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It is attractive and advantageous to utilize marginal land to support regional biomass energy development and improve energy security. In this study, an integrated and comprehensive decision-making framework is proposed to support the strategic planning and tactical management of regional biomass supply networks from an energy-land-carbon nexus perspective. It combines a multi-objective fuzzy chance-constraint programming model with spatial analysis of marginal land and multi-criteria assessment of biorefinery sites. The model is verified through a case study of a major agricultural region, Shandong Province in China. Local agricultural residues remain a key feedstock for bioethanol production. The results highlight the importance of considering the multi-objective tradeoffs and the intricate resource and environmental nexus for stakeholders to achieve sustainability in real practice. A cost-minimization objective drives the construction of large-scale biomass plants to enhance efficiency. An emissions-minimization goal favors smaller, decentralized plants to reduce transport distances and improve local land use. Maximizing social welfare promotes marginal land development, creating more employment opportunities. Decision-makers' management goals, risk preferences, and external fluctuations significantly influence the spatial planning of bioethanol supply chains, marginal land utilization, and operational strategies. Overall, the proposed methodology offers decision-makers an effective tool for achieving optimal decisions while accounting for complex system interdependencies, conflicting objectives, and uncertainties.

Abstract Background There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near‐infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. Methods Five minutes resting‐state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting‐state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut‐off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. Results The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)‐based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR‐based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut‐off value of resting‐state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. Conclusion Resting‐state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut‐off values of resting‐state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.

To address global phosphorus reduction challenges, we establish a quantitative framework for anthropogenic phosphorus emissions using a lifecycle model and decomposition analysis. Focusing on China's Pearl River Delta urban agglomeration, we highlight persistent difficulties in controlling phosphorus emissions from agricultural fertilizers and the emerging issue from industrial products. Emission intensity is a crucial factor for phosphorus reduction, yet gradually offset by affluence and population growth. Prioritizing agricultural control with supplementary industrial reduction, we delve into the decoupling challenge between phosphorus emissions, population expansion, and economic development. Proposing green economic development, our approach contributes to achieving sustainable phosphorus management goals.

Extreme heat-precipitation events, such as heatwaves and extreme precipitation, can have substantial impacts on the population, particularly in urbanized watersheds. However, few studies have investigated individual and compound extreme heat-precipitation events, causing much valuable information loss for watershed climate risk management. This study focuses on the Pearl River Basin (PRB), a highly urbanized area in southern China, and aims to predict changes in population exposure to extreme heat-precipitation events. To achieve this, a ranked ensemble global climate model (GCM) was used to generate projections for individual extreme precipitation, heatwaves, and sequential and coincident heat waves and precipitation extremes (SHWPs and CHWPs) under three future scenarios (SSP-RCPs). The main findings of the study are as follows: Precipitation extremes represent increasing extreme days and intensity under all three scenarios across the PRB. Towards the end of the 21st century, the SSP5-8.5 scenario predicts that heat waves will last ten times longer than historical records. Comparing two types of compound extreme events, we conclude that the 21st century will see a near-term high risk for SHWPs and a long-term high risk for CHWPs in the PRB. Furthermore, in both individual and compound heat-precipitation events, five hotspot cities in the PRB (i.e., Guangzhou, Dongguan, Foshan, Shenzhen, and Huizhou) will face higher population exposure to extreme heat-precipitation events. These cities share common characteristics: key to economic development, coastal, and densely populated. This study can provide insight into extreme climate risk management in other tropical and subtropical basins.

Documenting the joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought can be invaluable for understanding drought evolution under climate change in a high-diversity watershed of south China. Through constructing the edge and joint distribution functions of multi drought indices (SPEI, SPI, SSI, and SWI) based on SWAT and copula methods, we explored the evolution of multi droughts under climate change in the East River basin. During 1997–2017 and 2023–2099, we used logistic, generalized pareto, and normal distributions to construct edge distribution functions of SPEI, SPI, SWI, and SSI. For the four indices, the probability of slight drought increased with rcp2.6, 4.5, 6.0, and 8.5, and it was higher than moderate drought. Also, Clayton, Frank, Gumbel, and Gaussian copula functions were used to construct joint distribution functions of SPEI and SSI, SPEI and SWI, SSI and SWI to quantify their interactions. During 1997–2017, the probability of slight drought was 26.15 to 41.06 %, and the return period changed from 3.8 to 2.4 years. The joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought in slightly was 24.4 to 31.32 %, 14.95 to 22.63 %, and 6.18 to 22.05 %, respectively. During 2023–2099, the joint probability of droughts in moderately was 3.76 to 14.19 %, and the return period was 7 to 26.6 years. Our results provide a quantitative assessment of single and joint probability of meteorological, hydrological and agricultural drought, which could be used to support watershed water resource management.

Intensive human and economic activities in urban areas have had adverse effects on local resources and ecology, leading to a decline in ecological resilience. Enhancing ecological resilience is crucial for improving the urban ecosystem's ability to withstand and recover from external risks. However, quantitative research on urban ecological resilience remains somewhat ambiguous, with many studies lacking comprehensive assessment methods from multiple perspectives. In this study, we established a comprehensive framework to assess urban ecological resilience based on four regime attributes. The study's results indicated the following key findings: The average urban ecological resilience value exhibited a trend of initially declining and then recovering. Cities proposed different approaches when considering and managing social and ecological relationships during the development process. A significant correlation between urbanization levels and ecological resilience was observed, with urban ecological resilience increasing in areas with low urbanization levels and sharply decreasing in areas with high urbanization levels. The findings from this study provide a specific theoretical foundation for decision-makers involved in urban planning and development strategies.

The projection of future ecosystem service (ES) dynamics under SSP-RCP scenarios would be beneficial for the development of effective climate mitigation strategies for policymakers. However, current projection frameworks generally neglect the downscaling of high-resolution climate and land use data, leading to uncertainties in the simulation of ESs under the SSP-RCP scenarios. To address this issue, this study proposes an integrated analysis framework to downscale climate and land use data. We first identified areas of high risk in terms of inadequate water-related ESs in the Pearl River Basin (PRB) of China. Subsequently, we analyzed key socio-environmental factors driving the dynamics of water-related ESs under future SSP-RCP scenarios. The results indicate that 1) water-related ESs in the PRB are expected to show an overall increasing trend, 2) the sub-watersheds located in the downstream is at a higher risk of experiencing insufficient supply capacity for water-related ESs, and 3) under the coupling effects of climate change, land use change, and socio-economic development, drastic changes in future land use are expected to have a stronger impact on watershed ESs than the climate (i.e., global warming). Our work provides valuable insights for policymakers and managers regarding future water and land resource planning. The proposed framework can be integrated with other hydrological or land surface models to project the spatial–temporal evolution characteristics of future watershed ESs with finer temporal resolution.

The resilience of the urban ecological network is an indispensable aspect of reflecting the recovery capacity after the external risk shock. Improving the resilience of the ecological network is conducive to enhancing the ecological benefits. However, the current studies are lack of resilience evaluation from a comprehensive perspective. Thus, in this study, taking three typical urban agglomerations as cases, a comprehensive evaluation framework was proposed to assess ecological network resilience. First, we selected the comprehensive reserve as ecological sources and combined them with ecological corridors to construct the ecological network. Then we evaluated the resilience of ecological networks from the perspectives of robustness and redundancy. Finally, we analyzed the resilience of the network under different importance nodes failed. The results showed that (1) the average values of the comprehensive reserve value (CRV) in three urban agglomerations were over than 0.8. (2) the resilience of ecological networks in three urban agglomerations was blow the optimal value throughout during the period from 1985 to 2020. (3) the resilience change trends of multiple urban agglomerations were significant differences after removing certain important nodes, indicating the current ecological network is redundant. The research will help to improve the evaluation of urban ecological resilience and enhance the improvement of sustainable urban management and ecological restoration.

In this study, a new concept concerning comprehensive characteristics of water resources utilization as an index for risk modeling within the water allocation management model is proposed to explore the tolerance of unbalanced allocation problem under the water–energy nexus. The model is integrated with interval two-stage stochastic programming for reflecting system uncertainties. These uncertainties are associated with the industrial production feature and the decision-making process. With respect to the water–energy nexus, energy proposed is mainly focused on the consumption intensity of water purification and transportation from different water sources. The developed model is applied for industrial water resources allocation management in Henan province, China. Multiple scenarios related to disparate energy consumption control and the comprehensive risk levels are simulated to obtain a reasonable trade-off among system profit, comprehensive risk, and energy consumption. The results indicated that the strict comprehensive risk management or energy consumption control measures could cause damage to system benefit owing to decreasing the flexibility of industrial water resources distributions, and the preliminary energy consumption or the comprehensive risk control would be beneficial to moderate the conflict between industrial sectors and water resources, and accelerate industrial structure transformation in the future. HIGHLIGHTS A comprehensive risk-oriented industrial water resources management model is proposed.; Uncertainties are reflected as stochastic and interval information.; Energy–water nexus is a constraint index for water purification and transportation.; The tolerance of unbalanced allocation problem is explored.; Trade-off among system profit, comprehensive risk, and energy consumption is analyzed.;

With the continuous development of the social giant system, the independence of subsystem boundaries has decreased under the drive of complex relationships and multiple uncertainties. Decision makers are required to consider the interactions between different systems to develop precise policy guidance. Given these challenges, an integrated optimization and multi-scale input–output (OMIO) model is proposed by integrating interval programming, chance-constrained programming, and integer programming into the input–output framework to provide comprehensive policy analysis. The optimized decision variables that carry uncertain information from energy system are identified as connection points to induce changes in economic-environmental effects. A typical fossil-energy-dependent region that mainly relies on fossil fuels, Shanxi Province, China, was used as a case study. It was found that the joint effects of energy system optimization and socioeconomic rebalance will promote the rise of the petroleum product sector, the logistics industry, and tertiary industries, as well as the popularity of electric vehicles. The increase in the use of clean energy and electric vehicles will stimulate GDP growth in the short term, and the emissions of carbon dioxide and air pollutants will be reduced to varying degrees. The study findings can provide comprehensive energy allocation strategies, socioeconomic effect analysis, and climate mitigation results to help fossil-energy-dependent regions better adapt to the requirements of sustainable development under multiple systematic uncertainties.

Background Studies have shown that platelet-rich plasma (PRP) can enhance the effect of meniscus repair, but some studies have suggested different views on the role of PRP. Purpose To determine whether PRP can enhance the effect of meniscus repair with respect to pain reduction and improved functionality and cure rate in patients with meniscus injury. Methods By searching PubMed, EMBASE, Cochrane Library databases, clinicaltrials.gov , and the CNKI database from their inception till December 1, 2020, we performed a meta-analysis of RCTs reporting the results of the Pain Visual Analog Scale (VAS), the pain of Knee injury and Osteoarthritis Outcome Score (KOOS), Lysholm score, the International Knee Documentation Committee (IKDC), healing rate, and adverse events. The risk of bias is assessed using Cochrane’s collaborative tools. The summary results are expressed with effect size and 95% confidence interval, and sensitivity were performed. Results The meta-analysis included 9 RCTs and 345 patients. In general, compared with the control group, used of PRP during meniscus surgery significantly improved the pain (SMD: -0.95, p < 0.00001,95% CI: -1.22 to -0.69, I2 = 42%) and knee joint function (SMD: 1.00, p = 0.01.95% CI: 0.22 to 1.79, I2 = 89%) of patients with meniscus injury at 6 months after treatment. However, both PRP and non-PRP showed improvements in the pain and knee joint function, with no significant difference between the groups at 1 months and beyond 12 months. The PRP enhancement technique showed benefit in improving the cure rate of meniscus repair (RR:1.44; p < 0.0001, 95% CI: 1.20–1.73). No serious adverse events were reported in any study. Conclusion As an enhancement program for meniscus repair, PRP is worthy of further consideration in improving the function and pain of patients during the mid-term follow-up after surgery, and PRP can further improve the healing rate of meniscus repair. However, the evidence still needs to be interpreted carefully because of the quantity and quality of the included studies.

BackgroundPurified platelet-rich plasma (P-PRP) is gradually being used in the treatment of osteoarthritis (OA), and its sources are mainly divided into autologous and allogeneic blood. However, it is unclear whether autologous PRP is more effective or allogeneic PRP is superior.ObjectiveIn this study, autologous and allogeneic P-PRP was injected at early stage of KOA in rabbits, and then the differences in the efficacy of the two P-PRPs against KOA were compared from several perspectives, including pathological histology and immunohistochemistry.MethodExperimental rabbits were divided into normal group (n = 8), model group (n = 8), autologous P-PRP group (n = 8), and allogeneic P-PRP group (n = 8) using a random number table method. The normal and model groups did not receive any treatment, and the autologous P-PRP and allogeneic P-PRP groups received intra-articular injections of autologous and allogeneic P-PRP, respectively, to observe the changes in the gross specimens of the knee joints of the experimental rabbits in each group. The histopathological changes of chondrocytes were also observed by HE-stained sections of articular cartilage, and the expression of chondrocytes Bone morphogenetic protein-2 (BMP-2) and Sox9 were detected by immunohistochemistry.ResultsCompared with the allogeneic P-PRP group, the differences were statistically significant (P 0.05).ConclusionIntra-articular injection of autologous P-PRP activated the expression of BMP-2 and Sox9 in chondrocytes and effectively improved KOA cartilage repair and reduced bone redundancy and joint fluid formation, and its efficacy was superior to that of intra-articular injection of allogeneic P-PRP.

The related dynamic change in meteorological and hydrological parameters is critical for available water resources, development management options, and making informed decisions. In this study, to enhance the resolution of the predicted meteorological and hydrological parameters under climate change, the statistical downscaling method (SDSM), the generalized regression neural network (GRNN) model, the Soil and Water Assessment Tool (SWAT) model, and the improved Tennant method were integrated into a framework. The available water resources were assessed in the Huangshui watershed of the Qinghai–Tibet Plateau, which has the highest average elevation in the world. The meteorological parameters were obtained by the SDSM model and the GRNN model. The SWAT model used the meteorological parameters to simulate the hydrological data under climate change scenarios. Considering the meteorological conditions and the high sediment content in the basin, the available water resources are evaluated by the improved Tennant method. The meteorological data of the Xining station from 1958 to 2011 were used to analyze the dynamic changes and mutation trends in the data. The results indicated that the precipitation would have a great increase during the wet season from May to September, and the flows and available water resources would decrease with increasing carbon emissions under different representative concentration pathways (RCPs).

Commonalities and asynchronous experiences of realizing zero-waste of water, energy, and food resources between the world and China have critical global importance to support sustainable development, especially for Guangdong-Hong Kong-Macao Greater Bay Area (GBA) urban agglomeration. In this study, a comprehensive assessment framework for the zero-waste city was proposed to evaluate zero-waste construction in the world (e.g., San Francisco, New York, and Tokyo) and China (e.g., Beijing, Shanghai, and GBA) from the perspective of water, energy, and food. The results showed that the zero-waste construction level of the GBA cities was weaker than that of the benchmark city and other world-class cities. The average score of the GBA cities was the lowest, 2.5% lower than the benchmark city and 11.8% lower than other world-class cities. Macao had apparent advantages in the social-economic and ecological-environment system, while the Pearl River Delta cities were considerably better than Macao and Hong Kong in the water and food systems. Future work could improve the level of zero-waste construction by learning from foreign zero-waste cities’ advanced experience, increasing efforts to promote the implementation of a circular economy, and building an all-around government sharing mechanism with public participation.

In this research, an integrated approach is developed through the incorporation of systems dynamics (SD), catastrophe progression (CP), and coupled coordination degree (CCD) analysis within a general modelling framework. The developed SD-CP-CCD is then employed to simulate and evaluate relationships among the water-energy-food (WEF) and the economic systems. It will improve traditional methods for WEF nexus analysis through a) incorporating urban WEF connections and changes into the cross-system coupling analysis framework, b) evaluating its coordination with economic growth and a multi-scale and regional disparity, and c) promoting policy recommendations to ensure the guarantee of urban WEF under economic growth. The approach is then verified through WEF nexus system of Urban Agglomerations of Pearl River Delta City Cluster (PRDCC) in China. Temporal and spatial characteristics of CCD in the region were analyzed. The results revealed their performance in cities with multiple economic backgrounds. Also, the fragile factors of each city were reflected by multi-scale exploration. Regional inequality and spatial agglomeration effects were considered. The results showed that CCD has noticeable temporal and spatial differences. Geographically, CCD varied from uncoordinated to high-level coordination. The eastern cities were much better coordinated than the western cities. Due to the increasing pressure of population and economic growth in the future, the upward trend of CCD would occur in most cities. The vulnerability factors of each city were explored. Simultaneously, apparent spatial inequality and agglomeration patterns were observed, with a downward trend over time. The temporal and spatial patterns of CCD revealed in this study indicated that PRDCC policymakers should formulate policies that suit the characteristics of cities and reduce the targeted regional imbalances.

The water–energy nexus has become a key factor in the implementation of low-carbon green development, which has led to the need for exploring effective management within the coupled integrated system with multi-energy flow supplies. In this study, the coupled relationship between water resources and energy in the integrated energy system was systematically analyzed, and a system operation optimization model was proposed through comprehensively considering cold, heat and electricity load, and nine kinds of energy conversion and supply equipment/technology from the perspective of a water resources and energy nexus in a typical industry park. The system operation scheme, energy supply mode, net benefit and water resource consumption under different water resource control scenarios were obtained. The results show that water resource control would directly bring about a directly positive influence on renewable energy utilization and energy storage reduction, and that a system’s external dependence and benefits, renewable energy utilization potential and other factors in an integrated energy system should be comprehensively considered. The development of more effective control indicators could be better to promote the effectiveness of bidirectional regulation in a water–energy nexus.

The temperature fluctuations inside commercially distributed feedback laser diode were experimentally measured and analyzed in detail in this study. In tunable diode laser absorption spectroscopy based gas sensing systems, the temperature of the laser source is usually fixed and a current signal is used to drive the laser for wavelength scanning or modulation. Even if the laser is controlled by a robust temperature controller, the internal temperature still fluctuates due to the delayed response of the temperature controller when rapidly changing the drive current. These temperature fluctuations result in distortions in the measured absorption signals which can be effectively suppressed by limiting the drive current modulation to the resonance frequency of the temperature control proportional-integral-derivative loop. This study demonstrates a reduction in the temperature dependent absorption distortions and improves the detection uncertainty using this technique.

With the carbon reduction targets being set in the Paris Agreement on Climate Change, China is facing great pressure to meet its emission reduction commitment. The electric power industry as the major source of carbon emissions needs to be a focus. However, the uncertainty of power systems, the risk of reducing emissions and the fuzziness of carbon capture technology popularization rate and carbon reduction targets makes previous planning methods unsatisfactory for current planning. This paper establishes an interval fuzzy programming with a risk measure model which takes carbon capture technology and carbon reduction targets into account, to ensure that the complex electric management system achieves the best developmental state. It was concluded that in order to reduce carbon emissions, wind power and hydropower would be the best choices, and coal-fired power would be the suboptimal choice, and solar power would play a complementary role. Besides, decision makers should put much more effort into promoting and improving carbon capture technology instead of simply setting emission reduction targets. The non-synchronism of the downward trend in carbon emissions per unit of electricity generation and electric power industry total carbon emissions need to be taken seriously.

In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general programming to reflect uncertainties that were expressed as interval values and probability distributions in the objective function and constraints. An MSIRP-based energy system optimization model is proposed for electric-power structure management of Zibo City in Shandong Province, China. Three power demand scenarios associated with electric-power structure adjustment, imported electricity, and emission reduction were designed to obtain multiple decision schemes for supporting regional sustainable energy system development. The power generation schemes, imported electricity, and emissions of CO2 and air pollutants were analyzed. The results indicated that the model can effectively not only provide a more stable energy supply strategies and electric-power structure adjustment schemes, but also improve the balanced development between conventional and new clear power generation technologies under uncertainty.

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that develops and persists after an individual experiences a major traumatic or life-threatening event. While pharmacological treatment and psychological interventions can alleviate some symptoms, pharmacotherapy is time-consuming with low patient compliance, and psychological interventions are costly. Repetitive Transcranial Magnetic Stimulation (rTMS) is a safe and effective technique for treating PTSD, with advantages such as high compliance, low cost, and simplicity of implementation. It can even simultaneously improve depressive symptoms in some patients. Current research indicates that high-frequency rTMS shows better therapeutic effects compared to low-frequency rTMS, with no significant difference in the likelihood of adverse reactions between the two. Theta Burst Stimulation (TBS) exhibits similar efficacy to high-frequency rTMS, with shorter duration and significant improvement in depressive symptoms. However, it carries a slightly higher risk of adverse reactions compared to traditional high-frequency rTMS. Combining rTMS with psychological therapy appears to be more effective in improving PTSD symptoms, with early onset of effects and longer duration, albeit at higher cost and requiring individualized patient control. The most common adverse effect of treatment is headache, which can be improved by stopping treatment or using analgesics. Despite these encouraging data, several aspects remain unknown. Given the highly heterogeneous nature of PTSD, defining unique treatment methods for this patient population is quite challenging. There are also considerable differences between trials regarding stimulation parameters, therapeutic effects, and the role of combined psychological therapy, which future research needs to address. [ABSTRACT FROM AUTHOR]