Miracle-dz/UniFAR-FTUs huggingface dataset:
A longitudinal observational study of the dynamics of Mycoplasma bovis antibodies in naturally exposed and diseased dairy cows.

Mycoplasma bovis is an important pathogen causing disease and substantial economic losses in cattle. However, knowledge of the dynamics of antibody responses in individual cows in the face of an outbreak is currently extremely limited. The use of commercial antibody tests to support clinical decision-making and for surveillance purposes is therefore challenging. Our objective was to describe the dynamics of M. bovis antibody responses in 4 Danish dairy herds experiencing an acute outbreak of M. bovis-associated disease, and to compare the antibody dynamics between dairy cows with different disease manifestations. A total of 120 cows were examined using a standardized clinical protocol and categorized into 4 disease groups: "mastitis," "systemic," "nonspecific," and "none. " Paired blood and milk samples were collected and tested using a commercial M. bovis antibody-detecting ELISA. Plots of raw data and generalized additive mixed models with cow and herd as random effects were used to describe serum and milk antibody dynamics relative to the estimated time of onset of clinical disease. Cows with mastitis had high optical density measurement (ODC%) of antibodies in both milk and serum at disease onset. The estimated mean ODC% in milk was below the manufacturer's cut-off for the other groups for the entire study period. The estimated mean serum ODC% in the "systemic" group was high at onset of disease and stayed above the cut-off until 65 d after disease onset. However, the lower 95% confidence interval (CI) for the mean ODC% was only above the manufacturer's cut-off between 7 and 17 d after onset of disease. The CI of the "systemic" and "none" groups did not overlap at any time between the day of disease onset and 65 d after disease onset, and the estimated mean ODC% for both the "nonspecific" and "none" groups were generally below the cut-off for the majority of the study period. In conclusion, the serum antibody responses were highly dynamic and showed a high level of variation between individual cows. This strongly suggests that serology is unlikely to be useful for individual diagnosis of M. bovis-associated disease in dairy cows. However, it might still be useful for herd- or group-level diagnosis. Antibodies in milk were only increased in cows with M. bovis mastitis, indicating that milk antibody measurements only have diagnostic utility for cows with mastitis.
Prefrontoparietal dysfunction during emotion regulation in anxiety disorder: a meta-analysis of functional magnetic resonance imaging studies

Objective Impairments in emotion regulation, and more specifically in cognitive reappraisal, are thought to play a key role in the pathogenesis of anxiety disorders. However, the available evidence on such deficits is inconsistent. To further illustrate the neurobiological underpinnings of anxiety disorder, the present meta-analysis summarizes functional magnetic resonance imaging (fMRI) findings for cognitive reappraisal tasks and investigates related brain areas. Methods We performed a comprehensive series of meta-analyses of cognitive reappraisal fMRI studies contrasting patients with anxiety disorder with healthy control (HC) subjects, employing an anisotropic effect-size signed differential mapping approach. We also conducted a subgroup analysis of medication status, anxiety disorder subtype, data-processing software, and MRI field strengths. Meta-regression was used to explore the effects of demographics and clinical characteristics. Eight studies, with 11 datasets including 219 patients with anxiety disorder and 227 HC, were identified. Results Compared with HC, patients with anxiety disorder showed relatively decreased activation of the bilateral dorsomedial prefrontal cortex (dmPFC), bilateral dorsal anterior cingulate cortex (dACC), bilateral supplementary motor area (SMA), left ventromedial prefrontal cortex (vmPFC), bilateral parietal cortex, and left fusiform gyrus during cognitive reappraisal. The subgroup analysis, jackknife sensitivity analysis, heterogeneity analysis, and Egger’s tests further confirmed these findings. Conclusions Impaired cognitive reappraisal in anxiety disorder may be the consequence of hypo-activation of the prefrontoparietal network, consistent with insufficient top-down control. Our findings provide robust evidence that functional impairment in prefrontoparietal neuronal circuits may have a significant role in the pathogenesis of anxiety disorder.
Meta-learning with differentiable closed-form solvers

Adapting deep networks to new concepts from a few examples is challenging, due to the high computational requirements of standard fine-tuning procedures. Most work on few-shot learning has thus focused on simple learning techniques for adaptation, such as nearest neighbours or gradient descent. Nonetheless, the machine learning literature contains a wealth of methods that learn non-deep models very efficiently. In this paper, we propose to use these fast convergent methods as the main adaptation mechanism for few-shot learning. The main idea is to teach a deep network to use standard machine learning tools, such as ridge regression, as part of its own internal model, enabling it to quickly adapt to novel data. This requires back-propagating errors through the solver steps. While normally the cost of the matrix operations involved in such a process would be significant, by using the Woodbury identity we can make the small number of examples work to our advantage. We propose both closed-form and iterative solvers, based on ridge regression and logistic regression components. Our methods constitute a simple and novel approach to the problem of few-shot learning and achieve performance competitive with or superior to the state of the art on three benchmarks.
Is social media bad for mental health and wellbeing? Exploring the perspectives of adolescents

Despite growing evidence of the effects of social media on the mental health of adolescents, there is still a dearth of empirical research into how adolescents themselves perceive social media, especially as knowledge resource, or how they draw upon the wider social and media discourses to express a viewpoint. Accordingly, this article contributes to this scarce literature. Six focus groups took place over 3 months with 54 adolescents aged 11–18 years, recruited from schools in Leicester and London (UK). Thematic analysis suggested that adolescents perceived social media as a threat to mental wellbeing and three themes were identified: (1) it was believed to cause mood and anxiety disorders for some adolescents, (2) it was viewed as a platform for cyberbullying and (3) the use of social media itself was often framed as a kind of ‘addiction’. Future research should focus on targeting and utilising social media for promoting mental wellbeing among adolescents and educating youth to manage the possible deleterious effects.
An Adaptive Multi‐Grid Solver for Applications in Computer Graphics

A key processing step in numerous computer graphics applications is the solution of a linear system discretized over a spatial domain. Often, the linear system can be represented using an adaptive domain tessellation, either because the solution will only be sampled sparsely, or because the solution is known to be ‘interesting’ (e.g. high frequency) only in localized regions. In this work, we propose an adaptive, finite elements, multi‐grid solver capable of efficiently solving such linear systems. Our solver is designed to be general‐purpose, supporting finite elements of different degrees, across different dimensions and supporting both integrated and pointwise constraints. We demonstrate the efficacy of our solver in applications including surface reconstruction, image stitching and Euclidean Distance Transform calculation.
Rigging Nearly Acyclic Tournaments Is Fixed-Parameter Tractable

Single-elimination tournaments (or knockout tournaments) are a popular format in sports competitions that is also widely used for decision making and elections. In this paper we study the algorithmic problem of manipulating the outcome of a tournament. More specifically, we study the problem of finding a seeding of the players such that a certain player wins the resulting tournament. The problem is known to be NP-hard in general. In this paper we present an algorithm for this problem that exploits structural restrictions on the tournament. More specifically, we establish that the problem is fixed-parameter tractable when parameterized by the size of a smallest feedback arc set of the tournament (interpreting the tournament as an oriented complete graph). This is a natural parameter because most problems on tournaments (including this one) are either trivial or easily solvable on acyclic tournaments, leading to the question — what about nearly acyclic tournaments or tournaments with a small feedback arc set? Our result significantly improves upon a recent algorithm by Aziz et al. (2014) whose running time is bounded by an exponential function where the size of a smallest feedback arc set appears in the exponent and the base is the number of players.
Periodontal regeneration via chemoattractive constructs

Abstract Aim Chemoattractants, such as stromal cell‐derived factor‐1α (SDF‐1α), can offer an advantage for periodontal regeneration by recruiting the patient’s own stem cells to stimulate self‐repair. We here developed a chemoattractive construct for periodontal regeneration using SDF‐1α and evaluated its efficacy in vivo. Materials and Methods SDF‐1α was loaded on gelatin sponge and tested in vitro for SDF‐1α release. Subsequently, SDF‐1α constructs were implanted into rat periodontal defects for 1 and 6 weeks, with unloaded materials and empty defects as controls. The regenerative efficacy was evaluated by micro‐CT, histological and histomorphometrical analyses. Results In vitro results showed limited SDF‐1α release up to 35 days. In contrast, SDF‐1α constructs significantly improved periodontal defect regeneration in terms of alveolar bone height, new bone area and functional ligament length. Additionally, SDF‐1α constructs decreased the inflammatory response at Week 6. Conclusion Chemoattractive constructs significantly improved periodontal regeneration in terms of alveolar bone height, new bone area and functional ligament length.
Combined Effectiveness of Honey and Immunonutrition on Bacterial Translocation Secondary to Obstructive Jaundice in Rats: Experimental Study

Background Obstructive jaundice is a serious, life-threatening condition that can lead to death as a result of sepsis and multiorgan failure due to bacterial translocation. Treatment should be started as soon as possible after diagnosis. Material/Methods Forty 24-week-old male Sprague Dawley rats, with an average weight of 250 g to 300 g, were included in this study. The rats were randomly placed into five groups, each group consisted of eight rats. The sham group underwent only common bile duct (CBD) dissection and no ligation was performed. CBD ligation was applied to the other groups. After the operation, one CBD group was fed with rat chow only, the others were fed with rat chow supplemented with honey, or immunonutrients, or honey plus immunonutrients. After 10 to 12 days, all rats were sacrificed; blood and tissue samples were collected for biochemical, microbiological, and histopathological evaluation. Results In the groups that were fed with honey and immunonutrients, alanine aminotransferase (ALT) levels were decreased significantly compared to the other groups. Statistically significant differences were detected in terms of bacterial translocation (BT) rates among liver and spleen samples, and laboratory values of serum, except for MLNs of the BDL+HI group, when compared to other groups. We found mean mucosal thickness of ileum samples have been improved notably in the BDL+HI group compared to the other groups, especially compared to the C/BDL group. Conclusions Immunonutrition applied with honey had immunostimulant effects, decreased BT due to an additive effect, and had positive effects on intestinal mucosa.
Are there unmet needs in contraceptive counselling and choice? Findings of the European TANCO Study

Abstract Introduction: Effective use of contraception requires women to make an informed choice about methods that match their individual needs and expectations. The European Thinking About Needs in Contraception (TANCO) study is a quantitative, online survey of healthcare provider and women’s views on aspects of counselling around contraception and contraceptive use. Methods: Healthcare providers and women attending their practices for contraceptive counselling were invited to complete online questionnaires. The women’s survey explored knowledge and use of contraceptive methods, satisfaction with current method, and interest in receiving more information about all methods. Healthcare provider views were gathered in parallel. Results: A total of 676 healthcare providers and 6027 women completed the online surveys in 11 countries. There was a high prevalence of contraceptive use and general satisfaction with current method across the countries. Fifty-five percent of women were using short-acting contraception (SAC) methods; 19% were using a long-acting reversible contraception (LARC) method. Sixty percent of women were interested in receiving more information about all methods; 73% of women said they would consider LARC if they received more comprehensive information. Healthcare providers tend to underestimate women’s interest in receiving information on contraception in general and, more specifically, LARC methods. Conclusions: Despite high levels of use and satisfaction with current methods, women were interested in receiving more information about all contraceptive methods. Greater exploration of women’s views on their needs and expectations of contraception could lead to increased knowledge, more effective discussions with healthcare providers and the greater likelihood of informed contraceptive choice.
Neural Programming by Example Chengxun

Programming by Example (PBE) targets at automatically inferring a computer program for accomplishing a certain task from sample input and output. In this paper, we propose a deep neural networks (DNN) based PBE model called Neural Programming by Example (NPBE), which can learn from input-output strings and induce programs that solve the string manipulation problems. Our NPBE model has four neural network based components: a string encoder, an input-output analyzer, a program generator, and a symbol selector. We demonstrate the effectiveness of NPBE by training it end-toend to solve some common string manipulation problems in spreadsheet systems. The results show that our model can induce string manipulation programs effectively. Our work is one step towards teaching DNN to generate computer programs.
Asymmetric Discrete Graph Hashing

Recently, many graph based hashing methods have been emerged to tackle large-scale problems. However, there exists two major bottlenecks: (1) directly learning discrete hashing codes is an NP-hardoptimization problem; (2) the complexity of both storage and computational time to build a graph with n data points is O(n2). To address these two problems, in this paper, we propose a novel yetsimple supervised graph based hashing method, asymmetric discrete graph hashing, by preserving the asymmetric discrete constraint and building an asymmetric affinity matrix to learn compact binary codes.Specifically, we utilize two different instead of identical discrete matrices to better preserve the similarity of the graph with short binary codes. We generate the asymmetric affinity matrix using m (m << n) selected anchors to approximate the similarity among all training data so that computational time and storage requirement can be significantly improved. In addition, the proposed method jointly learns discrete binary codes and a low-dimensional projection matrix to further improve the retrieval accuracy. Extensive experiments on three benchmark large-scale databases demonstrate its superior performance over the recent state of the arts with lower training time costs.
Role of Microbiota in Sexually Dimorphic Immunity

Sex differences in peripheral immune responses are well recognized. This is associated with sex differences in many immunological diseases. As the intestinal microbiota is known to influence the immune system, such sex differences in immune responses may be a consequence of sex-specific microbiota. Therefore, this mini-review discusses sex differences in intestinal microbiota and the possible role of microbiota in shaping sexually dimorphic immunity. Sex differences in microbiota composition are clearly found in mice studies and also in human studies. However, the lack of standardization in human studies may mask the sexual dimorphism in microbiota composition in human studies, since many factors such as age, genetic background, BMI, diet, and sex hormones appear to interfere with the sexual dimorphism in microbiota composition. Only a few mice studies found that differences in gut microbiota composition are causative for some aspects of sexually dimorphic immunity. Therefore, future studies should focus on a causal relationship between sexually dimorphic immunity and microbiota, considering the abovementioned interfering confounding factors. This would benefit the development of more sex-specific effective treatment options for immunological diseases.
Connecting Structure–Property and Structure–Function Relationships across the Disciplines of Chemistry and Biology: Exploring Student Perceptions

While many university students take science courses in multiple disciplines, little is known about how they perceive common concepts from different disciplinary perspectives. Structure–property and structure–function relationships have long been considered important explanatory concepts in the disciplines of chemistry and biology, respectively. Fourteen university students concurrently enrolled in introductory chemistry and biology courses were interviewed to explore their perceptions regarding 1) the meaning of structure, properties, and function; 2) the presentation of these concepts in their courses; and 3) how these concepts might be related. Findings suggest that the concepts of structure and properties were interpreted similarly between chemistry and biology, but students more closely associated the discussion of structure–property relationships with their chemistry courses and structure–function with biology. Despite receiving little in the way of instructional support, nine students proposed a coherent conceptual relationship, indicating that structure determines properties, which determine function. Furthermore, students described ways in which they connected and benefited from their understanding. Though many students are prepared to make these connections, we would encourage instructors to engage in cross-disciplinary conversations to understand the shared goals and disciplinary distinctions regarding these important concepts in an effort to better support students unable to construct these connections for themselves.
Base Substrate Sorghum Supplied with Nitrogen Additive Enhanced the Proliferation of Oyster ( Pleurotus ostreatus ( Jacq . : Fr . ) Kummer ) Mushroom Spawn Mycelium

The experiment was conducted to evaluate the performance of Pleurotus ostreatus (Jacq.: Fr.) Kummer mycelium on spawn media prepared from base substrate sorghum supplemented with combination of additives namely wheat bran, CaCO3, CaSO4, urea, sucrose and citric acid. Five spawn substrate combinations in 3 replications had been tested and data on fresh mycelial weight change 5, 10, 15, and 20 days after inoculation (DAI) and percentage mycelium coverage (PMC) at 20 DAI were collected. Completely randomized design was employed and the data was analyzed using SAS version 9.0. The result indicated differences in mycelial fresh weight (p < 0.05) after inoculation with the highest substrate weight reduction recorded at 20 DAI. Consequently, spawn substrate media combined from sorghum, wheat bran, CaCO3, CaSO4, and urea was found to be the most favorable media mix while 20 DAI was incubation period for better mycelial growth. Similarly, the qualitative data was found to be in support of the above result and there was significant difference in PMC at 20 DAI. Therefore, this study indicated substrate media combined from sorghum (87.2%), wheat bran (10%), CaCO3 (1.5%), CaSO4 (0.5%), and urea (0.8%) as the best alternative media for the production of P. ostreatus mushroom spawn.
Relationship between herd size and measures of animal welfare on dairy cattle farms with freestall housing in Germany.

The objective of this study was to examine the association of herd size with animal welfare in dairy cattle herds. Therefore, 80 conventional dairy cattle farms were classified by the number of cows into 4 herd size classes, C1 (<100 cows), C2 (100-299 cows), C3 (300-499 cows), and C4 (≥500 cows), and assessed using multiple animal-based measures of the Welfare Quality Assessment protocol for dairy cattle. Data were recorded from April 2014 to September 2016 by an experienced single assessor in northern Germany. Each farm was visited 2 times at an interval of 6 mo (summer period and winter period) to avoid seasonal effects on the outcome. The average herd size was 383 ± 356 Holstein-Friesian cows (range 45 to 1,629). Only farms with freestall (cubicle) housing and a maximum of 6 h access to pasture per day were included in the study. Data were statistically analyzed using a generalized linear mixed model. None of the farms reached the highest overall rating of "excellent. " The majority of the farms were classified as "enhanced" (30%) or "acceptable" (66%), and at 6 assessments the farms were rated as "not classified" (4%). Regarding single indicators, mean trough length per cow, percentage of cows with nasal discharge, and vulvar discharge increased with increasing herd size, whereas it was vice versa for displacements of cows. Percentage of lean cows, percentage of dirty lower legs, and duration of the process of lying down showed a curvilinear relationship with the number of cows per farm. Herd size was not associated with any other measures of the Welfare Quality protocol. In conclusion, herd size effects were small, and consequently herd size cannot be considered as a feasible indicator of the on-farm animal welfare level. Housing conditions and management practices seem to have a greater effect on animal welfare than the number of dairy cows per farm.
Turbo Learning for Captionbot and Drawingbot

We study in this paper the problems of both image captioning and text-to-image generation, and present a novel turbo learning approach to jointly training an image-to-text generator (a.k.a. CaptionBot) and a text-to-image generator (a.k.a. DrawingBot). The key idea behind the joint training is that image-to-text generation and text-to-image generation as dual problems can form a closed loop to provide informative feedback to each other. Based on such feedback, we introduce a new loss metric by comparing the original input with the output produced by the closed loop. In addition to the old loss metrics used in CaptionBot and DrawingBot, this extra loss metric makes the jointly trained CaptionBot and DrawingBot better than the separately trained CaptionBot and DrawingBot. Furthermore, the turbo-learning approach enables semi-supervised learning since the closed loop can provide pseudo-labels for unlabeled samples. Experimental results on the COCO dataset demonstrate that the proposed turbo learning can significantly improve the performance of both CaptionBot and DrawingBot by a large margin.