Mechanical Transmission Research Articles

The transmission routes of African swine fever during an outbreak in Serbia July–August 2023: African swine fever virus detections in environmental samples and insects

African swine fever (ASF) is a highly contagious viral disease of domestic pigs and wild boar (Sus scrofa) caused by an arbovirus- African swine fever virus (ASFV), which is classified into the family Asfarviridae. Even though the main transmission route of ASFV is direct contact between animals and carcasses releasing ASFV into the environment, the role of other transmission routes such as via environmental contamination or insects remains in great part unclear. During an epidemic f ASF in Serbia in 2023, environmental samples (soil, feed, water and swabs from the pig barns), and insects [resulting in collection of adult and/or larval stages of non-biting flies (Diptera: Calliphoridae and Muscidae)] were collected in four locations in South Banat district of Serbia. To assess the possibility that insects carry the ASFV in infected courtyards, sticky fly traps and open Petri dishes containing meat mixed with humid cotton wads were offered in three locations during the five days of the experiment in the Belgrade area. Furthermore, to confirm the role of flies in ASF in mechanical transmission pathway in Serbia, L2 and L3 larvae of flies (Lucilia sericata Meigan, 1826; Stomoxys calcitrans Linnaeus, 1758) were collected from the pig carcasses from infected farms, bred to adults in the Laboratory and an ASFV spiked meat meal was placed into cages with three-day-old flies (n = 52) to estimate positivity of flies and duration of mechanical transmission of ASFV. The results from the environmental samples showed no positive ASFV DNA detection, the same was true for the samples from meat-based traps and sticky fly traps, while ASFV DNA was detected in three samples containing eggs, L1 and L3 fly larvae collected from carcasses and adult flies (L. sericata). In experimental conditions, only one S. calcitrans fly tested positive on day 1 post-infection. The results implicate the possible role of Lucilia sp. flies in the mechanical transmission of ASFV as well as S. calcitrans in Serbia during an outbreak, while ASFV DNA was not detected in environmental samples in this study.

Dynamics of Xylella fastidiosa and plum leaf scald: Insights from a long‐term study in Brazilian orchards

AbstractXylella fastidiosa is one of the most dangerous plant‐pathogenic bacteria globally, affecting various host species. Plum leaf scald (PLS) is the primary disease affecting plum trees in Brazil, with plant eradication efforts significantly increasing in recent years. This study aims to elucidate the disease dynamics and its vector in three monitored orchards from 2010 to 2015 and associate the pattern of pathogen dispersal with mechanical pruning. The incidence was lower in Porto Amazonas, starting at 0% and reaching 14% after 5 years. In contrast, the orchards in Araucaria and Palmeira showed an initial incidence around 5% in the first year, exceeding 80% by the end of the study. Sharpshooter leafhoppers, the vectors, were collected at ground and plant canopy level during the last 3 years. In 2013, more leafhoppers were found near the ground, but their numbers equalized across heights in the following years. Kernel smoothing revealed spatial dependence, and an autologistic model indicated an aggregated infection pattern with increased PLS risk for neighbouring plants. The border effect at the epidemic's onset was linked to pathogen entry via external vectors. The disease's progression along rows was attributed to effective mechanical pathogen transmission through pruning. Therefore, in regions with several summer prunings, it is recommended to sanitize pruning shears to prevent pathogen transmission. Constant monitoring and control of the vector are essential for effective disease management.

Emerging Begomovirus ToLCNDV Molecular Detection & Chip Grafting Inoculation Transmission Assay under Natural Conditions in Tomato Plants from District Poonch Azad Kashmir & Pakistan

Tomato leaf curl New Delhi virus (ToLCNDV) is a bipartite, emerging Begomovirus species, usually coupled with satellite molecules and affects tomato cultivation in entire Pakistan. Present study was conducted to evaluate and analyze tomato germplasm against ToLCNDV using Chip graft inoculation assay (CGIA) as most accurate and reliable technique. Molecular studies were conducted for confirmation. According to PCR results, viral contamination was confirmed as ToLCNDV was recorded from all tested seedling samples. Further mechanical transmission confirmed that seedlings from ToLCNDV-infected seeds act as inoculum. Based on disease symptoms developed, plants were classified as tolerant, moderately tolerant, moderately susceptible, and susceptible. It is pertinent to mention that the magnitude of the virus impact particularly on hosts different from Solanaceae and Cucurbitaceae, and seed transmission and ToLCNDV qualify as a potential candidate of Quarantine Pest. Present work is novel study demonstrating ToLCNDV as a seed-transmissible virus in tomato plants from Rawalakot Azad Kashmir & this research further provides a fictitious starting point for plant pathologists suggesting practical implications regarding management approaches.

ACTIVE, ACTUATED, AND ASSISTIVE: A SCOPING REVIEW OF EXOSKELETONS FOR THE HANDS AND WRISTS

BACKGROUND: Assistive technology is often incorporated into rehabilitation and support for those impacted by upper limb impairments. When powered, these devices provide additional force to the joints of users with muscle weakness. Actuated devices allow dynamic movement compared to splints, therefore improving the ability to complete activities of daily living. However, these devices are not often prescribed and are underrepresented in research and clinical settings. OBJECTIVE: This review examines the current body of literature concerning devices designed to aid the hands and wrists in daily activities. Focusing on active, powered, and actuated devices, to gain a clearer understanding of the current limitations in their design and prescription. METHODOLOGY: The scoping review was conducted using the PRISMA-ScR guidelines. A systematic search was done on MEDLINE, EMBASE, Scopus, Web of Science, and NHS the Knowledge Network from inception to May 2023. Articles were included if the device was portable; supported the hands and wrist actively using an actuator; and could be used for assistive living during or post-rehabilitation period. FINDINGS: A total of 135 studies were included in the analysis of which 34 were clinical trials. The design and control methods of 121 devices were analyzed. Electrical stimulation and direct mechanical transmission were popular actuation methods. Electromyography (EMG) and joint movement detection were highly used control methods to translate user intentions to device actuation. A total of 226 validation methods were reported, of which 44% were clinically validated. Studies were often not conducted in operational environments with 69% at technology readiness levels ≤ 6, indicating that further development and testing is required. CONCLUSION: The existing literature on hand and wrist exoskeletons presents large variations in validation methods and technical requirements for user-specific characteristics. This suggests a need for well-defined testing protocols and refined reporting of device designs. This would improve the significance of clinical outcomes and new assistive technology. Layman's Abstract Assistive devices are often incorporated into rehabilitation and support for those impacted by upper limb impairments. When powered, these devices provide additional force for users with muscle weakness. Unlike splints, these devices do not constrict movement, therefore improving the ability to complete activities of daily living. However, these devices are rarely prescribed or presented in research and clinical settings. This review examines the current literature concerning powered devices that aid the hands and wrists to investigate who uses them, how they are designed and how they are validated. The scoping review was conducted using a validated guideline. A systematic search was done on 5 databases up to May 2023. Articles were included if the device was portable; supported the hands and wrist using motors; and could be used for everyday tasks. A total of 135 studies were included in the analysis, of which 34 were clinical trials. The design and method of device function of 121 devices were analysed. Muscle and joint movement detection were highly used to control device movement. A total of 226 validation methods were reported, of which 44% were clinically validated. Studies were often conducted in research and clinical environments (69%) rather than at home settings. In conclusion, existing literature on hand and wrist exoskeletons presents large variations in design, control methods and validation practices. This suggests a need for well-defined testing protocols. This would improve the significance of clinical outcomes of new assistive technology. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/43827/33279 How To Cite: Galbert A, Buis A. Active, actuated, and assistive: A scoping review of exoskeletons for the hands and wrists. Canadian Prosthetics & Orthotics Journal. 2024; Volume 7, Issue 1, No.9. https://doi.org/10.33137/cpoj.v7i1.43827 Corresponding Author: Professor Arjan Buis, PhDDepartment of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, Scotland.E-Mail: arjan.buis@strath.ac.ukORCID ID: https://orcid.org/0000-0003-3947-293X

Simulation Approaches for the Study of the Oil Flow Rate Distribution in Lubricating Systems with Rotating Shafts

This study addresses the issue of predicting the distribution of lubricant flow through the outlets of a rotating shaft used in vehicle power transmission. A typical geometry with closely spaced rows of holes, suitable for the lubrication of multi-disk clutches, was considered. Both lumped parameter and computational fluid dynamics approaches were applied and compared. The test rig for model validation was designed with a variable speed shaft featuring an axial oil inlet and three equally spaced pairs of radial outlet holes. The main characteristic of the experimental facility is the possibility to selectively measure the flow rates through each outlet. It was found that the three-dimensional model based on the multiple reference frame approach provides a reliable prediction of how the flow rate is distributed. Generally, the flow rate is lower through the outlet closest to the inlet and is maximum at the farthest exit. The flow distribution is minimally affected by the shaft speed. The influence of geometric parameters on making the flow distribution more uniform was studied. It was found that a better flow balance is obtained with a low ratio between the diameter of the radial holes and that of the axial channel. The results obtained offer best-practice guidelines for accurately simulating comparable systems, in order to optimize reliability of the mechanical transmission and energy efficiency of the flow generation unit.

Robotic Dexterous Hands’ Structure Design and Drive-Transmission System

The robotic dexterous hand is one of the most important components of robots. As a new type of end-effector, it can help the robot to interact with the environment, enabling the function of grasping and dexterous operation to objects in various situations such as daily life, medical treatment and industry. This paper investigates the development history and current situation of the robotic dexterous hand in the world, conducts the research and comparative analysis focusing on the characteristics of the existing robotic dexterous hands’ mechanical transmission and drive system, comprehensively obtains its development trend, and finally draws the conclusion and makes the prospect of the future development of the robotic dexterous hand.

Transparent and Flexible Hierarchical Porous Structure of Polyvinyl Alcohol Aerogel: A Microstructure Study.

Aerogels have gained increasing attention due to their unique properties since their introduction in 1932. Silica aerogel, one of the earliest and most advanced types, is known for its high transparency and excellent thermal insulation. However, its internal pearl-like structure makes it extremely brittle, which limits its practical applications. To address this, through multiple refinements in formulation and production techniques, we developed a novel Polyvinyl Alcohol (PVA) aerogel using an innovative one-step standing method. This method significantly reduces the gelling time compared to the freeze-thaw method and eliminates the need for refrigeration, making it a more environmentally friendly and sustainable process. The resulting one-step standing PVA aerogel features a hierarchical porous structure, remarkable transparency, improved strength, and enhanced thermal insulation. Mechanical tests demonstrated that the PVA aerogel produced by the one-step standing method exhibited a significantly higher Young's modulus of 4.2596 MPa, surpassing that of silica, copper nanowire (Cu NM), and graphene aerogels. Additional tests, including transmittance and thermal analysis, further confirmed that the one-step standing PVA aerogel excels in both transparency and thermal insulation. This combination of improved mechanical performance and light transmission opens novel potential applications, such as drug delivery systems, where the aerogel's pore structure can store drugs while maintaining strength and transparency.

An Analysis of and Improvements in the Gear Conditions of the Automated Mechanical Transmission of a Battery Electric Vehicle Considering Energy Consumption and Power Performance

The design of the gear quantity and transmission parameters of a vehicle has large effects on its economical and power performance. This paper mainly researches the gear conditions (including the gear quantity and each gear’s transmission parameters) of two-gear and three-gear AMT (Automated Mechanical Transmission). This research uses Cruise software to build a multi-gear simulation model of a BEV (Battery Electric Vehicle) and adopts the LHS (Latin hypercube sampling) method to design an experiment plan and conduct a simulation experiment. This paper proposes a systematic method for influencing factor analyses and the optimization of transmission parameters, combining fuzzy theory, multiple regression, and particle swarm optimization. The research results show that the gear quantity allowing for optimal overall performance is three. The highest score obtained in the results of the simulation experiment for three-gear AMT is 11.15% higher than that of the two-gear AMT. The optimal design plan for the two-gear AMT is a small ig1 with a big k1, in which case the highest score of the regression model increases by 2.67% compared with that before modeling. The optimal design plan for the three-gear AMT is a big k1 with a big k2, in which case the highest score of the regression model increases by 12.78% compared with that before modeling. Then, this research uses PSO (particle swarm optimization) to further optimize the regression models and compares the difference between the highest scores in the results of the simulation experiment. The difference between the highest scores of the three-gear and two-gear AMT further increases to 21.95% after optimization. As shown in the results, the key factor influencing the performance of two-gear and three-gear AMT is gear quantity.

A reduced graphene oxide-coated conductive surgical silk suture targeting microresistance sensing changes for wound healing

Conventional sutures used in surgical procedures often lack the capability to effectively monitor physical and chemical activities or the microbial environment of surgical wounds due to their inadequate mechanical properties, insufficient electrical accuracy and unstability. Here, we present a straightforward layer-by-layer coating technique that utilizes 3-glycidoxypropyltrimethoxysilane (CA), graphene oxide (GO), and ascorbic acid (AA) to develop conductive silk-based surgical sutures (CA-rGSFS). The CA-rGSFS feature a continuous reduced graphene oxide (rGO) film on their surface, forming robust hydrogen bonds with silk fibroin. The reduction process of rGO is confirmed through Raman analysis, demonstrating an enhanced D peak to G peak ratio. Notably, the CA-rGSFS exhibit exceptional mechanical properties and efficient electron transmission, with a knot-pull tensile strength of 2089.72 ± 1.20 cN and an electrical conductivity of 130.30 ± 11.34 S/m, respectively, meeting the requirements specified by the United States Pharmacopeia (USP) for 2-0 sutures. These novel CA-rGSFS demonstrate the ability to accurately track resistance changes in various fluid environments with rapid response, including saline, intestinal, and gastric fluids. The suture also retains remarkable stretchablility and stability even after enduring 3000 tensile cycles, highlighting their potential for precise surgical site monitoring during the wound healing process.

End-to-End Intelligent Fault Diagnosis of Transmission Bearings in Electric Vehicles Based on CNN

Environmental noise and transmission components can cause significant interference in vibration signals, rendering the extraction of bearing fault features challenging in service scenarios. Traditional fault diagnosis methods rely heavily on professional domain knowledge, prior models, and signal preprocessing methods. The accuracy of fault diagnosis depends on the quality of the fault-sensitive features extracted by vibration signal preprocessing methods. An improved convolutional neural network (CNN) end-to-end intelligent fault diagnosis model based on raw vibration data (RVDCNN) is proposed. The time-domain vibration signal of the transmission bearing is converted into a continuous two-dimensional numerical matrix, and a two-dimensional CNN model is constructed through network structure optimization. The original time-domain vibration signal numerical matrix of the bearing is trained and tested to extract and learn abstract fault features of different fault types, and then the fault classification of the bearing is achieved. To verify the generalizability of the RVDCNN intelligent fault diagnosis model, it is applied to the recognition of rolling bearings in the two-speed mechanical automatic transmission of electric vehicles, achieving recognition accuracy of 99.11% for seven types of bearings.

A Two-Stage Facial Kinematic Control Strategy for Humanoid Robots Based on Keyframe Detection and Keypoint Cubic Spline Interpolation

A plentiful number of facial expressions is the basis of natural human–robot interaction for high-fidelity humanoid robots. The facial expression imitation of humanoid robots involves the transmission of human facial expression data to servos situated within the robot’s head. These data drive the servos to manipulate the skin, thereby enabling the robot to exhibit various facial expressions. However, since the mechanical transmission rate cannot keep up with the data processing rate, humanoid robots often suffer from jitters in the imitation. We conducted a thorough analysis of the transmitted facial expression sequence data and discovered that they are extremely redundant. Therefore, we designed a two-stage strategy for humanoid robots based on facial keyframe detection and facial keypoint detection to achieve more natural and smooth expression imitation. We first built a facial keyframe detection model based on ResNet-50, combined with optical flow estimation, which can identify key expression frames in the sequence. Then, a facial keypoint detection model is used on the keyframes to obtain the facial keypoint coordinates. Based on the coordinates, the cubic spline interpolation method is used to obtain the motion trajectory parameters of the servos, thus realizing the robust control of the humanoid robot’s facial expression. Experiments show that, unlike before where the robot’s imitation would stutter at frame rates above 25 fps, our strategy allows the robot to maintain good facial expression imitation similarity (cosine similarity of 0.7226), even at higher frame rates.

Simulation and Experimental Study of Ultrasonic Vibratory Grinding of Internal Splines

As an important component of mechanical transmission systems, internal splines are widely used in aerospace, industrial equipment, and other fields. However, internal splines are prone to deformation and shrinkage after heat treatment. At present, most internal splines with a pitch circle diameter greater than φ60 mm can be processed and shaped by ordinary corundum grinding wheels, but there is no effective processing method for the shaping of small- and medium-sized internal splines. This paper establishes a single abrasive material removal model; uses Abaqus to simulate three-body free grinding; and analyzes the effects of abrasive rotation angle, rotation speed, and grinding depth on material removal under different conditions. By comparing the tooth lead deviation and tooth direction deviation before and after internal spline grinding, the experimental results show that after ultrasonic vibration grinding, the internal spline tooth profile deviation is reduced by 41.9%, and the tooth direction deviation is reduced by 44.1%, which provides a new processing method for the deformation recovery of internal splines after heat treatment.

A multi-source domain feature-decision dual fusion adversarial transfer network for cross-domain anti-noise mechanical fault diagnosis in sustainable city

Rotating machinery forms the critical backbone of infrastructure in a sustainable city, with bearings playing a pivotal role as key mechanical transmission components. Therefore, the health status of these bearings directly influences the safe operation of the infrastructure. Accurate and reliable diagnosis of defects in these components minimizes downtime, reduces maintenance costs, and prevents major accidents, ultimately providing insights in the construction and management of a sustainable city. Typically, in actual industrial scenarios, varying working conditions and various types of machines can result in significant discrepancies in the distribution of sample data. Moreover, the non-negligible noise may degrade the diagnostic performance. Therefore, realizing an accurate and reliable bearing diagnosis considering the cross-domain and noise environment remains a challenge. Leveraging the merits of information fusion and multi-source domain transfer learning, this article proposes a multi-source domain feature-decision dual fusion adversarial transfer network (DFATN) to break through the aforesaid limitations. Initially, an adversarial transfer framework is developed, incorporating novel feature matching evaluation and joint distribution difference losses. This framework is designed to facilitate the learning of feature invariants across domains and to enhance the sharing of domain-specific knowledge, even in noise. Relying on channel-spatial interactive feature fusion, a multi-scale feature extractor (MFE) is constructed to share the interaction and enhance the modeling of complex features in multiple dimensions. Additionally, a fault state-related decision fusion mechanism (SDF) is also implemented to integrate diagnostic information, significantly enhancing the generalization performance and robustness of the proposed network. By employing both public Paderborn University (PU) and laboratory-collected (Lab) datasets, the effectiveness and superiority of the proposed DFATN on bearing fault diagnosis are validated. For cross-working condition tasks, the proposed method realizes impressive performance, with average accuracies of 96.52% and 98.76% for Paderborn University (PU) and laboratory-collected (Lab) datasets, respectively. For cross-machine tasks, the average accuracy is 83.36%, outperforming other latest cross-domain fault diagnosis techniques.

Predictive Model for Scuffing Temperature Field Rise of Spiral Bevel Gears under Different Machining Conditions

Spiral bevel gears are extensively employed in mechanical transmissions; however, they are prone to adhesive wear when operating under high-speed and heavy-load conditions. Research indicates that the tooth surface roughness of gears significantly influences the friction and wear of the meshing gears. The present study delves into the origins of tooth surface roughness through the integration of the W-M function and fractal theory. Utilizing an involute helical gear with surface roughness for tooth cutting, a three-dimensional model is established with roughened tooth surfaces. This paper introduces an approach to developing three-dimensional gear models with roughness and applies the finite element method to perform thermodynamic analysis on gears exhibiting diverse levels of surface roughness. The thermal analysis of gears with varying degrees of roughness was conducted using the finite element method. Comparative analysis of the results under specific operating conditions elucidated the impact of roughness on tooth surface temperature rise. In order to validate the simulation model, an experimental test platform for spiral bevel gears of identical size was established. This model integrates tooth surface roughness with thermodynamic analysis, allowing for the rapid assessment of tooth surface temperature rise under different machining conditions, and reducing the cost of validating predicted tooth surface load-carrying capacity.

Model Predictive Control of Aero-Mechanical Actuators with Consideration of Gear Backlash and Friction Compensation

To address the issues of low positional accuracy and significant torque pulsation caused by gear backlash and nonlinear friction in the mechanical transmission mechanism of aeronautical flap electromechanical actuators, we propose a model predictive control method for flap electromechanical actuator considering gear backlash and friction compensation. Firstly, we model the gear backlash in the electromechanical actuator’s mechanical transmission mechanism and design a corresponding torque current compensation method using a simplified dead zone model. Secondly, the LuGre compensation friction model is introduced, and a friction torque current compensation method is developed to address the nonlinear friction torque generated during system operation. Finally, the proposed current compensation strategies are employed to mitigate the adverse effects of gear backlash and nonlinear friction on system control performance. The simulation results demonstrate that the proposed method enhances position tracking accuracy, reduces torque pulsation, and significantly improves the overall control performance of the system.

Transient destabilization of interhemispheric functional connectivity induced by spreading depolarization

ABSTRACT Cortical spreading depolarization (CSD), a slowly propagating wave of transient cellular depolarization, is a reliable cortical response to various brain insults (stroke, trauma, seizures) and underlying mechanism of migraine aura. Little is known about CSD effects on brain network activity. Using undirected (mutual information, MI) and directed (transfer entropy, TE) measures, we studied the dynamics of cross-hemispheric connectivity associated with the development of unilateral CSD in freely behaving rats and the involvement of inhibitory transmission in mechanisms of the coupling changes. We show that the development of CSD in the cortex of one hemisphere is followed by the transient loss of undirected functional connectivity (MI) between ipsilateral and contralateral cortical regions. The post-CSD functional disconnection of the hemispheres was accompanied by an increase in driving force from an unaffected contralateral cortex to an affected one (TE). Mild cortical disinhibition produced by pretreatment with an inhibitory receptor blocking agent (penthylenetetrazole) did not affect CSD but attenuated (MI) or eliminated (TE) the CSD-induced connectivity changes. The effects of CSD on functional connectivity in awake rodents were similar at the individual and group levels, suggesting that the described connectivity response may be a promising network biomarker of CSD occurrence in patients.

First Report of Paprika mild mottle virus Infecting pepper (Capsicum annuum L.) in China.

Paprika mild mottle virus (PaMMV), a tobamovirus from the Virgaviridae family, has been reported to infect pepper (Capsicum annuum L.) in the Netherlands (García-Luque et al., 1993), Japan (Hamada et al., 2003), Bulgaria (Ruíz del Pino et al., 2003), and Israel (Luria et al., 2018). Pepper has become the most widely planted vegetable and the most heavily consumed spicy condiment, with a large planting area (>21,000 km2) in China (Zou et al., 2021). However, the crop's productivity is limited by viral diseases. In August 2021, a survey of viral diseases was conducted across five pepper-growing regions in Linyi, Shandong Province, China, revealed that 5% to 10% of plants in most fields exhibited symptoms such as stunting, leaf narrowing, chlorosis, and crinkling of leaf tissue (Fig. S1-a). Subsequently, seven symptomatic samples (Fig. S1-b) were collected from a plot (118° 29' E, 34° 65' N) where thin-skinned peppers were grown. All samples tested positive in a Western blot assay using a polyclonal antibody for tobacco mosaic virus (TMV), indicating the presence of a tobamovirus (Fig. S1-c). To identify the virus, total RNAs were extracted from 10 different symptomatic pepper plant samples, using the RNeasy Plant Mini Kit (QIAGEN, Hilden, Germany) and combined into a single sample in equal amounts (100 ng/μL each). RNA-Seq was performed on this mixture using the Illumina NovaSeq 6000 (Illumina, San Diego, USA). Raw reads (6.92G) in fastq format were processed with in-house perl scripts to yield clean reads (6.68G), which were assembled into 780 contigs (mean length: 2036 bp) using Trinity software (v2.6.6). These contigs were then analysed using the NCBI BLASTX program (http://www.ncbi.nlm.nih.gov/blast) against the viral RefSeq database. The results demonstrated that the contigs exhibited an average genome coverage of 40.16%. Notably, one unique contig (6453 bp) was mapped to the PaMMV genome (reference sequence KX187305.1) with 98.34% identity. To verify the RNA-Seq result, a PaMMV-specific primer pair (forward: 5'-GAGTTCATAGAGGCAGTACC-3'; reverse: 5'-CTTCGATTTAAGTGGAGGGAT-3') was designed for amplifying an 800-nt fragment of the PaMMV coat protein (CP) gene by RT-PCR. The 800-nt fragment was successfully amplified from all the symptomatic samples (Fig. S1-d). Sequenced RT-PCR products (GenBank No. OR365081.1) showed 99.75% nucleotide identity with PaMMV isolates (OQ198318.1, China, goat) according to BLAST analysis. Mechanical transmission of PaMMV from three infected pepper plants collected in Linyi to healthy pepper plants confirmed pathogenicity. Three pepper cultivars (trade name: Qiemen, Tianyu, Haonong11) were tested and showed varying symptoms post-inoculation (Fig. S1-e). All cultivars were confirmed in the lab to be PMMoV-sensitive and exhibited significant viral disease symptoms after PMMoV inoculation (data not shown). Each variety was inoculated with at least 3 seedlings from different field-collected virulence sources. Qiemen (cultivar: sweet pepper) exhibited severe symptoms with necrotic spots, Tianyu (cultivar: Chaotian pepper) had mild leaf wrinkling, and Haonong11 (cultivar: Pickled pepper) showed yellow mottle and leaf shrinking. All tested seedlings were positive for PaMMV by RT-PCR (Fig. S1-f). To our knowledge, this is the first report of PaMMV infecting pepper in China, highlighting the need for vigilant monitoring to protect the chili industry and prevent the virus's spread to other crops.

Clutch Torque Optimization for Heavy-Duty Vehicles Starting Based on Intelligent Identification of Driver’s Starting Intention, Vehicle Mass, and Road Grade

<div>For heavy-duty vehicles equipped with automated mechanical transmission (AMT), the control of automatic clutch torque is crucial during the start-up process. However, the difficulty of controlling clutch torque is exacerbated by differences in driver’s starting intentions, changes in vehicle mass, and road gradient. Therefore, this article proposes the clutch starting torque optimization strategy based on intelligent recognition of driver’s starting intention, vehicle mass, and road gradient. First, an intelligent recognition strategy is proposed based on the combination of data-driven and onboard transmission control unit (TCU) algorithms, which improves the accuracy of recognizing the driver’s intention to start as well as the vehicle mass and road gradient. Based on the vehicle’s historical state data information, the predictive model is trained offline using a long–short-term memory (LSTM) network to obtain predicted parameter identification results, which are then used to calibrate the computed values of the onboard TCU algorithm. Second, the clutch torque optimization strategy is designed based on the driver’s starting intention, while considering the effects of road gradient and vehicle mass on the clutch starting resistance torque. The weight coefficients of the objective performance function are adjusted according to the driver’s starting intention, and the Pontryagin’s minimum principle (PMP) is used to solve the clutch target torque. Finally, offline data training and real-vehicle testing are performed. The results show that the optimization strategy can effectively reduce the friction work and the degree of impact during the starting process, minimize the clutch slipping time, and improve the smoothness of vehicle starting and driving comfort.</div>

New persistent plant RNA virus carries mutations to weaken viral suppression of antiviral RNA interference.

Persistent plant viruses are widespread in natural ecosystems. However, little is known about why persistent infection with these viruses may cause little or no harm to their host. Here, we discovered a new polerovirus that persistently infected wild rice plants by deep sequencing and assembly of virus-derived small-interfering RNAs (siRNAs). The new virus was named Rice tiller inhibition virus 2 (RTIV2) based on the symptoms developed in cultivated rice varieties following Agrobacterium-mediated inoculation with an infectious RTIV2 clone. We showed that RTIV2 infection induced antiviral RNA interference (RNAi) in both the wild and cultivated rice plants as well as Nicotiana benthamiana. It is known that virulent virus infection in plants depends on effective suppression of antiviral RNAi by viral suppressors of RNAi (VSRs). Notably, the P0 protein of RTIV2 exhibited weak VSR activity and carries alanine substitutions of two amino acids broadly conserved among diverse poleroviruses. Mixed infection with umbraviruses enhanced RTIV2 accumulation and/or enabled its mechanical transmission in N. benthamiana. Moreover, replacing the alanine at either one or both positions of RTIV2 P0 enhanced the VSR activity in a co-infiltration assay, and RTIV2 mutants carrying the corresponding substitutions replicated to significantly higher levels in both rice and N. benthamiana plants. Together, our findings show that as a persistent plant virus, RTIV2 carries specific mutations in its VSR gene to weaken viral suppression of antiviral RNAi. Our work reveals a new strategy for persistent viruses to maintain long-term infection by weak suppression of the host defence response.

The CRITIC-AHP performance degradation staged fusion evaluation of wet clutch friction components

The performance of wet clutches plays a crucial role in the efficiency and durability of mechanical transmission systems. As a vital component of the clutch, the degradation of friction components directly affects its stability and reliability. To investigate the performance degradation of friction components, we establish a multi-indicator evaluation system and conduct an accelerated life test, which is validated by an accelerated model. Next, we build a Random Forest model to classify the friction stage. Criteria Importance through Intercriteria Correlation (CRITIC) and the Analytic Hierarchy Process (AHP) is proposed to assign weights for each degradation indicator during different stages. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) scoring method combines indicator weights to construct a CRITIC-AHP staged fusion evaluation model of friction components. Notably, the average relative error of the evaluation results of the model is 9.35%.