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Their structures will be presented to provide better understanding of their structural similarities and possible correlations with mechanisms of actions. This can help identifying anti-SARS-CoV-2 promising therapeutic agents.Learning to select appropriate actions based on their values is fundamental to adaptive behavior. This form of learning is supported by fronto-striatal systems. The dorsal-lateral prefrontal cortex (dlPFC) and the dorsal striatum (dSTR), which are strongly interconnected, are key nodes in this circuitry. Substantial experimental evidence, including neurophysiological recordings, have shown that neurons in these structures represent key aspects of learning. The computational mechanisms that shape the neurophysiological responses, however, are not clear. To examine this, we developed a recurrent neural network (RNN) model of the dlPFC-dSTR circuit and trained it on an oculomotor sequence learning task. We compared the activity generated by the model to activity recorded from monkey dlPFC and dSTR in the same task. This network consisted of a striatal component which encoded action values, and a prefrontal component which selected appropriate actions. After training, this system was able to autonomously represent and update action values and select actions, thus being able to closely approximate the representational structure in corticostriatal recordings. We found that learning to select the correct actions drove action-sequence representations further apart in activity space, both in the model and in the neural data. The model revealed that learning proceeds by increasing the distance between sequence-specific representations. This makes it more likely that the model will select the appropriate action sequence as learning develops. Our model thus supports the hypothesis that learning in networks drives the neural representations of actions further apart, increasing the probability that the network generates correct actions as learning proceeds. Altogether, this study advances our understanding of how neural circuit dynamics are involved in neural computation, revealing how dynamics in the corticostriatal system support task learning.Existing regression based tracking methods built on correlation filter model or convolution model do not take both accuracy and robustness into account at the same time. In this paper, we propose a dual-regression framework comprising a discriminative fully convolutional module and a fine-grained correlation filter component for visual tracking. The convolutional module trained in a classification manner with hard negative mining ensures the discriminative ability of the proposed tracker, which facilitates the handling of several challenging problems, such as drastic deformation, distractors, and complicated backgrounds. The correlation filter component built on the shallow features with fine-grained features enables accurate localization. By fusing these two branches in a coarse-to-fine manner, the proposed dual-regression tracking framework achieves a robust and accurate tracking performance. Extensive experiments on the OTB2013, OTB2015, and VOT2015 datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods.Infectious bronchopneumonia is a lower respiratory tract disease with major economic consequences in dairy calves. Thoracic radiography (TR) and thoracic ultrasonography (TUS) are two imaging diagnostic procedures available in bovine medicine for identifying thoracic lesions. selleck inhibitor However, no study has investigated whether one of these tests is superior to the other or if they provide comparable results for the detection of thoracic lesions in calves. The objective of this study was therefore to estimate and to compare the performances of TUS and TR for the detection of thoracic lesions in dairy calves. A prospective cross-sectional study was performed in a hospital setting. A total of 50 calves (≥7 days old; ≤100 kg; standing; pCO2 ≥ 53 mmHg; any reason of presentation) were enrolled. Every calf underwent TUS and TR. Only calves with thoracic lesions on TUS and/or TR were controlled by thoracic computed tomography (CT) (the gold standard). Calves without lesions were not controlled by CT. A two-stage Bayesian framework was used. The sensitivities (Se) and specificities (Sp) of both tests individually and used in series or parallel were estimated. The Se and Sp of TUS were 0.81 (95 % BCI (Bayesian Credible Interval) 0.65; 0.92) and 0.90 (95 % BCI 0.81; 0.96), respectively. The Se and Sp of TR were 0.86 (95 % BCI 0.62; 0.99) and 0.89 (95 % BCI 0.67; 0.99), respectively. This study did not reveal any differences between both tests. Using TUS and TR in series was more specific than using both tests in parallel. The performances of TUS alone were not different from the performances of both tests in series or in parallel. In conclusion, TUS and TR were equivalent in detecting thoracic lesions in this study. Using TUS alone allowed an accurate detection of thoracic lesions in dairy calves. Further studies enrolling a larger sample (> 400 calves) and allowing adequate power to be achieved would be necessary to confirm these results.Vaccinating pigs against Salmonella Typhimurium (ST) might be a way to control ST infections at farm level and reduce human infections. Two main issues have to be addressed before such a mandatory vaccination program can be implemented the effective reduction of attributable human incidence has to be demonstrated and all socio-economic barriers impacting the attitude and motivation of the pig sector have to be lifted. The present research used a quantitative microbial risk assessment model to estimate the effect of different hypothetical Salmonella spp. and ST mitigation strategies on the annual prevalence of human salmonellosis along the minced pork production chain. In addition, a qualitative study aimed to list the potential concerns of the pig sector about the implementation of a hypothetical future vaccination program. The following themes were the most often mentioned awareness, vaccine cost-benefit/effectiveness, legislation, monovalent vaccine, time and labour required to vaccinate, vaccine registration and trade restriction.