Search Results (379)

In automated sorting and grasping of livestock meat cuts, the ideal assumption of symmetric mass distribution is often violated due to irregular morphology and soft tissue deformation. Under the combined effects of gripping forces and gravity, the originally balanced configuration evolves into an asymmetric state, resulting in dynamic shifts of the center of gravity (CoG) that undermine the stability and accuracy of robotic grasping. To address this challenge, this study proposes a CoG trajectory prediction method tailored for meat-cut grasping tasks. First, a dynamic model is established to characterize CoG displacement during grasping, quantitatively linking gripping force to CoG shift. Then, the prediction task is reformulated as a nonlinear state estimation problem, and a Small-Target Bayesian–Probability Hypothesis Density (STB-PHD) algorithm is developed. By incorporating historical error feedback and adaptive covariance adjustment, the proposed method compensates for asymmetric perturbations in real time. Extensive experiments validated the effectiveness of the proposed method: the Optimal Sub-Pattern Allocation (OSPA) metric reached 4.82%, reducing the error by 4.35 percentage points compared to the best baseline MGSTM (9.17%). The task completion time (TC Time) was 6.15 s, demonstrating superior performance in grasping duration. Furthermore, the Average Track Center Distance (ATCD) reached 8.33%, outperforming the TPMBM algorithm (8.86%). These results demonstrate that the proposed method can accurately capture CoG trajectories under deformation, providing reliable control references for robotic grasping systems. The findings confirm that this approach enhances both stability and precision in automated grasping of deformable objects, offering valuable technological support for advancing intelligence in meat processing industries. Full article

Amid the rapid evolution of the digital economy reshaping global competitiveness, China has advanced regional coordination through the Digital China initiative and the “Data Elements ×” Three-Year Action Plan (2024–2026). To further integrate digital transformation with high-quality growth in the urban agglomerations of the middle and lower Yellow River, this study aims to strengthen regional competitiveness, expand digital industries, foster new productivity, refine the development pathway, and safeguard balanced economic, social, and ecological progress. Taking the Yellow River urban clusters as the research object, a comprehensive assessment framework encompassing seven subsystems is established. By employing a mixed-weighting approach, entropy-based TOPSIS, hotspot analysis, coupling coordination models, spatial gravity shift techniques, and grey relational methods, this study investigates the spatiotemporal dynamics between the digital economy and high-quality development. The findings reveal that: (1) temporally, the coupling–coordination process evolves through three distinct phases—initial fluctuation and divergence (1990–2005), synergy consolidation (2005–2015), and high-level stabilization (2015–2022)—with the average coordination index rising from 0.21 to 0.41; (2) spatially, a persistent “core–periphery” structure emerges, while subsystem coupling consistently surpasses coordination levels, reflecting a pattern of “high coupling but insufficient coordination”; (3) hot–cold spot analysis identifies sharp east–west contrasts, with the gravity center shift and ellipse trajectory showing weaker directional stability but greater dispersion; and (4) grey correlation results indicate that key drivers have transitioned from economic scale and infrastructure inputs to green innovation performance and data resource allocation. Overall, this study interprets the empirical results in both temporal and spatial dimensions, offering insights for policymakers seeking to narrow the digital divide and advance sustainable, high-quality development in the Yellow River region. Full article

The ongoing global warming threatens the Greenland Ice Sheet (GIS), which has exhibited an overall mass loss since 1990. This loss varies annually and interannually, reflecting the intricate interactions between the ice sheet and atmospheric and oceanic circulations. We investigate GIS mass balance variations (2002–2024) using data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions. Monthly mass anomalies from the International Combination Service for Time-variable Gravity Fields (COST-G) solution are compared with cumulative climate indices (North Atlantic Oscillation—NAO, Greenland Blocking Index—GBI, Atlantic Multidecadal Oscillation—AMO) and meteorological parameters (temperature, precipitation, surface albedo). Empirical Orthogonal Function analysis reveals five principal modes of variations, the first capturing annual and interannual frequencies (4–7 and 11 years), while subsequent modes only describe interannual frequencies. Wavelet analysis shows significant annual correlations between GIS mass changes and temperature (r = −0.88), NAO (r = 0.74), and GBI (r = −0.85). An annual cycle connects GIS mass changes, climatic indices, and meteorological parameters, while interannual variations highlight the role of the AMO and the NAO. The presence of an 11-year periodicity with the mass variations for NAO, GBI, and temperature strongly correlates with solar activity. Full article

Robot manipulators are suitable for many industrial tasks, such as assembly and pick-and-place operations. However, high-acceleration motions result in shaking forces and moments to the base, which can cause vibration of the manipulator and instability in the case of a mobile base. Furthermore, gravity compensation of the manipulator links requires additional motor torque, which can increase energy consumption. Balanced manipulators address these problems by employing a mechanical design that results in the balancing of gravity and other static forces, or the removal of shaking forces and/or moments. This review paper provides an overview of mechanical design approaches for balanced robotic manipulation, with an emphasis on experimentally prototyped designs. We first define the types of balancing according to the literature. We then provide an overview of different approaches to the mechanical design of balanced manipulators, along with simple examples of their implementation. Experimental prototypes in this field are then comprehensively presented and summarized to allow readers to compare their development maturity. At the end of the paper, we outline challenges and future directions of research. Full article

Significant chromite losses to tailings in gravity separation plants arise from both suboptimal separator design and inefficient beneficiation processes, posing major challenges to resource utilization, energy efficiency, and environmental sustainability. These losses are particularly critical because the material, already comminuted to liberation size, is discarded, leading to reduced concentrate yield, wasted energy input, and increased environmental pollution. To address this issue, an industrial-scale custom-designed shaking table was developed and tested to recover marketable-grade chromite concentrate (≥42% Cr₂O₃) from processing plant tailings containing 3.25%–4.25% Cr₂O₃, which had accumulated over years of chromite beneficiation. Experimental results showed that, under optimized operating parameters (320 rpm stroke frequency, 13 mm stroke length, 1° deck slope, 1300 g/L pulp density, 800 kg/h feed rate, and 7 tph wash water flow rate), Cr₂O₃ recovery increased from 8% to 27% for the first and second floor operations and from approximately 17% to 41% for the third and fourth floor operations compared with existing plant performance. The results revealed a strong interdependence between Cr₂O₃ recovery and concentrate grade, both of which are critical indicators of process efficiency. Intermediate particle sizes (−0.250 + 0.150 mm) provided the most favorable balance, yielding high recovery rates without substantially compromising the concentrated grade. Full article

To accurately assess the development potential of a high-speed rail (HSR) express in the logistics system, this study constructs a forecasting method for HSR express volume. Grey relational analysis is used to identify key influencing factors, and a multiple regression model is established to predict intercity express volume. A generalized cost model for road, HSR, and air express is developed, considering infrastructure availability and delivery timeliness. Cost differences between supply and demand sides are analyzed, and a Logit model is applied to quantify mode share, deriving HSR express volume. A gravity model allocates the volume between cities. The method is validated in Henan Province, China. Results show that: (1) Intercity express volume in China will continue growing over the next decade, with HSR forming a stable share, and Henan playing a significant role as a central hub; (2) Suppliers prefer HSR for medium-to-long distances with lower timeliness demands, while consumers prefer it for shorter, time-sensitive deliveries; (3) Lower consumer prices significantly increase HSR mode share, urging suppliers to balance cost and infrastructure investment. This method supports HSR express forecasting and promotes sustainable logistics. Full article

This paper presents a design of spring static-balanced manipulators for reduced spring attachment adjustments. Gravitational joint torque is balanced by spring torque to maintain static balance, but joint reaction force by gravity force and spring force is still an important issue for manipulators. Springs, with their stiffness and attachment parameters, cause torque on the same joint, and then there is a torque-sharing effect between them, and the parameters of one spring can be represented by other springs. The sharing ratio between coupled springs is defined as the ratio of the torque due to the spring attached to the succeeding link to the gravitational torque. For adjacent springs, the bounds of the sharing ratio are from 0 to 1; for non-adjacent springs at a succeeding link or preceding link, the upper bound of the sharing ratio is determined, or the sharing ratio is determined, respectively. The 3-DOF manipulators are an illustrative example: the relationship between joint reaction force and the joint torque-sharing ratio is investigated, and on the optimum joint reaction force, the best sharing ratio and spring attachment installations are found. It is shown that the joint reaction force is reduced in manipulators, and this method is used in spatial manipulators with a systematic spring static balance method. Full article

Submarine rift systems represent critical tectonic features whose accurate bathymetric characterization remains challenging yet essential for understanding plate boundary dynamics. However, traditional bathymetric inversion methods based on altimetric gravity data exhibit poor performance in resolving rift and steep-slope terrains. To address this limitation and enhance accuracy in complex topographic regions, we propose a multi-gravity-component fusion framework based on an improved DenseNet architecture. By integrating shipborne bathymetry, gravity anomaly (GA), vertical gravity gradient (VGG), vertical deflection components (meridian component ξ and prime vertical component η), and GEBCO_2024, we construct a 16 × 16 × 9 input tensor. The model incorporates adaptive transition layers to preserve fine-scale tectonic features and curvature-based stratification to balance learning across diverse terrains. Validation using 43,035 independent points yields an RMSE of 84.75 m, representing a 47.6% reduction relative to GEBCO_2024. Crucially, in the identified rift targets, errors decreased by 69.3–87.1%. Ablation studies reveal that vertical deflection components (ξ, η) dominate the physical constraints, with their removal increasing the RMSE by 91.08 m (a 107.5% increase relative to the baseline error). Architectural innovations and stratification reduce steep-slope RMSE by 6.1%. These results validate the efficacy of directional gravity derivatives for tectonic feature inversion and demonstrate significant potential for application to mid-ocean ridge systems. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

The regionalization of input–output tables enables a granular understanding of economic systems, allowing for interregional and interindustry analysis for goods and services in a local economy. This paper details the construction of an intermunicipal IO matrix for the state of Rio Grande do Sul (Brazil), a region marked by both economic diversification and significant territorial disparities. Using the 16-sector state IO matrix (base year 2019) provided by the state-level treasury (SEFAZ-RS) as a starting point, we adapt the Interregional Input–Output Adjustment System (IIOAS), integrating gravity-based trade modelling and RAS balancing, to produce a disaggregated structure for 497 municipalities. The regionalization follows three main steps: (i) generation of an initial matrix assuming proportional municipal shares in sectoral supply and demand; (ii) iterative RAS-based adjustments to align with municipal and state-level constraints; and (iii) incorporation of complementary municipal data—including employment, GDP, household consumption, and exports—to refine final demand and value-added allocations. The results demonstrate the feasibility of deriving spatially intermunicipal IO structures from limited data. The results show that, while industrial and service activities are concentrated around the Porto Alegre metropolitan area, rural subregions remain specialized in low value-added primary sectors. Full article

In this study, a nonlinear dynamic model is developed to examine the stability and vibration behavior of a self-balancing electric Segway operating over irregular stochastic terrains. The Segway is treated as a three-degrees-of-freedom cart–inverted pendulum system, incorporating elastic and damping effects at the wheel–ground interface. Road irregularities are generated in accordance with international standard using high-order filtered noise, allowing for representation of surface classes from smooth to highly degraded. The governing equations, formulated via Lagrange’s method, are transformed into a Lorenz-like state-space form for nonlinear analysis. Numerical simulations employ the fourth-order Runge–Kutta scheme to compute translational and angular responses under varying speeds and terrain conditions. Frequency-domain analysis using Fast Fourier Transform (FFT) identifies resonant excitation bands linked to road spectral content, while Kernel Density Estimation (KDE) maps the probability distribution of displacement states to distinguish stable from variable regimes. The Lyapunov stability assessment and bifurcation analysis reveal critical velocity thresholds and parameter regions marking transitions from stable operation to chaotic motion. The study quantifies the influence of the gravity–damping ratio, mass–damping coupling, control torque ratio, and vertical excitation on dynamic stability. The results provide a methodology for designing stability control systems that ensure safe and comfortable Segway operation across diverse terrains. Full article

The study compared the effects of conventional and vegan processing aids in the clarification of must, focusing on the phenolic and sensory characteristics of must and wine. The hypothesis was that plant protein could provide results similar to those of conventional aids containing proteins of animal origin, especially in aromatic grapes, where hyperoxidation is avoided. Conducted in 2024 in Etyek-Buda, Hungary, the initial trials subjected the Irsai Olivér grape must to gravity sedimentation with various agents. Vegan processing aids, notably the combination of pea protein and chitin-glucan, showed a gentle impact on the assimilable nitrogen content and a similar reduction in turbidity to those with animal proteins. Nitrogen flotation trials compared gelatin and the vegan alternative (a combination of pea protein and chitin–glucan) in Irsai Olivér and Chardonnay must clarification. The removal of phenolic substances was monitored using the Folin–Ciocalteu method, the acid butanol assay, and the vanillin assay. In addition, nitrogen levels were evaluated before and after the flotation experiments. The plant-based processing aid effectively improved the sensory quality of Irsai Olivér. However, the gelatin-treated Chardonnay was fresher and less bitter than the vegan option, which was less balanced and more bitter with weaker aroma and flavor. Full article

This study presents a novel approach to the development of self-compacting concrete (SCC) by partially replacing both cement and fine aggregate (sand) with waste marble sludge (WMS), a byproduct of the marble industry. The research aims to evaluate the feasibility of incorporating this industrial waste into SCC to enhance sustainability without compromising performance. To assess the fresh and hardened properties of the proposed mixtures, a comprehensive experimental program was conducted. Tests included slump flow, T₅₀, and V-funnel for evaluating workability, as well as measurements of specific gravity, compressive strength, flexural strength, Brazilian tensile strength, and water absorption at 28 days of curing. The results demonstrated that the mix containing 5% cement replacement and 20% sand replacement with marble sludge exhibited the highest mechanical performance, achieving a compressive strength of 48.2 MPa, tensile strength of 3.9 MPa, and flexural strength of 4.4 MPa. Furthermore, increasing the percentage of cement replacement led to enhanced flowability, as evidenced by an increase in slump flow diameter and a reduction in V-funnel flow time, indicating improved workability. Overall, the findings suggest that controlled incorporation of WMS can produce SCC with desirable mechanical and rheological properties, offering a promising pathway for sustainable concrete production. In addition to the technical performance, a carbon footprint analysis was conducted to examine the environmental benefits of marble sludge utilization. The mixture with 10% cement and 20% sand replacement exhibited the lowest carbon footprint, while the 7.5% replacement level provided the best balance between strength and sustainability. Full article

Background: There is no consensus on the best treatment method for calcaneal fractures. The topic of lower limb biomechanics following calcaneal fracture treatment with various fixation methods has not been fully explored. The aim of the study was to assess the balance and load distribution of the lower limbs in patients after various methods of stabilization of calcaneal fractures. Methods: In this two-center study, we retrospectively collected data from 19 patients treated with internal plate fixation at a mean age of 46 years and 27 patients treated with Ilizarov external fixation at a mean age of 50 years. Using the Zebris Medical pedobarophragmatic platform, we assessed the percentage distribution of lower limb loads and balance. Results: There were no significant differences in total load distribution for both the operated (p = 0.489) and non-operated limb (p = 0.46), between the Ilizarov method group and the internal plate group. In the Ilizarov fixation group, total load distribution was 46.89% on the treated limb, and 53.11% on the uninjured limb, p = 0.077. In the internal plate fixation group, the mean total load distribution was 41.57% in the treated limb, and 57.89% in the uninjured limb, p = 0.008. The median CoG (center or gravity) sway path length was 132.41 cm and 170.21 cm in the Ilizarov and internal plate group, respectively, p = 0.023. The median CoG sway areas were 0.84 cm² and 7.57 cm² in the Ilizarov method group and internal plate fixation group, respectively, p < 0.001. Conclusions: The Ilizarov method was associated with more symmetrical load distribution and improved balance performance compared to internal plate fixation. Static biomechanical parameters of calcaneal fracture treatment were better in the Ilizarov group compared to patients with internal plate fixation. Full article

The adaptability of a hexapod robot to complex terrain is highly dependent on its own posture, which directly affects its stability and flexibility. In order to adapt to a change in terrain, it is necessary to adjust posture in real time when walking. At the same time, external factors such as ground state and landing impact will also interfere with posture. Therefore, it is necessary to maintain balance after adjustment. This paper proposes a pose adjustment method utilizing joint angle control. It enhances robot stability, flexibility, and terrain adaptability through torso posture and center of gravity optimization, aiming to maintain balance. The strategy’s effectiveness was validated via Adams–Simulink co-simulation. Optimal position and posture adjustment for the torso was then implemented at the six-legged support stage after each step, employing inverse kinematics and a triangular gait. It is found that without pose adjustment, the direction deviation will accumulate and significantly deviate from the trajectory. The introduction of this adjustment can effectively correct the direction deviation and torso posture angle, increase the stability margin, ensure stable straight-line walking, and significantly reduce joint energy consumption. Crawling experiments with the physical prototype further validate the strategy. It rapidly counters instantaneous attitude fluctuations during leg alternation, maintaining a high stability margin and improving locomotion efficiency. Consequently, the robot achieves enhanced directional stability, overall stability, and energy efficiency when traversing terrain. Full article