Search Results (169,563)

To address the issues of low recognition rates and poor detection accuracy for road negative obstacles caused by insufficient feature representation, we propose a novel detection framework: the Negative Road Obstacles Segmentation Network (NROSegNet). The detection performance of the algorithm is improved through a data enhancement strategy based on feature splicing and an adaptive feature enhancement module. Specifically, the data augmentation strategy introduces negative obstacle features into other datasets through geometric transformations and random splicing, effectively increasing the diversity of training data. This can solve the problem of an uneven distribution of data features while improving the performance of the model in capturing illumination changes and local details. The framework further adopts a dynamic multi-scale feature enhancement module to improve the perception of local details and global semantics. A robust multimodal data fusion mechanism and edge-aware optimization strategy are designed to effectively alleviate the problems of noise interference and boundary blur. The experimental results show that the NROSegNet proposed in this paper achieves 70.6 and 83.0 in mIoU and mF1, respectively, which is 2.8 percentage points and 2.9 percentage points higher than other methods. The results fully demonstrate its excellent performance in precise segmentation and boundary detail processing. Full article

To better utilize multimodal information for agriculture applications, this paper proposes a cherry tomato bunch detection network using dual-channel cross-feature fusion. It aims to improve detection performance by employing the complementary information of color and depth images. Using the existing YOLOv8_n as the baseline framework, it incorporates a dual-channel cross-fusion attention mechanism for multimodal feature extraction and fusion. In the backbone network, a ShuffleNetV2 unit is adopted to optimize the efficiency of initial feature extraction. During the feature fusion stage, two modules are introduced by using re-parameterization, dynamic weighting, and efficient concatenation to strengthen the representation of multimodal information. Meanwhile, the CBAM mechanism is integrated at different feature extraction stages, combined with the improved SPPF_CBAM module, to effectively enhance the focus and representation of critical features. Experimental results using a dataset obtained from a commercial greenhouse demonstrate that DCFA-YOLO excels in cherry tomato bunch detection, achieving an mAP50 of 96.5%, a significant improvement over the baseline model, while drastically reducing computational complexity. Furthermore, comparisons with other state-of-the-art YOLO and other object detection models validate its detection performance. This provides an efficient solution for multimodal fusion for real-time fruit detection in the context of robotic harvesting, running at 52fps on a regular computer. Full article

Gas pipeline networks are vital urban infrastructure, susceptible to leaks caused by natural disasters and adverse weather, posing significant safety risks. Detecting and localizing these leaks is crucial for mitigating hazards. However, existing methods often fail to effectively model the time-varying structural data of pipelines, limiting their detection capabilities. This study introduces a novel approach for leak detection using a spatial–temporal attention network (STAN) tailored for small-hole leakage conditions. A graph attention network (GAT) is first used to model the spatial dependencies between sensors, capturing the dynamic patterns of adjacent nodes. An LSTM model is then employed for encoding and decoding time series data, incorporating a temporal attention mechanism to capture evolving changes over time, thus improving detection accuracy. The proposed model is evaluated using Pipeline Studio software and compared with state-of-the-art models on a gas pipeline simulation dataset. Results demonstrate competitive precision (91.7%), recall (96.5%), and F1-score (0.94). Furthermore, the method effectively identifies sensor statuses and temporal dynamics, reducing leakage risks and enhancing model performance. This study highlights the potential of deep learning techniques in addressing the challenges of leak detection and emphasizes the effectiveness of spatial–temporal modeling for improved detection accuracy. Full article

The ORA (olfactory receptor class A) gene family in teleosts is related to the V1R (vomeronasal 1 receptors) family in mammals and plays a key role in odor detection. Although ORA genes have been identified in several teleosts, their characteristics in mandarin fish (Siniperca chuatsi) have not been explored. In this study, we conducted a comprehensive genomic analysis of the mandarin fish and discovered a complete ORA gene family consisting of five members located on chromosome 2 (ORA1, ORA2, ORA3, ORA4) and chromosome 16 (ORA6). Phylogenetic, synteny, and gene structure analyses revealed typical exon–intron conservation with strong evidence of purifying selection. Tissue expression analysis showed distinct expression profiles for each ORA gene, with some showing sexual dimorphism in specific tissues. The expression of ORA1 and ORA2 in the olfactory epithelium exhibits sexual dimorphism, while ORA3 shows sexual dimorphism in the brain. In situ hybridization confirmed that ORA1, ORA2, ORA3, and ORA6 are expressed in the microvillar sensory neurons of the olfactory epithelium, while ORA4 is expressed in crypt cells. Additionally, molecular docking simulations indicated that the five ORA proteins have a high binding affinity with seven bile acids (LAC, GLAC, CA, TLCA, 3-KLCA, 7-KLCA, and 12-KLCA), with ORAs showing stronger binding affinity with LCA and CA. This study comprehensively characterizes the ORA gene family in mandarin fish, examining its phylogeny, synteny, gene structure, and selection pressure. Furthermore, we found that each ORA displays a distinct expression pattern across multiple tissues, with notable sexual dimorphism, and shows potential binding interactions with specific bile acids and pheromones. Our findings provide valuable insights that enhance the overall understanding of fish ORAs and their potential functions. Full article

This paper provides an overview of the three-year effort to design and implement a prototypical sense-and-avoid (SAA) system based on a multisensory architecture leveraging data fusion between optical and radar sensors. The work was carried out within the context of the Italian research project named TERSA (electrical and radar technologies for remotely piloted aircraft systems) undertaken by the University of Pisa in collaboration with its industrial partners, aimed at the design and development of a series of innovative technologies for remotely piloted aircraft systems of small scale (MTOW < 25 Kgf). The system leverages advanced computer vision algorithms and an extended Kalman filter to enhance obstacle detection and tracking capabilities. The “Sense” module processes environmental data through a radar and an electro-optical sensor, while the “Avoid” module utilizes efficient geometric algorithms for collision prediction and evasive maneuver computation. A novel hardware-in-the-loop (HIL) simulation environment was developed and used for validation, enabling the evaluation of closed-loop real-time interaction between the “Sense” and “Avoid” subsystems. Extensive numerical simulations and a flight test campaign demonstrate the system’s effectiveness in real-time detection and the avoidance of non-cooperative obstacles, ensuring compliance with UAV aero mechanical and safety constraints in terms of minimum separation requirements. The novelty of this research lies in (1) the design of an innovative and efficient visual processing pipeline tailored for SWaP-constrained mini-UAVs, (2) the formulation an EKF-based data fusion strategy integrating optical data with a custom-built Doppler radar, and (3) the development of a unique HIL simulation environment with realistic scenery generation for comprehensive system evaluation. The findings underscore the potential for deploying such advanced SAA systems in tactical UAV operations, significantly contributing to the safety of flight in non-segregated airspaces Full article

Single-photon avalanche detectors (SPADs) have significant applications in fields such as autonomous driving. However, processing massive amounts of background data requires substantial storage and computational resources. This paper designs a linear SPAD sensor capable of three detection modes: 2D intensity detection, 3D synchronous detection, and 3D asynchronous detection. A configurable coincidence circuit is used to effectively suppress background light. To overcome the significant resource demands for storage and computation, this paper designs a histogram circuit that simultaneously possesses data storage and shifting capabilities. This circuit can not only perform statistical counting on time data but also shift data to quickly complete computational analysis. The chip is fabricated using a 0.13 μm mixed-signal CMOS process, with a pixel scale of 64 elements, a time resolution of 132 ps, and a power consumption of 12.9 mW. Test results indicate that the chip has good detection capabilities and good background light suppression. When the background light intensity is 6000 lux, the maximum background data are suppressed by 95.4%, and the average suppression rate increases to 86% as the coincidence threshold is raised from 0 to 1. Full article

Currently, semiconductor gas sensors are being actively studied and used in various fields, including ecology, industry, and medical diagnostics. One of the major challenges is to reduce their operating temperature to room temperature. To address this issue, sensor layers based on WO_3−x/WS₂ nanostructures synthesized by the hydrothermal method have been proposed. In this paper, the morphology of the material’s surface and its elemental composition were investigated, as well as the optical band gap. Additionally, changes in the resistance of the WO_3−x/WS₂ sensor layers under the influence of alcohol vapors at room temperature were analyzed. The results showed that the layers exhibited a significant response, with short response and recovery times. The achieved response value to 1000 ppm of isopropanol was 1.25, with a response time of 13 s and a recovery time of 12 s. The response to 1000 ppm of ethanol was 1.35, and the response and recovery times were 20 s. This indicates that these sensor layers have promising potential for various applications. Full article

Beckmannia syzigachne is one of the most competitive weeds in winter wheat fields in China. In this study, 120 suspected resistant populations of Beckmannia syzigachne were collected from the Anhui, Hubei, Jiangsu, and Shandong Provinces from 2017 to 2019. In total, 110 populations exhibited different levels of resistance to clodinafop-propargyl, 114 populations expressed different levels of resistance to mesosulfuron-methyl, and 105 populations were resistant to both herbicides at different levels. The resistant weeds were mainly distributed in Anhui and Jiangsu Provinces. The detection results of acetyl coA carboxylase (ACCase) and acetolactate synthase (ALS) genes in the resistant populations indicated that ACCase gene mutations occurred in 97 out of 110 populations resistant to clodinafop-propargyl and ALS gene mutations occurred in 25 out of 114 populations resistant to mesosulfuron-methyl. There were several mutation types, including Ile-1781-Leu, Trp-2027-Cys, Ile-2041-Asn, Ile-2041-Val, Asp-2078-Gly, and Gly-2096-Ala in the ACCase sequence and Pro-197-Ser, Pro-197-Thr, Pro-197-His, Pro-197-Leu, Asp-376-Glu, and Trp-574-Leu in the ALS sequence. Among these mutation types, Pro-197-His, Asp-376-Glu, and Trp-574-Leu in the ALS sequence were the first identified in Beckmannia syzigachne. Full article

Wastewater surveillance is a powerful public health tool which gained global prominence during the COVID-19 pandemic. This article describes the development and implementation of the national wastewater surveillance network in France: SUM’EAU. Preliminary work included defining a sampling strategy, evaluating/optimising analytical methods, launching a call for tenders to select network laboratories and producing wastewater monitoring indicators. SUM’EAU was then deployed in three stages: (i) a pilot study, (ii) the transfer of analytical activities from the National Reference Laboratory to four selected network laboratories, and (iii) the extension of the system to additional sampling sites. Currently, SUM’EAU monitors SARS-CoV-2 across 54 wastewater treatment plants in mainland France. Once a week on business days, 24 h flow-proportional composite samples are collected at plant inlets and transported at 5 °C (±3 °C) to partner laboratories for analysis. The analytical process involves sample concentration, RNA extraction, and digital RT-PCR/q-RT-PCR to detect and quantify the presence of the SARS-CoV-2 genome in wastewater. Subsequently, data are transferred to Santé publique France, the French National Public Health Agency, for analysis and interpretation. While SUM’EAU has been instrumental in monitoring the COVID-19 pandemic and holds significant potential for broader application, securing sustainable funding for its operation remains a major challenge. Full article

Actinobacillus pleuropneumoniae is a major swine pathogen, classified into 19 serotypes based on capsular polysaccharide (CPS) loci. This study aimed to improve the diagnostic method to differentiate between serotypes 9 and 11, which are challenging to distinguish using conventional serological and molecular methods. A novel qPCR assay based on locked nucleic acid (LNA) probes was developed and validated using a collection of reference strains representing all known 19 serotypes. The assay demonstrated specificity in detecting the nucleotide variation characteristic of the serotype 9 reference strain. However, the analysis of a clinical isolate collection identified discrepancies between LNA-qPCR and serological results, prompting further investigation of the cps and O-Ag loci. Subsequent nanopore sequencing and whole-genome sequencing of a collection of 31 European clinical isolates, previously identified as serotype 9, 11, or undifferentiated 9/11, revealed significant genetic variations in the cps and O-Ag loci. Ten isolates had a cpsF sequence identical to that of the serotype 11 reference strain, while six isolates had single-nucleotide polymorphisms that were unlikely to cause significant coding changes. In contrast, 15 isolates had interruptions in the cpsF gene, distinct from that found in the serotype 9 reference strain, potentially leading to a serotype 9 CPS structure. In the O-Ag loci, differences between serotypes 9 and 11 were minimal, although some isolates had mutations potentially affecting O-Ag expression. Overall, these findings suggest that multiple genetic events can lead to the formation of a serotype 9 CPS structure, hindering the development of a single qPCR assay capable of detecting all cpsF gene mutations. Our results suggest that, currently, a comprehensive analysis of the cpsF gene is necessary to accurately determine whether the capsule of an isolate corresponds to serotype 9 or 11. Although such analyses are feasible with the advent of third-generation sequencing technologies, their accessibility, cost, and time to result limit their use in routine diagnostic applications. Under these circumstances, the designation of the hybrid serovar 9/11 remains a valid approach. Full article

This paper presents the concept of a radiofrequency (RF) sensor designed to estimate the mass of the regolith acquired by a sampling device or excavator in planetary environments. The sensor utilizes a microstrip line with an open end as the sensing element, with the mass estimation based on measurements of the phase of the reflection coefficient (S11 of the scattering matrix) for the line immersed in the regolith. The Rotary Clamshell Excavator (RCE) was employed for the experimental evaluation of the sensor’s performance. The RCE successfully passed an environmental test campaign, demonstrating its suitability for future lunar missions. The test results indicate that the RF sensor can estimate the mass of the acquired regolith with reasonable accuracy, approximately 15%, making it a viable solution for rough mass estimation in sampling devices and excavators. Full article

Background: Autoantibodies such as rheumatoid factor (RF) and anticitrullinated protein autoantibodies (ACPAs) are useful tools for rheumatoid arthritis (RA). The presence of ACPAs against citrullinated proteins (CPs), especially citrullinated fibrinogen (cFBG), seems to be a useful serological marker for diagnosing RA. RA patients’ sera were found to be enriched in exosomes that can transmit many proteins. Exosomes have been found to express citrullinated protein such as cFBG. Objective: We conducted this study in two stages. In the first phase, we aimed to evaluate the association between autoantibodies and risk factors. In the next step, ACPA-positive serum samples from the first phase were subjected to exosomal studies to explore the presence of cFBG, which is a frequent target for ACPAs. Methods: We investigated the autoantibodies in one hundred and sixteen Saudi RA patients and correlated with host-related risk factors. Exosomes were extracted from patients’ sera and examined for the presence of cFBG using monoclonal antibodies. Results: The study reported a high female-to-male ratio of 8:1, and seropositive RA (SPRA) was more frequent among included RA patients. The frequency and the levels of ACPAs were similar in both genders. Autoantibodies incidences have a direct correlations with patient age, while the average titers decreased as the age increased. Further, the highest incidence and levels of autoantibodies were reported in patients with RA duration between 5 and 10 years. Smoking and family history have no impact on autoantibody, except for ACPAs titers among smokers’ RA. Our analysis of serum exosomes revealed that about 50% of SPRA patients expressed cFBG. Conclusions: The female-to-male ratio is 8:1, which is higher than the global ratio. We can conclude that patients’ age and disease duration contribute to the autoantibodies, particularly RF and anti-MCV, whereas smoking and family history had no effects on autoantibodies. We detected cFBG in all exosomes from SPRA patients; thus, we suggest that the precise mechanism of exosomes in RA pathogenesis can be investigated to develop effective treatment strategies. Full article

Capsule endoscopy is a common method for detecting digestive diseases. The location of a capsule endoscope should be constantly monitored through a visual inspection of the endoscopic images by medical staff to confirm the examination’s progress. In this study, we proposed a computer-aided analysis (CADx) method for the localization of a capsule endoscope. At first, a classifier based on a Swin Transformer was proposed to classify each frame of the capsule endoscopy videos into images of the stomach, small intestine, and large intestine, respectively. Then, a K-means algorithm was used to correct outliers in the classification results. Finally, a localization algorithm was proposed to determine the position of the capsule endoscope in the alimentary tract. The proposed method was developed and validated using videos of 204 consecutive cases. The proposed CADx, based on a Swin Transformer, showed a precision of 93.46%, 97.28%, and 98.68% for the classification of endoscopic images recorded in the stomach, small intestine, and large intestine, respectively. Compared with the landmarks identified by endoscopists, the proposed method demonstrated an average transition time error of 16.2 s to locate the intersection of the stomach and small intestine, as well as 13.5 s to locate that of the small intestine and the large intestine, based on the 20 validation videos with an average length of 3261.8 s. The proposed method accurately localizes the capsule endoscope in the alimentary tract and may replace the laborious real-time visual inspection in capsule endoscopic examinations. Full article

Conservation agriculture (CA) is a sustainable land management approach to improve soil quality while mitigating degradation. Although extensive information regarding the effect of CA on soil properties and microbiome is available, complete studies on the cumulative effect on specific interactions between soil parameters, crop productivity, and microbial communities over time are still lacking, mainly in arid regions. Thus, this study aimed to investigate the effects of no-tillage and residue retention over long- and short-term (24 and 3 years, respectively) periods. Six treatments were established in a maize–oat–triticale system from 1995 in a semiarid region: P + H—plow + harrow; H—harrow; MP—multi-plow (short-term); NT—no-tillage; NT33—NT + 33% residue surface cover (long-term); NT66—NT + 66% residue surface cover. Results indicated that CA improved soil quality by increasing soil organic matter (SOM), total carbon, and glomalin; it also enhanced microbial abundance, particularly fungi, and β-galactosidase activity. Nevertheless, conventional tillage practices led to SOM degradation and reduced crop yields. Principal component analysis revealed distinct groupings of treatments based on soil properties and microbial communities. Furthermore, changes could be detected from the short term. These findings highlight the importance of adopting sustainable agricultural practices to maintain soil health and ensure agricultural productivity in semi-arid regions. Full article

Background: Adenomatoid tumor (AT) is a rare benign neoplasm of mesothelial origin, which mainly occurs in the male and female genital tracts. The most common site for AT occurrence in women is the uterus, which makes the presentation in the fallopian tube(s) a rarity with an incidence of approximately 0.5%. The reported extragenital sites include serosal surfaces, adrenal glands, and visceral organs, are even less common. Macroscopically, ATs present as white-grayish or yellowish irregular yet circumscribed firm nodules, often containing cystic components. Owing to a vast array of histomorphological growth patterns, ATs tend to mimic malignancy and trigger overresection. Such clinical situations have been described by several studies for the ovaries, uterus, and fallopian tubes, underlining the importance of differential diagnosis in order to avoid superfluous treatment. Methods: Herein, we report a presentation of an AT at the oviductal lumen, detected incidentally during prophylactic bilateral salpingo-oophorectomy in a 67-year-old patient with a BRCA1 mutation. Results: Immunohistochemical staining revealed a positive expression for calretinin, WT1, and cytokeratin 7, and negative expression for both PAX8 and CD34, thus confirming the diagnosis of AT and excluding tubal malignancy. Conclusions: This report, with a concise review of the global literature on tubal AT, brings attention to the solitary and asymptomatic nature of the tumor. With a clear diagnosis, no surgical radicality is necessary. Full article