Search Results (267)

Forestry logging is among the most hazardous economic activities, so identifying where hazards and risks concentrate supports targeted prevention. This scoping review mapped evidence on logging hazards and risks, their co-occurrence with operations, and preventive measures. PRISMA-ScR was followed. Only peer-reviewed journal articles (2015–2025) in English on occupational hazards/risks, risk-assessment methods or preventive measures in logging were included, found in Scopus, Web of Science, Inspec and Dimensions (last search 15 September 2025). Independent data screening and extraction were performed by two reviewers, with a third reviewer resolving any disagreements. No formal risk-of-bias appraisal was conducted. Forty-two studies were included. Hazards and risks concentrated in three phases—chainsaw/manual cutting, skidding/cable yarding, and loading/short-haul transport—where acute injury mechanisms (struck-by events, slips/trips/falls, rollovers, lacerations) coexisted with chronic exposures (musculoskeletal strain, noise, vibration, diesel exhaust). Preventive measures emphasised engineering and organisational controls, complemented by raining and PPE, but were inconsistently specified and evaluated. Evidence was heterogeneous and geographically concentrated in few countries, limiting generalisability. A small set of tasks consistently concentrates acute and chronic risks; prevention should integrate accident control and health protection, prioritising engineering/organisational measures supported by training and PPE. Future studies should standardise descriptors and outcome metrics to enable comparisons. Full article

Background: Diabetic peripheral neuropathy (DPN) is one of the most common complications of diabetes mellitus (DM), leading to sensory loss, balance disturbances, and an increased risk of ulcers and amputations. Early screening is crucial, and devices for measuring vibration perception threshold (VPT) play an important role in the timely detection and management of this condition. Objective: The aim of this systematic review was to evaluate the diagnostic accuracy and reliability of VPT measurement devices in individuals with DM. Methods: A systematic search was conducted in four databases, including studies that assessed the diagnostic accuracy and reliability of VPT measurement devices in patients with type 1 or type 2 DM, with VPT compared against reference standards for DPN, including nerve conduction studies (NCS) and clinical diagnosis. Cross-sectional and case–control studies were included. Risk of bias was assessed using the Quality Appraisal of Reliability (QAREL) tool and the JBI Critical Appraisal Checklist for Diagnostic Test Accuracy Studies. Results: Eighteen studies were analyzed. Most studies demonstrated moderate sensitivity and specificity and an acceptable level of reliability, with results varying according to technical and methodological factors. Conclusions: VPT measurement devices appear to be useful screening tools for detecting DPN; however, their diagnostic accuracy and reliability are not uniform and largely depend on technical and methodological factors. Standardized threshold values and measurement procedures, along with further research comparing the effectiveness of different protocols, are needed to improve clinical utility. Full article

To address the challenge of effectively extracting early-stage failure features in rolling bearings, this paper proposes a two-stage harmonic optimization-gram method based on spectral amplitude modulation (SAM-TSHOgram). The method first employs amplitude spectra with varying weighting exponents to preprocess the signal, performing nonlinear adjustments to the vibration signal’s spectrum to enhance weak periodic impact characteristics. Subsequently, a two-stage evaluation strategy based on spectral coherence (SCoh) was designed to adaptively identify the optimal frequency band (OFB). The first stage employs the Periodic Harmonic Correlation Strength (PHCS) metric, based on autocorrelation, to coarsely screen candidate bands with strong periodic structures. The second stage utilizes the Sparse Harmonic Significance (SHS) metric, based on spectral negative entropy, to refine the candidate set, selecting bands with the most prominent harmonic features. Finally, SCoh is integrated over the selected OFB to generate an Improved Envelope Spectrum (IES). The proposed method was validated using both simulated and experimental vibration signals from bearings and gearboxes. The results demonstrate that SAM-TSHOgram significantly outperforms conventional approaches such as EES, Fast Kurtogram, and IESFOgram in terms of signal-to-noise ratio (SNR) enhancement, harmonic clarity, and diagnostic robustness. These findings confirm its potential for reliable early fault detection in rolling bearings. Full article

To address the conflicts among objectives and the decision-making challenges in the multi-condition adaptive design of battery boxes for new energy vehicles, this study proposes a multi-objective collaborative optimization method based on an improved relaxation factor, aiming to achieve a comprehensive enhancement in both structural lightweighting and mechanical performance. A finite element model of the CTB high-strength steel roll-formed battery box was established and validated through modal testing. According to the Chinese National Standard GB 38031-2025, the mechanical responses of the battery box under random vibration, extreme operating conditions, and impact loads were analyzed to identify performance weaknesses. Sensitivity analysis was conducted to screen the design variables, and an improved relaxation factor strategy based on weight distribution difference information was introduced to construct a multi-objective collaborative optimization model. Furthermore, the entropy-weighted TOPSIS method was employed to enable intelligent decision-making on the Pareto solution set. The results demonstrate that the proposed method outperforms conventional approaches in both convergence speed and solution distribution uniformity. After optimization, the mass of the battery box was reduced by 12.38%, while multiple mechanical performance indicators were simultaneously improved, providing valuable theoretical and engineering guidance for the structural design of power battery systems. Full article

A heavy-duty vibrating screen with excitation sources is a mining vibrating machine synchronized by two eccentric rotors, exhibiting typical coupled dynamic behavior. Aiming at the coupling dynamic behavior of dual excitation sources based on the nonlinear vibration of a heavy-duty mining screen, theoretical research and experimental analysis of coupling synchronization are carried out, and the dynamic reasons for the dual excitation sources to achieve vibration synchronization are discussed. Based on nonlinear vibration theory, electromechanical coupling nonlinear dynamics equations for a dual excitation source vibrating screen are established in this paper, and the coupled dynamics factors of the two eccentric rotors are analyzed. The impact of coupling strength on the equilibrium state of the nonlinear vibration system is discussed, and the evolution process of the synchronous motion of the two eccentric rotors is further investigated, revealing the causal relationship by which the dual excitation sources achieve synchronization due to coupled dynamics behavior. The results show that the coupling effect of the multi-exciter is based on the nonlinear vibration of the vibration system, and the motion characteristics and motion mode of the exciter will change, and, finally, a coupled synchronous motion state will be reached. The research results can provide ideas for the mechanical structure design of heavy-duty mining screens excited by multiple excitation sources and can provide a theoretical basis and application reference for the selection of structural parameters of this kind of mining machinery. Full article

Screening is a critical link in the separation of gold ores. However, issues such as the agglomeration of material masses and screen aperture blinding often lead to low screening precision and poor desliming performance, severely impacting the efficiency of subsequent crushing processes. To address these challenges, this paper proposes a rigid–flexible coupled screening method for viscous and moist gold ores. The time-frequency response characteristics of the screen surface motion were investigated, the influence of processing capacity and moisture content on screening performance was analyzed, and an industrial performance evaluation of the rigid–flexible coupled screen surface was conducted. Laboratory and industrial test results demonstrate that the rigid–flexible coupled screen surface exhibits a periodic, non-regular waveform with a maximum peak vibration intensity of 14.79 g. Screening efficiency is synergistically inhibited by moisture content and processing capacity. When the ore moisture content is below 3% and the processing capacity ranges from 15 to 22.5 t/(h·m²), the screening efficiency can exceed 85%. Compared with conventional screen surfaces, the implementation of the rigid–flexible coupled screen surface achieved a desliming efficiency of 91%, a maximum processing capacity in the crushing stage of 380 tons per hour, a nearly 12% improvement in the screening efficiency of the closed-circuit checking process for crushed products, and an approximately 8% reduction in the circulating load ratio of the crushing circuit. These enhancements collectively ensure the stable operation of both the screening and crushing processes. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent in patients with type 2 diabetes (T2D), and advanced fibrosis is the strongest predictor of liver-related morbidity and mortality. Therefore, early noninvasive risk stratification is critical. While the Fibrosis-4 (FIB-4) index and vibration-controlled transient elastography (VCTE) are widely used, the newer FibroScan-AST (FAST) score has shown promise in detecting at-risk metabolic-associated steatohepatitis (MASH) with significant fibrosis. Evidence comparing the FAST and FIB-4 indices in Middle Eastern T2D populations remains limited. We compared the diagnostic performances of these models for advanced fibrosis in Saudi patients with T2D and MASLD. Methods: We conducted a retrospective analysis of 273 patients diagnosed with T2D and MASLD. All patients underwent VCTE. To identify advanced fibrosis, we used liver stiffness measurement (LSM) as a surrogate marker for liver biopsy. We calculated the FAST and FIB-4 indices for each patient. To assess the diagnostic performance of these scores, we evaluated their sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUROC). Results: In this cohort study, 26.4% of participants had a high-risk FAST score (>0.35; median: 0.13). Patients with high-risk FAST scores (>0.35) were younger, had higher BMIs, elevated liver enzyme levels, and poorer glycemic control than those in the lower-risk groups. High-risk FAST scores were strongly correlated with elevated LSM, FIB-4, and controlled attenuation parameter values (p < 0.001). The FAST score demonstrated better performance than the FIB-4 index in detecting advanced fibrosis. It showed higher accuracy (85.4% vs. 77.3%), sensitivity (82.0% vs. 48.0%), and negative predictive value (95.5% vs. 87.8%) while maintaining a similar specificity. The AUROC values were 0.936 (95% CI: 0.901–0.971) for the FAST score compared to 0.711 (95% CI: 0.625–0.797) for the FIB-4 index. Conclusions: The FAST score demonstrated better diagnostic accuracy than the FIB-4 index and identified patients with poor metabolic control and obesity as being at the highest risk among Saudi patients with T2D and MASLD. These findings support the integration of other elastography-based tests into stepwise fibrosis screening pathways for diabetic populations, potentially improving the early detection of advanced fibrosis and patient outcomes. Full article

To enhance shell–mud separation and overall harvesting efficiency for Mactra veneriformis under intertidal mudflat conditions, a vibratory harvesting device driven by a crank–rocker mechanism that produces approximately rectilinear simple-harmonic motion was developed. Dynamic analysis of clam motion on the screen deck identified vibration amplitude, vibration frequency, excitation direction angle, and screen deck inclination angle as key determinants of screening performance. Single-factor tests, a Plackett–Burman design, a steepest-ascent experiment, and response surface methodology (RSM) optimization were conducted. Their influences on forward travel speed ranked as follows: screen deck inclination angle > excitation direction angle > vibration amplitude > vibration frequency. The optimized settings were vibration amplitude of 8.5 mm, excitation direction angle of 45°, screen deck inclination angle of 11°, and vibration frequency of 10 Hz. Intertidal mudflat trials yielded a harvesting efficiency of 342 kg/h and a clam breakage rate of 4.6%, meeting the design targets. After harvesting, the shear strength of the mudflat decreased, with disturbance mainly confined to the surface layer, thereby meeting the low-disturbance requirement and enabling ecologically friendly harvesting. These results provide a basis for the design and optimization of M. veneriformis harvesting machinery. Full article

The mechanized processing of waste agricultural film is a crucial technical pathway for addressing agricultural-film pollution. Achieving resource recovery through mechanized waste-film processing—and thereby promoting the sustainable management of agricultural-film pollution—remains a major challenge for green agricultural development. This study systematically reviews the progress and limitations of shredding and film–impurity separation technologies deployed in China’s mechanized waste-film treatment. Based on multi-database searches and citation tracking of the literature published between 2000 and 2025, it comparatively evaluates key unit operations, including cutterhead/blade kinematics, specific energy-consumption (SEC) control, and airflow (air-classification) separation, complemented by engineering analyses of representative machinery. The findings indicate that integrated mechanized recovery lines have become the mainstream approach, although the recovered fraction still contains a high impurity load. Drum-type and shear-type shredding exhibit trade-offs between energy efficiency and mitigation of film wrapping/entanglement. Airflow separation and drum-screen or vibrating-screen modules show reduced separation efficiency and process stability at high moisture contents or when impurities have particle sizes comparable to the film; system complexity and maintenance burdens also warrant consideration. To address these issues, a process framework is proposed that integrates drum pre-crushing, shear fine shredding, air classification, and multi-stage screening, together with variable-frequency drive (VFD) speed control, torque monitoring, and modular design, providing a sustainable pathway for the clean separation and resource recovery of agricultural plastic film waste. Full article

Snoring, a common sleep-disordered breathing phenomenon, impairs sleep quality for both the sufferer and any bed partner. While mild snoring primarily disrupts sleep continuity, severe cases often indicate obstructive sleep apnea (OSA), a disorder affecting 9–17% of the global population, linked to significant comorbidities and socioeconomic burden (see Introduction for supporting data). Here, we propose a low-cost, real-time snoring detection and intervention system that integrates a multiple-spectrum deep learning framework with an Internet of Things (IoT)-enabled smart pillow. The modified Parallel Convolutional Spatiotemporal Network (PCSN) combines three parallel convolutional neural network (CNN) branches processing Constant-Q Transform (CQT), Synchrosqueezing Wavelet Transform (SWT), and Hilbert–Huang Transform (HHT) features with a Long Short-Term Memory (LSTM) network to capture spatial and temporal characteristics of sounds associated with snoring. The smart pillow prototype incorporates two Micro-Electro-Mechanical System (MEMS) microphones, an ESP8266 off-shelf board, a speaker, and two vibration motors for real-time audio acquisition, cloud-based processing via Arduino cloud, and closed-loop haptic/audio feedback that encourages positional changes without fully awakening the snorers. Experiments demonstrated that the modified PCSN model achieves 98.33% accuracy, 99.29% sensitivity, 98.34% specificity, 98.3% recall, and 98.32% F1-score, outperforming existing systems. Hardware costs are under USD 8 and a smartphone app provides authorized users with real-time visualization and secure data access. This solution offers a cost-effective and accurate approach for home-based OSA screening and intervention. Full article

The aim of this review was to harmonize major consensus statements (European Working Group on Sarcopenia in Older People 2; Asian Working Group for Sarcopenia 2019; Foundation for the National Institutes of Health Sarcopenia Project operational criteria) into a stage- and setting-stratified algorithm. It maps diagnostic strata to dose-defined resistance and combined training, integrates multimodal and technology-enabled options (whole-body electrical muscle stimulation, whole-body vibration, virtual reality, AI-assisted telerehabilitation) with safety cues, and embeds nutrition (≥1.2 g/kg/day protein, vitamin D, key micronutrients) and education to sustain adherence. Sarcopenia is a consequential geriatric syndrome linked to falls, loss of independence, hospitalization, mortality, and psychosocial burden, yet translation to practice is hindered by heterogeneous definitions, diagnostics, and treatment guidance. Literature searches via PubMed/MEDLINE, EBSCO, SciELO, and Google Scholar (January 2000 to August 2025) yielded 354 records; after screening and deduplication, 132 peer-reviewed studies were included. We summarize tools for screening, strength, muscle mass, and function (e.g., Sarcopenia Five-Item Questionnaire, grip strength, dual-energy X-ray absorptiometry, gait speed) and identify resistance exercise as the cornerstone, with aerobic, balance, and flexibility training adding functional and metabolic benefits. Clinic-ready tables and figures operationalize a stepwise program across primary to severe sarcopenia and across acute or iatrogenic to community settings. Early screening plus structured, exercise-centered care, augmented by targeted nutrition and education, offers pragmatic, scalable benefits. Full article

To address the challenges in identifying effective fault features and achieving sufficient diagnostic accuracy and robustness in variable-speed printing press bearings, where complex mixed-condition vibration signals exhibit non-stationarity, strong nonlinearity, ambiguous time-frequency characteristics, and overlapping fault features across multiple operating conditions, this paper proposes an adaptive optimization signal decomposition method combined with dual-modal time-series and image deep feature fusion for variable-speed multi-condition bearing fault diagnosis. First, to overcome the strong parameter dependency and significant noise interference of traditional adaptive decomposition algorithms, the Crested Porcupine Optimization Algorithm is introduced to adaptively search for the optimal noise amplitude and integration count of ICEEMDAN for effective signal decomposition. IMF components are then screened and reorganized based on correlation coefficients and variance contribution rates to enhance fault-sensitive information. Second, multidimensional time-domain features are extracted in parallel to construct time-frequency images, forming time-sequence-image bimodal inputs that enhance fault representation across different dimensions. Finally, a dual-branch deep learning model is developed: the time-sequence branch employs gated recurrent units to capture feature evolution trends, while the image branch utilizes SE-ResNet18 with embedded channel attention mechanisms to extract deep spatial features. Multimodal feature fusion enables classification recognition. Validation using a bearing self-diagnosis dataset from variable-speed hybrid operation and the publicly available Ottawa variable-speed bearing dataset demonstrates that this method achieves high-accuracy fault identification and strong generalization capabilities across diverse variable-speed hybrid operating conditions. Full article

The separation of walnut kernels from shells is a crucial step in walnut processing. Pneumatic sorting is the mainstream method. However, due to the overlapping suspension speeds of half-shells and eighth-shells, complete separation was not achieved. This paper proposes using a toothed vibrating screen to separate the two. Using EDEM to simulate and analyze the motion forms, collision processes, and stress conditions of walnut shells and kernels on the vibrating screen, the effectiveness of this method was demonstrated, and the mechanisms of shell–kernel retention and loss during the separation process were revealed. Results indicate that 1/8 kernels, being smaller, easily fall into tooth grooves and move upward step by step under the excitation force during reciprocating vibration. The 1/2 shells, being larger, are difficult to fall into the teeth grooves, and their smooth surfaces cause them to slide easily, moving downward continuously under the action of reciprocating vibration and gravity. Using the cleaning rate and loss rate as evaluation indicators, it was found that as the inclination angle of the vibrating screen increased step by step, the cleaning rate consistently increased monotonously. The loss rate initially rose slowly, then surged sharply after reaching 22°, at which point the loss rate was at its lowest, around 10%, and the cleaning rate was at its maximum, at 95%. The shortest retention time of walnut shells on the screen is 2.85 s, and the longest is 10.6 s, with the number of collisions being 458 and 2619, respectively; the collisions between the shells and the kernels account for 51.8%. The failure to thoroughly separate is due to the shell and kernel entangling within the separation area, making it impossible to segregate them. They enter the opposite region, collide, and cause loss and retention phenomena. Full article

A vibration-based protocol is presented for identifying barely visible impact damage (BVID) in type-IV composite-overwrapped pressure vessels (COPVs). A 1 kJ hemispherical-tip strike was applied to a fully pressurized vessel, which was subsequently depressurized and characterized by free–free experimental modal analysis over a 168-point grid. The frequency response functions (FRFs) at the impact meridian exhibited distinct peaks near 3.70, 4.34, and 4.90 kHz with larger amplitudes and lower coherence than at the diametrically opposite meridian, indicating local circumferential stiffness loss. A detailed finite element model of the liner, bosses, and carbon/epoxy overwrap was updated by idealizing a cylindrical sub-volume with a 90% reduction in orthotropic stiffness. The pristine and “damaged” numerical modal sets agreed closely (mean frequency error < 2%), and for most of the first 60 modes, the diagonal Modal Assurance Criterion (MAC) remained ≥ 0.90. However, in several nearly degenerate circumferential mode pairs, the diagonal MAC dropped to 0.49–0.88 because the local asymmetry rotated the eigenvectors within a common subspace, showing that classical MAC alone cannot expose such early-stage defects. Radial displacement scan-lines provided the missing spatial resolution. Modes whose antinodal regions intersect the dent showed pronounced local amplitude bulges and slight angular shifts in the peak toward the impact site, whereas modes with a nodal line across the damage were virtually unchanged. The combined use of FRF asymmetry, MAC screening, and scan-line deformation profiling localized the impact to the correct circumferential sector with centimeter-scale resolution along the scan ring, yielding predictive signatures for rapid, non-pressurized in situ assessment of impacted COPVs after depressurization. Full article

The permanent magnet levitation (PML) transportation system utilizes Halbach arrays to achieve zero-power levitation. However, the system’s lateral negative stiffness characteristic leads to a significant increase in lateral force during operation, exacerbating lateral vibration and compromising system stability. Taking the Xingguo Line PML system as the research object, this study systematically analyzes the nonlinear characteristics of the levitation force and lateral force in a single-point levitation system through theoretical modeling, finite element simulation, and experimental validation. The concept of a ‘Magnetic Wheelset’ coupling the left and right levitation points of the bogie is proposed. The influence of five mounting forms—Aligned, X-type, Different center distance, Double V-type, and Single V-type—on the levitation performance of the Magnetic Wheelset is investigated. The coefficient of variation (CV) method is employed to evaluate force stability, and an optimal case is subsequently screened out using a dual-objective constraint approach that incorporates mean levitation force and lateral force thresholds. Results indicate that the X-type mounting at 25° is the optimal case. At 40 km/h, compared to the baseline Aligned configuration, the root mean square (RMS) values of the bogie’s vertical and lateral vibration accelerations are reduced by 14.7% and 23.8%, respectively. The vehicle’s vertical and lateral ride comfort indices decrease by 0.33 and 0.27, respectively, and the track beam’s vertical and lateral vibration accelerations are reduced by 19.4% and 13.3%. The methodology presented in this study provides a valuable reference for vibration suppression in PML systems. Full article