Search Results (340)

To address peak edge operation and excessive valve switching in hydraulically coupled multi-zone campus irrigation, this study proposes a collaborative scheduling framework that combines short-term evapotranspiration (ET) forecasting with safety-constrained reinforcement learning. Temperature, relative humidity, and light intensity are used to construct vapor pressure deficit and radiation proxy features, and a lightweight predictor provides two-hour-ahead ET statistics as forward-looking disturbance information. A safety layer composed of Top-2 gating and total flow projection is then used to map policy outputs into a feasible action space under parallel irrigation and total flow constraints. Using seven consecutive days of field data from October 2025, the proposed method reduced total water consumption to 131.04 m³, corresponding to reductions of 9.13% and 6.12% relative to fixed-schedule and hysteresis threshold rotational irrigation, respectively. It also reduced the maximum total flow from 2.00 to 1.60 L/s, lowered valve switching cycles to 12, and reduced the border ratios at 0.90 and 0.95 to 0. Additional ablation, sensing noise/packet loss, and Top-K extension experiments further showed that ET forecasting improves anticipatory scheduling, whereas safety projection is essential for zero-violation operation. These results demonstrate that the proposed framework provides a practical and deployable solution for safe and water-efficient multi-zone irrigation scheduling under shared pump constraints. Full article

This paper proposes a non-overlapping planar cross-arranged ultra-wideband shared-aperture base station antenna array targeting the 2 to 6 GHz application bandwidth. The low-frequency module (double-layer parasitic coupling) and the high-frequency module (chamfered slotted patch) are independently designed, and metal baffles are introduced around the antenna elements to reshape the boundary conditions and physically block the electromagnetic coupling paths. Both simulation and experimental results demonstrate that the fabricated prototype successfully exceeds the targeted 2–6 GHz spectrum, achieving an actual continuous coverage from 1.84 to 6.3 GHz. Specifically, the antenna achieves a gain higher than 5.9 dBi in the measured low-frequency band (1.84–3.72 GHz) and higher than 6.1 dBi in the high-frequency band (3.63–6.3 GHz), with a voltage standing wave ratio (VSWR) below 2 across the entire band. The metal baffles successfully correct the high-frequency radiation pattern distortion and ensure stable directional radiation over the full operating bandwidth. This design provides an efficient, robust, and manufacturable solution for 5G offshore wind power multi-band base station antennas. Full article

The growing challenge for electricity in South Africa is placing pressure on the country’s current electricity-generating capacity. Moreover, conventional power plants are the main source of high concentrations of greenhouse gases in the country. South Africa is the seventh-largest producer of coal globally, and coal takes the largest share in the generation of electricity, with significant negative environmental impacts. There is insufficient electricity grid infrastructure, which prevents remote areas from receiving electricity from the centralized power grid. South Africa has promise in adopting sustainable energy systems such as biomass, hydropower, wind, and solar energy. The country obtains 2500 h of sunshine per year, and the radiation content is 4–6 kWh/m². Solar and wind have significant potential, while biomass and hydropower have less potential. However, some challenges and limitations that affect the use of RE have been identified. Increasing offshore wind and solar energy will enable South Africa to attain its target of increasing the percentage of renewable energy in the energy mix from 11% to 41% by 2030. The diversification of production and reduction in greenhouse gas emissions require South Africa to actively modernize its transmission infrastructure and speed up the approval process of projects. Full article

Breast-conserving therapy (BCT), consisting of lumpectomy followed by adjuvant radiation, provides oncologic outcomes equivalent to mastectomy for many patients with breast cancer. As survivorship increases, the demand for aesthetic restoration after BCT has grown; however, reconstructive strategies in this setting remain less standardized than those following mastectomy. Reconstruction after BCT presents distinct challenges due to partial tissue loss, nonuniform radiation injury, progressive fibrosis, and wide variability in patient expectations and tolerance for revision surgery. Consequently, mastectomy-based reconstructive algorithms are often insufficient for guiding care in this population. This review synthesizes contemporary reconstructive options following BCT through a personalized medicine framework, emphasizing patient-specific risk factors that influence technique selection, timing, and long-term outcomes. Key determinants include radiation exposure, breast morphology, comorbid conditions, prior breast surgery, and psychosocial preferences. Oncoplastic volume displacement, implant-based augmentation, fat grafting, and autologous reconstruction each demonstrate distinct risk profiles in the post-BCT tissue environment and require individualized application. Timing of reconstruction and willingness to undergo staged procedures play a central role in outcome durability and patient satisfaction. Across reconstructive strategies, revision burden emerges as a clinically meaningful, patient-centered outcome that is not adequately captured by traditional short-term complication metrics. A risk-informed approach that integrates individualized risk assessment with transparent counseling and shared decision-making may improve alignment between reconstructive planning and patient goals. Personalized reconstruction after BCT requires moving beyond technique-driven paradigms toward flexible, longitudinal care pathways. Future efforts should focus on developing BCT-specific predictive models and incorporating patient-reported outcomes to advance personalized reconstructive care. Full article

Aconitum carmichaelii Debeaux has been a traditional medicinal resource in China for over two millennia. However, sustainable utilization and preservation strategies for A. carmichaelii require a thorough understanding of environmental factors influencing its distribution. An optimized MaxEnt model was constructed using the ENMeval package based on 185 quality-controlled occurrence records and 10 selected environmental variables (bioclimatic, edaphic, topographic, and anthropogenic). The optimized model demonstrated reliable predictive accuracy, with an area under curve (AUC) value of 0.896. Soil moisture (37.7% contribution), human footprint (HFP) (23.9%), and July solar radiation (11.1%) were the primary variables determining A. carmichaelii distribution. The suitable thresholds were defined as soil moisture > 87.34 mm, HFP > 10.69, and July solar radiation < 19,125.72 kJ m⁻² day⁻¹. At present, highly suitable habitat covers approximately 8.243 × 10⁵ km², predominantly located in the Sichuan Basin and surrounding regions, including Sichuan, Chongqing, Guizhou, and northeastern Yunnan. Future predictions under all Shared Socioeconomic Pathway (SSP) scenarios indicate a significant reduction in highly suitable habitat, with losses of 63.01% (2041–2060, SSP126), 62.62% (2041–2060, SSP245), 61.35% (2041–2060, SSP370), and 61.99% (2061–2080, SSP585). Habitat contraction mainly occurs toward higher altitudes and southwestern areas, with a maximum displacement distance of 50.56 km under the SSP585 scenario. This study enhances our understanding of environmental factors affecting the distribution of A. carmichaelii and offers guidance for its sustainable management and cultivation amid global climate change. Full article

Variations in terrestrial carbon flux influence atmospheric CO₂ exchange and related climate feedback, with Net ecosystem productivity (NEP) serving as a key metric for assessing ecosystem carbon source–sink dynamics. Given the vital ecological barrier function of the Tibetan Plateau (TP), understanding the spatiotemporal variability of NEP and its climatic controls is essential for elucidating carbon sink and climate interactions under ongoing climate change. The spatiotemporal dynamics of NEP across the TP from 1979 to 2018 are investigated using the process-based Community Land Model version 5.0 (CLM5.0). And climate sensitivity experiments are conducted to quantify the relative contributions of different climate factors to NEP variability. Furthermore, future changes in NEP for the period 2025–2100 under multiple Shared Socioeconomic Pathway (SSP) scenarios are projected. The results indicate that the TP functioned predominantly as a net carbon sink during the historical period, with a multi-year mean NEP of 23.96 g C m² yr⁻¹. Spatially, NEP showed a significantly increasing gradient from the northwest to the southeast. During 1979–2018, NEP exhibited an overall decreasing trend across most regions of the TP. Air temperature was identified as the dominant controlling factor, accounting for approximately 68% of the interannual NEP variability, followed by solar radiation (21%) and precipitation (11%). The dominant climatic drivers of NEP variation differ among regions: air temperature predominates in the southwestern and southeastern regions, radiation dominates in the northwestern and central areas, and precipitation exerts a controlling effect in the northern and western regions. Future projections suggest that NEP remains positive under all SSP scenarios, indicating that the TP is likely to persist as a carbon sink throughout the 21st century. This study provides important reference for the development of ecological protection, restoration planning, and regional carbon neutrality strategies. Full article

Atmospheric aerosols modulate Earth’s radiation balance through direct effects and through their role as cloud condensation nuclei (CCN), contributing to variability in near-surface temperature (NST). Galactic cosmic rays (GCRs) further influence aerosol–cloud interactions by enhancing particle formation and growth, but combined aerosol optical depth (AOD)–GCR effects on NST remain poorly constrained across climates. Using satellite and reanalysis data, we examine joint influences on NST anomalies at three neutron-monitoring stations, Oulu, Newark, and Hermanus, during 2000–2022. The sites share similar geomagnetic cutoffs but contrasting climates, enabling separation of ionization from geomagnetic shielding. Multiple linear regression (MLR) captures AOD effects and their modulation by GCR flux. Adding an interaction term (AOD × GCR) improves fit, raising adjusted R² from 0.22→0.31 (Oulu), 0.37→0.52 (Newark), and 0.69→0.78 (Hermanus). ECMWF reanalysis shows hydrophilic organic matter aerosol (OMA) dominates (0.19, 0.29, 0.41 µg kg⁻¹ at Oulu, Newark and Hermanus), with sulphate elevated at Oulu/Newark and coarse sea salt at Hermanus. Elevated OMA and sulphate at Oulu/Newark imply GCR-enhanced fine CCN and cooling, whereas humid, sea-salt-rich Hermanus favors ion-mediated growth of larger hygroscopic particles that increase longwave trapping and warming. Findings provide site-specific evidence that GCR ionization modulates aerosol processes and contributes to regional NST variability, informing improved parameterizations in climate models. Full article

Background/Objectives: Atypical fibroxanthoma (AFX) and cutaneous undifferentiated pleomorphic sarcoma (cUPS)/pleomorphic dermal sarcoma (PDS) are related dermal neoplasms of uncertain histogenesis that occupy opposite ends of a shared clinical and histopathologic spectrum, with AFX displaying typically low-grade behavior and PDS representing its more aggressive counterpart. The recent literature has confirmed that AFX and PDS also overlap at the molecular and genomic levels; however, little is known about their gene-expression profiles. Methods: We performed gene-expression profiling using RNA sequencing with a Pan-Cancer RNA Panel on a small series of AFX and PDS samples. Results: Unsupervised cluster analysis showed a clear separation between the two groups. We confirmed a TP53 UV-radiation signature in both. However, while AFX and PDS share common DNA mutation profiles in our cohort, RNA sequencing reveals distinct gene-expression signatures that may aid in differentiating these related tumors. In particular, the MAPK pathway, cell adhesion, DNA repair, EMT-like signatures and inflammatory responses play key roles in distinguishing the two groups, at least in our limited cohort, consistent with their differing biological behavior. Differences in the expression of receptor tyrosine kinases were also observed. Conclusions: Gene-expression profiling have the potential to be a valuable tool for distinguishing AFX from PDS, clarifying their positions at opposite ends of a spectrum and providing deeper insight into the biology of these neoplasms. Full article

This article proposes a parallel current-summing LCC multilevel inverter (MLI) to suppress harmonic distortion of radiated EMI for wireless power transfer. Traditionally, ZVS has been an issue for staircase voltage output multilevel inverters because a shared current output became faster than some of the voltage transitions in staircase voltage output. The other common problem was capacitor voltage imbalance and resultant output voltage distortion if a sophisticated voltage balancing function is not used. The proposed LCC MLI ensures ZVS by separating each voltage transition into multiple bridge legs. Each bridge leg outputs different phases of currents for each voltage transition. The individual output currents are summed at the matching network of wireless power transfer, generating a near-sinusoid output current to suppress harmonic distortions. In this way, each leg achieves ZVS even though the summed output current at the LCC network is faster than some of the voltage transitions. To avoid the capacitor voltage imbalance issue, the proposed MLI eliminated the flying capacitor. Instead, the four parallel legs are supplied by a shared DC input link. Therefore, the four legs can output identical voltages without using a typical DC flying capacitor. The necessity of multiple input voltage sources is, therefore, also eliminated. Measurement demonstrates that the proposed method effectively reduces radiated harmonic EMI by up to 14 dB. Full article

This study uses a globally coupled climate framework to examine how regional differences in sulfate emissions, through both direct and indirect aerosol effects, regulate interactions between clouds and radiation and drive nonlinear thermodynamic and hydrological responses in the East Asia and South Asia summer monsoon region. We employ the Community Earth System Model to compare the Shared Socioeconomic Pathways 1–2.6 and 5–8.5 against the historical scenario with perturbations of anthropogenic sulfate. The results reveal regional contrasts in sulfate concentration and aerosol optical depth: direct shortwave radiation increases in East Asia, while South Asia experiences radiation weakening due to higher aerosol optical depth. Indirect aerosol effects induce cloud adjustments, with East Asia developing more low clouds and higher cloud droplet number concentrations and liquid water paths, leading to greater attenuation of surface shortwave radiation and changes in precipitation and convection. Over the Tibetan Plateau, a higher fraction of high clouds and changes in cloud-top heights jointly drive warming, raising net radiation and strengthening both latent-heat and sensible-heat release. South Asia exhibits a north–south oriented precipitation pattern, with intensified warm advection but a distribution shaped by upper and mid-tropospheric circulations. Overall, the coupling of cloud macro-distribution and cloud microphysics emerges as the principal driver, with direct and indirect effects amplifying nonlinear regional responses. To improve predictability, we advocate multi-model comparisons, observational constraints, tighter bounds on cloud-droplet size distributions, liquid water paths, and cloud droplet number concentrations. Full article

Background/Objective: Pediatric trauma frequently prompts computed tomography (CT) in emergency departments; however, the cumulative radiation burden and its distribution across initial clinical risk strata remain incompletely characterized. We aimed to describe CT utilization and cumulative effective dose in a tertiary care pediatric trauma cohort and examine how radiation exposure accrues across pragmatic presentation-based risk groups. Methods: We conducted a retrospective cohort audit of pediatric trauma presentations at our institution. Risk stratification was based on the triage category and readily available initial physiological parameters. CT utilization and radiation burden were assessed at the patient level using the cumulative effective dose (mSv) derived from scanner dose metrics and region-specific conversion coefficients. Secondary analyses examined the dose distribution according to ED disposition and consultation pathways. Sensitivity analyses were performed using green triage only as an “ultra-low-risk” definition. Results: Among the 935 children, 545 (58.3%) underwent at least one CT examination. Although higher-risk categories had higher CT use and higher per-patient dose, a substantial share of the cohort’s cumulative radiation burden accrued in children initially classified as low-risk and/or ultimately discharged. Combined-region CT protocols contributed disproportionately to the higher dose categories. The findings were consistent in sensitivity analyses using a stricter ultra-low-risk definition. Conclusions: In this single-center audit, CT utilization and cumulative radiation burden were high, and non-trivial radiation exposure accrued among children initially classified as low-risk. These findings support targeted radiation stewardship interventions, including pathway optimization and the implementation of validated decision tools, where feasible, particularly for discharge-eligible and low-risk presentations. Full article

Desert–Gobi–wasteland regions possess abundant wind resources and are strategic areas for future renewable energy development and meteorological monitoring. However, existing studies have limited capability in addressing the highly complex and dynamic environmental characteristics of these regions. In particular, few modeling approaches can jointly represent terrain variability, solar radiation distribution, and wind-field characteristics within a unified framework. Moreover, conventional deep reinforcement learning methods often suffer from learning instability and coordination difficulties when applied to multi-agent layout optimization tasks. To address these challenges, this study constructs a multidimensional environmental simulation model that integrates terrain, solar radiation, and wind speed, enabling a quantitative and controllable representation of the meteorological monitoring network layout problem. Based on this environment, an Environment-Aware Proximal Policy Optimization (EA-PPO) algorithm is proposed. EA-PPO adopts a compact environment-related state representation and a utility-guided reward mechanism to improve learning stability under decentralized decision-making. Furthermore, a Global Layout Optimization Algorithm based on EA-PPO (GLOAE) is developed to enable coordinated optimization among multiple monitoring nodes through shared utility feedback. Simulation results demonstrate that the proposed methods achieve superior layout quality and convergence performance compared with conventional approaches, while exhibiting enhanced robustness under dynamic environmental conditions. These results indicate that the proposed framework provides a practical and effective solution for intelligent layout optimization of meteorological monitoring networks in desert–Gobi–wasteland regions. Full article

Background: Electronic health records (EHR) have long held promise for sharing information efficiently, but this remains challenging. This quality improvement initiative sought to improve the accurate documentation of anthracycline and radiation therapy exposures in pediatric oncology patients who were treated at different institutions through a quality improvement methodology and EHR tools. Methods: A custom-built EHR smartform was previously created. Modifications were made to the smartform, and quality improvement methods were utilized to improve receipt of radiation summaries from other institutions and documentation of chemotherapeutic doses. Results: Three months after interventions, including clinician education and smartform updates, accurate anthracycline documentation improved from ≤60% to 100%. At 12 months post-intervention, accurate anthracycline documentation remained > 90%. Documentation of radiation therapy improved similarly at 3 months post-intervention, with sustained improvement to 81% at 12 months post-intervention. Conclusions: Accurate documentation of radiation and chemotherapeutic exposures for pediatric oncology patients improved with education and changes to an EHR smartform. A central data location with quality assurance tools to ensure accuracy is one solution enabling accurate tracking of exposures and care plans for children with chronic illnesses. Full article

Mediterranean biogeography is characterized as a global “hotspot” for climate change; understanding the impacts of these changes on local agricultural systems through high-resolution analyses has thus become a critical need. This study addresses this gap by evaluating the holistic effects of climate change on site-specific agriculture systems, focusing on the Eğirdir–Karacaören (EKB) and Beyşehir (BB) lake basins in the Lakes Region of Türkiye. This study employed machine learning modeling techniques to forecast changes in the yields of key crops, such as wheat, maize, apple, alfalfa, and sugar beet. Detailed spatial analyses of changes in agro-climatic conditions (heat stress, chilling requirement, frost days, and growing degree days for key crops) between the reference period (1995–2014) and two decadal periods projected for 2040–2049 and 2070–2079 were conducted under the Shared Socioeconomic Pathways (SSP3-7.0). Daily temperature, precipitation, relative humidity, and solar radiation data, derived from high-resolution climate simulations, were aggregated into annual summaries. These datasets were then spatially matched with district-level yield statistics obtained from the official data providers to construct crop-specific data matrices. For each crop, Random Forest (RF) regression models were fitted, and a Leave-One-Site-Out (LOSOCV) cross-validation method was used to evaluate model performance during the reference period. Yield prediction models were evaluated using the mean absolute error (MAE). The models achieved low MAE values for wheat (33.95 kg da⁻¹ in EKB and 75.04 kg da⁻¹ in BB), whereas the MAE values for maize and alfalfa were considerably higher, ranging from 658 to 986 kg da⁻¹. Projections for future periods indicate declines in relative yield across both basins. For 2070–2079, wheat and maize yields are projected to decrease by 10–20%, accompanied by wide uncertainty intervals. Both basins are expected to experience a substantial increase in heat stress days (>35 °C), a reduction in frost days, and an overall acceleration of plant phenology. Results provided insights to inform region-specific, evidence-based adaptation options, such as selecting heat-tolerant varieties, optimizing planting calendars, and integrating precision agriculture practices to improve resource efficiency under changing climatic conditions. Overall, this study establishes a scientific basis for enhancing the resilience of agricultural systems to climate change in two lake basins within the Mediterranean biogeography. Full article

The energy sector in all countries around the world is undergoing a transformation, with the main trend being the increasing share of renewable sources. Some countries, such as those in the European Union, have set themselves the goal of completely phasing out fossil fuels by 2050. Currently, the energy systems of European countries are far from this goal, and fossil fuels play a key role in balancing energy systems. This article presents a one-year simulation of a hypothetical Polish energy system based solely on renewable sources and utilizing biomethane, synthetic ammonia, and solid biomass as sources to ensure energy supply in the event of unfavorable weather conditions, which means a lack of wind and solar radiation. Six variants of these systems were analyzed, demonstrating the feasibility of such a system using only biogas as a stabilizing fuel. The required generating capacities of wind turbines, photovoltaic panels, and installations for converting biomethane, ammonia, and solid biomass into electricity were determined. Calculations were based on historical data recorded in 2024 in the Polish energy system. It was found that by increasing currently installed PV and wind turbines by a factor of 4.8 and installing 24 GW of ICE engines fueled with biomethane and an additional 10 GW of ORC modules, current electricity demand would be covered 100% by renewable energy sources. The same goal can be achieved without ORC modules by increasing the installed power of PV and wind turbines by a factor of 6.8. The novelty of this research is the application of the fully renewable concept of electricity generation systems to Polish reality using real-life data. Full article