Search Results (544)

Objectives: Computer-aided schizophrenia (SZ) detection methods mainly depend on electroencephalogram and brain magnetic resonance images, which both capture physical signals from patients’ brains. These inspection techniques take too much time and affect patients’ compliance and cooperation, while difficult for clinicians to comprehend the principle of detection decisions. This study proposes a novel method using face diagnosis images based on traditional Chinese medicine principles, providing a non-invasive, efficient, and interpretable alternative for SZ detection. Methods: An innovative face diagnosis image analysis method for SZ detection, which learns feature representations based on Vision Transformer (ViT) directly from face diagnosis images. It provides a face features distribution visualization and quantitative importance of each facial region and is proposed to supplement interpretation and to increase efficiency in SZ detection while keeping a high detection accuracy. Results: A benchmarking platform comprising 921 face diagnostic images, 6 benchmark methods, and 4 evaluation metrics was established. The experimental results demonstrate that our method significantly improves SZ detection performance with a 3–10% increase in accuracy scores. Additionally, it is found that facial regions rank in descending order according to importance in SZ detection as eyes, mouth, forehead, cheeks, and nose, which is exactly consistent with the clinical traditional Chinese medicine experience. Conclusions: Our method fully leverages semantic feature representations of first-introduced face diagnosis images in SZ, offering strong interpretability and visualization capabilities. It not only opens a new path for SZ detection but also brings new tools and concepts to the research and application in the field of mental illness. Full article

Introduction: The Wide Awake Local Anesthesia No Tourniquet (WALANT) technique has revolutionized outpatient hand surgery, enabling procedures such as carpal tunnel release and trigger finger release without a tourniquet. Its benefits include patient cooperation during surgery, especially for tendon repairs. However, WALANT has limitations, including a steep learning curve, longer operative preparation time, and risks such as digital ischemia and adrenaline-induced cardiac ischemia. This study evaluates the safety and effectiveness of local anesthesia with a tourniquet for short-duration outpatient hand surgeries. Materials and Methods: This case series included 300 patients undergoing carpal tunnel or trigger finger release between February 2023 and March 2024. Local anesthesia with lidocaine was administered, and a tourniquet was applied to the proximal arm. Demographic data, operative time, and pain levels during tourniquet use (measured by VAS) were recorded. Results: The average surgical time was 12 min. Most procedures involved carpal tunnel release. The average VAS pain score was 3.73, with older patients and longer surgeries reporting higher discomfort. Tourniquet release was required in only 1% of cases due to discomfort. Conclusions: For short outpatient hand surgeries, local anesthesia with a tourniquet is a safe, effective alternative to WALANT, challenging its routine use and highlighting the need for tailored anesthetic approaches. Full article

Background/Objectives: Obinutuzumab was approved for front-line treatment of chronic lymphocytic leukemia in combination with chlorambucil pulses administered every 2 wks. Alternative schedules of chlorambucil enable the administration of higher total chlorambucil doses, and have better antileukemia activity. So far, evidence on the feasibility of combining obinutuzumab with alternative chlorambucil schedules is lacking. We performed this retrospective analysis to analyze real life outcomes in chronic lymphocytic leukemia patients receiving a combination of obinutuzumab with different chlorambucil schedules. Methods: This was a retrospective survey performed in order to analyze the feasibility and efficacy of different obinutuzumab and chlorambucil combinations in a real-life setting. Patients receiving this combination as a front-line therapy for chronic lymphocytic leukemia in participating centers, outside of clinical trials, in 2017 and 2018 were included. Results: Seventy-three patients fulfilling entry criteria were identified. Their median age was 76 years, and ranged from 58 to 90 years. The median follow up time was 59 months. The response rate was 89%, with a median progression-free survival time of 27 months, and an overall survival time of 49 months. Chlorambucil was administered as planned in 15 of the 22 (79%) patients treated with chlorambucil pulses every 2 weeks; in 15 of the 42 (34%) patients treated with 7-day courses of chlorambucil administered every 4 weeks; and in 0 of the 10 patients treated with a continuous high dose of chlorambucil (p = 0.002). Changes in treatment schedules were made due to side effects. The progression-free and overall survival rates were similar between the three groups. Conclusions: The combinations of obinutuzumab with more intensive chlorambucil schedules are less feasible, preventing the administration of the intended higher total dose of chlorambucil, and do not improve outcomes in comparison to chlorambucil pulses administered every 2 weeks. Full article

This study introduces a multi-criteria decision-making (MCDM) framework for optimizing multi-energy network scheduling (MENS). As energy systems become more complex, the need for adaptable solutions that balance consumer demand with environmental sustainability grows. The proposed approach integrates conventional and alternative energy sources, addressing uncertainties through fermatean fuzzy sets (FFS), which enhances decision-making flexibility and resilience. A key component of the framework is the use of stochastic optimization and cooperative game theory (CGT) to ensure efficiency and reliability in energy systems. To evaluate the importance of various scheduling criteria, the study applies the logarithmic percentage change-driven objective weighing (LOPCOW) method, offering a systematic way to assign weights. The weighted aggregated sum product assessment (WASPAS) method is then used to rank potential solutions. The hybrid scheduling alternative, combining distributed and centralized solutions, stands out as the best alternative, significantly improving resource optimization and system resilience. While implementation costs may increase, the hybrid approach balances flexibility and rigidity, optimizing resource use and ensuring system adaptability. This work provides a comprehensive framework that enhances the efficiency and sustainability of energy systems, helping decision-makers address fluctuating demands and renewable energy integration challenges. Full article

Dihydrogen activation by metallogermylenes was investigated experimentally and theoretically. A neutral NHC-coordinated chlorometallogermylene was synthesized and converted to a cationic base-free metallogermylene of molybdenum via chloride abstraction. The cationic molybdogermylene showed enhanced reactivity toward H₂ compared to the tungsten analog. The reaction mechanism was investigated by theoretical calculations, which revealed a novel route that proceeds via a new type of metal–ligand cooperative activation between the metal and divalent germanium moiety. The activation energy of this route is much lower than that of the alternative route via an “oxidative addition” type of reaction on the single Ge(II) center, which is generally proposed for organotetrylenes. The features of the frontier orbitals and the origin of the metal effect on the H₂ activation are also described. Full article

The water industry is facing challenges because of population increases and the resulting development of agricultural operations. Alternative resources that balance the environment, the economy, and society while lessening the strain on limited water supplies will need to be adopted by farmers. One possibility addressing this dilemma is wastewater reuse. The adoption of Reg. (EU) 2020/741 necessitates a paradigm change by moving away from the “fit-for-all” strategy and toward the “fit-for-purpose” approach, which is now regarded as the foundation of the reuse supply chain. However, despite progress, appropriate rules that clearly and concisely outline the procedures to be followed are still needed. Thus, to establish an interdisciplinary and cooperative research agenda, this study tackles the potential and forces behind change by concentrating on tactics for long-term fixes. The need to look at consumer and farmer acceptability as well as the overall environmental advantages of carbon footprint reduction and wastewater fertigation are interesting research avenues. Nutrient-rich streams in agriculture may increase carbon absorption and reduce greenhouse gas emissions from the soil while simultaneously serving as a fertilizer substitute. The literature suggests that additional research is necessary to fully explore the significant economic potential. Full article

To address the technical challenges of implementing Continuous Descent Operations (CDO) in high-traffic-density terminal control areas, we propose a cooperative low-carbon trajectory planning method for multiple arriving aircraft. Firstly, this study analyzes the CDO phases of aircraft in the terminal area, establishes a multi-phase optimal control model for the vertical profile, and introduces a novel vertical profile optimization method for CDO based on a genetic algorithm. Secondly, to tackle the challenges of CDO in busy terminal areas, a T-shaped arrival route structure is designed to provide alternative paths and to generate a set of four-dimensional (4D) alternative trajectories. A Mixed Integer Programming (MIP) model is constructed for the 4D trajectory planning of multiple aircraft, aiming to maximize the efficiency of arrival traffic flow while considering conflict constraints. The complex constrained MIP problem is transformed into an unconstrained problem using a penalty function method. Finally, experiments were conducted to evaluate the implementation of CDO in busy terminal areas. The results show that, compared to actual operations, the proposed optimization model significantly reduces the total aircraft operating time, fuel consumption, CO₂ emissions, SO₂ emissions, and NO_x emissions. Specifically, with the optimization objective of minimizing total cost, the proposed method reduces the total operation time by 22.4%; fuel consumption, CO₂ emissions, SO₂ emissions by 22.9%, and NO_x emissions by 23.7%. The method proposed in this paper not only produces efficient aircraft sequencing results, but also provides a feasible low-carbon trajectory for achieving optimal sequencing. Full article

The rapid growth of the digital economy has significantly enhanced the convenience of information transmission while reducing its costs. As a result, the participation in social networks (SNs) has surged, intensifying the mutual influence among network participants. To support objective decision-making and gather public opinions within SNs, the research on the consensus-reaching process (CRP) has become increasingly important. However, CRP faces three key challenges: first, as the number of decision-makers (DMs) increases, the efficiency of reaching consensus declines; second, minority opinions and non-cooperative behaviors affect decision outcomes; and third, the relationships among DMs complicate opinion adjustments. To address these challenges, this paper introduces an enhanced CRP mechanism. Initially, the hippopotamus optimization algorithm (HOA) is applied to update the initial community division in Leiden clustering, which accelerates the clustering process, collectively referred to as HOAL. Subsequently, a two-stage opinion adjustment method is proposed, combining minority opinion handling (MOH), non-cooperative behavior management, and dual-fine tuning (DFT) management, collectively referred to as DFT-MOH. Moreover, trust relationships between DMs are directly integrated into both the clustering and opinion management processes, resulting in the HOAL-DFT-MOH framework. The proposed method proceeds by three main steps: (1) First, the HOAL clusters DMs. (2) Then, in the initial CRP stage, DFT manages subgroup opinions with a weighted average to synthesize subgroup perspectives; and in the second stage, MOH addresses minority opinions, a non-cooperative mechanism manages uncooperative behaviors, and DFT is used when negative behaviors are absent. (3) Third, the prospect-regret theory is applied to rank decision alternatives. Finally, the approach is applied to case analyses across three different scenarios, while comparative experiments with other clustering and CRP methods highlight its superior performance. Full article

To improve the regulatory capacity of distributed resources within the park and enhance the flexibility of market transactions, this paper introduces a distributed dispatch and profit allocation method grounded in cooperative game theory and the generalized Nash bargaining framework. Initially, models for individual park equipment are established. Subsequently, a distributed dispatch model is constructed, followed by the development of a profit allocation strategy based on contribution levels, using the generalized Nash bargaining method. The model is solved using the alternating direction method of multipliers. The results show that the proposed approach achieves fast convergence, optimizes resource sharing and mutual support within the park, lowers operational costs, ensures a fairer distribution of profits, and promotes increased cooperation among park entities. Full article

Background/Objectives: The historically most commonly used preoperative radiotherapy regimen for soft tissue sarcomas (STSs) consists of 50 Gray (Gy) delivered in 25 fractions over 5 weeks, achieving excellent local control, but with significant challenges due to prolonged treatment duration and early side effects. Reducing therapy duration while maintaining optimal local and distant control would be highly beneficial for patients. We aimed to investigate the outcome of an ultrahypofractionated radiotherapy (uhRT) regimen which may represent a shorter and more patient-friendly alternative. Methods: This multi-center, open-label, phase 2 clinical trial with a clustered cohort design was conducted within the Swiss Sarcoma Network (SSN). Adult patients (aged ≥ 18 years) with STS of the extremities or superficial trunk and an Eastern Cooperative Oncology Group (ECOG) performance status of 0–3 were included. Participants were assigned to either normofractionated radiotherapy (nRT) at 50 Gy in 25 fractions or uhRT at 25 Gy in 5 fractions. Data were collected prospectively in real-world-time clinical settings. The primary outcome was local recurrence-free survival (LRFS), with overall survival (OS) and wound complications as secondary outcomes. Results: Between March 2020 and October 2023, 138 patients were included in the study; 74 received nRT and 64 received uhRT. The median follow-up times were 2.2 years for uhRT and 3.6 years for nRT. The LRFS rates at 1 year were 97.0% for nRT and 94.8% for uhRT (p = 0.57). The two-year LRFS rates were 91.9% and 94.8%, respectively (p = 0.57). The one- and two-year OS rates were 97.1%/86.3% and 98.2%/88.8%, respectively (p = 0.72). The wound complication rate was comparable between the nRT (12.0%) and uhRT (12.5%) groups (p = 0.99). Conclusions: UhRT for STSs offers an effective and safe alternative to traditional nRT, with comparable early LRFS, OS and wound complication rates. Given the two-year median follow-up, which is critical for evaluating local recurrence, uhRT shows promise as a shorter and more convenient treatment regimen. UhRT may be a safe and effective alternative treatment option to traditional nRT. Full article

The Mobile Cognitive Radio Network (MCRN) are an alternative to spectrum scarcity. However, like any network, it comes with security issues to analyze. One of the attacks to analyze is the Primary User Emulation (PUE) attack, which leads the system to give the attacker the service as a legitimate user and use the Primary Users’ (PUs) spectrum resources. This problem has been addressed from perspectives like arrival time, position detection, cooperative scenarios, and artificial intelligence techniques (AI). Nevertheless, it has been studied with one PUE attack at once. This paper implements a countermeasure that can be applied when several attacks simultaneously exist in a cooperative network. A deep neural network (DNN) is used with other techniques to determine the PUE’s existence and communicate it with other devices in the cooperative MCRN. An algorithm to detect and share detection information is applied, and the results show that the system can detect multiple PUE attacks with coordination between the secondary users (SUs). Scenarios are implemented on software-defined radio (SDR) with a cognitive protocol to protect the PU. The probability of detection (PD) is measured for some signal-to-noise ratio (SNR) values in the presence of one PUE or more in the network, which shows high detection values above 90% for an SNR of -7dB. A database is also created with the attackers’ data and shared with all the SUs. Full article

In this work, we unveil the advantages of synergizing cooperative rate splitting (CRS) with user relaying and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR RIS). Specifically, we propose a novel STAR RIS-assisted CRS transmission framework, featuring six unique transmission modes that leverage various combinations of the relaying protocols (including full duplex-FD and half duplex-HD) and the STAR RIS configuration protocols (including energy splitting-ES, mode switching-MS, and time splitting-TS). With the objective of maximizing the minimum user rate, we then propose a unified successive convex approximation (SCA)-based alternative optimization (AO) algorithm to jointly optimize the transmit active beamforming, common rate allocation, STAR RIS passive beamforming, as well as time allocation (for HD or TS protocols) subject to the transmit power constraint at the base station (BS) and the law of energy conservation at the STAR RIS. To alleviate the computational burden, we further propose a low-complexity algorithm that incorporates a closed-form passive beamforming design. Numerical results show that our proposed framework significantly enhances user fairness compared with conventional CRS schemes without STAR RIS or other STAR RIS-empowered multiple access schemes. Moreover, the proposed low-complexity algorithm dramatically reduces the computational complexity while achieving very close performance to the AO method. Full article

This paper proposes a two-stage, three-layer stochastic robust model and its solution method for a multi-energy access system (MEAS) considering different weather scenarios which are described through scenario probabilities and output uncertainties. In the first stage, based on the principle of the master–slave game, the master–slave relationship between the grid dispatch department (GDD) and the MEAS is constructed and the master–slave game transaction mechanism is analyzed. The GDD establishes a stochastic pricing model that takes into account the uncertainty of wind power scenario probabilities. In the second stage, considering the impacts of wind power and photovoltaic scenario probability uncertainties and output uncertainties, a max–max–min three-layer structured stochastic robust model for the MEAS is established and its cooperation model is constructed based on the Nash bargaining principle. A variable alternating iteration algorithm combining Karush–Kuhn–Tucker conditions (KKT) is proposed to solve the stochastic robust model of the MEAS. The alternating direction method of multipliers (ADMM) is used to solve the cooperation model of the MEAS and a particle swarm algorithm (PSO) is employed to solve the non-convex two-stage model. Finally, the effectiveness of the proposed model and method is verified through case studies. Full article

Due to photovoltaic (PV) power generation depending on the environment, its output power is volatile, and effectively dealing with its power fluctuation has become a key concern. Aiming at this problem, this article presents an optical storage cooperative control technology based on an Alternating Sequence Filter (ASF), which controls the power management of the Energy Storage System (ESS) consisting of a vanadium redox battery, battery, and supercapacitor. Firstly, an ASF is designed to stabilize the PV power generation by alternating sequence and improve system response speed. Secondly, according to the output signal of the filter, the charge and discharge of the three energy storage units are dynamically adjusted, and the power fluctuation is compensated in real-time to improve the system stability and conversion efficiency. Finally, the simulation results of actual illumination show that the control strategy calls the ESS to stabilize the power fluctuation, so that the power of the direct current bus is stabilized at about 15 kw, and the fluctuation is maintained between −4.48% and 4.05%. The strategy significantly reduces power fluctuation and improves the dynamic response ability and energy storage utilization of the system. Full article

This study proposes a swarm-based Unmanned Aerial Vehicle (UAV) system designed for surveillance tasks, specifically for detecting and tracking ground vehicles. The proposal is to assess how a system consisting of multiple cooperating UAVs can enhance performance by utilizing fast detection algorithms. Within the study, the differences in one-stage and two-stage detection models have been considered, revealing that while two-stage models offer improved accuracy, their increased computation time renders them impractical for real-time applications. Consequently, faster one-stage models, such as the tested YOLOv8 architectures, appear to be a more viable option for real-time operations. Notably, the swarm-based approach enables these faster algorithms to achieve an accuracy level comparable to that of slower models. Overall, the experimentation analysis demonstrates how larger YOLO architectures exhibit longer processing times in exchange for superior tracking success rates. However, the inclusion of additional UAVs introduced in the system outweighed the choice of the tracking algorithm if the mission is correctly configured, thus demonstrating that the swarm-based approach facilitates the use of faster algorithms while maintaining performance levels comparable to slower alternatives. However, the perspectives provided by the included UAVs hold additional significance, as they are essential for achieving enhanced results. Full article