Search Results (7,218)

This paper investigates a class of uncertain fractional-order delayed cellular neural networks (UFODCNNs) with fuzzy operators and nonlinear activations. Both fuzzy AND and fuzzy OR are considered, which help to improve the robustness of the model when dealing with various uncertain problems. To achieve the finite-time (FT) synchronization and Mittag–Leffler synchronization of the concerned neural networks (NNs), a nonlinear adaptive controller consisting of three information feedback modules is devised, and each submodule performs its function based on current or delayed historical information. Based on the fractional-order comparison theorem, the Lyapunov function, and the adaptive control scheme, new FT synchronization and Mittag–Leffler synchronization criteria for the UFODCNNs are derived. Unlike previous feedback controllers, the control strategy proposed in this article can adaptively adjust the strength of the information feedback, and partial parameters only need to satisfy inequality constraints within a local time interval, which shows our control mechanism has a significant advantage in conservatism. The experimental results show that our mean synchronization time and variance are $11.397\%$ and $12.5\%$ lower than the second-ranked controllers, respectively. Full article

Background and Objective: Postoperative nausea and vomiting (PONV) ranks among the most common postoperative complications, affecting up to 80% of patients undergoing laparoscopic bariatric surgery. This condition negatively impacts patient comfort and well-being while also potentially delaying ambulation and increasing the risk of anastomotic and wound dehiscence. Although various interventions can mitigate the risk of PONV, none are entirely effective; therefore, combined prophylactic strategies are the standard approach. In recent years, numerous techniques and interventions have emerged; consequently, this scoping review aims to assess the current evidence regarding PONV prevention in patients undergoing laparoscopic bariatric procedures. Methods: This review was conducted in accordance with PRISMA guidelines and registered with OSF. A search was performed across the MEDLINE (PubMed), Scopus, Embase, and Web of Science databases. Inclusion criteria encompassed randomized controlled trials (RCTs) published up to May 2025, focusing on adult patients undergoing laparoscopic bariatric surgeries with PONV as a primary or secondary outcome. Results: A total of 81 studies were included in this review, encompassing a broad range of perioperative techniques, including opioid-sparing adjuvants, regional anesthesia, and pharmacological interventions. Conclusions: While there is general consensus and guidance advocating for a multimodal approach to PONV prevention, debates persist regarding the optimal techniques and antiemetic drug regimens to implement. Emerging evidence, particularly concerning regional anesthesia strategies and combined pharmacological prophylaxis, including novel agents, highlights the potential advantages of innovative approaches. Highlights: Effective management of postoperative nausea and vomiting in patients undergoing laparoscopic bariatric surgery is essential, given its impact on patient comfort, recovery, and the potential to prevent wound or anastomotic dehiscence. Although multimodal antiemetic strategies are regarded as standard, disagreements remain regarding specific measures to be adopted. New techniques and strategies, including advanced regional anesthesia techniques, pharmacological, and non-pharmacological methods, offer promising avenues for improved prophylaxis. Full article

Jujube (Ziziphus jujuba Mill.) is a nutritionally rich and economically significant fruit, highly valuable for its flavor, bioactive compounds, and therapeutic properties. However, it is highly perishable and has a short postharvest lifespan. This review aims to provide knowledge for preserving quality and improving postharvest storage by integrative strategies aimed at extending the shelf life of jujube. The literature was collected from recent peer-reviewed studies on postharvest physiology and handling technologies of jujube fruit. Key physiological factors, influencing postharvest deterioration such as water loss, softening, browning, and decay, are discussed, along with the underlying biochemical and enzymatic mechanisms driving quality decline. Conventional strategies such as cold storage, MAP, and CA effectively slow respiration, delay reddening, and extend storage up to 2–4 months, while emerging approaches such as ozone and cold plasma treatments reduce microbial decay and maintain antioxidant activity. Edible coatings like chitosan, aloe vera, and composites cut weight loss by 20–40%, and chemical regulators such as 1-MCP and calcium dips further delay ripening, preserve firmness, and enhance postharvest quality. Emphasis is placed on integrating innovative technologies with physiological insights to optimize storage conditions, control microbial contamination, and maintain nutritional integrity. The significance of this review lies in integrating physiological insights with innovative preservation methods, offering practical guidance for researchers, growers, and industry stakeholders to achieve sustainable, safe, and market-oriented solutions for jujube storage. Full article

The rise of English-medium instruction (EMI) in higher education presents challenges for supporting language development alongside disciplinary learning, as it is typically delivered by content specialists with limited time and little or no background in language pedagogy. Against this backdrop, this study examines the effectiveness of computer-assisted content-based structured input (CBSI), compared to input flood (IF) and unmodified disciplinary input (Control), in enhancing students’ acquisition of English verb patterns in an EMI university course in Poland. All participants received the same asynchronous, computer-assisted disciplinary instruction, aligned with the course syllabus. The groups differed only in the type of input enhancement, which was developed by a language specialist in coordination with the course instructor. A split-block design was used to measure learning gains through a pre-test, post-test, and delayed post-test. Students in the CBSI group showed significantly greater and more sustained improvement than those in the IF and Control groups. These findings support CBSI as an effective and pedagogically feasible way to promote language development in EMI, integrating linguistic and disciplinary concerns while respecting the roles and integrity of both domains. Full article

Erythema ab igne (EAI), also known as “hot water bottle rash” or “toasted skin syndrome”, is a benign cutaneous condition caused by chronic exposure to low-level infrared heat. It typically begins as transient erythema and evolves into a reticulated brown pigmentation with telangiectasias. A skin biopsy, ideally taken from the central area of the hyperpigmented lesion, is recommended to exclude differential diagnoses. Although usually benign, EAI has been associated with rare malignant transformations, supported only by low-level evidence. Elimination of the heat source is essential, and topical treatments such as hydroquinone or retinoids may be considered, while agents like 5-fluorouracil or imiquimod are reserved for dysplastic lesions. Women with endometriosis frequently use heating devices to alleviate dysmenorrhea and chronic pelvic pain. However, prolonged or inappropriate heat application can lead to chronic thermal injury, including EAI, and may delay medical consultation. While controlled trials confirm short-term analgesic efficacy of heat therapy, extrapolating these findings to unrestricted home use without standardized safety recommendations can be misleading. EAI illustrates the broader impact of chronic pain in endometriosis, linking cutaneous manifestations with neuroplastic alterations and psychiatric comorbidities. A nuanced approach combining patient education on safe use of heat, close dermatologic monitoring, and multidisciplinary pain management is warranted. Full article

Cyperus esculentus is a very destructive perennial weed, rapidly propagating and spreading through large amounts of daughter tubers. Successful control relies on depleting the soil tuber bank. This study investigated the effect of different control measures, applied across several cropping systems, on tuber bank dynamics over time. Therefore, 52 infested fields were monitored over 3 consecutive years, with annual quantification of the C. esculentus tuber bank. In maize monocropping systems, substantial 3-year tuber bank reductions (>90%) are achievable with preplant incorporation of dimethenamid-P or S-metolachlor, followed by a post-emergence application of mesotrione and pyridate at the 4–5 leaf stage, combined with delayed sowing (after 20 May) or mechanical measures (e.g., hoeing, harrowing). On non-maize fields, effective strategies (median tuber bank reductions of 57–70%) include intensive black fallow with at least four control timings or winter cereal cropping followed by intensive control (at least three measures) during the stubble phase. Established, fertilized grasslands also offer moderate reductions (17–67%) via intensive grazing or mowing. These results demonstrate that significant C. esculentus reductions are possible across different crops, but control remains challenging, requiring intensive, repeated strategies over multiple years. Less intensive approaches may undermine previous efforts. Full article

Dynamic hydrogels are revolutionizing tumor microenvironment (TME) engineering through their stimuli-responsive adaptability, mechanical tunability, and capacity for multifunctional integration. In addition, they are excellent biomaterials for cancer treatments, including their biomimetic properties and controlled cargo release capability. This review introduces the rational design and principles of dynamic hydrogels for recreating the tumor microenvironment and cancer therapy, including natural/synthetic hydrogels, multi-stimuli responsive hydrogels, and multi-drug loading hydrogels. These designs emphasize their unique roles in overcoming drug resistance, enhancing immunotherapy, and enabling patient-specific models. We highlight breakthroughs such as dual-responsive nanocomposites and microfluidic-integrated 3D platforms while addressing translational hurdles like cytotoxicity and regulatory delays. By proposing strategies to bridge material science with clinical needs, this work positions dynamic hydrogels as pivotal tools for next-generation precision oncology. Full article

Passive transit signal priority (TSP) strategies are widely recognized as effective tools for mitigating bus delays along urban arterials. However, existing TSP models primarily focus on through movements of transit vehicles, leading to potential delays for buses making turning movements. Moreover, these models do not adequately address signal coordination in multi-modal traffic systems involving both buses and private vehicles, resulting in increased delays and frequent stops for private vehicles. To address these limitations, this study proposes a binary mixed-integer linear programming (BMILP)-based signal progression band optimization model designed for multi-modal, path-level signal coordination. The model creates multiple progression bands for both straight and turning buses to minimize potential transit delays and enhance public transport service levels. By incorporating the mutual interactions between buses and private vehicles, progression bands for private vehicles are simultaneously optimized, enabling coordinated signal control that considers all users. The objective function maximizes passenger-equivalent service demand satisfied by the progression bands, explicitly accounting for mixed traffic flows and passenger loads. Numerical experiments on an urban arterial corridor demonstrate that, compared with the benchmark BUSBAND method, the proposed model achieves a 26% reduction in average bus delays, a 37% reduction in passenger car delays, and a 22% decrease in total stops, while also improving overall travel time reliability. Full article

Controlled demolition is a critical engineering practice that enables the safe and efficient dismantling of structures while minimizing risks to the surrounding environment. This study presents, for the first time, a detailed, structured framework for understanding the fundamental principles of controlled demolition by outlining key procedures, methodologies, and directions for future research. Through original, carefully designed charts and full-scale numerical simulations, including two 23-story building scenarios with different delay and blasting sequences, this paper provides real-life insights into the effects of floor-to-floor versus axis-by-axis delays on structural collapse behavior, debris spread, and toppling control. Beyond traditional techniques, this study explores how emerging technologies, such as real-time structural monitoring via object tracking, LiDAR scanning, and Unmanned Aerial Vehicle (UAV)-based inspections, can be further advanced through the integration of artificial intelligence (AI). The potential Deep learning (DL) and Machine learning (ML)-based applications of tools like Convolutional Neural Network (CNN)-based digital twins, YOLO object detection, and XGBoost classifiers are highlighted as promising avenues for future research. These technologies could support real-time decision-making, automation, and risk assessment in demolition scenarios. Furthermore, vision-language models such as SAM and Grounding DINO are discussed as enabling technologies for real-time risk assessment, anomaly detection, and adaptive control. By sharing insights from full-scale observations and proposing a forward-looking analytical framework, this work lays a foundation for intelligent and resilient demolition practices. Full article

Aging is characterized by a progressive decline in physiological function that impairs performance and increases vulnerability to disease and mortality. Delaying this deterioration is key to promoting healthy aging. Age-associated functional decline is closely linked to alterations in intermediary metabolism, including disrupted lipid metabolism and impaired mitochondrial function. Counteracting these metabolic changes, particularly those affecting basal metabolic rate and energy utilization, may be a feasible strategy to extend healthspan. The Renin-Angiotensin System (RAS), which controls blood pressure through Angiotensin II, an octapeptide hormone generated from Angiotensin I by Angiotensin-Converting Enzyme (ACE), has been identified as a potential target for aging therapies. ACE inhibitors, such as the commonly prescribed vasodilator lisinopril, have been shown to exert beneficial effects on healthspan. Disentangling their systemic effects from direct cellular actions on intermediary metabolism is challenging in humans but can be pursued in model organisms. Drosophila melanogaster expresses two ortholog of mammalian ACE, Ance and Acer, which have diverged to acquire different functions. Since fundamental cellular processes are evolutionarily conserved and flies have an open circulatory system, Drosophila provides a versatile model for translational studies on ACE inhibition and aging. Recent studies in Drosophila reveal sex-, age-, and genetic background-specific effects of lisinopril on metabolic rates and aging-related organismal phenotypes. Integrating preclinical findings from Drosophila with clinical studies will be essential to define the therapeutic potential of RAS inhibition in extending lifespan and delaying aging. Full article

The search for natural additives from underutilized halophytes and fruit by-products aligns with circular economy principles, addressing consumer demand for healthier and more sustainable alternatives to salt and synthetic antioxidants in foods. Salicornia ramosissima, a halophytic plant rich in minerals, and Malpighia emarginata (acerola), a fruit rich in bioactive compounds, were selected for their potential to enhance meat preservation while reducing reliance on conventional salt and chemical additives. This study evaluated the effects of replacing salt with S. ramosissima powder (1% and 2%) and adding acerola extract (0.3%) in Mertolenga D.O.P. beef hamburgers. Control, 1% salt, acerola, and salicornia formulations were analyzed over 10 days for the following: (1) microbial counts (mesophiles, psychrotrophics, Enterobacteriaceae, Pseudomonas spp., Brochothrix thermosphacta, lactic acid bacteria, fungi, Salmonella spp., and E. coli); (2) physicochemical parameters (pH, a_w, and CIE-Lab color); and (3) sensory attributes (odor, color, and freshness). Higher Salicornia concentrations negatively affected color (lower a* values) and sensory perception (darker appearance). Acerola extract improved color stability and delayed the development of off-odors, contributing to higher freshness scores throughout storage. No significant differences in microbial counts were observed between treatments. Overall, acerola and low-dose Salicornia showed potential as natural ingredients for meat preservation, with minimal impact on physicochemical and microbiological quality. These findings support the use of halophytes and fruit extracts in sustainable meat preservation strategies. Full article

This article investigates the zonotope-based state estimation for boost converter system with Markov jump process. DC-DC boost converters are pivotal in modern power electronics, enabling renewable energy integration, electric vehicle charging, and microgrid operations by elevating low input voltages from sources like photovoltaics to stable high outputs. However, their nonlinear dynamics and sensitivity to uncertainties/disturbances degrade control precision, driving research into robust state estimation. To address these challenges, the boost converter is modeled as a Markov jump system to characterize stochastic switching, with time delays, disturbances, and noises integrated for a generalized discrete-time model. An adaptive event-triggered mechanism is adopted to administrate the data transmission to conserve communication resources. A zonotopic set-membership estimation design is proposed, which involves designing an observer for the augmented system to ensure $H_{\infty }$ performance and developing an algorithm to construct zonotopes that enclose all system states. Finally, numerical simulations are performed to verify the effectiveness of the proposed approach. Full article

Background: Multimodal analgesia, combining adductor canal block (ACB) and local infiltration analgesia (LIA), is commonly used for pain control after total knee arthroplasty (TKA). However, ACB alone may not fully cover the anteromedial knee, a region extensively disrupted by TKA. Recent studies suggest that blocking branches of the anterior femoral cutaneous nerve (AFCN) could enhance analgesia, but targeted AFCN blocks are technically challenging. We evaluated supra-sartorial subcutaneous infiltration (SSSI) at the femoral triangle apex as a simpler alternative to AFCN blocks. Methods: We retrospectively reviewed 19 patients undergoing TKA with a standardized multimodal analgesic protocol, including intraoperative LIA limited to posterior capsule (PC-LIA), postoperative SSSI, and delayed intermittent ACB via catheter. SSSI involved infiltrating 20 mL of 0.3% ropivacaine into the subcutaneous plane above the sartorius muscle at the level of femoral triangle apex. Pain was assessed using Numerical Rating Scale (NRS) scores at rest and during movement at 9:00 PM on postoperative day 0 (POD 0) and 9:00 AM on POD 1, with scheduled ACB doses administered at the time of NRS pain score assessments. Rescue ACB boluses were given for intolerable pain before the first scheduled dose. Results: Eleven patients (58%) required no rescue analgesia before the first scheduled ACB, maintaining NRS scores ≤ 4 at rest and with movement for a minimum of 575–785 min post-spinal anesthesia. Eight patients needed rescue ACB, with variable pain relief. Conclusions: SSSI, when combined with PC-LIA, provided clinically meaningful analgesia in 58% of our patient cohort following TKA, though the variability observed suggests limited consistency. As a practical alternative to targeted AFCN blocks, SSSI could potentially complement ACB in multimodal pain management, but its efficacy remains uncertain due to the retrospective, non-controlled study design without a comparator group. Further investigation through prospective randomized controlled trials is warranted to validate these preliminary findings. Full article

This study tackles the challenges associated with permanent magnet synchronous motor (PMSM) position control under complex operating conditions—characterized by strong coupling, nonlinearity, and time-varying parameters—which often lead to slow response, low control accuracy, and weak disturbance rejection capability. A high-performance control system is developed based on an active disturbance rejection controller (ADRC), with three key improvements proposed. Firstly, a modified nonlinear function is designed to suppress chattering. Secondly, a delay compensation module is integrated to synchronize the input signals of the extended state observer (ESO). Finally, an automated parameter tuning method is introduced using the Newton-Raphson optimization algorithm. Comparative simulations are conducted to validate the effectiveness of the proposed system, demonstrating its advantages of rapid response, minimal overshoot, and enhanced disturbance rejection capability. For the proposed strategy, the maximum position tracking error is 0.1 rad, the adjustment time is 0.15 s, the dynamic speed drop is 0.025 rad, and the recovery time is 0.15 s—all comprehensive performance indicators outperform those of other control strategies. Additionally, automated parameter tuning eliminates the need for manual adjustments, reduces operational complexity, and improves tuning accuracy, thereby significantly advancing the position control performance of PMSMs. Full article

The growing demand for real-time video streaming in power-constrained embedded systems, such as drone navigation and remote surveillance, requires encoding solutions that prioritize low latency. In these applications, even small delays in video transmission can impair the operator’s ability to react in time, leading to instability in closed-loop control systems. To mitigate this, encoding must be lightweight and designed so that streaming can start as soon as possible, ideally even while frames are still being processed, thereby ensuring continuous and responsive operation. This paper presents the design of a hardware implementation of the Logarithmic Hop Encoding (LHE) algorithm on a Field-Programmable Gate Array (FPGA). The proposed architecture is deeply pipelined and parallelized to achieve sub-frame latency. It employs adaptive compression by dividing frames into regions of interest and uses a quantized differential system to minimize data transmission. Our design achieves an encoding latency of between 1.87 ms and 2.1 ms with a power consumption of only 2.7 W when implemented on an FPGA clocked at 150 MHz. Compared to a parallel GPU implementation of the same algorithm, this represents a 6.6-fold reduction in latency at approximately half the power consumption. These results show that FPGA-based LHE is a highly effective solution for low-latency, real-time video applications and establish a robust foundation for its deployment in embedded systems. Full article