Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypovigilance in limited self-driving automation: Peripheral visual stimulus for a balanced level of automation and cognitive workload

Higher levels of vehicle automation might lead to a reduction in driver situational awareness, as driver intervention to control the vehicle is only demanded in novel, previously unencountered situations that the automation might not be able to handle. In this paper we address this question by presenting a study on continuous, in-vehicle visual stimulus to reduce driver reaction time after a period of hypovigilance. We relied on peripheral vision, which is processed subconsciously, to implement an unobtrusive method based on luminescence. Data analysis showed a tendency among drivers to respond faster to a Take Over Request when their peripheral vision detected the stimulus.
Antibiotics with Interleukin-15 Inhibition Reduce Joint Inflammation and Bone Erosions but Not Cartilage Destruction in Staphylococcus aureus-Induced Arthritis

ABSTRACT Staphylococcus aureus-induced arthritis causes rapid joint destruction, often leading to disabling joint damage despite antibiotics. We have previously shown that interleukin-15 (IL-15) inhibition without antibiotics is beneficial in S. aureus-induced arthritis. We therefore hypothesized that the inhibition of IL-15, in combination with antibiotics, might represent a useful therapy that would reduce inflammation and joint destruction but preserve the host's ability to clear the infection. Female wild-type C57BL/6 mice were intravenously inoculated with the toxic shock syndrome toxin 1 (TSST-1)-producing LS-1 strain of S. aureus with 0.8 × 108 CFU S. aureus LS-1/mouse. Three days later, treatment consisting of cloxacillin, followed by flucloxacillin, together with either anti-IL-15 antibodies (aIL-15ab) or control antibodies, was started. Studied outcomes included survival, weight change, bacterial clearance, and joint damage. The addition of aIL-15ab to antibiotics in S. aureus-induced arthritis reduced synovitis and bone erosions compared to controls. The number of bone-resorbing osteoclasts in the joints was reduced, whereas cartilage destruction was not significantly altered. Importantly, the combination therapy did not adversely affect the clinical outcome of S. aureus-induced arthritis, such as survival or weight change, or compromise the host's ability to clear the infection. Since the clinical outcome of S. aureus-induced arthritis was not affected, the addition of aIL-15ab to antibiotics ought to be safe. Taken together, the combination of aIL-15ab and antibiotics is a beneficial, but not optimal, treatment of S. aureus-induced arthritis since it reduces synovitis and bone erosions but has a limited effect on cartilage destruction.
Improving Object Counting with Heatmap Regulation

In this paper, we propose a simple and effective way to improve one-look regression models for object counting from images. We use class activation map visualizations to illustrate the drawbacks of learning a pure one-look regression model for a counting task. Based on these insights, we enhance one-look regression counting models by regulating activation maps from the final convolution layer of the network with coarse ground-truth activation maps generated from simple dot annotations. We call this strategy heatmap regulation (HR). We show that this simple enhancement effectively suppresses false detections generated by the corresponding one-look baseline model and also improves the performance in terms of false negatives. Evaluations are performed on four different counting datasets --- two for car counting (CARPK, PUCPR+), one for crowd counting (WorldExpo) and another for biological cell counting (VGG-Cells). Adding HR to a simple VGG front-end improves performance on all these benchmarks compared to a simple one-look baseline model and results in state-of-the-art performance for car counting.
On inferential Iterative Learning Control: With example to a printing system

Since performance variables cannot be measured directly, Iterative Learning Control (ILC) is usually applied to measured variables. In this paper, it is shown that this can deteriorate performance. New batch-wise sensors that measure the performance variables directly are well-suited for use in ILC and can potentially improve performance. In this paper, recent developments in inferential control are utilized to arrive at control structures suited for inferential ILC. The proposed frameworks extend earlier results and encompass various controller structures. The results are supported with a simulation example.
Why Children Understand and Misunderstand Sentences 1 Why Children Understand and Misunderstand Sentences : An Eye-tracking Study of Passive Sentences *

Although by 3or 4-years of age, children are remarkably good at understanding most sentences, many studies have shown that even 5and 6-year old children have difficulty understanding some types of sentences. The reason(s) why are unclear in large part because we know little about how children process sentences. To investigate how children process the sentences, we collected accuracy, reaction time, and eye-gaze data while 3to 6-year old English-speaking children listened to active and passive sentences and performed a picture-matching comprehension task. Consistent with previous work, children were faster and more accurate on active than passive sentences. Our data suggest that, although 3-year old children have (at least some of) the linguistic machinery that underlies passives, they cannot interpret them, and even 6-year old children’s processing of passives is not yet adult-like insomuch as it is off-line. Our data further suggest that at age 5, children still rely on a 1 NP = Agent heuristic to process active and passive sentences, but that by age 6, children only use the 1 NP = Agent heuristic when they misinterpret passives. Thus, we argue that children misinterpret passives, not because of syntactic limitations, but rather because of sentence processing limitations. More generally, we argue that children’s sentence processing is still developing at age 6.
Characterization and classification of uterine magnetomyography signals using KNN classifier

Prediction of premature labor is very important factor as it increases the chances of morbidity and mortality of mothers and babies. Uterine physiological signals are analyzed to extract the features that are helpful in the prediction of labor. The uterine magnetomyography (MMG) measures the magnetic activity of uterine muscles. The objective of this study was to determine if a particular analytic method is effective in quantifying uterine magnetomyography data for estimating the onset of labor. Twenty-four MMG signals were taken from physionet database. Signals were divided into two groups depends on their days to delivery after recording. The signals were analyzed to extract features. The extracted features were successfully discerned between patients that were delivered within 24 h and those were not. It can be useful for the classification of antepartum and labor patients. For characterization and classification of MMG signals, features were validated with K-nearest neighbor (KNN) classifier. We achieved the classification accuracy 66.67%, Sensitivity 75% and Specificity 75%.
The CRISPR/Cas system can be used as nuclease for in planta gene targeting and as paired nickases for directed mutagenesis in Arabidopsis resulting in heritable progeny.

The CRISPR/Cas nuclease is becoming a major tool for targeted mutagenesis in eukaryotes by inducing double-strand breaks (DSBs) at pre-selected genomic sites that are repaired by non-homologous end joining (NHEJ) in an error-prone way. In plants, it could be demonstrated that the Cas9 nuclease is able to induce heritable mutations in Arabidopsis thaliana and rice. Gene targeting (GT) by homologous recombination (HR) can also be induced by DSBs. Using a natural nuclease and marker genes, we previously developed an in planta GT strategy in which both a targeting vector and targeting locus are activated simultaneously via DSB induction during plant development. Here, we demonstrate that this strategy can be used for natural genes by CRISPR/Cas-mediated DSB induction. We were able to integrate a resistance cassette into the ADH1 locus of A. thaliana via HR. Heritable events were identified using a PCR-based genotyping approach, characterised by Southern blotting and confirmed on the sequence level. A major concern is the specificity of the CRISPR/Cas nucleases. Off-target effects might be avoided using two adjacent sgRNA target sequences to guide the Cas9 nickase to each of the two DNA strands, resulting in the formation of a DSB. By amplicon deep sequencing, we demonstrate that this Cas9 paired nickase strategy has a mutagenic potential comparable with that of the nuclease, while the resulting mutations are mostly deletions. We also demonstrate the stable inheritance of such mutations in A. thaliana.
Fundamentals of glycogen metabolism for coaches and athletes

Abstract The ability of athletes to train day after day depends in large part on adequate restoration of muscle glycogen stores, a process that requires the consumption of sufficient dietary carbohydrates and ample time. Providing effective guidance to athletes and others wishing to enhance training adaptations and improve performance requires an understanding of the normal variations in muscle glycogen content in response to training and diet; the time required for adequate restoration of glycogen stores; the influence of the amount, type, and timing of carbohydrate intake on glycogen resynthesis; and the impact of other nutrients on glycogenesis. This review highlights the practical implications of the latest research related to glycogen metabolism in physically active individuals to help sports dietitians, coaches, personal trainers, and other sports health professionals gain a fundamental understanding of glycogen metabolism, as well as related practical applications for enhancing training adaptations and preparing for competition.
Rehabilitation Reduced Readmission and Mortality Risks in Patients With Stroke or Transient Ischemic Attack: A Population-based Study

Background: It remains unclear whether rehabilitation has an impact on reducing the long-term risk of mortality or readmission following stroke or transient ischemic attack (TIA). Objectives: To investigate the association between the dosage and continuation of rehabilitation and the risk of outcome events (OEs) after stroke or TIA. Research Design: A retrospective cohort study using Taiwan’s National Health Insurance database. Subjects: In total, 4594 patients admitted with first-ever acute stroke or TIA were followed-up for 32 months. Measures: The occurrence of 3 OEs: (1) vascular readmissions/all-cause mortality [vascular event (VE)], (2) all-cause readmissions/mortality (OE1), and (3) all-cause mortality (OE2), in model 1: none, low-intensity, and high-intensity rehabilitation; and model 2: inpatient plus/or outpatient rehabilitation. Results: Comparing with patients without rehabilitation, in model 1, patients receiving low-intensity rehabilitation had a lower risk of VE [Hazard ratio (HR), 0.77; 95% CI, 0.68–0.87] and OE1 (HR, 0.77; CI, 0.71–0.84), but not OE2 (HR, 0.91; CI, 0.77–1.07). Patients receiving high-intensity rehabilitation had lower risks of all VE (HR, 0.68; CI, 0.58–0.79), OE1 (HR, 0.79; CI, 0.71–0.88), and OE2 (HR, 0.56; CI, 0.44–0.71). In model 2, patients receiving inpatient plus outpatient rehabilitation had a lowest risk of VE (HR, 0.55; CI, 0.47–0.65), OE1 (HR, 0.65; CI, 0.58–0.72), and OE2 (HR, 0.45; CI, 0.35–0.59). Sensitivity analysis with TIA excluded rendered the similar trend. Subgroup analyses found that the positive effect was not demonstrated in hemorrhagic stroke patients. Conclusions: Rehabilitation use was associated with reduction of readmissions/mortality risks following stroke or TIA. The optimal intensity and duration of rehabilitation and the discrepancy shown in hemorrhagic stroke need further clarification.
Evaluating word semantic properties using Sketch Engine

The paper describes approach to use statistically-based tools incorporated into Sketch Engine system for electronic text corpora processing to mining big textual data for search and extract word semantic properties. It presents and compares series of word search experiments using different statistical approaches and evaluates results for Bulgarian language EUROPARL 7 Corpus search to extract word semantic properties. Finally, the methodology is extended for multilingual application using Slovak language EUROPARL 7 Corpus.
Extracellular Matrix Density Regulates Extracellular Proteolysis via Modulation of Cellular Contractility

The Extracellular Matrix (ECM) undergoes changes in composition and organization during tumor progression. In breast cancer, increased deposition and cross linking-induced alignment of collagen I create a stiffer microenvironment that directly contributes to cancer invasion. While ECM stiffness-induced invasion has been documented, it remains unclear if ECM density also contributes to invasion independent of ECM stiffness. In this paper, using collagen I-coated glass coverslips of varying density, we sought to study the influence of ECM density on the invasiveness of human MDA-MB-231 breast cancer cells. We first showed that cell spreading and contractility increases with ECM density. Concomitant with increase in cell contractility, matrix degradation was seen to increase with ECM density and was associated with higher invadopodia activity. The density-dependent increase in degradation was associated with higher activity of MMP-2, MMP-9 and MT1-MMP. Treatment with either the MMP inhibitor GM6001 or the myosin II inhibitor blebbistatin, were found to inhibit cell contractility and suppress matrix degradation. Contractility was found to modulate the activity of MMP-2 and MMP-9, and the localization of MT1-MMP at invadopodia. Taken together, our results indicate that ECM density regulates ECM degradation through modulation of cell contractility.
Bioinformatics in Latin America and SoIBio impact, a tale of spin-off and expansion around genomes and protein structures

Abstract Owing to the emerging impact of bioinformatics and computational biology, in this article, we present an overview of the history and current state of the research on this field in Latin America (LA). It will be difficult to cover without inequality all the efforts, initiatives and works that have happened for the past two decades in this vast region (that includes >19 million km2 and >600 million people). Despite the difficulty, we have done an analytical search looking for publications in the field made by researchers from 19 LA countries in the past 25 years. In this way, we find that research in bioinformatics in this region should develop twice to approach the average world scientific production in the field. We also found some of the pioneering scientists who initiated and led bioinformatics in the region and were promoters of this new scientific field. Our analysis also reveals that spin-off began around some specific areas within the biomolecular sciences: studies on genomes (anchored in the new generation of deep sequencing technologies, followed by developments in proteomics) and studies on protein structures (supported by three-dimensional structural determination technologies and their computational advancement). Finally, we show that the contribution to this endeavour of the Iberoamerican Society for Bioinformatics, founded in Mexico in 2009, has been significant, as it is a leading forum to join efforts of many scientists from LA interested in promoting research, training and education in bioinformatics.
Detecting the Immune System Response of a 500 Year-Old Inca Mummy

Disease detection in historical samples currently relies on DNA extraction and amplification, or immunoassays. These techniques only establish pathogen presence rather than active disease. We report the first use of shotgun proteomics to detect the protein expression profile of buccal swabs and cloth samples from two 500-year-old Andean mummies. The profile of one of the mummies is consistent with immune system response to severe pulmonary bacterial infection at the time of death. Presence of a probably pathogenic Mycobacterium sp. in one buccal swab was confirmed by DNA amplification, sequencing, and phylogenetic analyses. Our study provides positive evidence of active pathogenic infection in an ancient sample for the first time. The protocol introduced here is less susceptible to contamination than DNA-based or immunoassay-based studies. In scarce forensic samples, shotgun proteomics narrows the range of pathogens to detect using DNA assays, reducing cost. This analytical technique can be broadly applied for detecting infection in ancient samples to answer questions on the historical ecology of specific pathogens, as well as in medico-legal cases when active pathogenic infection is suspected.
Symmetric Indefinite Linear Solver Using OpenMP Task on Multicore Architectures

Recently, the Open Multi-Processing (OpenMP) standard has incorporated task-based programming, where a function call with input and output data is treated as a task. At run time, OpenMP’s superscalar scheduler tracks the data dependencies among the tasks and executes the tasks as their dependencies are resolved. On a shared-memory architecture with multiple cores, the independent tasks are executed on different cores in parallel, thereby enabling parallel execution of a seemingly sequential code. With the emergence of many-core architectures, this type of programming paradigm is gaining attention—not only because of its simplicity, but also because it breaks the artificial synchronization points of the program and improves its thread-level parallelization. In this paper, we use these new OpenMP features to develop a portable high-performance implementation of a dense symmetric indefinite linear solver. Obtaining high performance from this kind of solver is a challenge because the symmetric pivoting, which is required to maintain numerical stability, leads to data dependencies that prevent us from using some common performance-improving techniques. To fully utilize a large number of cores through tasking, while conforming to the OpenMP standard, we describe several techniques. Our performance results on current many-core architectures—including Intel’s Broadwell, Intel’s Knights Landing, IBM’s Power8, and Arm’s ARMv8—demonstrate the portable and superior performance of our implementation compared with the Linear Algebra PACKage (LAPACK). The resulting solver is now available as a part of the PLASMA software package.
Fluid Therapy and Acute Kidney Injury: A Question of Balance?

Fluid therapy remains one of the fundamental treatment options available for patients with acute kidney injury. However, there remains debate over several aspects of this treatment with many questions unanswered. Firstly, how do we prescribe fluid in this group of patients? Secondly, what is the role of fluid therapy in patients with or at risk of developing acute kidney injury and thirdly, what role does fluid balance play, if any, in the development of acute kidney injury. The following narrative review will attempt to tie some of the aspects of the treatment of this devastating syndrome together and formulate an overall hypothesis for fluid management in acute kidney injury.
Usefulness of a Rapid Real-time PCR Assay in Prenatal Screening for Group B Streptococcus Colonization

Background Group B streptococcus (GBS) infection is a leading cause of neonatal morbidity and mortality worldwide. Here, we present the analytical and diagnostic usefulness of a new real-time PCR-based assay (Xpert GBS; Cepheid, USA) for rapid and accurate prenatal GBS screening. Methods We enrolled 175 pregnant women who were between 35 and 39 weeks of gestation. The analytical performance of the Xpert GBS assay was first tested using a reference GBS strain. Next, to test diagnostic performance, rectovaginal swabs were obtained from pregnant women who visited the hospital for regular antenatal screening after 34 weeks of gestation. The results of the Xpert GBS assay were compared to those of standard culture for the detection of prenatal GBS colonization. Results When any positive result from Xpert GBS or culture was considered a true positive, the sensitivity of the Xpert GBS assay and culture were 91% (20/22; 95% CI [confidence interval], 72-98) and 68% (15/22; 95% CI, 47-84), respectively. The specificity of both methods was 100% (153/153; 95% CI, 97-100). The sensitivity and specificity of the Xpert GBS assay, using the culture results as a reference, were 86.7% and 95.6%, respectively. In the Xpert GBS assay, the median threshold cycle of vaginally colonized samples was significantly lower than rectally colonized samples (P<0.01). Conclusions The Xpert GBS assay is an accurate, rapid, easy-to-use test for the detection of maternal GBS colonization in prenatal screening that might be especially useful in clinical settings where standard culture is not feasible.
Blockade of Attachment and Fusion Receptors Inhibits HIV-1 Infection of Human Cervical Tissue

Identification of cellular factors involved in HIV-1 entry and transmission at mucosal surfaces is critical for understanding viral pathogenesis and development of effective prevention strategies. Here we describe the evaluation of HIV-1 entry inhibitors for their ability to prevent infection of, and dissemination from, human cervical tissue ex vivo. Blockade of CD4 alone or CCR5 and CXCR4 together inhibited localized mucosal infection. However, simultaneous blockade of CD4 and mannose-binding C-type lectin receptors including dendritic cell–specific intercellular adhesion molecule–grabbing integrin was required to inhibit HIV-1 uptake and dissemination by migratory cells. In contrast, direct targeting of HIV-1 by neutralizing mAb b12 and CD4-IgG2 (PRO-542) blocked both localized infection and viral dissemination pathways. Flow cytometric analysis and immunostaining of migratory cells revealed two major populations, CD3+HLA-DR− and CD3−HLA-DR+ cells, with a significant proportion of the latter also expressing dendritic cell–specific intercellular adhesion molecule–grabbing integrin. Bead depletion studies demonstrated that such HLA-DR+ cells accounted for as much as 90% of HIV-1 dissemination. Additional studies using immature monocyte-derived dendritic cells demonstrated that although mannose-binding C-type lectin receptors and CD4 are the principal receptors for gp120, other mechanisms may account for virus capture. Our identification of the predominant receptors involved in HIV-1 infection and dissemination within human cervical tissue highlight important targets for microbicide development.
ISSCC 2017 / SESSION 3 / DIGITAL PROCESSORS / 3 . 7 3 . 7 A 1920 × 1080 30 fps 2 . 3 TOPS / W Stereo-Depth Processor for Robust Autonomous

Precise depth estimation is a key kernel function to realizing autonomous navigation on micro-aerial vehicles (MAVs). The state-of-the-art semi-global matching (SGM) algorithm has become favored for its high accuracy. In particular, it effectively handles low texture regions due to its global optimization of the disparity between a left and right image over the entire frame. However, SGM involves massively parallel computation (~2TOP/s) and extremely high bandwidth memory access (38.6Tb/s) for 30fps HD resolution. This leads to ~20s runtime for an HD image pair on a 3GHz CPU [1] requiring ~386MB memory and >35W power consumption. Together, these factors place it well outside the realm of MAVs. Prior ASIC implementations have used either simpler local methods [2] or aggressively truncated global algorithms [3] that produce a depth map with significantly inferior quality or limited disparity range (32 or 64 pixels) and therefore fail to support standard automotive scene benchmarks [2-5]. In addition, due to the high memory requirement of SGM, prior methods [3-4] have used external DRAM to store intermediate computation, significantly reducing performance and efficiency.