Search Results (308)

Electricity markets with a high share of variable renewable energy require significant balancing reserves to ensure stability by preserving the balance of supply and demand. However, they were originally conceived for dispatchable technologies, which operate with predictable and controllable generation. As a result, adapting market mechanisms to accommodate the characteristics of variable renewables is essential for enhancing grid reliability and efficiency. This work studies the strategic behavior of a wind power producer (WPP) in the Iberian electricity market (MIBEL) and the Portuguese balancing markets (BMs), where wind farms are economically responsible for deviations and do not have support schemes. In addition to exploring current market dynamics, the study proposes new market designs for the balancing markets, with separate procurement of upward and downward secondary balancing capacity, aligning with European Electricity Regulation guidelines. The difference between market designs considers that the wind farm can hourly bid in both (New 1) or only one (New 2) balancing direction. The study considers seven strategies (S1–S7) for the participation of a wind farm in the past (S1), actual (S2 and S3), New 1 (S4) and New 2 (S5–S7) market designs. The results demonstrate that new market designs can increase the wind market value by 2% compared to the optimal scenario and by 31% compared to the operational scenario. Among the tested approaches, New 2 delivers the best operational and economic outcomes. In S7, the wind farm achieves the lowest imbalance and curtailment while maintaining the same remuneration of S4. Additionally, the difference between the optimal and operational remuneration of the WPP under the New 2 design is only 22%, indicating that this design enables the WPP to achieve remuneration levels close to the optimal case. Full article

The landmark Philippine Supreme Court case Llorente vs. Llorente illuminates the complex intersections of transnational migration, inheritance law, and colonial legacies in the Philippines. The case centers on Lorenzo Llorente, a Filipino US Navy serviceman whose estate became the subject of a fifteen-year legal battle between his first wife Paula and his second wife Alicia. Lorenzo returned from the battles of World War II to find his wife in Nabua living with his brother and pregnant with his brother’s child. Lorenzo obtained a divorce in California in 1952. He later returned to the Philippines and married Alicia, naming her and their three adopted children as heirs in his will. Upon his death in 1985, Paula challenged the validity of the US divorce and claimed rights to Lorenzo’s estate under Philippine succession laws. While lower courts initially favored Paula’s claims by rigidly applying Philippine laws that are rooted in the colonial era and privileged blood relations, the Supreme Court ultimately upheld Lorenzo’s will in 2000, recognizing his right to divorce as a US citizen. This case reveals how postcolonial Philippine legal frameworks, still heavily influenced by Spanish colonial law, often fail to accommodate the complex realities of transnational families and diverse kinship practices, instead imposing rigid interpretations that fracture rather than heal family relations. Inheritance, previously a highly shared and negotiated process mediated by the elders, can now escalate to family disputes which play out in the impersonal space of the courtroom. Full article

The Department of Veterans Affairs’ (VA’s) transportation system plays an important role in ensuring access to transportation services for veterans, particularly those in rural or underserved areas. However, concerns remain regarding the effectiveness of collaboration among the various VA transportation stakeholders. Persistent transportation challenges hinder veterans’ access to essential healthcare services and resources. Electric autonomous ride-sharing services (ARSSs) offer a promising opportunity to enhance transportation access; however, their current limitations and the perspectives of VA transportation personnel must be considered. This study explored the current perspectives of the VA transportation system and assessed ARSSs as an innovative and sustainable alternative through interviews with eight VA transportation stakeholders representing seven transportation sectors. Our findings revealed the VA’s strengths, including personalized service, flexible accommodations, and collaborative care models, but also identified challenges, including limited funding, staff shortages, volunteer constraints, and restrictive eligibility criteria. The introduction of ARSSs was identified as an opportunity to alleviate some of these constraints by reallocating human resources and improving access to essential services, although concerns remain regarding ARSSs’ ability to accommodate veterans with disabilities and address rural route complexities. Effective communication strategies and streamlined coordination were key recommendations for improving service delivery and expanding transportation access for veterans. Full article

Conventional shared energy storage (SES) allocation and coordinated operation mechanism are mismatched with the actual time-varying demand of the distribution system, resulting in low utilization of energy storage and renewable energy sources (RES), which restricts the system operational efficiency and RES integration. To solve this issue, this paper proposes a centralized shared energy storage (CSES) optimization framework for AC/DC distribution systems with dual-time-scale coordination to address this issue. Firstly, optimal scheduling models for AC/DC distribution systems are formulated. Secondly, a novel CSES optimization framework is established where a large-scale CSES directly connects to multiple subnetworks. This framework maximizes RES utilization by coordinating CSES operation, leveraging complementary RES potential. Thirdly, based on dual-time-scale coordination, intraday stage adjustments are made based on the day-ahead scheduling to accommodate and coordinate with source–load changes. Day-ahead SOC trajectory is processed using linear interpolation to obtain intraday SOC trajectory, ensuring that the state of charge (SOC) constraints are satisfied. An alternating direction multiplication method (ADMM) algorithm is used to coordinate the intraday optimization. Finally, case studies on an AC/DC distribution system comprising three IEEE 33-node AC subnetworks show that the proposed strategy can increase the RES utilization rate to 99.31%, 88.10%, and 99.91%, and reduce the operational cost by 16.51%. Full article

As the share of renewable energy in modern power systems continues to grow, its inherent uncertainty and variability pose severe challenges to grid stability and the accuracy of traditional thermal power dispatch. To address this issue, this study fully exploits the fast response and flexible operation of variable-speed pumped storage (VS-PS) by developing a day-ahead scheduling model for a wind–photovoltaic–thermal–VS-PS system. The optimization model aims to minimize system operating costs, carbon emissions, and thermal power output fluctuations, while maximizing the regulation flexibility of the VS-PS plant. It is assessed using the improved multi-objective jellyfish search (IMOJS) algorithm, and its effectiveness is demonstrated through comparison with a fixed-speed pumped storage (FS-PS) system. Simulation results show that the proposed model significantly outperforms the traditional FS-PS system: it increases renewable energy accommodation capacity by an average of 68.51%, reduces total operating costs by 14.13%, and lowers carbon emissions by 3.63%. Full article

Existing few-shot remote sensing scene classification (FS-RSSC) works primarily follow the meta-learning paradigm, which meta-trains a model on an auxiliary dataset before adapting it to target FS-RSSC tasks. To ensure good performance, the auxiliary dataset should share similar distributions with the target tasks. However, acquiring such an auxiliary dataset is difficult and economically costly in real-world FS-RSSC applications. To address this issue, we aim to handle FS-RSSC tasks by directly fine-tuning a general pre-trained model, eliminating the need for an auxiliary dataset related to the target tasks. In this paper, we propose a novel fine-tuning framework, named TA-MSA, which consists of a Task-Adaptive (TA) fine-tuning strategy and a Multi-level Spatial feature Aggregation (MSA) module. The TA fine-tuning strategy is composed of two components: (1) a layer-specific optimizer that alleviates distribution shifts between the pre-trained and target remote sensing datasets, and (2) a task-specific training scheme designed to accommodate variations in discriminative features across different FS-RSSC tasks. Additionally, to suppress the negative effect of the cluttered backgrounds and enhance the spatial features of true discriminative regions, the MSA module extracts multi-level spatially important features using trainable spatial templates for classification. Experimental analysis demonstrates the superiority of the proposed TA-MSA framework. On three FS-RSSC benchmarks (NWPU-RESISC45, UC Merced LandUse, and WHU-RS19), our TA-MSA framework outperforms many state-of-the-art methods, achieving an average classification accuracy of 76.78% in the 5-way 1-shot setting and 91.89% in the 5-way 5-shot setting. Full article

Mobile manipulators have the potential to replace manual labor in various scenarios. However, current mobile base designs have limitations when it comes to accommodating complex movements that involve both high-altitude tasks and ground-based composite tasks. This paper presents a new design for the mobile manipulator base, which utilizes a time-sharing drive with gears and differential wheels. Additionally, a new foldable mechanical gear-track system has been developed, enabling the robot to effectively operate on both the ground and the mechanical gear-tracks. To address the challenges of power distribution and localization caused by the mechanical characteristics of the designed track, this study proposes a precise pose estimation method for the robot on the mechanical gear-track, along with a compliance control method for the gears. Furthermore, a segmented multi-sensor fusion navigation approach is introduced to meet the high-precision motion control requirements at the entrance of the designed track. Experimental results demonstrate the effectiveness of the proposed new mobile manipulator base, as well as its corresponding control methods. Full article

Background: Over the past decade, Italy has made progress in adopting recovery-oriented approaches in mental health care, though full alignment with international guidelines remains incomplete. This study investigates the feasibility, acceptability, and impact of integrating recovery-oriented practices in an Italian Community Mental Health Service (CMHS), focusing on both user and professional perspectives to identify strengths and areas for improvement. Methods: A longitudinal pilot study was conducted at the South Verona CMHS. Data on users’ socio-demographic and clinical characteristics, symptoms, functioning, needs, and autonomy were collected at baseline and six-month follow-up. Participants included individuals in supported accommodation and outpatient care. The Mental Health Recovery Star (MHRS) assessed recovery progress. Qualitative data from focus groups and interviews captured users’ and professionals’ experiences. Results: Nineteen professionals completed the MHRS with 25 users, who demonstrated significant improvements in MHRS scores (p = 0.003), romantic relationships (p < 0.001), employment (p < 0.001), functioning (p = 0.015), psychopathology (p = 0.001), functional autonomy (p = 0.003), and unmet needs (p = 0.026). Qualitative findings emphasized the value of a personalized, holistic approach but noted gaps in follow-up and shared decision-making. Focus groups (30 participants) highlighted recovery as a process of hope, meaning, and empowerment. Participants called for ongoing education, structural changes, and peer-support initiatives. Professionals reported increased motivation. Conclusions: Integrating recovery-oriented practices within the South Verona CMHS was both feasible and acceptable. The MHRS positively impacted service users’ personal recovery and professionals’ motivation. The study underscores the need for continued training, structural reforms, and peer-support initiatives to foster lasting changes and enhance CMHS practices. Full article

This article offers the architectural definition and interpretative keys to a unique project. It is a space shared by the three main Abrahamic faiths: the Jewish, Christian and Muslim religions. Although conceptually other religions could be accommodated. Its configuration is very elementary: a cubic volume, massive and almost blind, with a cylindrical space crowned by a simple skylight. Each of the religions is based on a scratching of the interior surfaces of the space, forming the ritual areas of each of them. And towards the center of the space there are other areas of prayer and celebration that could be shared among the believers of the different religions, from the conviction that they are addressed to the same God. In this configuration there is a will of invitation, of offering to all men of good will. The article, written by the architect of this space, mentions some plastic and conceptual references that have served as inspiration for the project and its presentation is intended to fuel the debate on the possibility of this space. Full article

In real-world scenarios, ECG data are collected from a diverse range of heterogeneous devices, including high-end medical equipment and consumer-grade wearable devices, each with varying computational capabilities and constraints. This heterogeneity presents significant challenges in developing a highly accurate deep learning (DL) global model for ECG classification, as traditional centralized approaches struggle to address privacy concerns, scalability issues, and model inconsistencies arising from diverse device characteristics. Federated Learning (FL) has emerged as a promising solution by enabling collaborative model training without sharing raw data, thus preserving privacy and security. However, standard FL assumes uniform device capabilities and model architectures, which is impractical given the varied nature of ECG data collection devices. Although heterogeneity has been explored in other domains, its impact on ECG classification and the classification of similar time series physiological signals remains underexplored. In this study, we adopted HeteroFL, a technique that enables model heterogeneity to reflect real-world resource constraints. By allowing local models to vary in complexity while aggregating their updates, HeteroFL accommodates the computational diversity of different devices. This study evaluated the applicability of HeteroFL for ECG classification using the MIT-BIH Arrhythmia dataset, identifying both its strengths and limitations. Our findings establish a foundation for future research on improving FL strategies for heterogeneous medical data, highlighting areas for further optimization and adaptation in real-world deployments. Full article

Background: This study aimed to compare the anterior segment characteristics of patients with central serous chorioretinopathy (CSCR) to those with diabetic retinopathy (DR) and healthy controls. Additionally, it explored the possible associations between quality of life and anxiety with CSCR. Methods: A single-center, cross-sectional study involving patients aged 23–61 years diagnosed with CSCR or DR, and healthy patients. Comprehensive ophthalmic examinations included best-corrected visual acuity (BCVA, LogMAR), objective and subjective refraction, and anterior and posterior segments optical coherence tomography (OCT) imaging. Participants completed the Quality-of-Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) and the Beck Anxiety Inventory (BAI). Statistical analysis included Kruskal–Wallis, Tukey post-hoc, Chi-square, and Spearman correlation tests to compare the three groups. Results: A total of 53 patients were recruited (16 CSCR, 8 DR, 29 controls; 52.8% males), with an additional 16 CSCR patients completed only the questionnaires. CSCR and DR patients were the same age as the controls (43.8 ± 9.0, 42.7 ± 9.9, 37.06 ± 13.61 years, respectively, p = 0.19). CSCR and DR patients had similar BCVA, lower than controls (0.19 ± 0.30, 0.15 ± 0.13, 0.01 ± 0.02 LogMAR, respectively, p < 0.01). CSCR patients exhibited more hyperopic refraction compared to healthy controls (p < 0.01) and reported significantly lower life enjoyment and satisfaction than DR and healthy individuals (51.56 ± 9.17, 53.75 ± 7.81, 60.03 ± 7.32, respectively, p < 0.01). No significant correlations were found between anxiety levels and pupil size, anterior chamber depth (ACD), amplitude of accommodation (AA), and intraocular pressure (IOP) among study groups (p > 0.05). Conclusions: CSCR patients demonstrated lower life enjoyment and satisfaction, reduced BCVA, and hyperopic refraction compared to healthy patients. They also tended to have higher stress and anxiety levels. Both CSCR and DR patients shared similar anterior segment characteristics. Full article

Complete Streets (CS) are defined as streets that accommodate all types of users, regardless of ability, safely and equitably allowing for the presence of pedestrians, bicyclists, transit users, and vehicle drivers to share the roadway. Several agencies have developed CS policies as a vital strategy to create more inclusive and accessible environments for all road users. CS are an efficient way to support the implementation of a multimodal transportation system, providing alternatives to car-oriented roadway designs. The Kentucky Transportation Cabinet recently developed the Complete Streets, Roads, and Highways Manual, aiming to implement a safe and equitable transportation system throughout the state. However, there is a need to evaluate the benefits of CS regarding their safety performance. This study aims to present crash data and summary statistics for CS projects that have been completed in Kentucky. The methodology involves a comparative analysis of safety data collected before and after the implementation of these projects. The results reveal that CS can be an effective approach to improve safety for all road users, including vulnerable and motor vehicle users. The findings also contribute to the existing knowledge on CS, offering insights into their impact on safety performance. Given that transportation agencies continue to prioritize sustainable and inclusive transportation solutions, the outcomes of this study will provide practical guidance for urban planners, policymakers, and transportation engineers seeking evidence-based solutions for creating safer roads. Full article

The optimization of energy consumption in response to global warming scenarios presents fundamental challenges in the built environment, particularly in Mediterranean climates, where comfort and energy efficiency require priority-based adaptation. This study examines the effectiveness of passive energy retrofit strategies applied to an educational building in Granada, Spain, accommodating both teaching and residential uses. The research uses advanced climatic data based on Shared Socioeconomic Pathways (SSPs), incorporating precise projections of climate evolution. Using simulations conducted in DesignBuilder, it evaluates three intervention packages for the building envelope—window replacement, facade insulation, and roof insulation—across three temporal scenarios: 2024, 2050, and 2080. The results indicate that passive measures could reduce heating demand by up to 90% in future scenarios, while cooling demand is projected to increase by more than 80% by the end of the century. Additionally, climate projections under the SSP scenarios show up to an 83% increase in energy demand, emphasizing the need for integrated passive and active strategies. The research includes a sensitivity analysis of the interaction between passive strategies and advanced climate scenarios. It offers decision-making models for energy retrofitting and provides replicable key insights to support energy retrofitting policies and climate resilience in the Mediterranean region. Full article

Heart transplantation remains the preferred treatment for carefully selected patients with end-stage heart failure refractory to medical therapy. Advances in donor management, organ preservation, donor and recipient selection, immunosuppressive strategies, and mechanical circulatory support have significantly improved the safety and efficacy of heart transplantation. However, the persistent shortage of donor hearts and their limited preservation period continues to restrict access to this lifesaving procedure. The advent of innovative machine perfusion and temperature control systems for heart allograft preservation offers a promising avenue to address these challenges. These technologies aim to extend preservation times and enable the use of extended-criteria donors, thereby expanding the donor pool. In this review, we examine the outcomes from clinical trials, registry data, and single-center studies, utilizing the TransMedics Organ Care System Heart, Paragonix SherpaPak Cardiac Transport System, and XVIVO Heart Preservation System. As the field of heart transplantation evolves to accommodate longer ischemia times, expand organ sharing, and utilize donors previously considered marginal, the integration of these advanced technologies will be essential for optimizing post-transplant outcomes. Full article

Traffic flow prediction can guide the rational layout of land use. Accurate traffic flow prediction can provide an important basis for urban expansion planning. This paper introduces a personalized lightweight federated learning framework (PLFL) for traffic flow prediction. This framework has been improved and enhanced to better accommodate traffic flow data. It is capable of collaboratively training a unified global traffic flow prediction model without compromising the privacy of individual datasets. Specifically, a spatiotemporal fusion graph convolutional network (MGTGCN) is established as the initial model for federated learning. Subsequently, a shared parameter mechanism of federated learning is employed for model training. Customized weights are allocated to each client model based on their data features to enhance personalization during this process. In order to improve the communication efficiency of federated learning, dynamic model pruning (DMP) is introduced on the client side to reduce the number of parameters that need to be communicated. Finally, the PLFL framework proposed in this paper is experimentally validated using LPR data from Changsha city. The results demonstrate that the framework can still achieve favorable prediction outcomes even when certain clients lack data. Moreover, the communication efficiency of federated learning under this framework has been enhanced while preserving the distinct characteristics of each client, without significant interference from other clients. Full article