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Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts’ inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers’ relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that‘Top Management Support (TMS)’ is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index.

Background Equity and efficiency are basic value dimensions to evaluate the effectiveness of China’s medical and health service system (MHS) reform and development. Coordinated development of equity and efficiency is necessary to realize high-quality development of medical and health services. This study aims to evaluate the equity, efficiency, and combined efforts in coordinating the MHS during 1991–2020 reform. Methods Data on China’s MHS were obtained from the China Statistical Yearbook 1992–2021. Ratios of urban to rural residents’ medical expenditure and number of medical professionals per 10,000 people were employed to evaluate MHS’s equity. The data envelopment analysis-Malmquist model was employed to evaluate MHS’s efficiency. We constructed a combined-efforts-in-coordination model to examine the coordination degree between equity and efficiency. Results Equity of medical expenditure burden significantly improved from during 1991–2007. Urban residents’ 1991 medical expenditure burden was 87.8% of that of rural residents, which increased to 100.1% in 2007. Urban areas’ mean medical expenditure burden was 105.94% of that in rural areas during 1991–2007. The gap in equity of medical expenditure burden between urban and rural areas slowly widened after 2007, with urban areas’ mean burden being 68.52% of that in rural areas during 2007–2020. Medical and health resources allocation shows an alarming inequity during this period, with mean number of medical professionals per 10,000 people in urban areas being 238.30% of that in rural areas. Efficiency experienced several fluctuations before 2008. Since 2008, efficiency was high (0.915) and remained stable, except in 2020. The combined-efforts-in-coordination score for medical expenditure burden was less than 0.2 for 80% of the years, while that for in medical and health resources was more than 0.5 for 99.67% of the years. Conclusions MHS inequity remains between urban and rural China, primarily because of disproportionate allocation of medical and health resources. The government should enhance rural medical professionals’ salary and welfare and provide medical subsidies for rural residents to adjust resource allocation levels in urban and rural areas, control differences in medical expenditure burden between urban and rural residents to a reasonable range, and continuously improve urban and rural residents’ equity level.

Coordinated movement of four limbs is a hallmark of healthy locomotion. No measures exist to quantify four-limb coordination. This study aimed to investigate temporal four-limb coordination and proposed a new metric for quantifying the inter-limb phase of rhythmic locomotion-related movements. Kinetic data of arm and leg movements generated during walking (self-selected speed) from healthy adults were used to extract the phases (φ) between all possible limb pairings. The φ series were used to calculate each pair’s Phase Coordination Index (PCI). The PCI quantifies the accuracy and consistency of generating anti-phased rhythmic movements (lower PCI values mean better coordination). We also calculated the Quadruple-PCI (Q-PCI) by combining all φ values of all limb pairs. We found a significant correlation between the PCI values of all limb pairings and the Q-PCI (pairs involving arms: Pearson’s R > 0.79, p < 0.001; leg–leg: Pearson’s R = 0.3, p < 0.01). The PCI values that involve arms (median values between 6.5% and 8.3%) were significantly higher than the leg–leg PCI (median values between 3.8% and 4.1%), and the Q-PCI (median values between 8.3% and 9.7%) was significantly higher than all other PCI values. We also found a negative correlation between the arm swing amplitude and the PCI values (Spearman’s Rho of different limb pairings ranging from −0.25 to −0.5, p < 0.05), suggesting that higher arm swing amplitude leads to better coordination. Four-limb coordination analysis is a novel method for comprehensive assessment of gait coordination, which is often compromised among persons with disabilities.

This paper proposes the assessment method of the protection coordination index (PCI) for overcurrent protection relay and upstream relay. The protection coordination index is an indicator of how properly the equipment is protected by protective relay. The PCI is used to check the appropriateness of the protection coordination for both the component-wise and pair-wise. The protection index of each protection component of the integrated digital relay is assessed by a fuzzy logic controller. Then the device-level protection index and the composite protection coordination index between up and downstream relays are also assessed. Since the setting criteria of the overcurrent relays are given in a certain range rather than a crisp value, it is difficult to indicate the protection level of the protective system as an index. Currently, there is no way of knowing how well the overcurrent relay setting is. Thus, a method was proposed to evaluate the protection index of overcurrent systems using fuzzy logic. This is the unique research result of this paper.

Examined the synergistic development and spatio-temporal evolution of China’s multi-level medical insurance system (MMIS) on a macroscopic level. We assess the comprehensive development of the MMIS across China’s 31 provinces from 2011 to 2020 by constructing a comprehensive indicators evaluation model. Subsequently, a coupling coordination index (CCI) model is employed to provide precise insights into the coupling coordination effects among various medical insurance schemes comprising MMIS. Lastly, spatial autocorrelation analysis is conducted to evaluate both the global and local spatio-temporal evolutionary characteristics of MMIS. The CCI of MMIS at the national average level exhibited a fluctuating upward trend, progressing from the moderate disorder recession degree (0.287) in 2011 to the well-coordinated degree (0.887) in 2020. However, the majority of provinces (83.87%) still lingered within the realm of barely coordinated degree ([0.500–0.600]). Specifically, the CCI within the eastern coastal region surpassed that of the western and central regions, with the central region showing the most pronounced increase in CCI. Over the past decade, MMIS demonstrated significant spatial agglomeration, as evidenced by the global Moran’s I ranging from [0.1668–0.3037]. Furthermore, findings from local spatial autocorrelation analysis suggest a gradual attenuation in the spatial clustering disparity of CCI across various provinces. Government ought to focus on the spatio-temporal evolution patterns of MMIS, and strengthen cooperation between the government and market in health governance, while utilizing information technology and data sharing to improve the overall quality of medical insurance benefits.

Background: Walking fatigability is prevalent in MS and can be measured by a percentage distance decline during a 6-min walking test. Walking is characterized by an accurate and consistent interlimb antiphase coordination pattern. A decline in coordination each minute during a 6-min walking test is observed in persons with MS (pwMS). Measuring coordination during a 6-min seated coordination task with minimized balance and strength requirements, is assumed to examine a more fundamental interlimb antiphase coordination pattern in pwMS. This research aimed to answer the following research question: How does interlimb antiphase coordination pattern change during a seated coordination task in pwMS with walking fatigability (WF), non-walking fatigability (NWF) and Healthy Controls (HC)? Methods: Thirty-five pwMS and 13 HC participated. Interlimb coordination was assessed by a seated 6-min coordination task (6MCT) with the instruction to perform antiphase lower leg movements as fast as possible. Outcomes were Phase Coordination Index (PCI) and movement parameters (amplitude, frequency). Results: Mixed models revealed a significant effect of time for the the variability of generating interlimb movements, with a difference in mean values between WF and HC. A significant group ∗ time interaction effect was found for movement amplitude, represented by a significant decrease in movement amplitude in the WF group from minute 1 to the end of the task. Conclusion: The higher variability in interlimb coordination and decrease in movement amplitude over time during the 6MCT in the WF group could be an indicator of decreased control of fundamental antiphase coordination pattern in pwMS with walking fatigability. Clinical Trial Registration: www.clinicaltrials.gov , identifier NCT04142853 (registration date: October 29, 2019) and NCT03938558 (registration date: May 6, 2019).

The accurate identification of PLES changes and the discovery of their evolution characteristics is a key issue to improve the ability of the sustainable development for resource-based urban areas. However, the current methods are unsuitable for the long-term and large-scale PLES investigation. In this study, a modified method of PLES recognition is proposed based on the remote sensing image classification and land function evaluation technology. A multi-dimensional index system is constructed, which can provide a comprehensive evaluation for PLES evolution characteristics. For validation of the proposed methods, the remote sensing image, geographic information, and socio-economic data of five resource-based urbans (Zululand in South Africa, Xuzhou in China, Lota in Chile, Surf Coast in Australia, and Ruhr in Germany) from 1975 to 2020 are collected and tested. The results show that the data availability and calculation efficiency are significantly improved by the proposed method, and the recognition precision is better than 87% (Kappa coefficient). Furthermore, the PLES evolution characteristics show obvious differences at the different urban development stages. The expansions of production, living, and ecological space are fastest at the mining, the initial, and the middle ecological restoration stages, respectively. However, the expansion of living space is always increasing at any stage, and the disorder expansion of living space has led to the decrease of integration of production and ecological spaces. Therefore, the active polices should be formulated to guide the transformation of the living space expansion from jumping-type and spreading-type to filling-type, and the renovation of abandoned industrial and mining lands should be encouraged.

Transit-oriented development (TOD) is increasingly recognized as a key strategy for enhancing transportation efficiency, environmental sustainability, and economic vitality while fostering inclusive communities in dense, multifunctional urban areas. However, the relationship between TOD's economic benefits and social equity remains underexplored. This study critically evaluates TOD in Dalian, China, introducing the expanded Node-Place-Economy (NPE) model, which integrates economic and social dimensions into the traditional Node-Place model. The NPE model offers a comprehensive framework for assessing TOD effectiveness, particularly in balancing economic growth and equitable resource distribution. The research highlights significant disparities between central and peripheral regions, with central areas performing better in both economic and social equity, while peripheral areas exacerbate socio-economic inequalities. Through spatial analysis and the Coupling Coordination Index (CCI), the study identifies factors influencing the synergy between economic vitality and social equity, such as the density of commercial, sports, and entertainment facilities. The findings emphasize the need for more equitable TOD planning, suggesting that future urban developments should prioritize social inclusiveness alongside economic efficiency. This research expands the theoretical foundation of TOD and offers practical insights for urban planners aiming to achieve sustainable and inclusive urban development.

Urban green spaces (UGSs) deliver vital ecological and social benefits, and their integrated management significantly contributes to ecological sustainability and public well-being. However, existing studies tend to separately examine ecological and social values of various UGS types, lacking comprehensive assessments of their interactions. In response, this study established an integrated biotope classification system based on vegetation structure and conducted extensive field surveys to map urban biotopes in Xi’an city. Ecological values were evaluated through twelve selected indicators, including biodiversity, air quality regulation, and carbon storage. Social values were assessed using the SolVES model across six dimensions: aesthetics, recreation, cultural , spiritual, biodiversity, and therapeutics. The coupling coordination degree (CCD) between ecological and social values was subsequently calculated, and key influencing factors were analyzed via Geodetector. The results reveal that: (1) Xi’an encompasses 28 distinct biotope types, with green spaces occupying the largest area (2.89 km 2 ; 79.97%) and blue spaces the smallest (0.32 km 2 ; 8.72%). (2) The CCD between ecological and social values is on the verge of disorder (0.467), indicating a critical need for improved coordination. (3) Open green spaces with herbaceous vegetation (G O He) exhibit the highest CCD. Conversely, closed one-layer broad-leaved forests primarily covered by hardscape (G C Ha B L-1) and closed multi-layer broad-leaved forests primarily covered by hardscape (G C Ha B L-2) present the lowest coordination levels. (4) Ecological characteristics significantly influence CCD, highlighting the importance of detailed biotope classification. The results emphasize that enhancing spatial configurations and optimizing functional arrangements within UGSs are essential strategies for improving eco-social synergies and coupling coordination. This study provides valuable insights and practical recommendations for targeted urban planning and sustainable development of urban green infrastructure in Xi’an and similar rapidly urbanizing regions.

Spatiotemporal analysis of gait pattern is meaningful in diagnosing and prognosing foot and lower extremity musculoskeletal pathologies. Wearable smart sensors enable continuous real-time monitoring of gait, during daily life, without visiting clinics and the use of costly equipment. The purpose of this study was to develop a light-weight, durable, wireless, soft-material-based smart insole (SMSI) and examine its range of feasibility for real-time gait pattern analysis. A total of fifteen healthy adults (male: 10, female: 5, age 25.1 ± 2.64) were recruited for this study. Performance evaluation of the developed insole sensor was first executed by comparing the signal accuracy level between the SMSI and an F-scan. Gait data were simultaneously collected by two sensors for 3 min, on a treadmill, at a fixed speed. Each participant walked for four times, randomly, at the speed of 1.5 km/h (C1), 2.5 km/h (C2), 3.5 km/h (C3), and 4.5 km/h (C4). Step count from the two sensors resulted in 100% correlation in all four gait speed conditions (C1: 89 ± 7.4, C2: 113 ± 6.24, C3: 141 ± 9.74, and C4: 163 ± 7.38 steps). Stride-time was concurrently determined and R2 values showed a high correlation between the two sensors, in both feet (R2 ≥ 0.90, p < 0.05). Bilateral gait coordination analysis using phase coordination index (PCI) was performed to test clinical feasibility. PCI values of the SMSI resulted in 1.75 ± 0.80% (C1), 1.72 ± 0.81% (C2), 1.72 ± 0.79% (C3), and 1.73 ± 0.80% (C4), and those of the F-scan resulted in 1.66 ± 0.66%, 1.70 ± 0.66%, 1.67 ± 0.62%, and 1.70 ± 0.62%, respectively, showing the presence of a high correlation (R2 ≥ 0.94, p < 0.05). The insole developed in this study was found to have an equivalent performance to commercial sensors, and thus, can be used not only for future sensor-based monitoring device development studies but also in clinical setting for patient gait evaluations.