Miracle-dz/UniFAR-FTUs huggingface dataset:
Lineage A Betacoronavirus NS2 Proteins and the Homologous Torovirus Berne pp1a Carboxy-Terminal Domain Are Phosphodiesterases That Antagonize Activation of RNase L

ABSTRACT Viruses in the family Coronaviridae, within the order Nidovirales, are etiologic agents of a range of human and animal diseases, including both mild and severe respiratory diseases in humans. These viruses encode conserved replicase and structural proteins as well as more diverse accessory proteins, encoded in the 3′ ends of their genomes, that often act as host cell antagonists. We previously showed that 2′,5′-phosphodiesterases (2′,5′-PDEs) encoded by the prototypical Betacoronavirus, mouse hepatitis virus (MHV), and by Middle East respiratory syndrome-associated coronavirus antagonize the oligoadenylate-RNase L (OAS-RNase L) pathway. Here we report that additional coronavirus superfamily members, including lineage A betacoronaviruses and toroviruses infecting both humans and animals, encode 2′,5′-PDEs capable of antagonizing RNase L. We used a chimeric MHV system (MHVMut) in which exogenous PDEs were expressed from an MHV backbone lacking the gene for a functional NS2 protein, the endogenous RNase L antagonist. With this system, we found that 2′,5′-PDEs encoded by the human coronavirus HCoV-OC43 (OC43; an agent of the common cold), human enteric coronavirus (HECoV), equine coronavirus (ECoV), and equine torovirus Berne (BEV) are enzymatically active, rescue replication of MHVMut in bone marrow-derived macrophages, and inhibit RNase L-mediated rRNA degradation in these cells. Additionally, PDEs encoded by OC43 and BEV rescue MHVMut replication and restore pathogenesis in wild-type (WT) B6 mice. This finding expands the range of viruses known to encode antagonists of the potent OAS-RNase L antiviral pathway, highlighting its importance in a range of species as well as the selective pressures exerted on viruses to antagonize it. IMPORTANCE Viruses in the family Coronaviridae include important human and animal pathogens, including the recently emerged viruses severe acute respiratory syndrome-associated coronavirus (SARS-CoV) and Middle East respiratory syndrome-associated coronavirus (MERS-CoV). We showed previously that two viruses within the genus Betacoronavirus, mouse hepatitis virus (MHV) and MERS-CoV, encode 2′,5′-phosphodiesterases (2′,5′-PDEs) that antagonize the OAS-RNase L pathway, and we report here that these proteins are furthermore conserved among additional coronavirus superfamily members, including lineage A betacoronaviruses and toroviruses, suggesting that they may play critical roles in pathogenesis. As there are no licensed vaccines or effective antivirals against human coronaviruses and few against those infecting animals, identifying viral proteins contributing to virulence can inform therapeutic development. Thus, this work demonstrates that a potent antagonist of host antiviral defenses is encoded by multiple and diverse viruses within the family Coronaviridae, presenting a possible broad-spectrum therapeutic target.
Characterisation of Nox4 Inhibitors from Edible Plants

Abstract NADPH oxidases transport electrons from cytosolic NADPH through biological membranes to generate reactive oxygen species. NADPH oxidase 4, broadly expressed in humans, is an interesting pharmacological target, since its activity is deregulated in several diseases, including pulmonary fibrosis, diabetic nephropathy, and cardiac hypertrophy. Whereas several candidate NADPH oxidase 4 inhibitors were recently described, most of these compounds are either unspecific or toxic. Here we set out to identify new NADPH oxidase 4 inhibitors from edible plants, in an attempt to decrease the number of hits with toxic side effects. We screened a compound library prepared from edible plants for new bioactives with the ability to inhibit the activity of NADPH oxidase 4. Using both cell-based and cell-free assays, we identified several compounds with significant inhibitory activity towards NADPH oxidase 4. For selected compounds, the activity profile towards NADPH oxidase 2 and NADPH oxidase 5 was established, and controls were carried out to exclude general reactive oxygen species scavengers. A number of promising NADPH oxidase 4 inhibitors from edible plants was identified and characterised. Several new chemical entities are disclosed which act as NADPH oxidase 4 inhibitors, and the efficacies of our best hits, in particular several diarylheptanoids and lignans, are comparable to the best available pharmacological NADPH oxidase 4 inhibitors. These findings will provide valuable tools to study mechanisms of NADPH oxidase inhibition.
A SOA based context-aware order picking system for warehouses using Laser Range Finder and wearable computer

This paper describes the architectural details and advantages of a SOA based context-aware order picking system, which was developed within the framework of SiWear, a German national funded project by the Federal Ministry of Economics and Technology (BMWi) for the production plants cum warehouses of the automobile manufacturing industries. The pivotal components of order picking system are a wearable computer with Head Mounted Display and a Hokoyu URG-04LX Laser Range Finder, which are used for the context-awareness in terms of computing not only the user's hand/arm interaction with the shelf, but the correct box number from where the user should pick the desired number of items. The complete system was evaluated during an exhaustive user study and the results are intuitive enough to be leveraged and generalized for the production plants cum warehouses of any industry.
Deep Convolutional Neural Network for Facial Expression Recognition Using Facial Parts

This paper proposes the design of a Facial Expression Recognition (FER) system based on deep convolutional neural network by using facial parts. In this work, a simple solution for facial expression recognition that uses a combination of algorithms for face detection, feature extraction and classification is discussed. The proposed method uses a two-channel convolutional neural network in which Facial Parts (FPs) are used as input to the first convolutional layer, the extracted eyes are used as input to the first channel while the mouth is the input into the second channel. Information from both channels converges in a fully connected layer which is used to learn global information from these local features and is then used for classification. Experiments are carried out on the Japanese Female Facial Expression (JAFFE) and the Extended Cohn-Kanada (CK+) datasets to determine the recognition accuracy for the proposed FER system. The results achieved shows that the system provides improved classification accuracy when compared to other methods.
An Innovative Method to Classify Remote-Sensing Images Using Ant Colony Optimization

This paper presents a new method to improve the classification performance for remote-sensing applications based on swarm intelligence. Traditional statistical classifiers have limitations in solving complex classification problems because of their strict assumptions. For example, data correlation between bands of remote-sensing imagery has caused problems in generating satisfactory classification using statistical methods. In this paper, ant colony optimization (ACO), based upon swarm intelligence, is used to improve the classification performance. Due to the positive feedback mechanism, ACO takes into account the correlation between attribute variables, thus avoiding issues related to band correlation. A discretization technique is incorporated in this ACO method so that classification rules can be induced from large data sets of remote-sensing images. Experiments of this ACO algorithm in the Guangzhou area reveal that it yields simpler rule sets and better accuracy than the See 5.0 decision tree method.
Parental Feeding Style and Pediatric Obesity in Latino Families

Introduction: Pediatric obesity has become an epidemic in the United States. Previous research has shown that parenting factors related to feeding style affect child weight and that Latino families are especially at risk for pediatric obesity. The goal of the current study was to evaluate the relationship between parental feeding style and child body mass index (BMI) in Latino families. Method: Latino parents of children between the ages of 2 and 8 (N = 124) completed a survey on parental feeding styles, acculturation, and demographics. The outcome variable was child BMI. Results: Among respondents, 89% were mothers, 72% were overweight or obese, and 40% reported an indulgent feeding style. Children had a mean age of 59 months (SD = 23.8) and a mean BMI z score of 0.77 (SD = 1.14). A demanding parental feeding style was associated with lower child BMI z score, r = −. 179, p < . 05, and higher acculturation level, r = . 213, p < . 05. Conclusions: Findings from the current study can be used to inform health care practitioners of the need to use culturally sensitive interventions that consider parents’ feeding behaviors. Future research is warranted in the area of ethnic variations of parenting and how these affect feeding and obesity in this highly vulnerable population.
Cone beam CT pre‐ and post‐daily treatment for assessing geometrical and dosimetric intrafraction variability during radiotherapy of prostate cancer

The purpose of this study was to quantify the relationship between treatment time and dose uncertainty due to intrafraction organ motion in prostate cancer radiotherapy (RT). Ten consecutive patients with prostate cancer treated by radical RT by volumetric modulated arc therapy (RapidArc) were considered. For each patient, pre‐ and post‐treatment cone beam computed tomography (CBCT) was performed in 10 fractions. The prostate, rectum and bladder were contoured on each CBCT. The change in organ position, volume and dosimetric uncertainty induced by organ motion were evaluated. Interval time between the two CBCTs ranged between 4 and 16 min (mean 7.3±0.7 min). Treatment with intrafraction prostate motion > 3 mm and > 5 mm were 24% and 5%, respectively. Regarding change in centroid position and volume, a poor time correlation was found for target and rectum, while a constant increase was obtained for bladder. The agreement index was highly correlated to time (r=−0.89 for bladder, r=−0.95 for rectum, and r=−0.84 for prostate). In terms of difference in dose volume histogram between pre‐ and post‐CBCT, the dose uncertainties for the targets and rectum amplified with the increasing time. The increasing intrafraction dose uncertainty with time requires the use of an RT technique with minimization of treatment time to improve confidence in planning dose distribution. PACS number: 87.55. tm
Unsupervised Correlation Analysis

Linking between two data sources is a basic building block in numerous computer vision problems. In this paper, we set to answer a fundamental cognitive question: are prior correspondences necessary for linking between different domains? One of the most popular methods for linking between domains is Canonical Correlation Analysis (CCA). All current CCA algorithms require correspondences between the views. We introduce a new method Unsupervised Correlation Analysis (UCA), which requires no prior correspondences between the two domains. The correlation maximization term in CCA is replaced by a combination of a reconstruction term (similar to autoencoders), full cycle loss, orthogonality and multiple domain confusion terms. Due to lack of supervision, the optimization leads to multiple alternative solutions with similar scores and we therefore introduce a consensus-based mechanism that is often able to recover the desired solution. Remarkably, this suffices in order to link remote domains such as text and images. We also present results on well accepted CCA benchmarks, showing that performance far exceeds other unsupervised baselines, and approaches supervised performance in some cases.
A simple modern correctness condition for a space-based high-performance multiprocessor

A number of U.S. national programs, including space-based detection of ballistic missile launches, envisage putting significant computing power into space. Given sufficient progress in low-power VLSI, multichip-module packaging and liquid-cooling technologies, we will see design of high-performance multiprocessors for individual satellites. In very high speed implementations, performance depends critically on tolerating large latencies in interprocessor communication; without latency tolerance, performance is limited by the vastly differing time scales in processor and data-memory modules, including interconnect times. The modern approach to tolerating remote-communication cost in scalable, shared-memory multiprocessors is to use a multithreaded architecture, and alter the semantics of shared memory slightly, at the price of forcing the programmer either to reason about program correctness in a relaxed consistency model or to agree to program in a constrained style. The literature on multiprocessor correctness conditions has become increasingly complex, and sometimes confusing, which may hinder its practical application. We propose a simple modern correctness condition for a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and the parallel programming system.
An Active Diode Full-Wave Charge Pump for Low Acceleration Infrastructure-Based Non-Periodic Vibration Energy Harvesting

An active diode IC-based full-wave charge pump is presented. It interfaces to a vibration harvester designed for low acceleration non-periodic bridge vibrations. The charge pump’s unique architecture uses only two comparators to switch the charge pump’s eight stages. This architecture reduces power and allows for a novel passive diode switching technique that also enables a reduction in the turn-on voltage. This switching technique initially functions based only on the AC input without a DC supply. This architecture is used to enable cold start-up using the charge pump’s external <inline-formula> <tex-math notation="LaTeX">$100~{\mu }\text{F}$ </tex-math></inline-formula> capacitors. These large capacitors create a stable power supply for start-up from one low voltage AC input based off of bridge vibrations that are random and infrequent. Its rectification circuitry is fabricated in 180 nm CMOS on a 1.2 mm<sup>2</sup> die. The circuit inputs, generated using a shaker table, are periodic sine-waves or non-periodic mechanical frequency up-converted vibration harvester outputs. Measurements show that the diode drop reduction allows cold start-up and boosting to >1.5 V with low power (<inline-formula> <tex-math notation="LaTeX">$\sim 8.5~{\mu }\text{W}$ </tex-math></inline-formula>) non-periodic harvester outputs or 220 mV open circuit voltage periodic (~100 Hz) inputs. This IC demonstrates ~50% efficiency with an up-conversion-based harvester and <inline-formula> <tex-math notation="LaTeX">${\sim } 1~{\mu }\text{W}$ </tex-math></inline-formula> active power dissipation.
Vertex-Specific Proteins pUL17 and pUL25 Mechanically Reinforce Herpes Simplex Virus Capsids

ABSTRACT Using atomic force microscopy imaging and nanoindentation measurements, we investigated the effect of the minor capsid proteins pUL17 and pUL25 on the structural stability of icosahedral herpes simplex virus capsids. pUL17 and pUL25, which form the capsid vertex-specific component (CVSC), particularly contributed to capsid resilience along the 5-fold and 2-fold but not along the 3-fold icosahedral axes. Our detailed analyses, including quantitative mass spectrometry of the protein composition of the capsids, revealed that both pUL17 and pUL25 are required to stabilize the capsid shells at the vertices. This indicates that herpesviruses withstand the internal pressure that is generated during DNA genome packaging by locally reinforcing the mechanical sturdiness of the vertices, the most stressed part of the capsids. IMPORTANCE In this study, the structural, material properties of herpes simplex virus 1 were investigated. The capsid of herpes simplex virus is built up of a variety of proteins, and we scrutinized the influence of two of these proteins on the stability of the capsid. For this, we used a scanning force microscope that makes detailed, topographic images of the particles and that is able to perform mechanical deformation measurements. Using this approach, we revealed that both studied proteins play an essential role in viral stability. These new insights support us in forming a complete view on viral structure and furthermore could possibly help not only to develop specific antivirals but also to build protein shells with improved stability for drug delivery purposes.
Measles outbreak linked to European B3 outbreaks, Wales, United Kingdom, 2017

The United Kingdom achieved interrupted endemic measles transmission for 36 months in 2016. Despite this, ongoing challenges from sporadic measles cases typically imported from abroad remain. We summarise a B3 measles genotype outbreak in south-east Wales occurring between May and September 2017, linked with other European outbreaks, and lessons learnt. Seventeen confirmed cases and one probable case occurred principally in education and healthcare-settings. Six confirmed cases attended healthcare settings when infectious, without being isolated.
Activity in Face-Responsive Brain Regions is Modulated by Invisible, Attended Faces: Evidence from Masked Priming

It is often assumed that neural activity in face-responsive regions of primate cortex correlates with conscious perception of faces. However, whether such activity occurs without awareness is still debated. Using functional magnetic resonance imaging (fMRI) in conjunction with a novel masked face priming paradigm, we observed neural modulations that could not be attributed to perceptual awareness. More specifically, we found reduced activity in several classic face-processing regions, including the “fusiform face area,” “occipital face area,” and superior temporal sulcus, when a face was preceded by a briefly flashed image of the same face, relative to a different face, even when 2 images of the same face differed. Importantly, unlike most previous studies, which have minimized awareness by using conditions of inattention, the present results occurred when the stimuli (the primes) were attended. By contrast, when primes were perceived consciously, in a long-lag priming paradigm, we found repetition-related activity increases in additional frontal and parietal regions. These data not only demonstrate that fMRI activity in face-responsive regions can be modulated independently of perceptual awareness, but also document where such subliminal face-processing occurs (i.e., restricted to face-responsive regions of occipital and temporal cortex) and to what extent (i.e., independent of the specific image).
A Comparison of Hash-Based Methods for Trajectory Clustering

The development of location-acquisition technologies has led to the emergence of massive spatial trajectory data. Recently many researchers have focused on techniques related to processing, managing and mining trajectories to extract knowledge and predictions useful for various applications. One of the first steps in processing trajectories is clustering and classification. Hash-based methods have been used and showed to be successful in clustering the large trajectory datasets. In this paper, we specifically focus on methods based on two types of hash functions: Locality-Sensitive and Distance-Based hash functions and compare them in terms of accuracy and bucket size balance. Our results suggest that, in comparison to Distance- Based hashes, Locality-Sensitive hashes results in higher accuracy but not necessarily higher bucket balance.
A Review on Methods for Detecting SNP Interactions in High-Dimensional Genomic Data

In this era of genome-wide association studies (GWAS), the quest for understanding the genetic architecture of complex diseases is rapidly increasing more than ever before. The development of high throughput genotyping and next generation sequencing technologies enables genetic epidemiological analysis of large scale data. These advances have led to the identification of a number of single nucleotide polymorphisms (SNPs) responsible for disease susceptibility. The interactions between SNPs associated with complex diseases are increasingly being explored in the current literature. These interaction studies are mathematically challenging and computationally complex. These challenges have been addressed by a number of data mining and machine learning approaches. This paper reviews the current methods and the related software packages to detect the SNP interactions that contribute to diseases. The issues that need to be considered when developing these models are addressed in this review. The paper also reviews the achievements in data simulation to evaluate the performance of these models. Further, it discusses the future of SNP interaction analysis.