Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of 4 Point‐of‐Care Screening Tests for Feline Leukemia Virus and Feline Immunodeficiency Virus

Background More than 3 million cats in the United States are infected with FeLV or FIV. The cornerstone of control is identification and segregation of infected cats. Hypothesis/Objectives To compare test performance with well‐characterized clinical samples of currently available FeLV antigen/FIV antibody combination test kits. Animals Surplus serum and plasma from diagnostic samples submitted by animal shelters, diagnostic laboratories, veterinary clinics, and cat research colonies. None of the cats had been vaccinated against FIV. The final sample set included 146 FeLV+, 154 FeLV−, 94 FIV+, and 97 FIV− samples. Methods Prospective, blind comparison to a gold standard: Samples were evaluated in 4 different point‐of‐care tests by ELISA antigen plate tests (FeLV) and virus isolation (FIV) as the reference standards. All test results were visually read by 2 blinded observers. Results Sensitivity and specificity, respectively, for FeLV were SNAP ® (100%/100%), WITNESS ® (89.0%/95.5%), Anigen® (91.8%/95.5%), and VetScan® (85.6%/85.7%). Sensitivity and specificity for FIV were SNAP ® (97.9%/99.0%), WITNESS ® (94.7%/100%), Anigen® (96.8%/99.0%), and VetScan® (91.5%/99.0%). Conclusions and Clinical Importance The SNAP ® test had the best performance for FeLV, but there were no significant differences for FIV. In typical cat populations with seroprevalence of 1–5%, a majority of positive results reported by most point‐of‐care test devices would be false‐positives. This could result in unnecessary segregation or even euthanasia.
Pooled Analysis of HCV Genotype 1 Resistance-Associated Substitutions in NS5A, NS3 and NS5B pre- and Post-Treatment with 12 Weeks of Daclatasvir, Asunaprevir and Beclabuvir

Background Daclatasvir (DCV; non-structural [NS]5A inhibitor) plus asunaprevir (ASV; NS3 inhibitor) plus beclabuvir (BCV; non-nucleoside NS5B inhibitor) is an approved regimen for hepatitis C virus (HCV) genotype (GT)-1 treatment in Japan. A comprehensive analysis of pre-treatment and treatment-emergent HCV resistance to this regimen ± ribavirin (RBV) was performed. Methods Data were pooled from five Phase 2/3 studies of DCV+ASV+BCV±RBV given for 12 weeks to GT-1a- or GT-1b-infected patients. The prevalence and impact of pre-treatment resistance-associated substitutions (RAS) in NS5A, NS3, and NS5B on sustained virological response (SVR) was assessed, as were emergent RAS and their post-treatment persistence. Results Baseline NS5A RAS (GT-1a: M28T, Q30H/L/R/S, L31M, Y93C/H; GT-1b: L31I/M, Y93C/H) were present in 5% (26/561) of GT-1a and 16% (85/537) of GT-1b sequences. SVR12 for GT-1b without RBV was 100% (82/82) with RAS and >99% (427/428) without RAS. For GT-1a, SVR12 without RAS was 97% (85/88) with RBV and 92% (410/447) without RBV; SVR12 with RAS was 100% (2/2) with RBV and 54% (13/24) without RBV. Baseline NS3 (at R155 or D168) and NS5B (at P495) RAS were rare (≤1%). Treatment-emergent NS5A RAS (mostly Q30E/H/K/R+Y93H/N) in GT-1a persisted 60 weeks post-treatment, while NS3 RAS (mostly R155K) and NS5B-P495L/S were no longer detected after 48 or 24 weeks, respectively. Conclusions DCV+ASV+BCV+RBV was highly efficacious in HCV GT-1 infection, including HCV GT-1b with NS5A RAS. The fitness of treatment-emergent RAS post-treatment was NS5A > NS3 > NS5B; NS3 and NS5B RAS were generally replaced by wild-type sequence within 48 weeks.
Interrogating Genes That Mediate Chlamydia trachomatis Survival in Cell Culture Using Conditional Mutants and Recombination

ABSTRACT Intracellular bacterial pathogens in the family Chlamydiaceae are causes of human blindness, sexually transmitted disease, and pneumonia. Genetic dissection of the mechanisms of chlamydial pathogenicity has been hindered by multiple limitations, including the inability to inactivate genes that would prevent the production of elementary bodies. Many genes are also Chlamydia-specific genes, and chlamydial genomes have undergone extensive reductive evolution, so functions often cannot be inferred from homologs in other organisms. Conditional mutants have been used to study essential genes of many microorganisms, so we screened a library of 4,184 ethyl methanesulfonate-mutagenized Chlamydia trachomatis isolates for temperature-sensitive (TS) mutants that developed normally at physiological temperature (37°C) but not at nonphysiological temperatures. Heat-sensitive TS mutants were identified at a high frequency, while cold-sensitive mutants were less common. Twelve TS mutants were mapped using a novel markerless recombination approach, PCR, and genome sequencing. TS alleles of genes that play essential roles in other bacteria and chlamydia-specific open reading frames (ORFs) of unknown function were identified. Temperature-shift assays determined that phenotypes of the mutants manifested at distinct points in the developmental cycle. Genome sequencing of a larger population of TS mutants also revealed that the screen had not reached saturation. In summary, we describe the first approach for studying essential chlamydial genes and broadly applicable strategies for genetic mapping in Chlamydia spp. and mutants that both define checkpoints and provide insights into the biology of the chlamydial developmental cycle. IMPORTANCE Study of the pathogenesis of Chlamydia spp. has historically been hampered by a lack of genetic tools. Although there has been recent progress in chlamydial genetics, the existing approaches have limitations for the study of the genes that mediate growth of these organisms in cell culture. We used a genetic screen to identify conditional Chlamydia mutants and then mapped these alleles using a broadly applicable recombination strategy. Phenotypes of the mutants provide fundamental insights into unexplored areas of chlamydial pathogenesis and intracellular biology. Finally, the reagents and approaches we describe are powerful resources for the investigation of these organisms.
Velocity-Level Control With Compliance to Acceleration-Level Constraints: A Novel Scheme for Manipulator Redundancy Resolution

Manipulators are subject to physical constraints at different levels, i.e., joint angle limits, joint velocity limits, and acceleration limits. Effective resolution of redundant manipulators with compliance to the physical constraints is a fundamental issue for safe operation. Existing results generally resolve the manipulator redundancy either at the velocity level or the acceleration level. On the one hand, the velocity-level redundancy resolution scheme is able to deal with the joint angle and joint velocity limits successfully but cannot address the joint acceleration limit. On the other hand, although the existing acceleration-level redundancy resolution scheme is able to overcome the failure of the velocity-level one in complying with acceleration constraints, it is at the cost of making the system equation more complicated, e.g., the dependence on the time derivative of the Jacobian matrix. Whether it is possible to conduct redundancy resolution at the velocity level but with the compliance to joint angle constraints, joint velocity constraints, and joint acceleration constraints remains an open problem in past decades. This paper gives a positive answer to this pending problem by providing a novel scheme. In the proposed scheme, the redundancy resolution problem is formulated as a quadratic program subject to joint angle, velocity, and acceleration constraints with the joint velocity being the decision variable and joint velocity norm as the performance index, which is widely adopted and closely related to the energy consumption. Then, a projection neural network is designed and proposed to online solve the problem with the joint acceleration constraint handled. Theoretical analysis is performed to guarantee the global convergence of the proposed projection neural network to the optimal solution to the redundancy resolution problem. Besides, simulation results based on a PUMA 560 industrial manipulator are presented and compared to verify the theoretical result and substantiate the efficacy and superiority of the proposed scheme.
Differences in game reading between selected and non-selected youth soccer players

ABSTRACT Applying an established theory of cognitive development―Skill Theory―the current study compares the game-reading skills of youth players selected for a soccer school of a professional soccer club (n = 49) and their non-selected peers (n = 38). Participants described the actions taking place in videos of soccer game plays, and their verbalisations were coded using Skill Theory. Compared to the non-selected players, the selected players generally demonstrated higher levels of complexity in their game-reading, and structured the information of game elements―primarily the player, teammate and field―at higher complexity levels. These results demonstrate how Skill Theory can be used to assess, and distinguish game-reading of youth players with different expertise, a skill important for soccer, but also for other sports.
Whole Grain and Legume Acceptability Among Youths With Type 1 Diabetes

Purpose This pilot study investigated the acceptability of whole grain and legume foods in youths with type 1 diabetes and determined demographic and behavioral factors associated with their acceptability. Methods Youths with type 1 diabetes (7.0 to 16.9 years) were recruited during a diabetes camp and completed self-report measures of food acceptability, eating behaviors, and demographics. An overall acceptability score for whole grains and for legumes was calculated as the sum of foods in each category rated as either “tried and liked” or “not tried and willing to try. ” Correlations of whole grain and legume acceptability with demographic characteristics were examined. Results One hundred twenty-eight youths participated (70% females, mean age 11.6 ± 2.3 years). Whole grain foods with the highest acceptability were corn bread (85% tried/ liked and 11% willing to try) and whole wheat bread (72% tried/liked and 3% willing to try). Total whole grain acceptability was negatively associated with days per week of fast food consumption (r = —0.21; P < .02) and living in an urban environment (r = −0.24; P < .01). Chili with beans (66% tried/liked and 8% willing to try) and baked beans (57% tried/liked and 19% willing to try) were the legume-containing foods with the highest acceptability. There were no significant associations between demographic factors and total legume acceptability. Conclusions These findings demonstrate the variability in acceptability among whole grains and legumes in youths with type 1 diabetes and the importance of addressing acceptability when counseling youths or designing nutrition interventions to improve consumption of these foods.
Anxiety and Depression in Chronic Obstructive Pulmonary Disease: Recognition and Management

Anxiety and depression are common in patients with chronic obstructive pulmonary disease (COPD), occurring more frequently than in the general population[1][1]–[4][2] or patients with other chronic diseases such as hypertension, diabetes, cancer, or musculoskeletal disorders. [5][3],[6][4] Their
One new 1,4-napthoquinone derivative from the roots of Juglans mandshurica

Abstract A new 1,4-napthoquinone derivative, namely (S)-(-)-3-(8-hydroxy-1,4-dioxo-1,4-dihydro-naphthalen-2-yl)-3-(4-hydroxy-3-methoxyphenyl)-propionic acid methyl ester (1), was isolated from the roots of Juglans mandshurica Maxim. The structure was identified based on HR-ESI-MS, 1D and 2D NMR spectroscopic methods.
Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking

Deep neural networks have become a primary tool for solving problems in many fields. They are also used for addressing information retrieval problems and show strong performance in several tasks. Training these models requires large, representative datasets and for most IR tasks, such data contains sensitive information from users. Privacy and confidentiality concerns prevent many data owners from sharing the data, thus today the research community can only benefit from research on large-scale datasets in a limited manner. In this paper, we discuss privacy preserving mimic learning, i.e., using predictions from a privacy preserving trained model instead of labels from the original sensitive training data as a supervision signal. We present the results of preliminary experiments in which we apply the idea of mimic learning and privacy preserving mimic learning for the task of document re-ranking as one of the core IR tasks. This research is a step toward laying the ground for enabling researchers from data-rich environments to share knowledge learned from actual users' data, which should facilitate research collaborations.
A Multicast Routing Scheme for a Universal Spiking Neural Network Architecture

A multicast routing infrastructure is proposed as a core feature of SpiNNaker, a massively parallel computer for the real-time simulation of large-scale spiking neural networks. The infrastructure is implemented using a communications router, based on an event-driven routing scheme, on each multicore processing node in the system. The design considerations emphasize the difference between the requirements of neural network communications and those of conventional computer networks and on-chip networks. The focus of the design is on neural modelling flexibility, power-efficiency, fault-tolerance and the communication throughput of the router.
The impact of modifying photosystem antenna size on canopy photosynthetic efficiency—Development of a new canopy photosynthesis model scaling from metabolism to canopy level processes

Abstract Canopy photosynthesis (Ac) describes photosynthesis of an entire crop field and the daily and seasonal integrals of Ac positively correlate with daily and seasonal biomass production. Much effort in crop breeding has focused on improving canopy architecture and hence light distribution inside the canopy. Here, we develop a new integrated canopy photosynthesis model including canopy architecture, a ray tracing algorithm, and C3 photosynthetic metabolism to explore the option of manipulating leaf chlorophyll concentration ([Chl]) for greater Ac and nitrogen use efficiency (NUE). Model simulation results show that (a) efficiency of photosystem II increased when [Chl] was decreased by decreasing antenna size and (b) the light received by leaves at the bottom layers increased when [Chl] throughout the canopy was decreased. Furthermore, the modelling revealed a modest ~3% increase in Ac and an ~14% in NUE was accompanied when [Chl] reduced by 60%. However, if the leaf nitrogen conserved by this decrease in leaf [Chl] were to be optimally allocated to other components of photosynthesis, both Ac and NUE can be increased by over 30%. Optimizing [Chl] coupled with strategic reinvestment of conserved nitrogen is shown to have the potential to support substantial increases in Ac, biomass production, and crop yields.
Lateral, not medial, prefrontal cortex contributes to punishment and aversive instrumental learning

Aversive outcomes punish behaviors that cause their occurrence. The prefrontal cortex (PFC) has been implicated in punishment learning and behavior, although the exact roles for different PFC regions in instrumental aversive learning and decision-making remain poorly understood. Here, we assessed the role of the orbitofrontal (OFC), rostral agranular insular (RAIC), prelimbic (PL), and infralimbic (IL) cortex in instrumental aversive learning and decision-making. Rats that pressed two individually presented levers for pellet rewards rapidly suppressed responding to one lever if it also caused mild punishment (punished lever) but continued pressing the other lever that did not cause punishment (unpunished lever). Inactivations of OFC, RAIC, IL, or PL via the GABA agonists baclofen and muscimol (BM) had no effect on the acquisition of instrumental learning. OFC inactivations increased responding on the punished lever during expression of well-learned instrumental aversive learning, whereas RAIC inactivations increased responding on the punished lever when both levers were presented simultaneously in an unpunished choice test. There were few effects of medial PFC (PL and IL) inactivation. These results suggest that lateral PFC, notably OFC and RAIC, have complementary functions in aversive instrumental learning and decision-making; OFC is important for using established aversive instrumental memories to guide behavior away from actions that cause punishment, whereas RAIC is important for aversive decision-making under conditions of choice.
Novel local binary textural pattern for analysis and classification of mammogram using support vector machine

Breast cancer is one of the most devastating and deadly diseases for women. It is estimated that between one in eight and one in twelve women will develop breast cancer during their lifetime. The most convenient practical method to detect breast cancer is mammography, because it allows the detection of the cancer at its early stages, a crucial issue for a high survival rate. Mammography is the only technique that has demonstrated the ability to detect breast cancer at an early stage and with high sensitivity and specificity. The search for features in this kind of image is complicated by the higher frequency textural variations in image intensity. In this paper, we have proposed few novel local binary textural patterns for classification of mammogram which was found to have consistent accuracy rate.
PREPARATION OF REGENERATED BINDING MATERIAL USING WASTE CONCRETE

To improve the efficiency of waste concrete reutilization,a high efficiency method for separating and recycling the components of waste concrete was proposed.Regenerated binding materials(RBMs)were prepared by calcining the separated hardened cement powder at low temperatures.X-ray diffraction,scanning electron microscopy,compressive strength testing and other methods were used to investigate the mineral phase compositions and the hydration characteristics of RBM.The results show that the RBMs prepared at different temperatures have various compositions and structures,which is the essential reason for the change of their hydration reactivity.RBM prepared at 650 ℃ has a main mineral phase of β-C2S,and its hydration reactivity is excellent.
The Motor Signature of Mild Cognitive Impairment: Results From the Gait and Brain Study

Background. Early motor changes associated with aging predict cognitive decline, which suggests that a “motor signature” can be detected in predementia states. In line with previous research, we aim to demonstrate that individuals with mild cognitive impairment (MCI) have a distinct motor signature, and specifically, that dual-task gait can be a tool to distinguish amnestic (a-MCI) from nonamnestic MCI. Methods. Older adults with MCI and controls from the “Gait and Brain Study” were assessed with neurocognitive tests to assess cognitive performance and with an electronic gait mat to record temporal and spatial gait parameters. Mean gait velocity and stride time variability were evaluated under simple and three separate dual-task conditions. The relationship between cognitive groups (a-MCI vs nonamnestic MCI) and gait parameters was evaluated with linear regression models and adjusted for confounders. Results. Ninety-nine older participants, 64 MCI (mean age 76.3±7.1 years; 50% female), and 35 controls (mean age 70.4±3.9 years; 82.9% female) were included. Forty-two participants were a-MCI and 22 were nonamnestic MCI. Multivariable linear regression (adjusted for age, sex, physical activity level, comorbidities, and executive function) showed that a-MCI was significantly associated with slower gait and higher dual-task cost under dual-task conditions. Conclusion. Participants with a-MCI, specifically with episodic memory impairment, had poor gait performance, particularly under dual tasking. Our findings suggest that dual-task assessment can help to differentiate MCI subtyping, revealing a motor signature in MCI.
Haemostasis and innate immunity – a complementary relationship

Coagulation and innate immunity are linked evolutionary processes that orchestrate the host defence against invading pathogens and injury. The complement system is integral to innate immunity and shares numerous interactions with components of the haemostatic pathway, helping to maintain physiological equilibrium. The term ‘immunothrombosis’ was introduced in 2013 to embrace this process, and has become an area of much recent interest. What is less apparent in the literature however is an appreciation of the clinical manifestations of the coagulation‐complement interaction and the consequences of dysregulation of either system, as seen in many inflammatory and thrombotic disease states, such as sepsis, trauma, atherosclerosis, antiphospholipid syndrome (APS), paroxysmal nocturnal haemoglobinuria (PNH) and some thrombotic microangiopathies to name a few. The growing appreciation of this immunothrombotic phenomenon will foster the drive for novel therapies in these disease states, including anticoagulants as immunomodulators and targeted molecular therapies.
Totally Looks Like - How Humans Compare, Compared to Machines

Perceptual judgment of image similarity by humans relies on rich internal representations ranging from low-level features to high-level concepts, scene properties and even cultural associations. Existing methods and datasets attempting to explain perceived similarity use stimuli which arguably do not cover the full breadth of factors that affect human similarity judgments, even those geared toward this goal. We introduce a new dataset dubbed Totally-Looks-Like (TLL) after a popular entertainment website, which contains images paired by humans as being visually similar. The dataset contains 6016 image-pairs from the wild, shedding light upon a rich and diverse set of criteria employed by human beings. We conduct experiments to try to reproduce the pairings via features extracted from state-of-the-art deep convolutional neural networks, as well as additional human experiments to verify the consistency of the collected data. Even though we create conditions to artificially make the matching task increasingly easier, we show that machine-extracted representations perform very poorly in terms of reproducing the matching selected by humans. The results suggest future directions for improvement of learned image representations. Data and code will be available at https://sites.google. com/view/totally-looks-like-dataset.
Block DCT coefficients and histogram for image retrieval

Retrieving images automatically using low level visual feature is a challenging research topic for the last two decades. Due to the advancement in the digital image technology multimedia content over the internet is increasing every second and thus accurate image retrieval is very important. Color, Texture, Shape and spatial layout are the low level visual features in Content Based Image Retrieval. These low level visual features are used for image representation and retrieval in CBIR. In this paper content based image retrieval system using image features extracted by sub-block based Discrete Cosine Transform(DCT) coefficients in YUV color space and color Histogram in HSV color space is used. Low frequency component of the DCT preserve the most important image features. The block texture feature vector generated from DCT coefficients and color histogram features are trained and classified using Support Vector Machines (SVM). Here a 64 Dimensional DCT coefficient and 32 dimensional histogram is used as feature vector which is more compact hence retrieval is comparatively fast.