Single Segment Research Articles

CLFNet: a multi-modal data fusion network for traffic sign extraction

Abstract When using image data for signage extraction, poor visibility conditions such as insufficient light, rainy days, and low light intensity are encountered, leading to low accuracy and poor boundary segmentation in vision-based detection methods. To address this problem, we propose a cross-modal latent feature fusion network for signage detection, which obtains rich boundary information by combining images with light detection and ranging depth images, thus compensating for the pseudo-boundary phenomenon that may occur when using a single RGB image segmentation. First, HRNet is utilized as the backbone network to extract the boundary information of the point cloud depth map and RGB image by introducing the boundary extraction module; Second, the sensitivity to the boundary is enhanced by applying the feature aggregation module to deeply fuse the extracted boundary information with the image features; Finally, boundary Intersection over Union (IOU) is introduced as an evaluation index. The results show that the method performs more superiorly compared to the mainstream RGBD network, with an improvement of 5.5% and 6.1% in IOU and boundary IOU, and an accuracy of 98.3% and 96.2%, respectively, relative to the baseline network.

Advanced WIfI Stage is Associated with Poor Outcomes in the BEST-CLI Trial

Wound, ischemia, and foot infection (WIfI) staging was established to provide objective classification in patients with chronic limb threatening ischemia (CLTI) and to predict 1-year major amputation risk. Our goal was to validate WIfI staging using data from the Best Endovascular versus Best Surgical Therapy in Patients with CLTI (BEST-CLI) trial. Data from the BEST-CLI Trial, a prospective randomized trial comparing surgical (OPEN) and endovascular (ENDO) revascularization, were used to assess the association of WIfI stage on long-term outcomes in an intention to treat analysis. Patients were prospectively allocated to two cohorts - cohort 1 and 2 - which included patients with and without adequate single segment greater saphenous vein (SSGSV), respectively. The primary outcome of this analysis was major amputation. There were 1,568 patients analyzed, representing 86% of the entire trial population; of these 35.5%, 29.6% and 34.9% were categorized as WIfI 4, WIfI 3, and WIfI 1/2, respectively. There were 1223 patients (606 OPEN, 617 ENDO) and 345 patients (OPEN 172, ENDO 173) in cohorts 1 and 2, respectively. On unadjusted Kaplan-Meier analysis, WIfI clinical stages 4 and 3, compared to WIfI 1/2, were associated with higher rates of major amputation (21.4%, 16.2% vs. 10.7%), death (33.5%, 35.7% vs. 24.6%), amputation/death (44.9%, 44.5% vs. 31.3%), MALE/death (34.4%, 33.9% vs. 29.5%), and reintervention/amputation/death (69.9% vs. 69% vs. 60.4%) (P<.05 for all) at 3 years. On risk adjusted analysis, compared to WIfI 1/2, major amputation was associated with WIfI 4 (HR 2.06, 95% CI 1.44 - 2.96, P<.001) and WIfI 3 (HR 1.62, 95% CI 1.1-2.37, P=.013) stages. Death was associated with both WIfI 4 (HR 1.3, 95% CI 1.03 - 1.63, P=.027) and WIfI 3 (HR 1.42, 95% CI 1.13-1.79, P=.003). MALE/death was associated with WIfI 4 (HR 1.29, 95% CI 1.02 - 1.63, P=.036. Reintervention amputation/death was associated with WIfI 4 (HR 1.28, 95% CI 1.09 - 1.50, P=.03) and WIfI 3 (HR 1.22, 99% CI 1.03 - 1.43), P=.018). When examining OPEN vs. ENDO revascularization by each WIfI stage, OPEN intervention was favored in cohort 1 for MALE/death for each stage. In BEST-CLI WIfI stage was strongly associated with major amputations, death, and MALE/death after revascularization for CLTI. Cohort 1 patients, with adequate preoperative SSGSV, had lower MALE/death with OPEN intervention across all WIfI stages. This validation of WIfI score in a prospective multicenter trial reinforces its importance in shared-decision making, informed consent, and prognostication.

Single plant segmentation and growth parameters measurement of maize seedling stage based on point cloud intensity

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Study on the effect of the distribution of bone cement of residual back pain after percutaneous vertebra plasty

To investigate the effect of bone cement distribution on efficacy of residual back pain after percutaneous vertebra plasty(PVP). From January 2017 to December 2020, a total of 65 cases with single segment osteoporotic thoracolumbar vertebral fractures underwent parallel vertebroplasty surgery. On the basis of the postoperative X-ray films of bone cement distribution were divided into two groups. The bone cement was biased to the lateral side of the vertebral body (partial group, 20 cases), there were 9 males and 11 famales with an average age of (70.3±7.4) years old ranging from 60 to 84 years old. The bone cement was over the vertebral midline, and completely filled with contralateral vertebral body (bilateral group, 45 cases), there were 10 males and 35 famales with an average age of (70.7±8.0) years old ranging from 60 to 86 years old. All of them underwent PVP surgery, bone cement was injected into the vertebral body through paitail transpedicular approach. The amount of bone cement injection, the visual analogue scale(VAS) of preoperation and 1 day, 1 month, 3 months after surgery between two groups were observed and compared. The amount of cement injection was (4.25±0.99) ml in the partial group, and (4.07±1.18) ml in the bilateral group, there was no significant difference between two groups (P>0.05). Postoperative pain was relieved than preoperative pain (P<0.05), the VAS of 1 day, 1 and 3 months after operation (3.90±1.37), (2.35±0.67) and (1.55±0.51) in the partial group were higher than (2.67±0.60), (1.62±0.58) and (1.31±0.47) in the bilateral group (P<0.05). There were 9 cases in partial group, the pain was not relieved due to unfilled cement until the contralateral bone was injected into the bone cement. The distribution of bone cement is one of the main factors affecting residual back pain after PVP, and in the clinical, we should make sure the distribution of bone cement over the midline of vertebral body.

Analysis of mooring performance and layout parameters of multi-segment mooring system for a 15 MW floating wind turbine

IntroductionFloating wind power is the important path for the development of offshore wind energy, and the performance of the mooring system of floating wind turbines (FOWTs) significantly affects their economic viability, safety, and sustainability.MethodsThis paper systematically analyses the positioning performance, mooring line extreme loads, and fatigue response of a FOWT equipped with both single segment and multi-segment mooring systems, based on the IEA 15 MW large turbine and a floating platform. The hydrodynamic performance of the floating platform is calculated, and the platform’s motion-sensitive directions are analysed through Response Amplitude Operators (RAOs). The natural periods of the platform are validated by free decay tests. The six degrees of freedom (DOFs) motion response and the mooring line peak tensions are analysed under normal and extreme conditions.ResultsThe results show that both mooring systems provide good motion performance and stable tilt angles for the platform. Under ALS (single-line failure) condition, the multi-segment mooring system demonstrates a notable capacity to resist impact loads, with comparatively minor fluctuations in mooring line tension. In the multi-segment system, fatigue damage primarily occurs in the upper mooring chain, with damage approximately 4.5 times greater than that of the bottom chain over a 1-year period. The effects of mooring line spread angles and lengths on performance are also analysed. The results indicate that the mooring line spread angle has slight impact on platform motion response and mooring line tension, while mooring line length significantly affects the extreme tension of the lines.DiscussionThe findings of this study can provide some references in the design of mooring systems for future FOWTs.

Knowledge-driven stochastic modeling of geological geometry features conditioned on drillholes and outcrop contacts

Geometry features in geosciences are crucial for understanding both near-surface and deeper Earth’s interior structures. Geometry features have traditionally been delineated through diverse data sources such as surface mapping, geophysics, and core samples. However, the quantitative integration of geological knowledge and insights with the geoscientific data remains insufficiently addressed in the model construction. We have formulated a novel framework that employs stochastic level set simulation to model subsurface geometric features. The uniqueness of our framework involves geological knowledge, represented by two-dimensional (2D) geological diagrams, in the numerical modeling using Procrustes analysis. We account for the geological diagrams’ intrinsic variability and uncertainty through transformations such as rotation, scaling, and translation. By using the designed loss functions, the resulting models align with the established geological knowledge and are also conditioned on the lithology from drillhole and surface observations (i.e., outcrop contacts). We apply the methodology to a field study of a Cu-Ni-PGE (copper-nickel-platinum group element) prospect hosted in a mafic intrusion, the Crystal Lake Gabbro (CLG), in northwest Ontario. Our study focuses on a single segment of the y-shaped CLG. The numerical outcomes of this application demonstrate that the incorporation of expert knowledge, drillholes, and surface data yields models with reliable geological geometry features, particularly the distribution of bottom boundary for intrusion models which is highly associated with economic mineralization.

Patient and procedural characteristics of successful endovascular procedures in the BEST-CLI Trial and their relationship to major adverse limb events

Abstract Background The Best Endovascular versus Best Surgical Therapy in Patients with Chronic Limb Threatening Ischemia (CLTI) (BEST-CLI) trial randomized 1830 subjects with chronic limb threatening ischemia (CLTI) to endovascular or surgical bypass revascularization. Major adverse limb events (MALE) were higher after endovascular revascularization compared to bypass in the cohort with bypass using adequate single segment great saphenous vein. However, 15% of endovascular procedures had a major endpoint due to lack of technical success of the index procedure. Purpose To assess the factors related to a MALE in subjects in the BEST-CLI trial with an initial endovascular procedure that was technically successful. Methods All patients with a technically successful endovascular procedure (defined as a residual stenosis &amp;lt; 50% in the superficial femoral, popliteal, and/ or tibial arteries with in-line flow to the foot) were included. MALE was defined as above ankle amputation of the index limb or a major index-limb reintervention (new bypass, interposition graft revision, thrombectomy, or thrombolysis). Patient, procedure, and limb characteristics at the time of the index procedure were compared to the risk of MALE over an average 2.7 years follow-up. Characteristics were compared with the Kruskal-Wallis or Chi-square tests as appropriate. Results Of 923 patients having endovascular therapy as the index revascularization, 773 (84%) had a technically successful procedure. The cause of failure in 122 (82%) of unsuccessful procedures was the inability to cross the lesion with a wire. Significant patient factors associated with MALE included younger age (64 vs 68 years, p&amp;lt;0.0001), current smoking (44% vs 33%, p=0.004), and end-stage renal disease (17% vs 10%, p=0.013). Diabetes mellitus was not associated with MALE (74% vs 68%, p=0.08). Significant limb characteristics associated with MALE included lesions treated in the superficial femoral (SFA) or above knee popliteal artery (87% vs 81%, p=0.042), length of lesion in the SFA or above knee popliteal artery (201 cm vs 172 cm, p=0.02), use of atherectomy and bare-metal stent (10% vs 5%, p=0.01), and total procedure time (172 vs 155 min, p=0.002). Lesions treated in the below-knee popliteal artery or tibial arteries (62% vs 62%, p=0.93) or lesion length in this region (134 vs 144 cm, p=0.70) were not related to the risk of MALE. Conclusions The risk of MALE after successful endovascular revascularization for CLTI was increased with younger age, current smoking, end-stage renal disease, longer lesion length, treatment of the SFA to above knee popliteal arteries, and treatment with atherectomy with bare-metal stenting. Treatment of below knee lesions were not associated with MALE. These results indicate the importance of both modifiable and non-modifiable patient factors as well as the anatomic location of disease in determining limb outcomes in CLTI.

KeraRing Implantation with Femtosecond Laser in Keratoconus Treatment at Different Stages

Objective: To investigate the reliability and effectiveness of femtosecond laser-assisted KeraRing (Mediphacos, Belo Horizonte, Brazil) implantation in treating keratoconus. Methods: Intrastromal corneal ring segments (KeraRing, Mediphacos, Brazil) were implanted in 15 eyes of 14 patients unable to tolerate contact lenses. Femtosecond laser (Intralase, 60 Hz) was used for corneal tunnel creation. Based on the distribution of ectatic area on the cornea, dual segments were implanted in 9 eyes, while single segments were implanted in 6 eyes. Preoperative and postoperative uncorrected visual acuity (UCVA), best-corrected visual acuity (BCVA), objective and subjective refraction, and topographic corneal curvature (K) values of the cases were compared using the Wilcoxon test. Results: The mean age of patients was 25±7.46 (range: 15-39) years, with a mean postoperative follow-up period of 10.8±7.37 (range: 1-24 months). BCVA improved in all eyes during the follow-up period, increasing from a mean of 0.12±0.1 to 0.38±0.24 (p

Thoracic hypertrophied ligamentum flavum: A retrospective study of pre-operative factors and surgical outcome

Objectives: Thoracic hypertrophied ligamentum flavum (HLF) is a rare cause of thoracic myelopathy which requires surgical treatment. The study aims to analyze the pre-operative factors and surgical outcomes in patients with thoracic myelopathy secondary to HLF. Materials and Methods: This is a retrospective study of patients who underwent surgery for thoracic myelopathy due to HLF at a single center from December 2015 to November 2023. We included patient’s demographic data, clinical symptoms, radiological details, operative details, and outcome. We used Nurick’s grading system for outcome evaluation in pre-operative, post-operative, and follow-up. Relationship of various pre-operative parameters was evaluated with surgical outcomes on binary scale (favorable group [Nurick’s grade 1 and 2] and unfavorable outcome [Nurick’s grade 3–5]) using univariate and multivariate analysis. Results: A total of 57 patients were included in the study. On analyzing various prognostic factors with respect to favorable and unfavorable outcomes using univariate analysis, four factors came out to be statistically significant which were segments involved (multi vs. single segment involvement) (P &lt; 0.05), walking difficulty (P &lt; 0.05), intramedullary signal changes on T2-weighted magnetic resonance imaging (MRI) (P &lt; 0.001), and pre-operative Nurick’s grade (P &lt; 0.001). On multivariate analysis, only one factor, pre-operative Nurick’s grade came out statistically significant. Conclusion: Various factors are important in predicting the outcome of a patient with thoracic myelopathy secondary to HLF. The most important of which is pre-operative Nurick’s grade. Other factors that also affect the outcome are the presence of multisegmented disease and intramedullary T2 signal changes on MRI.

Nonlinear Frequency Response Analysis of Distributed Parameter Systems with One Spatial Coordinate

AbstractThe objective of this paper is to investigate possible strategies for applying nonlinear frequency response (NFR) analysis based on the concept of higher‐order frequency response functions to distributed parameter systems. Three approaches are presented and compared: one based on applying the existing procedure directly to the partial differential model, and two based on approximation of the distributed parameter system with a series of lumped parameter segments. One of them treats the complete series of segments integrally, while the other treats it segment by segment, so it uses only the model of a single segment. A simple example, an isothermal plug‐flow reactor with a simple reaction mechanism, is used as a case study. Pros and cons for all three approaches are given.

Introduction

Welcome to the first issue of the Journal of Connected Speech. We intend the journal to be a home for research and discussion in the wide area of communication beyond the single speech segment.

Characterization of duck tembusu virus NS2A membrane topology and functional residues in transmembrane domain-3 on viral proliferation

Flavivirus nonstructural protein 2A (NS2A) is a small endoplasmic reticulum (ER)-resident, hydrophobic transmembrane protein that function in viral replication, virion assembly and evasion of the host immune response. Despite previous studies on the role of duck Tembusu virus (DTMUV) NS2A in inhibiting the host immune response, its membrane topology has not been clearly addressed (Zhang et al., 2020; Zhang et al., 2022). Here, we present the first report on the membrane topology model and functional characterization of DTMUV NS2A. Our findings demonstrate that DTMUV NS2A localizes to the endoplasmic reticulum (ER) and associates with viral double-stranded RNA, with a single segment (TMD3, amino acids 72 to 95) spanning the ER membrane. To better delineate the residues in NS2A-TMD3 related to viral properties, specific mutations were introduced to generate DTMUV replicons and infectious cDNA clones. Functional analysis indicates that L77, Q86 and L89 of NS2A are crucial for viral RNA synthesis, while residues M79 and F83 are crucial for the assembly or release of viral particles. Moreover, these mutations attenuated the virulence of DTMUV in vivo. Collectively, our results shed light on the relationship between the transmembrane of DTMUV NS2A and its functions in virus proliferation, providing insights for further understanding the molecular mechanisms of NS2A in the virus life cycle.

Fiber optic temperature sensor based on Vernier effect generated by a linear sagnac interferometer in parallel with a Fabry-Perot interferometer

A novel fiber-optic temperature sensor based on a Linear Sagnac Interferometer (LSI) in parallel with a Fabry-Pérot Interferometer (FPI) has been developed. This sensor leverages the superposition of the FPI and LSI to generate a Vernier effect. Theoretical and experimental results demonstrate that within the temperature range of 40 °C–50 °C, the temperature sensitivity of the parallel structure reaches 13.27 nm/°C, aligning well with theoretical predictions. Notably, when the LSI and Circular Sagnac Interferometer (CSI) exhibit identical temperature sensitivities and free spectral ranges (FSR), the length of the LSI is only half that of the CSI. The LSI is constructed from a single segment of Panda fiber and does not form a loop. Consequently, this sensor is simpler and easier to manufacture compared to conventional CSI sensors, offering significant advantages in structural simplicity and fabrication efficiency. This makes the proposed sensor a valuable reference for sensing applications in diverse environments.

Advancements in prostate zone segmentation: integrating attention mechanisms into the nnU-Net framework

Abstract Prostate cancer is one of the most lethal cancers in the world. Early diagnosis is essential for successful treatment of prostate cancer. Segmentation of prostate zones in magnetic resonance images is an important task in the diagnosis of prostate cancer. Currently, the state-of-the-art method for this task is no-new U-Net. In this paper, a method to incorporate the attention U-Net architecture into no-new U-Net is proposed and compared with a classical U-net architecture as research. The experimental results indicate that there is no significant statistical difference between the proposed modification of no-new U-Net with the generalizability of the attention mechanism or the ability to achieve more accurate results. Moreover, two novel workflows are proposed for prostate segmentation, transitional zone segmentation and peripheral zone calculation workflow, and separate models for peripheral zone and transitional zone segmentation workflow. These workflows are compared with a baseline single peripheral zone and transitional zone segmentation model workflow. The experimental results indicate that separate models for peripheral zone and transitional zone segmentation workflow generalizes better than the baseline between data sets of different sources. In peripheral zone segmentation separate models for peripheral zone and transitional zone segmentation workflow achieves 1.9% higher median Dice score coefficient than the baseline workflow when using the attention U-Net architecture and 5.6% higher median Dice score coefficient when using U-Net architecture. Moreover, in transitional zone segmentation separate models for peripheral zone and transitional zone segmentation workflow achieves 0.4% higher median Dice score coefficient than the baseline workflow when using the attention U-Net architecture and 0.7% higher median Dice score coefficient when using U-Net architecture. Meanwhile, prostate segmentation, transitional zone segmentation and peripheral zone calculation workflow generalizes worse than the baseline. In peripheral zone segmentation prostate segmentation, transitional zone segmentation and peripheral zone calculation workflow achieves 4.6% lower median Dice score coefficient than the baseline workflow when using the attention U-Net architecture and 3.6% lower median Dice score coefficient when using U-Net architecture. In transitional zone segmentation prostate segmentation, transitional zone segmentation and peripheral zone calculation workflow achieves a similar median Dice score coefficient to the baseline workflow.

Mycoviruses from Aspergillus fungi involved in fermentation of dried bonito

Fungi are exploited for fermentation of foods such as cheese, Japanese sake, and soy sauce. However, the diversity of viruses that infect fungi involved in food fermentation is poorly understood. Fermented dried bonito (“katsuobushi”) is one of the most important processed marine products in Japan. Fungi involved in katsuobushi fermentation are called katsuobushi molds, and Aspergillus spp. have been reported to be dominant on the surface of katsuobushi during fermentation. Because various mycoviruses have been found in members of the genus Aspergillus, we hypothesized that katsuobushi molds are also infected with mycoviruses. Here, we describe seven novel mycoviruses belonging to six families (Chrysoviridae, Fusariviridae, Mitoviridae, Partitiviridae, Polymycoviridae, and Pseudototiviridae) from isolated katsuobushi molds (Aspergillus chevalieri and A. sulphureus) detected by fragmented and primer-ligated double-stranded RNA sequencing. Aspergillus chevalieri fusarivirus 1 has a unique bi-segmented genome, whereas other known fusariviruses have a single genomic segment. Phenotypic comparison between the parental A. chevalieri strain infected with Aspergillus chevalieri polymycovirus 1 (AchPmV1) and isogenic AchPmV1-free isolates indicated that AchPmV1 inhibits the early growth of the host. This study reveals the diversity of mycoviruses that infect katsuobushi molds, and provides insight into the effect of mycoviruses on fungi involved in fermentation.

A ship trajectory clustering algorithm based on segmentation direction

With the increase of ship AIS data. Through AIS data mining algorithm, it is possible to extract guidelines for the best path of a specific water area by using trajectory segment clustering. The defects of the current trajectory segment clustering algorithm are mainly reflected in: the lack of direction of the path after clustering; For trajectory segment clustering, the whole trajectory is considered rather than a single trajectory segment. In this paper, the trajectory direction and density are used as a measure of similarity between trajectories, and the trajectory segment clustering algorithm is used to analyze the compressed ship trajectory segment data. The first step is to eliminate clusters that contain too few trajectories, and clusters that have too small a distance value between trajectories. For two nearby clusters in opposite directions, the Hausdorff distance is determined. When the distance is less than the threshold, the trajectory is considered to be a two-way route. Finally, the trajectory clusters after clustering are fused to form a view of the overall traffic flow frame of ships in the water area. The framework can describe the main driving direction of the ship in the water and provide decision-making suggestions for the driver's path planning.

Multi-spectral image transformer descriptor classification combined with molecular tools for early detection of tomato grey mould

Accurate early detection of plant diseases is a critical milestone in the development of self-navigating robots for precision agriculture and still remains one of the most significant challenges. Plant pathogens, like Botrytis cinerea causing grey mould disease, pose significant threats to agriculture and food safety. This study focuses on the early detection of B. cinerea in tomato crops using Artificial Intelligence. Specifically, the Deep Learning (DL) YOLOv8 architecture was employed to apply single class segmentation on plant captures to extract the tomato leaves locational information. Each plant capture includes five images from hyperspectral wavelengths (at 460, 540, 640, 775 and 875 nm) and one RGB images. The leaf segmentation achieved 81.7 % Mean Average Precision (mAP) at Intersection over Union (IoU) threshold 0.5 (mAP50). Then the for each leaf segment, and array of descriptors is extracted through various Transformer models. Finally, the descriptors are classified through a KNN or an LSTM solution and the results of all the descriptors for each leaf from each of the Transformer models, for each of the six images of the capture, are ensembled to yield the class of each leaf. The best ensemble results were produced by only accumulating results from some of the Transformer and specifically the MaxViT-L, the ViT-B (P:16 × 16 – C), the VOLO (D:5) and the XCIT-L (L:24 – P:16 × 16), by only using the results provided by the images at the hyperspectral wavelengths at 540, 640 nm and the RGB image, and by applying the LSTM solution. The process achieved a 79.41 % classification accuracy and 71.12 % F1-Score for all classes. Additionally, early, rapid and accurate detection of grey mould at the early stages of the infection or at latent infections when symptoms are not visible was assessed by comparative qPCR-based methods (qRT-PCR) for fungal biomass estimation in plant tissues and the rest of this study's methodology. The findings of this study represent a significant advancement in crop disease detection and management, and highlight the potential for integrating these methods into on-site digital systems (robots, mobile apps, etc.) under real-world settings. The results, demonstrate the effectiveness of combining segmentation and transformer-based classification models for early and accurate detection of grey mould disease.

Review on Amprobot an Assistive Robotic Arm for Amputee Patients

In this paper, an aim has been set to prepare a literature review based on the development and the production of robotic prosthetic arm for amputee patients. As written in 2011 census, the population with disabilities were approx. 2.68 crore, which accounts for 2.23% for the total population. In India, various companies like M/s. TTK Healthcare Limited and organizations like the Indian Institute of Technology (IIT) working on developing advanced prosthetic technologies and considerable R and D has been involved in the development and deployment of robotic arms and advanced prosthetic solutions for amputees. However, the implementation of these studies is yet to be enforced in the Indian Market to the best level. Thus, there was a huge gap between Study and its Practical usage. Research and results have been produced for many single segments explaining various factors to be considered for Robotic Arm. However, to date, very few attempts have been made to practically implement and optimize the overall design. The various different articles and their processes are studied thoroughly.

Reliability testing of an IMU-based 2-segment foot model for clinical gait analysis

BackgroundThe one of the most commonly used reference system for clinical gait analysis is an optical motion capture system (OMC) using a multi-segment foot model. A time- and cost-efficient alternative could be an inertial measurement unit (IMU)-based systems. However, these are limited to a single segment approach for the foot and ankle. Therefore, the current setup was modified to be based on a 2-segment foot model, allowing for a separate analysis of the hind- and midfoot. The study aimed to evaluate the reliability (inter-rater, intra-rater, and test-retest reliability) of an IMU-based 2-segment foot model. Material and methodsTwelve healthy subjects were recruited to test the inter-rater, intra-rater, and test-retest reliability of the new IMU based 2-segment foot model. Gait analysis was performed on a treadmill at a constant speed of 4 km/h. Kinematic data of the tibia/hindfoot, tibia/forefoot and hindfoot/forefoot over 100 % gait cycle were analyzed. The reliability was tested by using statistical parametric mapping (SPM) and the intraclass correlation coefficient (ICC). ResultsThe SPM showed no significant difference for inter-, intra-rater, and test-retest reliability, but for a small segment of tibia/forefoot dorsiflexion test-retest reliability (2.1° difference). The single standard deviation measurement error for the sagittal and transverse plane was <5° and worse for the frontal plane. ConclusionThe new 2-segment foot model revealed a high inter-rater, intra-rater, and test-retest reliability. It is suitable for use in adult clinical practice. Still, comparative data to the OMC system using a multi-segment foot model are missing.

Clinical efficacy of one-stage anterior debridement and bone graft fusion for the treatment of cervical pyogenic spondylodiscitis

Objective: To investigate the efficacy of one-stage anterior debridement and bone graft fusion for the treatment of cervical pyogenic spondylodiscitis. Methods: This is a retrospective case series study. Retrospective analysis of clinical data from 23 patients with cervical pyogenic spondylodiscitis treated with one-stage anterior approach debridement and bone graft fusion was performed in the Department of Spinal Surgery, the First Affiliated Hospital of Xinjiang Medical University from January 2015 to January 2020. There were 14 males and 9 females,aged (51.9±12.8) years (range:26 to 82 years). Preoperatively, 14 patients had neurological deficits, classified according to the American Spinal Injury Association (ASIA) impairment scale as follows: grade A in 1 case, grade B in 1 case, grade C in 5 cases, and grade D in 7 cases. All patients underwent the one-stage anterior debridement and fusion procedure. The surgical time, blood loss, hospital stay, fusion time, and surgical complications were documented. Clinical efficacy was assessed using the visual analogue scale (VAS), the neck disability index (NDI), and the ASIA impairment scale. Preoperative and postoperative data were compared using paired sample t tests, repeated measures analysis of variance, and generalized estimating equations. Results: All the 23 patients underwent the operative procedures successfully. The operation time was (102.8±19.8) minutes (range:60 to 140 minutes), blood loss was (84.4±40.2) ml (range:30 to 160 ml), and the length of hospital stay was (17.4±6.0) days (range:10 to 30 days). Blood cultures were positive for the causative pathogen in 14 cases (60.8% positivity rate), while 9 cases had negative results. Irrigation fluid cultures yielded the causative pathogen in 19 cases (82.6% positivity rate), with 4 cases negative. All patients were followed up for more than 12 months, with a follow-up duration of (19.0±5.9) months (range:12 to 36 months). At the final follow-up, VAS improved from (5.9±1.1) points preoperatively to (0.8±0.3) points; NDI improved from (38.3±6.0)% preoperatively to (9.3±3.0)%, with statistically significant differences (both P<0.01). All patients experienced improvement in neurological function, with the exception of one patient in grade C and two in grade D, all other patients recovered to grade E. The C2-7 Cobb angle and the affected segment Cobb angle were corrected. white blood cell, erythrocyte sedimentation rate and C-reactive protein levels returned to normal. All patients achieved bony fusion, with a fusion time of (8.9±1.9) months (range:6 to 12 months). Two diabetic patients developed postoperative incision infection; no other surgery-related complications occurred in the remaining patients. Conclusion: One-stage anterior debridement and bone graft fusion can correct kyphosis, restore normal alignment, and improve neurological function in the treatment of single and double segment cervical pyogenic spondylodiscitis, representing a viable treatment option for cervical pyogenic spondylodiscitis.