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The promotion and use of liquid feeding face the challenge of insufficiently stable delivery. This issue can be resolved, in part, by using the spiral flow produced by a spiral pipe (SPP). The aim of this study is to investigate how the structural characteristics of the spiral pipe affect the flow state of the liquid feed, and for this purpose, the computational fluid dynamics (CFD) technique has been employed and the liquid feed delivery process has been simulated by means of an Eulerian two-fluid model The results reveal a significant improvement in the slurry’s homogeneity as it traveled through a spiral pipe compared with a straight pipe (STP). The swirl number normally increased with the number, length, height, and angle of the spiral pipe’s guide vanes. The solid-phase distribution was more homogeneous when values of N = 1, L = 1D, H = 3/8R, and θ = 20° were used, respectively, and the COV within 10D downstream of the outlet of the spiral pipe was 3.902% smaller than that of the straight pipe. The results of this study can be used as a reference for the design of liquid feed-conveying pipes.

The plant-specific NAC gene family is one of the largest transcription factor families, participating in plant growth regulation and stress response. Despite extensive characterization in various plants, our knowledge of the NAC family in oat is lacking. Herein, we identified 333 NAC genes from the latest release of the common oat genome. We provide a comprehensive overview of the oat NAC gene family, covering gene structure, chromosomal localization, phylogenetic characteristics, conserved motif compositions, and gene duplications. AsNAC gene expression in different tissues and the response to various abiotic stresses were characterized using RT-qPCR. The main driver of oat NAC gene family expansion was identified as segmental duplication using collinearity analysis. In addition, the functions of AsNAC109 in regulating abiotic stress tolerance in Arabidopsis were clarified. This is the first genome-wide investigation of the NAC gene family in cultivated oat, which provided a unique resource for subsequent research to elucidate the mechanisms responsible for oat stress tolerance and provides valuable clues for the improvement of stress resistance in cultivated oat.

ABSTRACT Candidiasis is a life-threatening disease that increases mortality in critically ill patients. However, such epidemiological data are still lacking in underdeveloped regions of China. A retrospective analysis (2016 to 2021) was conducted in Meizhou People’s Hospital, China to study the burden of candidiasis, particularly candidemia, and antifungal susceptibilities of the species among hospitalized patients. Of the 7,864 candidiasis cases, 461 (5.86%) were candidemia cases. Candida albicans (64.25%) was the most identified species, followed by C. tropicalis (12.61%), C. glabrata (10.79%), and C. parapsilosis (9.79%). In non-C. albicans (NCA) candidemia cases, the number of C. glabrata cases was higher (102/461, 22.37%) than C. tropicalis (64/461, 14.04%). Gastrointestinal pathology, respiratory dysfunctions, septic shock, and malignancies were common underlying comorbidities, respectively. A central venous catheter was an independent risk factor for both C. albicans and NCA candidemia. The mortality rate was not statistically significant for either C. albicans or NCA. Amphotericin B and 5-flucytosine were highly effective (98 to 100%), while azoles were least effective (67.74 to 95.66%). Candidemia cases caused by C. tropicalis and C. glabrata had significantly lower azole susceptibility than non-candidemia-causing isolates. This study provides valuable information for prescribers to choose the right empirical therapy, for researchers to explore different resistance mechanisms, and for health care managers to control candidiasis better. IMPORTANCE This study provides important information on the burden of candidiasis, particularly candidemia, and the antifungal susceptibility of Candida species among hospitalized patients in an underdeveloped region of China. First, the finding that azoles were least effective against Candida species causing candidemia is particularly noteworthy, as it suggests the possibility of resistance to this class of antifungal agents. This information can guide the choice of empirical therapy and help in the selection of appropriate antifungal agents for the treatment of candidemia, thereby reducing the risk of resistance development. Second, the study provides important information for researchers to explore different resistance mechanisms in Candida species. Finally, the study has important implications for health care managers in controlling the spread of candidiasis. The high prevalence of candidemia cases in the study highlights the need for appropriate infection control measures to prevent the spread of the disease.

A novel indoor positioning method for a pigsty based on ultra-wideband (UWB) technology is proposed via reasonably arranging the base stations and positioning tags, which can provide strong support for the accurate positioning of specific pig pens in the pig house. The distribution of Dilution of Precision (DOP) values is analyzed in different deployment schemes which include the amount, the height, the deployment shape, and the distance of the base stations through positioning simulation. Moreover, the positioning effect of dynamic following positioning, the root-mean-square error (RMSE), and the variance of static positioning are measured. It is noteworthy that the Kalman filtering algorithm is adopted to smooth the dynamic following positioning experimental data for reducing the positioning error. The simulated results show that the DOP values decrease with the increase in height and distance, and these results and laws are consistent with the experimental results. However, the DOP values are best reached when the height is from 1.75 m to 2.75 m, and the distance is over 3.00 m. Furthermore, the DOP values of quadrilateral deployment are smaller than the ones of triangular deployment. In addition, the variance of static positioning and dynamic following positioning is decreased by utilizing the Kalman filtering algorithm. Therefore, the excellent positioning system and its solutions in a pigsty can be provided by our proposed indoor positioning method.

This study proposes a GC-YOLOv5s crack-detection network of UAVs to work out several issues, such as the low efficiency, low detection accuracy caused by shadows, occlusions and low contrast, and influences due to road noise in the classic crack-detection methods in the complicated traffic routes. A Focal-GIOU loss function with a focal loss has been introduced in this proposed algorithm, which is applied to address the issue of the imbalance of difficult and easy samples in crack images. Meanwhile, the original localization loss function CIOU is replaced by a GIOU loss function that is more suitable for irregular target (crack) detection. In order to improve the ability of the modified model of representing the features, a Transposed Convolution layer is simultaneously added in place of the original model’s upsampling layer. According to the advantage of computing resources of the Ghost module, the C3Ghost module is applied to decrease the amount of network parameters while maintaining adequate feature representation. Additionally, a lightweight module, CSPCM, is designed with the Conmix module and the Ghost concept, which successfully reduces the model parameters and zooms out the volume. At the same time, this modified module can have enough detection accuracy, and it can satisfy the requirements of UAV detection of small models and rapidity. In order to prove the model’s performance, this study has established a new UAV road-crack-detection dataset (named the UMSC), and has conducted extensive trials. To sum up, the precision of GC-YOLOv5s has increased by 8.2%, 2.8%, and 3.1%, respectively, and has reduced the model parameters by 16.2% in comparison to YOLOv5s. Furthermore, it outperforms previous YOLO comparison models in Precision, Recall, mAP_0.5, mAP_0.5:0.95, and Params.

This paper proposes an improved model based on YOLOv5s, specifically designed to overcome the challenges faced by current target detection algorithms in the field of electric bike helmet detection. In order to enhance the model’s ability to detect small targets and densely populated scenes, a specialized layer dedicated to small target detection and a novel loss function called Normalized Wasserstein Distance (NWD) are introduced. In order to solve the problem of increasing model parameters and complexity due to the inclusion of a small target detection layer, a Cross-Stage Partial Channel Mixing (CSPCM) on top of Convmix is designed. The collaborative fusion of CSPCM and the Deep Feature Consistency (DFC) attention mechanism makes it more suitable for hardware devices. In addition, the conventional Nearest Upsample technology is replaced with the advanced CARAFE Upsample module, further improving the accuracy of the model. Through rigorous experiments on carefully constructed datasets, the results show significant improvements in various evaluation indicators such as precision, recall, mAP.5, and mAP.95. Compared with the unmodified YOLOv5s algorithm, the proposed enhanced model achieves significant improvements of 1.1%, 8.4%, 5.2%, and 8.6% on these indicators, respectively, and these enhancements are accompanied by a reduction of 778,924 parameters. The experimental results on our constructed dataset demonstrate the superiority of the improved model and elucidate its potential applications. Furthermore, promising improvements for future research are suggested. This study introduces an efficient approach for improving the detection of electric bike helmets and verifies the effectiveness and practicality of the model through experiments. Importantly, the proposed scheme has implications for other target detection algorithms, especially in the field of small target detection.

Tobacco dust represents a critical threat to the operators’ respiratory health. Even when wet scrubbers display high purification efficiencies and strong adaptability to dust, their potential applications in the tobacco industry have not been studied. In the present research, removal efficiency of wet scrubber for tobacco dust and fine dust were examined at laboratory and industrial level. Results showed that the dust removal efficiency of the wet scrubber under laboratory conditions reached a maximum value of 99.17%. In addition, the dust discharge concentration was reduced to a minimum value of 1.1 mg/m3. Our data indicated that after using the wet scrubber, large dust particles (≥10 μm) were more effectively removed than fine dust particles (≤5 μm). After the use of the wet scrubber at the industrial facility, the overall dust removal efficiency reached a value of 98.9%, and dust concentration at the discharge point was as low as 1 mg/m3. This value complies with the ultra-low discharge standard and industrial production requirements. Our study demonstrated the feasibility of using wet scrubbers in the removal of tobacco dust and provides new insights for dust suppression in the tobacco processing industry.

Abstract Influenza remains a severe respiratory illness that poses significant global health threats. Recent studies have identified distinct microbial communities within the respiratory tract, from nostrils to alveoli. This research explores specific anti-influenza respiratory microbes using a mouse model supported by 16S rDNA sequencing and untargeted metabolomics. The study found that transferring respiratory microbes from mice that survived H9N2 influenza to antibiotic-treated mice enhanced infection resistance. Notably, the levels of Aeromicrobium were significantly higher in the surviving mice. Mice pre-treated with antibiotics and then inoculated with Aeromicrobium camelliae showed reduced infection severity, as evidenced by decreased weight loss, higher survival rates, and lower lung viral titres. Metabolomic analysis revealed elevated LysoPE (16:0) levels in mildly infected mice. In vivo and in vitro experiments indicated that LysoPE (16:0) suppresses inducible nitric oxide synthase (INOS) and cyclooxygenase-2 (COX2) expression, enhancing anti-influenza defences. Our findings suggest that Aeromicrobium camelliae could serve as a potential agent for influenza prevention and a prognostic marker for influenza outcomes.

Abstract Background Chicken coccidiosis is a protozoan disease that leads to considerable economic losses in the poultry industry. Live oocyst vaccination is currently the most effective measure for the prevention of coccidiosis. However, it provides limited protection with several drawbacks, such as poor immunological protection and potential reversion to virulence. Therefore, the development of effective and safe vaccines against chicken coccidiosis is still urgently needed. Methods In this study, a novel oral vaccine against Eimeria tenella was developed by constructing a recombinant Lactobacillus plantarum (NC8) strain expressing the E. tenella RON2 protein. We administered recombinant L. plantarum orally at 3, 4 and 5 days of age and again at 17, 18 and 19 days of age. Meanwhile, each chick in the commercial vaccine group was immunized with 3 × 102 live oocysts of coccidia. A total of 5 × 104 sporulated oocysts of E. tenella were inoculated in each chicken at 30 days. Then, the immunoprotection effect was evaluated after E. tenella infection. Results The results showed that the proportion of CD4+ and CD8+ T cells, the proliferative ability of spleen lymphocytes, inflammatory cytokine levels and specific antibody titers of chicks immunized with recombinant L. plantarum were significantly increased (P

Coastal wetlands play a vital role in the migration and transformation of heavy metal pollutants in watersheds. There were 30 surface sediment samples that were analysed to investigate the distribution and ecological risks of heavy metals in the coastal wetlands around the Bohai Sea. Our results showed that the average concentrations of Pb, Cr, Ni, Cu, Zn, and Cd in these wetlands were 17.92 ± 5.81, 50.29 ± 20.50, 31.53 ± 9.71, 25.37 ± 4.29, 80.13 ± 15.11, and 0.92 ± 0.54 mg/kg, respectively. Relative to other wetlands, Pb (25.43 ± 2.68 mg/kg) and Cd (1.67 ± 0.06 mg/kg) contents were higher in the Liaohe Delta wetland (LHDW). Cu (28.44 ± 3.71 mg/kg), Cr (83.11 ± 5.80 mg/kg), and Ni (45.91 ± 3.02 mg/kg) contents were higher in the Yellow River Delta wetland (YRDW). The Zn (120.86 ± 7.41 mg/kg) content was higher in the Qilihai wetland. Heavy metal concentrations in coastal wetland sediments are shown to be positively correlated with organic matter content. Our results showed that the concentration of heavy metals decreases with increasing sediment particle size. In this study, Cd showed the highest pollution index and, therefore, more attention should be paid to the potential ecological risks of Cd in coastal wetlands around the Bohai Sea, especially in the LHDW and YRDW.

ABSTRACT E3 ubiquitin ligase (E3) plays a vital role in regulating inflammatory responses by mediating ubiquitination. Previous studies have shown that ankyrin repeat and SOCS box-containing protein 3 (ASB3) is involved in immunomodulatory functions associated with cancer. However, the impact of ASB3 on the dynamic interplay of microbiota and inflammatory responses in inflammatory bowel disease (IBD) is unclear. Here, we systematically identify the E3 ligase ASB3 as a facilitative regulator in the development and progression of IBD. We observed that ASB3 exhibited significant upregulation in the lesions of patients with IBD. ASB3−/− mice are resistant to dextran sodium sulfate-induced colitis. IκBα phosphorylation levels and production of proinflammatory factors IL-1β, IL-6, and TNF-α were reduced in the colonic tissues of ASB3−/− mice compared to WT mice. This colitis-resistant phenotype was suppressed after coprophagic microbial transfer and reversed after combined antibiotics removed the gut commensal microbiome. Mechanistically, ASB3 specifically catalyzes K48-linked polyubiquitination of TRAF6 in intestinal epithelial cells. In contrast, in ASB3-deficient organoids, the integrity of the TRAF6 protein is shielded, consequently decelerating the onset of intestinal inflammation. ASB3 is associated with dysregulation of the colitis microbiota and promotes proinflammatory factors’ production by disrupting TRAF6 stability. Strategies to limit the protein level of ASB3 in intestinal epithelial cells may help in the treatment of colitis.IMPORTANCEUbiquitination is a key process that controls protein stability. We determined the ubiquitination of TRAF6 by ASB3 in intestinal epithelial cells during colonic inflammation. Inflammatory bowel disease patients exhibit upregulated ASB3 expression at focal sites, supporting the involvement of degradation of TRAF6, which promotes TLR-Myd88/TRIF-independent NF-κB aberrant activation and intestinal microbiota imbalance. Sustained inflammatory signaling in intestinal epithelial cells and dysregulated protective probiotic immune responses mediated by ASB3 collectively contribute to the exacerbation of inflammatory bowel disease. These findings provide insights into the pathogenesis of inflammatory bowel disease and suggest a novel mechanism by which ASB3 increases the risk of colitis. Our results suggest that future inhibition of ASB3 in intestinal epithelial cells may be a novel clinical strategy.

This paper investigates the odometry drift problem in differential-drive indoor mobile robots and proposes a multi-sensor fusion approach utilizing a Fuzzy Inference System (FIS) within a Wheel-Inertial-Visual Odometry (WIVO) framework to optimize the 6-DoF localization of the robot in unstructured scenes. The structure and principles of the multi-sensor fusion system are developed, incorporating an Iterated Error State Kalman Filter (IESKF) for enhanced accuracy. An FIS is integrated with the IESKF to address the limitations of traditional fixed covariance matrices in process and observation noise, which fail to adapt effectively to complex kinematic characteristics and visual observation challenges such as varying lighting conditions and unstructured scenes in dynamic environments. The fusion filter gains in FIS-IESKF are adaptively adjusted for noise predictions, optimizing the rule parameters of the fuzzy inference process. Experimental results demonstrate that the proposed method effectively enhances the localization accuracy and system robustness of differential-drive indoor mobile robots in dynamically changing movements and environments.

ABSTRACTEnterotoxigenic Escherichia coli (ETEC) is one of the major pathogens contributing to piglet diarrhea, with significant implications for both piglet health and the economic aspects of the livestock industry. SW207 is an isolate of Bacillus halotolerans isolated from the cold- and disease-resistant Leixiang pigs in Northeastern China. We have discovered that SW207 can survive in the pig’s gastrointestinal fluid and under conditions of high bile salt concentration, displaying potent antagonistic activity against ETEC. In this study, we established a weaned piglet diarrhea model infected with ETEC to investigate the role of SW207 in preventing diarrhea and improving intestinal health. Results indicate that SW207 upregulates the expression of tight junction proteins, including claudin-1, occludin, and zonula occludens-1, at both the transcriptional and translational levels. Furthermore, SW207 reduces serum endotoxin, D-lactic acid, and various oxidative stress markers while enhancing piglet mechanical barrier function. In terms of immune barrier, SW207 suppressed the activation of the TLR4/MyD88/NF-κB pathway, reducing the expression of various inflammatory factors and upregulating the expression of small intestine mucosal sIgA. Concerning the biological barrier, SW207 significantly reduces the content of E. coli in the intestines and promotes the abundance of beneficial bacteria, thereby mitigating the microbiota imbalance caused by ETEC. In summary, SW207 has the potential to prevent weaned piglet diarrhea caused by ETEC, alleviate intestinal inflammation and epithelial damage, and facilitate potential beneficial changes in the intestinal microbiota. This contributes to elucidating the potential mechanisms of host-microbe interactions in preventing pathogen infections.IMPORTANCEEnterotoxigenic Escherichia coli (ETEC) has consistently been one of the significant pathogens causing mortality in weaned piglets in pig farming. The industry has traditionally relied on antibiotic administration to control ETEC-induced diarrhea. However, the overuse of antibiotics has led to the emergence of drug-resistant zoonotic bacterial pathogens, posing a threat to public health. Therefore, there is an urgent need to identify alternatives to control pathogens and reduce antibiotic usage. In this study, we assessed the protective effect of a novel probiotic in a weaned piglet model infected with ETEC and analyzed its mechanisms both in vivo and in vitro. The study results provide theoretical support and reference for implementing interventions in the gut microbiota to alleviate early weaned piglet diarrhea and improve intestinal health.

ABSTRACTCanine distemper virus (CDV) poses a severe threat to both domesticated and wild animals, including multiple carnivores. With the continued expansion of its host range, there is an urgent need for the development of a safer and more effective vaccine. In this study, we developed subunit vaccines based on a bacterium-like particle (BLP) delivery platform containing BLPs-F and BLPs-H, which display the CDV F and H glycoprotein antigens, respectively, using the antigen-protein anchor fusions produced by a recombinant baculovirus insect cell expression system. The combination of BLPs-F and BLPs-H (CDV-BLPs), formulated with colloidal manganese salt [Mn jelly (MnJ)] adjuvant, triggered robust CDV-specific antibody responses and a substantial increase in the number of interferon gamma (IFN-γ)-secreting CD4+ and CD8+ T cells in mice. Dogs immunized intramuscularly with this vaccine not only produced CDV-specific IgG but also displayed elevated concentrations of IFN-γ and interleukin 6 in their serum, along with an increase of the CD3+CD4+ and CD3+CD8+ T cell subsets. Consequently, this heightened immune response provided effective protection against disease development and reduced viral shedding levels following challenge with a virulent strain. These findings suggest that this BLP-based subunit vaccine has the potential to become a novel canine distemper vaccine.IMPORTANCEMany sensitive species require a safe and effective distemper vaccine. Non-replicating vaccines are preferred. We constructed subunit particles displaying canine distemper virus (CDV) antigens based on a bacterium-like particle (BLP) delivery platform. The CDV-BLPs formulated with theMn jelly adjuvant induced robust humoral and cell-mediated immune responses to CDV in mice and dogs, thereby providing effective protection against a virulent virus challenge. This work is an important step in developing a CDV subunit vaccine.

Abstract Vaccination is still the most promising strategy for combating influenza virus pandemics. However, the highly variable characteristics of influenza virus make it difficult to develop antibody-based universal vaccines, until now. Lung tissue-resident memory T cells (TRM), which actively survey tissues for signs of infection and react rapidly to eliminate infected cells without the need for a systemic immune reaction, have recently drawn increasing attention towards the development of a universal influenza vaccine. We previously designed a sequential immunization strategy based on orally administered Salmonella vectored vaccine candidates. To further improve our vaccine design, in this study, we used two different dendritic cell (DC)-targeting strategies, including a single chain variable fragment (scFv) targeting the surface marker DC-CD11c and DC targeting peptide 3 (DCpep3). Oral immunization with Salmonella harboring plasmid pYL230 (S230), which displayed scFv-CD11c on the bacterial surface, induced dramatic production of spleen effector memory T cells (TEM). On the other hand, intranasal boost immunization using purified DCpep3-decorated 3M2e-ferritin nanoparticles in mice orally immunized twice with S230 (S230inDC) significantly stimulated the differentiation of lung CD11b+ DCs, increased intracellular IL-17 production in lung CD4+ T cells and elevated chemokine production in lung sections, such as CXCL13 and CXCL15, as determined by RNAseq and qRT‒PCR assays, resulting in significantly increased percentages of lung TRMs, which could provide efficient protection against influenza virus challenge. The dual DC targeting strategy, together with the sequential immunization approach described in this study, provides us with a novel “prime and pull” strategy for addressing the production of protective TRM cells in vaccine design.

Abstract Squeeze casting (SC) is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters. Unfortunately, a universal efficient method for the determination of optimal process parameters is still unavailable. In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters, by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software, manual reading and statistical analysis, the current state and characteristics of the research methods used for the determination of SC process parameters are summarized. The literature data show that the number of publications in the literature related to the design of SC process parameters generally trends upward albeit with significant fluctuations. Analysis of the research focus shows that both “mechanical properties” and “microstructure” are the two main subjects in the studies of SC process parameters. With regard to materials, aluminum alloys have been extensively studied. Five methods have been used to obtain SC process parameters: Physical experiments, numerical simulation, modeling optimization, formula calculation, and the use of empirical values. Physical experiments are the main research methods. The main methods for designing SC process parameters are divided into three categories: Fully experimental methods, optimization methods that involve modeling based on experimental data, and theoretical calculation methods that involve establishing an analytical formula. The research characteristics and shortcomings of each method were analyzed. Numerical simulations and model-based optimization have become the new required methods. Considering the development needs and data-driven trends of the SC process, suggestions for the development of SC process parameter research have been proposed.

The molecular mechanism of broad-spectrum neutralization of a rabbit monoclonal antibody 1H1 against Omicron sublineages is revealed by cryo-EM.

Generally, the interesting objects in aerial images are completely different from objects in nature, and the remote sensing objects in particular tend to be more distinctive in aspect ratio. The existing convolutional networks have equal aspect ratios of the receptive fields, which leads to receptive fields either containing non-relevant information or being unable to fully cover the entire object. To this end, we propose Horizontal and Vertical Convolution, which is a plug-and-play module to address different aspect ratio problems. In our method, we introduce horizontal convolution and vertical convolution to expand the receptive fields in the horizontal and vertical directions, respectively, to reduce redundant receptive fields, so that remote sensing objects with different aspect ratios can achieve better receptive fields coverage, thereby achieving more accurate feature representation. In addition, we design an attention module to dynamically aggregate these two sub-modules to achieve more accurate feature coverage. Extensive experimental results on the DOTA and HRSC2016 datasets show that our HVConv achieves accuracy improvements in diverse detection architectures and obtains SOTA accuracy (mAP score of 77.60% with DOTA single-scale training and mAP score of 81.07% with DOTA multi-scale training). Various ablation studies were conducted as well, which is enough to verify the effectiveness of our model.

Taking the gear assembly of the reducer assembly line as a research background, the hole-finding strategy for robot assembly with keyed circular pegs is proposed to solve the problem of low hole-finding efficiency and success rate. in the circular hole-finding task, deviation domains were divided based on a static mechanism, position vector trajectory optimization in the step distance and direction was designed, and a deviation domain-force mapping relationship was established using a genetic algorithm-support vector machine (GA-SVM) classification algorithm; the accuracy of this algorithm is approximately 90.00%. Thirty groups completed the circular hole-finding task in an average time of 5.4 s. For the square hole-finding task, dual monocular cameras were integrated to identify corner points of the flat key and keyway. Image semantic segmentation based on deep learning was used for the corner-point recognition of the flat key to suppress the effect of changes in light intensity; the recognition has an average error of 0.39 mm. Coarse and fine adjustment circumferential deflection strategies were adopted sequentially. The 30 groups of square hole-finding tasks exhibited a 96.70% success rate in an average time of 10.2 s. The proposed hole-finding strategy improves the efficiency and success rate of the gear assembly.

Abstract In this paper, we tackle the challenging problem of point cloud completion from the perspective of feature learning. Our key observation is that to recover the underlying structures as well as surface details, given partial input, a fundamental component is a good feature representation that can capture both global structure and local geometric details. We accordingly first propose FSNet, a feature structuring module that can adaptively aggregate point-wise features into a 2D structured feature map by learning multiple latent patterns from local regions. We then integrate FSNet into a coarse-to-fine pipeline for point cloud completion. Specifically, a 2D convolutional neural network is adopted to decode feature maps from FSNet into a coarse and complete point cloud. Next, a point cloud upsampling network is used to generate a dense point cloud from the partial input and the coarse intermediate output. To efficiently exploit local structures and enhance point distribution uniformity, we propose IFNet, a point upsampling module with a self-correction mechanism that can progressively refine details of the generated dense point cloud. We have conducted qualitative and quantitative experiments on ShapeNet, MVP, and KITTI datasets, which demonstrate that our method outperforms state-of-the-art point cloud completion approaches.

ABSTRACT The influenza virus continues to pose a great threat to public health due to the frequent variations in RNA viruses. Vaccines targeting conserved epitopes, such as the extracellular domain of the transmembrane protein M2 (M2e), a nucleoprotein, and the stem region of hemagglutinin proteins, have been developed, but more efficient strategies, such as nanoparticle-based vaccines, are still urgently needed. However, the labor-intensive in vitro purification of nanoparticles is still necessary, which could hinder the application of nanoparticles in the veterinary field in the future. To overcome this limitation, we used regulated lysis Salmonella as an oral vector with which to deliver three copies of M2e (3M2e-H1N1)-ferritin nanoparticles in situ and evaluated the immune response. Then, sequential immunization using Salmonella-delivered nanoparticles followed by an intranasal boost with purified nanoparticles was performed to further improve the efficiency. Compared with 3M2e monomer administration, Salmonella-delivered in situ nanoparticles significantly increased the cellular immune response. Additionally, the results of sequential immunization showed that the intranasal boost with purified nanoparticles dramatically stimulated the activation of lung CD11b dendritic cells (DCs) and elevated the levels of effector memory T (TEM) cells in both spleen and lung tissues as well as those of CD4 and CD8 tissue-resident memory T (TRM) cells in the lungs. The increased production of mucosal IgG and IgA antibody titers was also observed, resulting in further improvements to protection against a virus challenge, compared with the pure oral immunization group. Salmonella-delivered in situ nanoparticles efficiently increased the cellular immune response, compared with the monomer, and sequential immunization further improved the systemic immune response, as shown by the activation of DCs, the production of TEM cells and TRM cells, and the mucosal immune response, thereby providing us with a novel strategy by which to apply nanoparticle-based vaccines in the future. IMPORTANCE Salmonella-delivered in situ nanoparticle platforms may provide novel nanoparticle vaccines for oral administration, which would be beneficial for veterinary applications. The combination of administering Salmonella-vectored, self-assembled nanoparticles and an intranasal boost with purified nanoparticles significantly increased the production of effector memory T cells and lung resident memory T cells, thereby providing partial protection against an influenza virus challenge. This novel strategy could open a novel avenue for the application of nanoparticle vaccines for veterinary purposes.

Currently, most routes of the oil and gas pipelines in mountainous areas are selected in a traditional manual manner, with the quality greatly depending on the experience and technical level of the route selection personnel. Thus, the result of route selection is often not scientific and reasonable enough. Therefore, a route selection method of oil and gas pipelines in mountainous areas based on geological information atlas was put forward. Specifically, the regional geological information atlas is established in terms of landform, geological risk, high consequence area and sensitive area, the cost grid map for route selection through the quantification of factor cost is built with consideration to the routing cost of pipeline, and thus the optimal route is obtained through the analysis with optimal route algorithm. In addition, this method was applied to a pipeline in the mountainous area in Southwest China. By comparing the calculated route and the existing route, it is found that the route analyzed by this method of pipelines in mountainous areas based on the geological information atlas could effectively avoid the complex terrain, poor geological environment, high consequence area and environment sensitive area, and the distance cost could be considered comprehensively, thus solving the problem of inadequate consideration to the comprehensive factors in manual route selection. In general, the route selected by this method could be used as a reference for the pipeline route designers.

The impact of the sintering temperature on the microstructure and characteristics of Al–Si composite was investigated in this study. Al-60Si (wt%) composites were sintered at different temperatures, and the microstructural features were evaluated. Optimal microstructural characteristics were observed when the composites were sintered at 850 °C for 2 h. The resulting material exhibited a thermal conductivity, coefficient of thermal expansion, and relative density of 131.4 W/(m·K), 10.02 × 10 ^–6 K ^–1 , and 99.87%, respectively. Elevating the temperature facilitated better wettability of the material, which in turn aided the filling of voids within the material by liquid Al. In addition, a decrease in the total number of interfaces within the material and the establishment of a connected network by the Al matrix contributed to enhanced thermal conductivity and coefficient of thermal expansion.

In this study, we electroplated Co and Cu on nano-spiked silicon substrates that were treated with femtosecond laser irradiations. With energy-dispersive X-ray (EDX) analysis by a scanning electron microscope (SEM), it was found that both Co and Cu are primarily coated on the spike surfaces without changing the morphology of the nanospikes. We also found that nanoscale bridges were formed, connecting the Co-coated silicon spikes. The formation of these bridges was studied and optimized through a series of time-controlled electroplating and oxidizing processes. The bridges are related to the oxidation of Co in the air. When it is irradiated with visible light, this special structure has shown a capability of interactions with carbon monoxide and carbon dioxide molecules. The electroplated cobalt may be used for gas sensors.