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Grain is a common bulk cargo. To ensure optimal utilization of transportation space and prevent overflow accidents, it is necessary to observe the grain's shape and determine the loading status during the loading process. Traditional methods often rely on manual judgment, which results in high labor intensity, poor safety, and low loading efficiency. Therefore, this paper proposes a method for recognizing the bulk grain-loading status based on Light Detection and Ranging (LiDAR). This method uses LiDAR to obtain point cloud data and constructs a deep learning network to perform target recognition and component segmentation on loading vehicles, extract vehicle positions and grain shapes, and recognize and make known the bulk grain-loading status. Based on the measured point cloud data of bulk grain loading, in the point cloud-classification task, the overall accuracy is 97.9% and the mean accuracy is 98.1%. In the vehicle component-segmentation task, the overall accuracy is 99.1% and the Mean Intersection over Union is 96.6%. The results indicate that the method has reliable performance in the research tasks of extracting vehicle positions, detecting grain shapes, and recognizing loading status. [ABSTRACT FROM AUTHOR]

Over the past century, the field of antibody discovery has undergone significant evolution, excluding the current exploration stage of artificial intelligence‐based antibody generation and the often overlooked non‐animal sourced antibody discovery, which typically requires mature in vitro affinity and the selection of high‐quality antigen formulations. This journey has traversed various stages, from methods involving serum‐based antibody acquisition, the isolation of B cells capable of perpetual antibody production through hybridoma technology, to the in‐depth exploration of genetic material using the phage display system, and the current stage involving diverse single B cell screening techniques. Additionally, the emergence of machine learning has brought impressive scientific and technological breakthroughs across research domains, proving to be a powerful application in the field of antibody discovery. However, each technique comes with its limitations, such as variability and control challenges in serum‐based acquisition, lengthy and difficult hybridoma‐derived antibody development, potential limitations in sequence and epitope diversity due to immunization biases in phage display techniques, and costly single B cell screening. Protein mass spectrometry sequencing, with shorter acquisition time and lower costs, is seen as a shortcut by diagnostic companies, impacting traditional antibody development. In diagnostic antibody development, methodological differences in downstream assays and the impact of constant regions outside the Fv core are often neglected. This paper deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products. [ABSTRACT FROM AUTHOR]

Adeno-associated virus (AAV) serotypes from primates are being developed and clinically used as vectors for human gene therapy. However, the evolutionary mechanism of AAV variants is far from being understood, except that genetic recombination plays an important role. Furthermore, little is known about the interaction between AAV and its natural hosts, human and nonhuman primates. In this study, natural AAV capsid genes were subjected to systemic evolutionary analysis with a focus on selection drives during the diversification of AAV lineages. A number of positively selected sites were identified from these AAV lineages with functional relevance implied by their localization on the AAV structures. The selection drives of the two AAV2 capsid sites were further investigated in a series of biological experiments. These observations did not support the evolution of the site 410 of the AAV2 capsid driven by selection pressure from the human CD4+ T-cell response. However, positive selection on site 548 of the AAV2 capsid was directly related to host humoral immunity because of the profound effects of mutations at this site on the immune evasion of AAV variants from human neutralizing antibodies at both the individual and population levels. Overall, this work provides a novel interpretation of the genetic diversity and evolution of AAV lineages in their natural hosts, which may contribute to their further engineering and application in human gene therapy. Author summary: Adeno-associated virus (AAV) is a viral vector that is universally applied in human gene therapy. Despite their versatile applications in gene therapy, the origin and evolution of AAV serotypes have not been extensively studied. In this study, positive selection upon diversification of AAV capsid genes was carefully investigated by evolutionary analysis. Numerous diversifying selected sites were dispersed among the AAV lineages, and evolutionary pathways were inferred for two selected sites of the AAV2 capsid gene. Furthermore, the putative immunological drives underlying the selection of AAV2 capsid genes were experimentally dissected. This work provides a novel interpretation of the evolution and diversity of AAV serotypes and might be helpful for their engineering and application in gene therapy. [ABSTRACT FROM AUTHOR]

The White Paper on Peak Carbon and Carbon Neutral Action 2022 states that China is to achieve peak carbon by 2030 and carbon neutrality by 2060. Based on the "3060 dual-carbon" goal, how to improve the efficiency of energy performance is an important prerequisite for building a low-carbon, energy-saving, green, and beautiful China. The office performance building studied in this paper is located in the urban area of Turpan, where the climate is characterized by an extremely hot summer environment and a cold winter environment. At the same time, the building is oriented east–west, with the main façade facing west, and the main façade consists of a large area of single-layer glass curtain wall, which is affected by western sunlight. As a result, there are serious problems with the building's energy consumption, which in turn leads to excessive carbon emissions and high life cycle costs for the building. To address the above problems, this paper analyzes and optimizes the following four dimensions. First, the article creates a Convolutional Neural Network (CNN) prediction model with Total Energy Use in Buildings (TEUI), Global Warming Potential (GWP), and Life Cycle Costs (LCC) as the performance objectives. After optimization, the R2 of the three are 0.9908, 0.9869, and 0.9969, respectively, thus solving the problem of low accuracy of traditional prediction models. Next, the NSGA-II algorithm is used to optimize the three performance objectives, which are reduced by 41.94%, 40.61%, and 31.29%, respectively. Then, in the program decision stage, this paper uses two empowered Topsis methods to optimize this building performance problem. Finally, the article analyzes the variables using two sensitivity analysis methods. Through the above research, this paper provides a framework of optimization ideas for office buildings in extremely hot and cold regions while focusing on the four major aspects of machine learning, multi-objective optimization, decision analysis, and sensitivity analysis systematically and completely. For the development of office buildings in the region, whether in the early program design or in the later stages, energy-saving measures to optimize the design have laid the foundation of important guidelines. [ABSTRACT FROM AUTHOR]

Quantitative cell motility studies are necessary for understanding biophysical processes, developing models for cell locomotion and for drug discovery. Such studies are typically performed by controlling environmental conditions around a lens-based microscope, requiring costly instruments while still remaining limited in field-of-view. Here we present a compact cell monitoring platform utilizing a wide-field (24 mm(2)) lensless holographic microscope that enables automated single-cell tracking of large populations that is compatible with a standard laboratory incubator. We used this platform to track NIH 3T3 cells on polyacrylamide gels over 20 hrs. We report that, over an order of magnitude of stiffness values, collagen IV surfaces lead to enhanced motility compared to fibronectin, in agreement with biological uses of these structural proteins. The increased throughput associated with lensfree on-chip imaging enables higher statistical significance in observed cell behavior and may facilitate rapid screening of drugs and genes that affect cell motility.

Dynamic detection in challenging lighting environments is essential for advancing intelligent robots and autonomous vehicles. Traditional vision systems are prone to severe lighting conditions in which rapid increases or decreases in contrast or saturation obscures objects, resulting in a loss of visibility. By incorporating intelligent optimization of polarization into vision systems using the iNC (integrated nanoscopic correction), we introduce an intelligent real-time fusion algorithm to address challenging and changing lighting conditions. Through real-time iterative feedback, we rapidly select polarizations, which is difficult to achieve with traditional methods. Fusion images were also dynamically reconstructed using pixel-based weights calculated in the intelligent polarization selection process. We showed that fused images by intelligent polarization selection reduced the mean-square error by two orders of magnitude to uncover subtle features of occluded objects. Our intelligent real-time fusion algorithm also achieved two orders of magnitude increase in time performance without compromising image quality. We expect intelligent fusion imaging photonics to play increasingly vital roles in the fields of next generation intelligent robots and autonomous vehicles. [ABSTRACT FROM AUTHOR]

We performed a meta‐analysis to evaluate the safety of benign prostatic hyperplasia wound after surgical removal in subjects on anticoagulant or antiplatelet therapy. A systematic literature search up to December 2021 was done and 19 studies included 5715 benign prostatic hyperplasia subjects at the start of the study; 1501 of them were on anticoagulant/antiplatelet therapy, and 4214 were control. We calculated the odds ratio (OR) and mean difference (MD) with 95% confidence intervals (CIs) to evaluate the safety of benign prostatic hyperplasia wound after surgical removal in subjects on anticoagulant or antiplatelet therapy by the dichotomous or continuous methods with a random or fixed‐influence model. Anticoagulant/antiplatelet therapy had significantly higher bleeding complication (OR, 1.88; 95% CI, 1.36–2.60, P <.001), higher blood transfusion (OR, 2.15; 95% CI, 1.63–2.83, P <.001), lower operation time (MD, −3.53; 95% CI, −6.80–0.27, P =.03), higher catheterization time (MD, 0.30 95% CI, 0.06–0.53, P =.01), longer length of hospital stay (MD, 0.82; 95% CI, 0.37–1.26, P <.001) and higher thromboembolic events (OR, 2.88; 95% CI, 1.26–6.62, P =.01) compared to control in benign prostatic hyperplasia subjects. Anticoagulant/antiplatelet therapy had a significantly higher bleeding complication, higher blood transfusion, lower operation time, higher catheterization time, longer length of hospital stay and higher thromboembolic events compared to control in benign prostatic hyperplasia subjects. Further studies are required. [ABSTRACT FROM AUTHOR]

A member of the family Coronaviridae, genus alphacoronavirus, porcine epidemic diarrhea virus (PEDV) is an enveloped, single-stranded positive-sense RNA virus (1). PEDV is the major causative agent of porcine epidemic [...]

Abstract Background Ultrasound (US) imaging can be enhanced using gas-filled microbubble contrast agents. Strong echo signals are induced at the tissue-gas interface following microbubble collapse. Applications include assessment of ventricular function and virtual histology. Aim While ultrasound and US contrast agents are widely used, their impact on the physiological response of vascular tissue to vasoactive agents has not been investigated in detail. Methods and results In the present study, rat dorsal aortas were treated with US via a clinical imaging transducer in the presence or absence of the US contrast agent, Optison. Aortas treated with both US and Optison were unable to contract in response to phenylephrine or to relax in the presence of acetylcholine. Histology of the arteries was unremarkable. When the treated aortas were stained for endothelial markers, a distinct loss of endothelium was observed. Importantly, terminal deoxynucleotidyl transferase mediated dUTP nick-end-labeling (TUNEL) staining of treated aortas demonstrated incipient apoptosis in the endothelium. Conclusions Taken together, these ex vivo results suggest that the combination of US and Optison may alter arterial integrity and promote vascular injury; however, the in vivo interaction of Optison and ultrasound remains an open question.