp in size, consisting of 22 transfer RNA genes, two ribosomal RNA genes, 13 protein-coding genes, and one non-coding control region. The base composition of the complete mtDNA sequence is 30.28% for A, 23.78% for T, 32.42% for C, 13.52% for G. Additionally, 10 haplotypes of D-loop sequences in 32 Lueyang black-bone chickens were detected, which were distributed into 4 clades (A, B, C and E). 4. It was concluded that genetic diversity is wide in Lueyang black-bone chickens, and this strain has multiple maternal origins from different regions in China and neighbouring regions.
Evaluating current and emerging antithrombotic therapy currently available for the treatment of acute coronary syndrome in geriatric populations

ABSTRACT Introduction: Acute coronary syndromes (ACS) represent one of the most perilous presentations of ischemic heart disease. Temporal trends clearly demonstrate that ACS occur later and later in life. Elderly patients with ACS comprise a populous and growing group, with more than half of individuals presenting with myocardial infarction being 75 years or older. Nevertheless, geriatric patients are greatly underrepresented in the landmark ACS trials evaluating innovative pharmacological strategies. Areas covered: The authors critically summarize recently published research on contemporary and emerging antithrombotic therapy for the treatment of ACS in geriatric patients. Expert opinion: Elderly ACS patients are characterized by simultaneously increased risk of cardiovascular events and bleeding. Very few studies assessing the efficacy and safety of novel ACS pharmacotherapy in geriatric patients are currently available. Guidelines on the treatment of ACS are based on the overall results of major randomized clinical trials (RCTs), and data supporting the recommended therapy in elderly mainly derive from subanalyses of these RCTs. Properly designed and powered RCTs are necessary to properly evaluate the net effect of current and emerging pharmacotherapy in geriatric patients. Until such data are available, elderly ACS patients should receive treatment according to the general recommendations.
Improving Fitness Function for Language Fuzzing with PCFG Model

In this paper, we propose to use machine learning techniques to model the vagueness of bugs for language interpreters and develop a fitness function for the language fuzzing based on genetic programming. The basic idea is that bug-triggering scripts usually contain uncommon usages which are not likely used by programmers in daily developments. We capture the uncommonness by using the probabilistic context-free grammar model and the Markov model to compute the probabilities of scripts such that bug-triggering scripts will get lower probabilities and higher fitness values. We choose the ROC (Receiver Operating Characteristic) curves to evaluate the performance of fitness functions in identifying bug-triggering scripts from normal scripts. We use a large corpus of JavaScript scripts from Github and POC test cases of bug-reports from SpiderMonkey's bugzilla for evaluations. The ROC curves from the experiments show that our method can provide better ability to rank the bug triggering scripts in the top-K elements.
Male Partners of Infertile Couples With Seminal Positivity for Markers of Bacterial Vaginosis Have Impaired Fertility

To access the possibility that key markers of bacterial vaginosis (KM-BV) could affect seminal parameters and thus fertility a prospective cohort study was designed (a) to develop rapid and sensitive multiplex polymerase chain reaction (M-PCR) assays to screen 13 key markers of bacterial vaginosis (KM-BV) in semen specimens, (b) to determine the prevalence of KM-BV in semen from randomized male partners of couples seeking fertility evaluation. A total of 229 semen samples were included in the study from males who visited the Sperm Analysis Section of Brazil between October 2015 and March 2016. Eligible men were 18 years or older and had a semen analysis due fertility evaluation (after failing to conceive with their partner after 1 year of unprotected intercourse). Basic seminal parameters were analyzed, and KM-BV was detected by M-PCR assays. M-PCR assays clearly distinguished 13 KM-BV in 146 semen samples (63.8%), mainly Gardnerella vaginalis (50.7%). Some important associations occurred between the presence of KM-BV in semen and changes in seminal parameters. KM-BV is commonly present in the semen of males seeking fertility evaluation and could potentially play significant roles in male subfertility and/or infertility.
Machine Learning Assisted High-Definition Map Creation

In recent years, autonomous driving technologies have attracted broad and enormous interests from both academia and industry and are under rapid development. High-Definition (HD) Maps are widely used as an indispensable component of an autonomous vehicle system by researchers and practitioners. HD Maps are digital maps that contain highly precise, fresh and comprehensive geometric information as well as semantics of the road network and surrounding environment. They provide critical inputs to almost all other components of autonomous vehicle systems, including localization, perception, prediction, motion planning, vehicle control etc. Traditionally, it is very laborious and costly to build HD Maps, requiring a significant amount of manual annotation work. In this paper, we first introduce the characteristics and layers of HD Maps; then we provide a formal summary of the workflow of HD Map creation; and most importantly, we present the machine learning techniques being used by the industry to minimize the amount of manual work in the process of HD Map creation.
Optimum Transmission Rate in Fading Channels with Markovian Sources and QoS Constraints

This paper evaluates the performance of reliability and latency in machine type communication networks, which composed of single transmitter and receiver in the presence of Rayleigh fading channel. The source's traffic arrivals are modeled as Markovian processes namely Discrete-Time Markov process, Fluid Markov process, and Markov Modulated Poisson process, and delay/buffer overflow constraints are imposed. Our approach is based on the reliability and latency outage probability, where transmitter not knowing the channel condition, therefore the transmitter would be transmitting information over the fixed rate. The fixed rate transmission is modeled as a two state Discrete time Markov process, which identifies the reliability level of wireless transmission. Using effective bandwidth and effective capacity theories, we evaluate the trade-off between reliability-latency and identify QoS requirement. The impact of different source traffic originated from MTC devices under QoS constraints on the effective transmission rate are investigated.
ReTestDroid: Towards Safer Regression Test Selection for Android Application

Mobile applications are widely used in our daily life and Android is the most popular open source mobile operating system. Because mobile applications update frequently, it is important fdevelopers to perform regression testing to ensure their quality. Modeling the control flow of an android application based on the activity lifecycle model only is imprecise for regression testing. Because many Android applications use asynchronous tasks, fragments, and native code frequently, which must be considered during change impact analysis. Otherwise, regression test selection techniques may miss some failure-revealing test cases, compromising the safety of these techniques. In this work, we propose a novel approach to model asynchronous task invocations, fragment-based activity lifecycle, and native code within the control flow graph of an Android application. Furthermore, we designed a regression test selection tool ReTestDroid based on our graph model. Our experiments on five real-life Android applications showed that our approach could enable much safer regression test selection while significantly saving regression-testing time.
Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis

Background: Vasopressin is used in conjunction with norepinephrine during treatment of patients with septic shock. Serum lactate is often used in monitoring of patients with sepsis; however, its importance as a therapeutic target is unclear. The objective of this study is to examine the relationship of vasopressin use on serum lactate levels in patients with sepsis. Methods: This study uses electronic heath records available via the Medical Information Mart for Intensive Care III. Patients were required to have a serum lactate monitoring during the intensive care unit (ICU) stay. The treatment was the administration of vasopressin between hours 3 and 18 of the ICU stay. Analysis was performed using a matched design. Results: Patients receiving vasopressin were more likely to have their serum lactate levels rise when compared to matched patients who did not receive vasopressin (odds ratio: 6.6; 95% confidence interval: 3.0-14.6, P < .001). Patients who received vasopressin had a median increase in serum lactate of 0.3 mmol/L, while patients who did not receive vasopressin had a median decrease in serum lactate of 0.7 mmol/L (P < .001). There was no statistically significant difference between the control and treated groups’ lactate trajectories prior to possible administration of vasopressin (P = .15). The results did not change significantly when norepinephrine initiation was used as the index time. Conclusions: In patients with sepsis, the administration of vasopressin was associated with a statistically significant difference in lactate change over the course of 24 hours when compared to matched patients who did not receive vasopressin.
Assisting Replace Method with Method Object: Selecting Fields and Preserving Data Access

The work of decomposing long methods into smaller ones is commonly assisted by the Extract Method refactoring technique. However, local variable usages can make code extraction difficult. Therefore, Replace Method with Method Object refactoring technique lets the developer create a field for each variable, and then code extractions can be performed without worrying about variable dependences. However, this can lead to classes having many fields used by a few of its methods. Moreover, the considered fields may not correctly describe the actual object state, making the class harder to understand. This paper proposes a data dependence analysis approach for guiding the Replace Method with Method Object refactoring technique, with the aim of reducing the set of variables becoming fields while properly handling data dependence. The resulting class is easier to understand, having less fields holding the state, while using local variables and parameters to confine all the other data dependence details.
A Study on Robustness of Complex Networks Against Random Node Removals

It is widely known that scale-free networks are robust against random node removals, which is one of major interesting findings in network science. This suggests that, for instance, communication networks such as the Internet is robust against random node failures caused by breakdowns and/or malicious attacks if their network topologies are scale-free networks. Generally, the ratio of failed devices (e.g., routers) to operational devices is not so high. In this paper, we revisit the robustness of complex networks against random node removals. Through simulations, we compare the robustness of scale-free and non-scale-free networks against random node removals. Our findings include that, contrary to common understanding, random networks are more robust than scale-free networks except for extremely high node removal ratios. We also show that the robustness of random networks can be further improved by bounding the minimum node degree of those networks.
Improving Cluster Resource Efficiency with Oversubscription

Volumes of studies on resource scheduling are proposed to improve the efficiency of computing clusters. As users usually overestimate the resource requirements for their jobs, further, most schedulers ignore the dynamic variation of jobs' runtime resource usage, the utilization of real-world clusters is significantly limited. In this paper, we argue that resource oversubscription, which allocates more resources than the physical capacity, is a necessary complement to existing systems. To alleviate resource contention, we augment oversubscription with lightweight prediction and dynamic CPU throttling. We implemented our approach called Datom, which is an extension module of the Apache Mesos cluster manager. We evaluated Datom with real-world video transcoding workloads and simulations with Google cluster trace. The results show that comparing to original Mesos, Datom increased CPU utilization, memory utilization and overall task throughput by up to 22%, 23%, 20% respectively, and shortened jobs' complete time by up to 20%, at the expenses of moderate penalty on job execution.
Filling the Gaps for Enhancing the Effectiveness of Community-Based Programs Combining Treatment and Prevention of Child Malnutrition: Results from the Rainbow Project 2015–17 in Zambia

Background: Child malnutrition, in all its forms, is a public health priority in Zambia. After implementations based on a previous evaluation in 2012–14 were made, the efficacy of the Rainbow Project Supplementary Feeding Programs (SFPs) for the integrated management of severe acute malnutrition (SAM), moderate acute malnutrition (MAM), and underweight was reassessed in 2015–17. Methods: The outcomes were compared with International Standards and with those of 2012–14. Cox proportional risk regression analysis was performed to identify predictors of mortality and defaulting. Results: The data for 900 under-five year-old malnourished children were analyzed. Rainbow’s 2015–17 outcomes met International Standards, for total and also when stratified for different type of malnutrition. A better performance than 2012–14 was noted in the main areas previously identified as critical: mortality rates were halved (5.6% vs. 3.1%, p = 0.01); significant improvements in average weight gain and mean length of stay were registered for recovered children (p < 0.001). HIV infection (5.5; 1.9–15.9), WAZ <–3 (4.6; 1.3–16.1), and kwashiorkor (3.5; 1.2–9.5) remained the major predictors of mortality. Secondly, training community volunteers consistently increased the awareness of a child’s HIV status (+30%; p < 0.001). Conclusion: Rainbow SFPs provide an integrated community-based approach for the treatment and prevention of child malnutrition in Zambia, with its effectiveness significantly enhanced after the gaps in activities were filled.
Prediction of the presence of a seventh ankyrin repeat in IκBε from homology modeling combined with hydrogen–deuterium exchange mass spectrometry (HDX‐MS)

The ankyrin repeat (AR) structure is a common protein–protein interaction motif and ankyrin repeat proteins comprise a vast family across a large array of different taxa. Natural AR proteins adopt a conserved fold comprised of several repeats with the N‐ and C‐terminal repeats generally being of more divergent sequences. Obtaining experimental crystal structures for natural ankyrin repeat domains (ARD) can be difficult and often requires complexation with a binding partner. Homology modeling is an attractive method for creating a model of AR proteins due to the highly conserved fold; however, modeling the divergent N‐ and C‐terminal “capping” repeats remains a challenge. We show here that amide hydrogen/deuterium exchange mass spectrometry (HDX‐MS), which reports on the presence of secondary structural elements and “foldedness,” can aid in the refinement and selection of AR protein homology models when multiple templates are identified with variations between them localizing to these terminal repeats. We report a homology model for the AR protein IκBε from three different templates and use HDX‐MS to establish the presence of a seventh AR at the C‐terminus identified by only one of the three templates used for modeling.
The Potential of LPS-Binding Protein to Reverse Amyloid Formation in Plasma Fibrin of Individuals With Alzheimer-Type Dementia

Many studies indicate that there is a (mainly dormant) microbial component in the progressive development of Alzheimer-type dementias (ADs); and that in the case of Gram-negative organisms, a chief culprit might be the shedding of the highly inflammagenic lipopolysaccharide (LPS) from their cell walls. We have recently shown that a highly sensitive assay for the presence of free LPS [added to platelet poor plasma (PPP)] lies in its ability (in healthy individuals) to induce blood to clot into an amyloid form. This may be observed in a SEM or in a confocal microscope when suitable amyloid stains (such as thioflavin T) are added. This process could be inhibited by human lipopolysaccharide-binding protein (LBP). In the current paper, we show using scanning electron microscopy and confocal microscopy with amyloid markers, that PPP taken from individuals with AD exhibits considerable amyloid structure when clotting is initiated with thrombin but without added LPS. Furthermore, we could show that this amyloid structure may be reversed by the addition of very small amounts of LBP. This provides further evidence for a role of microbes and their inflammagenic cell wall products and that these products may be involved in pathological clotting in individuals with AD.
The effect of positioning and diaphragmatic breathing exercises on respiratory muscle activity in people with chronic obstructive pulmonary disease

Background Body positioning and diaphragmatic breathing may alter respiratory pattern and reduce dyspnoea in people with chronic obstructive pulmonary disease (COPD). Objectives To determine the effect of positioning and diaphragmatic breathing on respiratory muscle activity in a convenience sample of people with COPD, using surface electromyography (sEMG). Methods This prospective descriptive study recorded sEMG measurements at baseline, after upright positioning, during diaphragmatic breathing and 5 minutes thereafter. Vital signs and levels of perceived dyspnoea were recorded at baseline and at the end of the study. Data were analysed using repeated measures ANOVAs with post hoc t-tests for dependent and independent variables. Results Eighteen participants (13 male; mean ± standard deviation age 59.0 ± 7.9 years) were enrolled. Total diaphragmatic activity did not change with repositioning (p = 0.2), but activity increased from 7.3 ± 4.2 µV at baseline to 10.0 ± 3.3 µV during diaphragmatic breathing (p = 0.006) with a subsequent reduction from baseline to 6.1 ± 3.5 µV (p = 0.007) at the final measurement. There was no change in intercostal muscle activity at different time points (p = 0.8). No adverse events occurred. Nutritional status significantly affected diaphragmatic activity (p = 0.004), with participants with normal body mass index (BMI) showing the greatest response to both positioning and diaphragmatic breathing. There were no significant changes in vital signs, except for a reduction in systolic/diastolic blood pressure from 139.6 ± 18.7/80.4 ± 13.0 to 126.0 ± 15.1/75.2 ± 14.7 (p < 0.05). Conclusion A single session of diaphragmatic breathing transiently improved diaphragmatic muscle activity, with no associated reduction in dyspnoea.
Epiviz Web Components: reusable and extensible component library to visualize functional genomic datasets

Interactive and integrative data visualization tools and libraries are integral to exploration and analysis of genomic data. Web based genome browsers allow integrative data exploration of a large number of data sets for a specific region in the genome. Currently available web-based genome browsers are developed for specific use cases and datasets, therefore integration and extensibility of the visualizations and the underlying libraries from these tools is a challenging task. Genomic data visualization and software libraries that enable bioinformatic researchers and developers to implement customized genomic data viewers and data analyses for their application are much needed. Using recent advances in core web platform APIs and technologies including Web Components, we developed the Epiviz Component Library, a reusable and extensible data visualization library and application framework for genomic data. Epiviz Components can be integrated with most JavaScript libraries and frameworks designed for HTML. To demonstrate the ease of integration with other frameworks, we developed an R/Bioconductor epivizrChart package, that provides interactive, shareable and reproducible visualizations of genomic data objects in R, Shiny and also create standalone HTML documents. The component library is modular by design, reusable and natively extensible and therefore simplifies the process of managing and developing bioinformatic applications.
Predicting the Breakability of Blocking Bug Pairs

Software systems becomes increasingly complex for the wide use of social-software-development platforms, such as GitHub. Complicated inter-dependencies within ecosystems impose new challenges in resolving the blocking bug pairs, in which the upstream bugs prevent the downstream bugs to be fixed. Generally, the downstream bugs cannot be fixed until the upstream bugs are fixed in blocking bug pairs, which keeps the downstream developers waiting for a long time. However, previous research found that some blocking pairs could be "broken" through a workaround, i.e., a temporary solution proposed by the downstream developers before the upstream bugs get fixed. In this paper, we propose an approach to describe and predict the breakability of the blocking bug pairs. Our goal is to help the ecosystem developers to predict whether the given blocking bug pair can be broken. We evaluate our approach on two real world ecosystems: Mozilla Firefox and Netbeans, and have the following two main findings. First, the participants within the blocking bug pair and the vitality of the downstream bug have much impact on the breakability. Second, we can build breakability predication models with the accuracy of approximate 80%. Moreover, for predicting unbreakable pairs which affect the downstream projects seriously, our approach achieves a precision over 92%. It can be used to effectively remind the upstream developers to fix these bugs as quickly as possible.