Search Results (5,008)

The problem of low water level and uneven distribution of flow in the multi-branch channels at the tail of the Ganjiang River (GJRT) during the dry season has been affecting the local water supply, navigation, and aquatic ecological environment. In recent years, water conservancy projects have been built in each branch of the multi-branch channels at the GJRT. Finding a way to utilize the water conservancy project group to carry out joint regulation and meet the water level and discharge requirements of each branch is an important issue that urgently needs to be solved. This paper analyzes the hydrodynamic process and its impact on water supply, navigation, and ecology in multi-branch channels without water conservation projects through hydrological data analysis and numerical simulation. By conducting numerical experiments on joint regulation of water conservation project group, a multi-objective regulation strategy is proposed to meet the water level and discharge of each branch. The results indicate that the discharge at the GJRT has been continuously decreasing from 1 September. Due to the jacking effect of Poyang Lake, the water level plunges at the GJRT from 1 October, which occurred later than the decrease in water level. The disruption of water levels and discharge makes it difficult to meet the regional water demand. The optimal time to initiate regulation is 1 October, and the target water level of Waizhou Station is 15.5 m, located upstream of the Ganjiang River tail. When the water level before each branch project gate is uniform and exceeds 15.5 m, the water level of Waizhou Station satisfies the requirement. However, the discharge of each branch does not meet the demand. In contrast to a scheduling regulation strategy that maintains the same water level in front of each gate, adopting a strategy with different water levels before each gate can effectively adjust the diversion ratio and fulfill the discharge demand of each branch at the tail of the Ganjiang River. Full article

Postoperative hemorrhage (POH) is a rare but serious complication of cranial neurosurgery, often resulting in neurological deterioration and necessitating urgent surgical intervention. Despite its clinical relevance, POH remains underreported and insufficiently understood. This study aimed to identify potential risk factors including perioperative variables and tumor-related characteristics associated with POH requiring surgical evacuation. A total of 1862 cranial tumor procedures were performed in our department over a 10-year period. Data on perioperative parameters and tumor characteristics were retrospectively collected and analyzed. Statistical analyses were conducted to assess associations of them to POH. Statistical analysis revealed several peri- and postoperative variables significantly associated with POH in univariate analyses. These included intraoperative blood loss (p = 0.012) and length of postoperative hospital stay (p = 0.016). Furthermore, the outcomes measured using the Glasgow Outcome Scale (p < 0.001) and the Karnofsky Performance Scale (p < 0.001) showed also statistical relevance as a result of postoperative bleeding in these patients. The findings suggest that specific perioperative factors particularly intraoperative blood loss are associated with an increased risk of POH after intracranial tumor surgery. Additionally, prolonged hospitalization and worsened functional outcomes were linked to the occurrence of postoperative hemorrhage. In contrast, tumor-specific characteristics and routine laboratory values showed no significant association with hemorrhagic complications in this cohort. Full article

With the rapid development of the global urbanization process, the resource utilization of construction waste has become one of the core issues of the development of a circular economy and has been widely concerned by the international community. However, China’s resource utilization efficiency in this field is still in the development stage, and cthere is still a gap with developed countries. It is urgent to systematically solve scientific problems such as low resource utilization efficiency, prominent technical bottlenecks, and imperfect whole process management mechanisms, so as to realize the coordinated high-quality development of the economy, society, and the environment. In order to scientifically predict the generation trend of construction waste and assess the resource potential, this study takes Beijing as the research object. Based on the historical data samples of construction waste in Beijing from 2001 to 2024, the analysis framework of “output estimation—trend prediction—value evaluation” is constructed. The ARIMA model is selected as the core tool of prediction, because it can match the phased change characteristics of construction waste output with the development of the city in time series data processing. Combined with the cost–benefit analysis method, it makes a quantitative analysis of the future production scale of construction waste and the economic benefits of resource utilization in Beijing. The research results show that from 2025 to 2034, the production of construction waste in Beijing will show a trend of first decreasing and then increasing, and it will reach 13.599 million tons by 2034. The resource utilization of construction waste in the next 10 years is expected to bring about USD 2.998 billion of economic benefits. This prediction result may be related to the policy guidance of Beijing’s urban renewal, changes in construction activities, and industrial technology upgrading. Accordingly, this study puts forward countermeasures and suggestions to help the development of industrialization, providing theoretical support and practical references for the sustainable development of the resource utilization of construction waste. Full article

Considering the significant role that emergency infrastructure projects (EIPs) play globally in responding to emergency events, public sentiment towards EIPs has become an increasingly important factor to consider. However, limited studies have analysed the public’s sentiment specifically towards EIPs in emergency and urgent circumstances. This study analyses public sentiment characteristics by collecting objective big data from popular posts and comments related to EIPs on Sina Weibo. Sentiment information was extracted using text mining methods, and sentiment was measured using a long short-term memory (LSTM) model. Findings indicate that (1) Positive sentiment predominates in the data. (2) Public sentiment of temporary EIPs remains relatively stable, while long-term adaptive EIPs earn more pronounced sentiment fluctuation. (3) There are regional differences in public sentiment; Hebei, Shandong and Shanghai exhibit slightly lower stability with positive sentiment being slightly lower than or equal to neutral sentiment. The findings contribute to the literature by focusing innovatively on the public perspective of EIPs under urgent circumstances by exploring public sentiment characteristics and evolution and are of particular significance for related government departments and project managers in decision-making and construction management. Full article

Amid accelerating climate change, intensifying urban heat island effects, and rising public demand for livable, walkable streets, there is an urgent practical need for interpretable and actionable evidence on streetscape quality. Yet, research on streetscape quality has often relied on single data sources and linear models, limiting insight into multidimensional perception; evidence from temperate monsoon cities remains scarce. Using Tianjin’s main urban area as a case study, we integrate street-view imagery with remote sensing imagery to characterize satellite-derived environmental indicators at the point scale and examine the following five perceptual outcomes: comfort, aesthetics, perceived greenness, summer heat perception, and willingness to linger. We develop a three-step interpretable assessment, as follows: Elastic Net logistic regression to establish directional and magnitude baselines; Generalized Additive Models with a logistic link to recover nonlinear patterns and threshold bands with Benjamini–Hochberg false discovery rate control and binned probability calibration; and Shapley additive explanations to provide parallel validation and global and local explanations. The results show that the Green View Index is consistently and positively associated with all five outcomes, whereas Spatial Balance is negative across the observed range. Sky View Factor and the Building Visibility Index display heterogeneous forms, including monotonic, U-shaped, and inverted-U patterns across outcomes; Normalized Difference Vegetation Index and Land Surface Temperature are likewise predominantly nonlinear with peak sensitivity in the midrange. In total, 54 of 55 smoothing terms remain significant after Benjamini–Hochberg false discovery rate correction. The summer heat perception outcome is highly imbalanced: 94.2% of samples are labeled positive. Overall calibration is good. On a standardized scale, we delineate optimal and risk intervals for key indicators and demonstrate the complementary explanatory value of street-view imagery and remote sensing imagery for people-centered perceptions. In Tianjin, a temperate monsoon megacity, the framework provides reproducible, actionable, design-relevant evidence to inform streetscape optimization and offers a template that can be adapted to other cities, subject to local calibration. Full article

Food allergies in school-aged children are a growing public health concern, requiring coordinated strategies to ensure safety in educational settings. This study aimed to evaluate the safety conditions for children and young people with food allergies in public schools of the municipality of Matosinhos, Portugal. A descriptive, cross-sectional, quantitative study was conducted during the 2022/2023 academic year, targeting coordinating teachers from all public schools. Data were collected using a structured questionnaire based on national guidelines for managing food allergies in schools. Results revealed significant gaps in preparedness: 35.99% of respondents reported the absence of a formal document on food allergies, 66.01% indicated no school training plan on the topic, and bar and canteen staff were often excluded from training (50.00% and 42.00%, respectively). Furthermore, 83.02% stated that preventive measures were not consistently adopted, and 49.99% felt insufficiently trained to act in emergencies. Based on these findings, an intervention project with tailored training sessions for coordinating teachers was proposed to improve safety and inclusion for students with food allergies. The study highlights the urgent need for standardized protocols, inclusive training, and preventive measures in schools to mitigate risks and foster a safe learning environment for children with food allergies. Full article

This study conducted an intensive air quality model evaluation as a response to the urgent need to understand the reliability, consistency, and uncertainty of air quality models supporting the implementation of the PM_2.5 Air Pollution Control Action Plan in China. Five regional air quality models of CMAQ version 5.02, CMAQ version 5.3.2, CAMx version 6.2, CAMx version 7.1, and NAQPMS have been evaluated for the CO, SO₂, NO₂, O₃, PM₁₀, and PM_2.5 concentration and components. A unified statistical method and the same observational data set of 2017, comprising 17 air pollution episodes collected from four super monitoring stations in the regions of Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing in China, have been used for the evaluation. All the participating models performed well in simulating the mean PM_2.5 concentrations, with an NMB ranging from −0.29 to −0.04, showing that the participating models are basically suitable for simulation and as evaluation tools for PM_2.5 in regulatory applications. However, the participating models showed a great variability for PM_2.5 components, with the NME ranging from 0.48 to 0.53. The models performed reasonably well in simulating the mean sulfate, nitrate, BC, and NH₄⁺ concentration in PM_2.5, while they were diversified in simulating the mean OC concentrations. The participating models also consistently performed well in simulating the concentration of NO₂, CO, and O₃. However, the models generally overestimated SO₂ concentrations, and to some extent underestimated PM₁₀ concentrations, which is likely attributable to uncertainties in emission sources and the rapid implementation of strict control policies for SO₂. The evaluation work of this study shows that there remains significant potential for further enhancement. Updating and improving the emission inventory should be prioritized to achieve better results, and further investigations into the uncertainties associated with the meteorological simulations, chemical mechanisms, and physical parameterization options of air quality models should also be conducted in future work. Full article

The objective of this study is to explore the applicability of irregular area cartograms for the visualization of sustainable development indicator components, utilizing earth observation (EO) data. The analysis focuses on selected Sustainable Development Goals (SDG 11 ‘Make cities and human settlements inclusive, safe, resilient and sustainable’ and SDG 13 ‘Take urgent action to combat climate change and its impacts’) and specific targets and indicators related to green urban areas and air quality (targets: 13.2, 11.6, and 11.7; indicators: 11.6.2., 11.7.1., 13.2.2.). A comprehensive review of the relevant literature indicates that irregular area cartograms are employed only sporadically in the context of SDG monitoring, particularly at lower levels of territorial division (i.e., communes and counties). To address this gap, a series of thematic maps, including choropleth maps and irregular area cartograms, was developed. These visualizations are based on EO-derived datasets and supplemented with statistical information obtained from the Local Data Bank of the Statistics Poland. The analysis demonstrates that irregular area cartograms provide an effective means of visualizing spatial disparities in variables such as urban green space availability and air pollution at the commune and county levels. These visualizations enhance the interpretability of complex indicator structures and support more nuanced assessments of progress toward selected Sustainable Development Goals, especially in spatially detailed analytical frameworks. Preliminary usability testing among potential users revealed that irregular area cartograms are perceived as an interesting visualization technique that enhances data interpretation. Full article

Maize lodging poses a significant challenge to agricultural production, severely constraining yield improvement and mechanized harvesting efficiency. Under modern agricultural practices characterized by high-density planting and multi-variety intercropping, there is an urgent need for precise and efficient monitoring technologies to address lodging issues. This study utilized unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) to acquire high-precision point cloud data of field maize at full maturity. An innovative method was proposed to automatically identify structural differences induced by lodging by analyzing canopy structural similarity across multiple height thresholds through point cloud stratification. This approach enables automated monitoring of maize lodging in complex field environments. The experimental results demonstrate the following: (1) High-precision point cloud data effectively capture canopy structural differences caused by lodging. Based on the structural similarity change curve, the height threshold for lodging can be automatically identified (optimal threshold: 1.76 m), with a deviation of only 2.3% between the calculated lodging area and the manually measured reference (ground truth). (2) Sensitivity analysis of the height threshold shows that when the threshold fluctuates within a ±5 cm range (1.71–1.81 m), the calculation deviation of the lodging area remains below 10% (maximum deviation = 8.2%), indicating strong robustness of the automatically selected threshold. (3) Although UAV flight altitude influences point cloud quality (e.g., low altitude: 25 m, high altitude: 80 m), the height threshold derived from low-altitude flights can be extrapolated to high-altitude monitoring to some extent. In this study, the resulting deviation in lodging area calculation was only 5.3%. Full article

Background: The maritime industry, vital for global trade, faces escalating cyber threats in 2025. Critical port infrastructures are increasingly vulnerable due to rapid digitalization and the integration of IT and operational technology (OT) systems. Methods: Using 112 incidents from the Maritime Cyber Attack Database (MCAD, 2020–2025), we developed a novel quantitative risk assessment model based on a Threat-Vulnerability-Impact (T-V-I) framework, calibrated with MITRE ATT&CK techniques and validated against historical incidents. Results: Our analysis reveals a 150% rise in incidents, with OT compromise identified as the paramount threat (98/100 risk score). Ports in Poland and Taiwan face the highest immediate risk (95/100), while the Panama Canal is assessed as the most probable next target (90/100). State-sponsored actors from Russia, China, and Iran are responsible for most high-impact attacks. Conclusions: This research provides a validated, data-driven framework for prioritizing defensive resources. Our findings underscore the urgent need for engineering-grade solutions, including network segmentation, zero-trust architectures, and proactive threat intelligence integration to enhance maritime cyber resilience against evolving threats. Full article

The building sector represents a major source of global carbon emissions, with heating and cooling systems being particularly critical contributors, making the evaluation of sustainable low-carbon alternatives an urgent priority. In this study, life cycle assessment (LCA) methodology is used to analyze ground source heat pump (GSHP) systems against traditional heating, ventilation, and air conditioning (HVAC) systems based on project data from the city of Jinan and electrical grid characteristics of Northern China. It is specified that the functional unit is providing heating and cooling that maintains the indoor temperature of the building between 18 °C and 26 °C for 20 years. Following ISO 14040 standards, carbon emissions and economic performance across four phases—production, transportation, construction, and operation—over a 20-year life cycle were quantified using actual material inventory data and region-specific carbon emissions factors. The results demonstrate obvious environmental advantages for GSHP systems, which achieve a 51% reduction in life cycle carbon emissions compared to traditional systems based on the current power generation structure. Furthermore, sensitivity analysis shows that as the proportion of renewable energy in the grid increases to meet carbon neutrality targets, the reduction potential can even reach 88%. Economic analysis reveals that despite higher initial investments, GSHP systems achieve favorable performance with a positive 20-year net present value and an acceptable dynamic payback period for the project. This study shows that GSHP systems represent a viable strategy for sustainable building design in northern China, and the substantial carbon reduction potential can be further enhanced through grid decarbonization and renewable energy integration. The implementation of the GSHP system in newly constructed buildings, which require both heating and cooling, in Northern China, can be an effective strategy for advancing carbon neutrality goals. Full article

Telecommunication infrastructures rely on cryptographic protocols designed for long-term confidentiality, yet data exchanged today faces future exposure when adversaries acquire quantum or large-scale computational capabilities. This harvest-now, decrypt-later (HNDL) threat transforms persistent communication records into time-dependent vulnerabilities. We model HNDL as a temporal cybersecurity risk, formalizing the adversarial process of deferred decryption and quantifying its impact across sectors with varying confidentiality requirements. Our framework evaluates how delayed post-quantum cryptography (PQC) migration amplifies exposure and how hybrid key exchange and forward-secure mechanisms mitigate it. Results show that high-retention sectors such as satellite and health networks face exposure windows extending decades under delayed PQC adoption, while hybrid and forward-secure approaches reduce this risk horizon by over two-thirds. We demonstrate that temporal exposure is a measurable function of data longevity and migration readiness, introducing a network-centric model linking quantum vulnerability to communication performance and governance. Our findings underscore the urgent need for crypto-agile infrastructures that maintain confidentiality as a continuous assurance process throughout the quantum transition. Full article

The heating and cooling sector accounts for nearly half of Europe’s energy consumption and remains heavily dependent on fossil fuels, emphasizing the urgent need for decarbonization. Simultaneously, the global shift toward renewable energy is accelerating, alongside growing interest in decentralized energy systems where prosumers play a significant role. In this context, district heating and cooling networks, serving nearly 100 million people, are strategically important. In next-generation systems, thermal prosumers can feed-in locally produced or industrial waste heat into the network via bidirectional substations, allowing energy flows in both directions and enhancing system efficiency. The complexity of these networks, with numerous users and interacting heat flows, requires advanced predictive models to manage large volumes of data and multiple variables. This work presents the development of a predictive model based on artificial neural networks (ANNs) for forecasting excess thermal renewable energy from a bidirectional substation. The numerical model of a substation prototype designed by ENEA provided the physical data for the ANN training. Thirteen years of simulation results, combined with extensive meteorological data from ECMWF, were used to train and to test a multi-step ANN capable of forecasting the six-hour thermal power feed-in horizon using data from the preceding 24 h, improving operational planning and control strategies. The ANN model demonstrates high predictive capability and robustness in replicating thermal power dynamics. Accuracy remains high for horizons up to six hours, with MAE ranging from 279 W to 1196 W, RMSE from 662 W to 3096 W, and R² from 0.992 to 0.823. Overall, the ANN satisfactorily reproduces the behavior of the bidirectional substation even over extended forecasting horizons. Full article

Access to nature is fundamental to human health and wellbeing, yet opportunities for direct and frequent engagement with natural environments are often restricted for individuals in the 80+ age category, particularly those in care settings or living in remote locations. There is therefore an urgent need to enhance nature connections in care settings and provide personalised, restorative experiences that reflect individuals preferred natural features. This prefeasibility pilot study developed a framework to inform the design of therapeutic care settings, grounded in the principles of biophilic neuroarchitecture and designed to support ageing well. Conducted over six months in two care environments, the study applied the biophilic pattern of Complexity and Order to simulate Natural Analogues within immersive virtual settings. Mixed methods combining wearable sensor data and self-reported wellbeing measures were used to assess psychophysiological, emotional, and cognitive responses among participants aged 80 and above. Findings revealed that VR content aligned with individual nature preferences elicited higher levels of engagement, relaxation, and positive affect. This study demonstrates the potential for implementing biophilic design applications to develop therapeutic care settings which promote wellbeing and healthy ageing, particularly where access to real nature is infrequent or limited. Full article

During catheter interventional procedures, the catheter inevitably encounters the vessel wall. When the push–pull force at the catheter–vessel wall interface exceeds a certain threshold, it may cause vascular damage. The mechanical feedback at the catheter–blood interface are still areas that urgently need to be addressed. This study provides essential experimental data and mechanical feedback to inform and validate such simulations. Therefore, this article first analyzed the movement form and mechanical state of the catheter and blood vessel during vascular interventional surgery. Based on this, this paper analyzes the movement forms and mechanical states of the catheter and blood vessels during intervention, focusing on the contact force between the catheter and blood vessels. The results of the three-point bending test indicate that the bending deformation force of the tube increases as the radius decreases, and the overall deformation progresses from elastic deformation to the yield limit. The normal force of the tube on the lumen and the average push–pull force at the end of the tube are all positively correlated with the moving speed and bending degree of the tube. Statistical analysis revealed that the degree of lumen curvature had a significantly greater influence on the push–pull force than catheter motion speed. The above research provides guidance for friction at the medical device–vessel interface and coating design. Full article