Search Results (16)

The preparation of platelet-rich plasma (PRP) requires precise density-based centrifugation of anticoagulated whole blood to achieve an optimal hematologic bioformulation while enhancing platelet recovery efficiency. Commercial PRP systems exhibit substantial heterogeneity in processing architecture, with variable platelet yields and inconsistent cellular composition profiles. In this clinical PRP device evaluation, 70 sequential samples sourced from two independent clinical facilities were used to evaluate the performance characteristics of the XCELL 60 mL single-spin centrifugation platform. Two different PRP preparations were consistently prepared as per physician preferences: PRP-1 and PRP-2. The main differences between these two preparations were the concentration of leukocytes and reduction in red blood cells. The system was evaluated based on critical PRP performance metrics. The results demonstrated the following: (1) A consistent 8-fold increase in platelet concentration relative to baseline whole blood was achieved. (2) The average platelet capture rate (PCR) was 83%. (3) The total available platelets (TAPs) in the PRP specimen produced from both groups combined were 10.8 ± 2595 billion platelets within a final product volume of 6 mL. (4) Hematocrit values were reduced to <2–6% across sites (reduction of 94% and 84% in RBCs, respectively). Finally, (5) a customizable leukocyte content (20.9–25.4 × 10⁹/L) was achieved without comprising platelet yield. This single-spin centrifugation architecture achieved performance parity with historically preferred double-spin systems while reducing the processing time and number of preparation steps. Engineering analysis established that high-precision platelet recovery and bioformulation control are achievable through optimized single-spin centrifugal design, enabling standardized therapeutic dosing for autologous regenerative medicine applications. Full article

Community water systems in the United States provide drinking water to more than 300 million people annually, making their reliability fundamental to public health. In regions with long histories of racial segregation and unequal infrastructure maintenance, water system failures can deepen existing environmental injustices. This study examines water quality conditions in the Jackson, Mississippi, metropolitan area following the 2022 distribution system collapse and a decade of repeated noncompliance with the Safe Drinking Water Act’s Lead and Copper Rule (LCR). Using the U.S. Environmental Protection Agency’s 2024 updated LCR tap sampling protocol, water samples from 29 sites were collected. Samples were analyzed for lead, copper, iron, zinc, chlorine, sulfate, pH, and total dissolved solids concentrations. Chlorine-to-sulfate mass ratios (CSMR) were also calculated to evaluate corrosion potential. Demographic surveys, statistical analyses, and geospatial visualizations were used to interpret neighborhood-level patterns. Our findings show that all sites met primary drinking water standards and complied with LCR action levels but exceeded secondary drinking water standards at 100% of study sites. Seven sites exhibited CSMR values above the threshold, indicating increased susceptibility to corrosion. These results highlight the need for targeted corrosion control, treatment optimization, and ongoing monitoring, particularly in historically marginalized communities. Full article

Under the background of “dual-carbon”, the development of energy internet is an inevitable trend for China’s low-carbon energy transition. This paper proposes a hydrogen-coupled electrothermal integrated energy system (HCEH-IES) operation mode and optimizes the source-side structure of the system from the level of carbon trading policy combined with low-carbon technology, taps the carbon reduction potential, and improves the renewable energy consumption rate and system decarbonization level; in addition, for the operation optimization problem of this electric–gas–heat integrated energy system, a flexible energy system based on electric–gas–heat is proposed. Furthermore, to address the operation optimization problem of the HCEH-IES, a deep reinforcement learning method based on Soft Actor–Critic (SAC) is proposed. This method can adaptively learn control strategies through interactions between the intelligent agent and the energy system, enabling continuous action control of the multi-energy flow system while solving the uncertainties associated with source-load fluctuations from wind power, photovoltaics, and multi-energy loads. Finally, historical data are used to train the intelligent body and compare the scheduling strategies obtained by SAC and DDPG algorithms. The results show that the SAC-based algorithm has better economics, is close to the CPLEX day-ahead optimal scheduling method, and is more suitable for solving the dynamic optimal scheduling problem of integrated energy systems in real scenarios. Full article

Power transformers are critical components in electrical power systems, where failures can cause significant outages and economic losses. Traditional maintenance strategies, typically based on offline inspections, are increasingly insufficient to meet the reliability requirements of modern digital substations. This work presents an integrated multi-sensor monitoring framework that combines online frequency response analysis (OnFRA^® 4.0), capacitive tap-based monitoring (FRACTIVE^® 4.0), dissolved gas analysis, and temperature measurements. All data streams are synchronized and managed within a SCADA system that supports real-time visualization and historical traceability. To enable automated fault diagnosis, a Random Forest classifier was trained using simulated datasets derived from laboratory experiments that emulate typical transformer and bushing degradation scenarios. Principal Component Analysis was employed for dimensionality reduction, improving model interpretability and computational efficiency. The proposed model achieved perfect classification metrics on the simulated data, demonstrating the feasibility of combining high-fidelity monitoring hardware with machine learning techniques for anomaly detection. Although no in-service failures have been recorded to date, the monitoring infrastructure is already tested and validated through laboratory conditions, enabling continuous data acquisition. Full article

Accurate estimation of passenger origin–destination (OD) matrices is critical for optimizing public transportation systems, yet conventional methods face challenges, such as incomplete alighting data, high infrastructure costs, and privacy concerns. With existing GPS sensors and the additional deployment of a single low-cost Bluetooth sensor (10–20 US dollars) per bus, the proposed method can derive passenger OD flow without requiring passengers to tap in or tap out. The GPS sensor updates the bus locations, and the Bluetooth sensor receives signals from surrounding devices, including those onboard devices and nearby external devices. A Fuzzy C-Means clustering algorithm was employed to differentiate passenger and non-passenger devices based on detected indicators, such as detection frequency, signal strength, vehicular mobility, etc. Validation on Shanghai’s Fengpu BRT line demonstrated 91.22–96.02% accuracy in boarding proportion estimation and 95.18–95.52% for alighting during peak hours. Compared to the historical data-based method, the proposed method achieved higher similarity to ground truth and reduced the mean squared error by 12.89–69.95%. Full article

The traditional villages in the Miao Frontier Corridor are the products of migrations, social interactions, and transportation, as well as production interchanges between the central plains and the frontiers of China in ancient times. They have made significant contributions to local multicultural inheritance and regional social development. However, with the increasing pressure of heritage conservation and sustainable development, there is growing attention on how traditional villages can tap into their cultural continuity and distinctiveness. This study introduces the concept of cultural routes, with the aim of integrating traditional villages of different ethnicities, regions, and characteristics from the perspective of diversity. It analyzes their spatial differentiation characteristics and the factors influencing them, providing basic support for the overall protection of traditional villages with special characteristics. Following this idea, 338 remaining traditional villages in the Miao Frontier Corridor were selected as the research objects. With the help of 91-satellite maps and a geographic information system (GIS), a cultural and geographic database of the traditional villages in the Miao Frontier Corridor was constructed to objectively explore the roles of the traditional villages’ natural geography, historical, and humanistic elements in the spatial categorization on a large scale. This study shows that the spatial distribution of the traditional villages in the Miao Frontier Corridor is uneven, exhibiting a cluster structure with of a “single primary nucleus with multiple secondary nuclei”. The spatial differentiation of traditional villages exhibits a similar clustering pattern based on individual natural geographic factors, such as elevation, mountain undulation, slope, and water systems. Additionally, there is discernible regularity concerning historical and humanistic factors, such as ethnicity type, age of village establishment, and the presence of guard stations. Further exploring the micro-spatial level, the natural geographical environment serves as the structural foundation of traditional village space, while the historical and humanistic environment fosters multiple differentiations in traditional village space in terms of influencing factors. Together, these factors jointly influence the spatial differentiation of traditional villages. This study enriches the dynamic aspects of linear cultural heritage preservation and also provides new insights into the specialized development within the overall protection of traditional villages. Full article

In contrast to “frank” pathogens, like Salmonella entrocolitica, Shigella dysenteriae, and Vibrio cholerae, that always have a probability of disease, “opportunistic” pathogens are organisms that cause an infectious disease in a host with a weakened immune system and rarely in a healthy host. Historically, drinking water treatment has focused on control of frank pathogens, particularly those from human or animal sources (like Giardia lamblia, Cryptosporidium parvum, or Hepatitis A virus), but in recent years outbreaks from drinking water have increasingly been due to opportunistic pathogens. Characteristics of opportunistic pathogens that make them problematic for water treatment include: (1) they are normally present in aquatic environments, (2) they grow in biofilms that protect the bacteria from disinfectants, and (3) under appropriate conditions in drinking water systems (e.g., warm water, stagnation, low disinfectant levels, etc.), these bacteria can amplify to levels that can pose a public health risk. The three most common opportunistic pathogens in drinking water systems are Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa. This report focuses on these organisms to provide information on their public health risk, occurrence in drinking water systems, susceptibility to various disinfectants, and other operational practices (like flushing and cleaning of pipes and storage tanks). In addition, information is provided on a group of nine other opportunistic pathogens that are less commonly found in drinking water systems, including Aeromonas hydrophila, Klebsiella pneumoniae, Serratia marcescens, Burkholderia pseudomallei, Acinetobacter baumannii, Stenotrophomonas maltophilia, Arcobacter butzleri, and several free-living amoebae including Naegleria fowleri and species of Acanthamoeba. The public health risk for these microbes in drinking water is still unclear, but in most cases, efforts to manage Legionella, mycobacteria, and Pseudomonas risks will also be effective for these other opportunistic pathogens. The approach to managing opportunistic pathogens in drinking water supplies focuses on controlling the growth of these organisms. Many of these microbes are normal inhabitants in biofilms in water, so the attention is less on eliminating these organisms from entering the system and more on managing their occurrence and concentrations in the pipe network. With anticipated warming trends associated with climate change, the factors that drive the growth of opportunistic pathogens in drinking water systems will likely increase. It is important, therefore, to evaluate treatment barriers and management activities for control of opportunistic pathogen risks. Controls for primary treatment, particularly for turbidity management and disinfection, should be reviewed to ensure adequacy for opportunistic pathogen control. However, the major focus for the utility’s opportunistic pathogen risk reduction plan is the management of biological activity and biofilms in the distribution system. Factors that influence the growth of microbes (primarily in biofilms) in the distribution system include, temperature, disinfectant type and concentration, nutrient levels (measured as AOC or BDOC), stagnation, flushing of pipes and cleaning of storage tank sediments, and corrosion control. Pressure management and distribution system integrity are also important to the microbial quality of water but are related more to the intrusion of contaminants into the distribution system rather than directly related to microbial growth. Summarizing the identified risk from drinking water, the availability and quality of disinfection data for treatment, and guidelines or standards for control showed that adequate information is best available for management of L. pneumophila. For L. pneumophila, the risk for this organism has been clearly established from drinking water, cases have increased worldwide, and it is one of the most identified causes of drinking water outbreaks. Water management best practices (e.g., maintenance of a disinfectant residual throughout the distribution system, flushing and cleaning of sediments in pipelines and storage tanks, among others) have been shown to be effective for control of L. pneumophila in water supplies. In addition, there are well documented management guidelines available for the control of the organism in drinking water distribution systems. By comparison, management of risks for Mycobacteria from water are less clear than for L. pneumophila. Treatment of M. avium is difficult due to its resistance to disinfection, the tendency to form clumps, and attachment to surfaces in biofilms. Additionally, there are no guidelines for management of M. avium in drinking water, and one risk assessment study suggested a low risk of infection. The role of tap water in the transmission of the other opportunistic pathogens is less clear and, in many cases, actions to manage L. pneumophila (e.g., maintenance of a disinfectant residual, flushing, cleaning of storage tanks, etc.) will also be beneficial in helping to manage these organisms as well. Full article

Smart water tap (SWT) time series model development for failure prediction requires acquiring data on the variables of interest to researchers, planners, engineers and decision makers. Thus, the data are expected to be ‘noiseless’ (i.e., without discrepancies such as missing data, data redundancy and data duplication) raw inputs for modelling and forecasting tasks. However, historical datasets acquired from the SWTs contain data discrepancies that require preparation before applying the dataset to develop a failure prediction model. This paper presents a combination of the generative adversarial network (GAN) and the bidirectional gated recurrent unit (BiGRU) techniques for missing data imputation. The GAN aids in training the SWT data trend and distribution, enabling the imputed data to be closely similar to the historical dataset. On the other hand, the BiGRU was adopted to save computational time by combining the model’s cell state and hidden state during data imputation. After data imputation there were outliers, and the exponential smoothing method was used to balance the data. The result shows that this method can be applied in time series systems to correct missing values in a dataset, thereby mitigating data noise that can lead to a biased failure prediction model. Furthermore, when evaluated using different sets of historical SWT data, the method proved reliable for missing data imputation and achieved better training time than the traditional data imputation method. Full article

Automated fare collection (AFC) systems can provide tap-in and tap-out records of passengers, allowing us to conduct a comprehensive analysis of spatiotemporal patterns for urban mobility. These temporal and spatial patterns, especially those observed over long periods, provide a better understanding of urban transportation planning and community historical development. In this paper, we explored spatiotemporal evolution of travel patterns using the smart card data of subway traveling from 2011 to 2017 in Shenzhen. To this end, a Gaussian mixture model with expectation–maximization (EM) algorithm clusters the travel patterns according to the frequency characteristics of passengers’ trips. In particular, we proposed the Pareto principle to negotiate diversified evaluation criteria on model parameters. Seven typical travel patterns are obtained using the proposed algorithm. Our findings highlighted that the proportion of each pattern remains relatively stable from 2011 to 2017, but the regular commuting passengers play an increasingly important position in the passenger flow. Additionally, focusing on the busiest commuting passengers, we depicted the spatial variations over years and identified the characters in different periods. Their cross-year usage of smart cards was finally examined to understand the migration of travel patterns over years. With reference to these methods and insights, transportation planners and policymakers can intuitively understand the historical variations of passengers’ travel patterns, which lays the foundation for improving the service of the subway system. Full article

The mine–agriculture–urban compound area formed under the combined effects of natural conditions, mineral resource endowments, and historical development is affected by severe man-made disturbances, and faces a prominent contradiction between economic development and ecological protection. Guiding the future development is an urgent problem in this region. This research used image data, logical reasoning, and empirical analysis, based on social and economic statistics and land-use data, to analyze the typical characteristics and problems of the social–ecological system in the mine–agriculture–urban compound area. Moreover, we identified future directions for the region guided by policy documents and built a philosophy framework for sustainable development and management of the region based on the concept of adaptability. The results showed the following: (1) At present, the output value of the coal industry accounts for 84.10% of the total regional output value, severely disturbing its social–ecological system, which needs to be protected and restored under human guidance and management. (2) The future development of this region depends on the one hand on green mining, and on the other hand, it is necessary to fully tap the potential of arable land and livestock farms to develop efficient and intensive agriculture. (3) The key contents of the social–ecological system management of the mine–agriculture–urban compound area include resolving the contradiction between development and protection, ensuring development, optimizing industrial structure, and safeguarding public interests. In conclusion, this research can expand the connotation and application scope of adaptive management and provide a reference for such areas facing the prominent contradiction between development and protection. Full article

Forests are intrinsically coupled to human dynamics, both temporally and spatially. This evolution is conditioned by global changes in climatic conditions (teleconnections) and distant socio-economical processes (telecoupling). The main goal of this study is to describe the teleconnections and telecoupling dynamics that have shaped structure and processes in a dry-edge—highly vulnerable to desertification—Mediterranean pine forest during the last century and to evaluate the contribution of historical management strategies to this coupled human and natural system’s (CHANS) overall resilience. For this study, we collected relevant human and natural system data from a dry edge Pinus pinaster Ait. located forest in Central Spain using a CHANS analytical framework operationalizing telecoupling and teleconnection. A key extractive economic activity in the studied forest was resin tapping, which was the main form of land use from the 1920s to the 1950s. Since the 1950s changes in the Spanish economy linked to the emergence of new resin-producing countries, such as China, led to a sharp decline in resin production. Despite additional human system transformations affecting forest governance (e.g., the Spanish Civil War, the transition to democracy, European integration, etc.) and changes in biophysical conditions linked to climate change (e.g., aridification, CO₂ fertilization), the standing stocks of P. pinaster increased during the monitoring period due to sound technical and management planning bolstering overall resilience. These historical management decisions, we argue, successfully reconciled overall resilience goals (defined as the maintenance of forest function beyond and desertification avoidance) with three successive historical forest use challenges: intensive firewood collection by local communities in fragile sandy soils, extensive pastoralism in the forest understory and tradeoffs between resin tapping damaged trees, timber production and tree cover as well as the emerging risks of wildfire and climate change. Full article

The hilly landscape of the Periadric area in Central Italy is characterized by mainly marly–clayey foredeep basin deposits (Plio–Pleistocene age). These lithotypes are generally considered aquicludes, if compared with the regional limestone aquifers of Apennines. However, a coarsening upward trend characterizes the upper portion of this stratigraphic sequence, with arenaceous deposits and even conglomerates on the top. From a geomorphological viewpoint, the areas with coarser outcrops show a flat shape and sub-vertical slopes, like boundaries. At the base of these scarps, springs can be found at the interface between coarse and fine deposits, whereas these arenaceous bodies are actual aquifers. Until now, the hydrodynamics and hydrochemical features of this kind of aquifer have not been investigated deeply, because they have always been considered a worthy water resource. However, they could play a crucial role in integrated water management, especially to cope with climate changes and drought periods. Considering these, the main purpose of this study was to investigate from a hydrogeological point of view and to assess the groundwater quantity and quality. Five examples throughout the Abruzzo region were considered. For evaluation and comparisons between water resources, the water volume that infiltrates yearly at each squared kilometer of an aquifer (Mm³/y/km²) was applied. This value was calculated through three different approaches to provide a recharge estimation for this kind of aquifer that is as exhaustive and representative as possible. The results allowed us to characterize the hydrogeological model and to quantify the resources between 0.1 and 0.16 Mm³/y/km², to be suitable for multi–purpose utilization. Full article

The paper’s main aim is to assess the measures implemented within the Rural Development Program (RDP) 2007–2013 in Poland. This programme is dedicated to the diversification of business activities in rural areas and rural livelihood and, thus, the improvement of the multifunctionality of rural areas. The analysis covered two measures from Axis 3, Improvement of the quality of life in rural areas and diversification of rural economy: M311, diversification into non-agricultural activities; and M312, Establishment and development of micro-enterprise. The study and the discussion are presented from a geographical perspective and, in a broader context, take into account several conditions (natural, urban, agricultural and historical) and the spatial diversity of the allocation of European Union (EU) funds. Models of a policy of multifunctional rural development, implemented after accession to the EU, are presented. The research’s spatial scope covers Poland’s territory on two spatial scales: the system of regions (16 NUTS2 units) and poviats (314 LAU level 1 units). The analysis covers all the projects implemented in Poland under the two measures of Axis 3 of the RDP 2007–2013. A set of conditions was prepared for all LAU1 units, forming the background for assessing the impact of the EU funds on the development of non-agricultural activities. To determine the relationship between the RDP measures and the selected groups of conditions, a synthetic index and a correlation index are used. They are also used to determine the mutual relations between the two analyzed activities in terms of the spatial scales used. Access to the EU funds (RDP) has considerably enlarged the opportunities for accelerating agricultural modernisation and restructuration towards multifunctional development, as well as the opportunities for implementing new development and work methods in the countryside in Poland. The attractiveness of the two studied RDP measures varied across regions. The beneficiaries’ activity depended on the local potential (resources), culture and tradition of the region, and size and potential of the farm. In the areas where agriculture is deeply rooted, beneficiaries were more willing to engage in ventures tapping into the resources available in their farms. Thus, they create additional livelihood of income and workplaces for household members. In turn, the beneficiaries from the areas where farms are smaller and economically weaker often undertake activities related to setting up a new business (outside farming). Full article

Restoring the health of degraded land is critical for overall human development as land is a vital life-supporting system, directly or indirectly influencing the attainment of the UN Sustainable Development Goals (UN-SDGs). However, more than 33% of the global land is degraded and thereby affecting the livelihood of billions of people worldwide. Realizing this fact, the 73rd session of the UN Assembly has formally adopted a resolution to celebrate 2021–2030 as the UN Decade on Ecosystem Restoration (UN-DER), for preventing, halting, and reversing degradation of ecosystems worldwide. While this move is historic and beneficial for both people and the planet, restoration of degraded land at different scales and levels requires a paradigm shift in existing restoration approaches, fueled by the application of applied science to citizen/community-based science, and tapping of indigenous and local knowledge to advanced technological breakthroughs. In addition, there is a need of strong political will and positive behavioral changes to strengthen restoration initiatives at the grassroot level and involvement of people from all walks of life (i.e., from politicians to peasants and social workers to scientists) are essential for achieving the targets of the UN-DER. Similarly, financing restoration on the ground by the collective contribution of individuals (crowd funding) and institutions (institutional funding) are critical for maintaining the momentum. Private companies can earmark lion-share of their corporate social responsibility fund (CSR fund) exclusively for restoration. The adoption of suitable bioeconomy models is crucial for maintaining the perpetuity of the restoration by exploring co-benefits, and also for ensuring stakeholder involvements during and after the restoration. This review underpins various challenges and plausible solutions to avoid, reduce, and reverse global land degradation as envisioned during the UN-DER, while fulfilling the objectives of other ongoing initiatives like the Bonn Challenge and the UN-SDGs. Full article

Coliform source tracking was undertaken on 48 water sources of which 42 are potable in 26 water supply systems spread across South Australia. The water sources in the study vary from unprotected springs in creek beds to deep confined aquifers. The frequency analysis of historical coliform detections indicate that aquifer types, depth to water and casing depth are important considerations; whilst maintaining well integrity and the presence of low permeable clay layers above the production zone are the dominant parameters for minimizing coliform contamination of water supply wells. However, in karst and fractured rock aquifers, pathways for coliform transport exist, as evidenced in the >200 MPN/100 mL level of coliform detection. Data indicate that there is no compelling evidence to support the contention that the wells identified as low risk are contaminated through geological strata and clay barriers. However, data strongly supports the suggestion that coliform detection from sample taps and wellheads stem from the surrounding groundwater and soil-plant sources as a result of failed well integrity, or potentially from coliform bacteria that can persist within biofilms formed on well casings, screens, pump columns and pumps. Coliform sub-typing results show that most coliform bacteria detected in town water supply wells are associated with the soil-water-plant system and are ubiquitous in the environment: Citrobacter spp. (65%), Enterobacter spp. (63%), Pantoea spp. (17%), Serratia spp. (19%), Klebsiella spp. (34%), and Pseudomonas spp. (10%). Overall, 70% of wells harbor detectable thermotolerant coliforms (TTC) with potentially 36% of species of animal origin, including Escherichia coli species found in 12% of wells. Full article