Search Results (434)

As a densely populated area, college student dormitories consume a large amount of electricity every year to heat the domestic hot water used by students. Applying solar energy to hot water systems can effectively alleviate this situation. This paper first conducts a simulation of the hot water load and the calculation of the available area of the solar roof in a dormitory building of a certain university. Then, different solar-coupled air source heat pump systems were designed, and simulation models of the two systems were established. The thermal performance parameters and solar energy utilization of the two systems were discussed, and the energy efficiency, economy, and environmental protection of the two systems were analyzed. The results show that after coupling with the solar collector, the system operation time is shortened by 26.2%, the annual performance coefficient is 3.4, which is 0.8 higher than that of the original system, and the annual heating energy consumption is reduced by 24.4%. In contrast, the annual energy self-sufficiency rate of the photovoltaic coupled with air source heat pump system is 94.6%, achieving nearly zero energy consumption for heating. Full article

Extraterrestrial exploration presents unique challenges for robotic systems, as traditional rigid rovers face limitations in stowage volume, traction on unpredictable terrain, and susceptibility to damage. Soft robotics offers promising solutions through bio-inspired designs that can mimic natural locomotion mechanisms. Here, we present an optimised, spider-inspired soft jumping robot for extraterrestrial exploration that addresses key challenges in soft robotics: actuation efficiency, controllability, and deployment. Drawing inspiration from spider physiology—particularly their hydraulic extension mechanism—we develop a lightweight limb capable of multi-modal behaviour with significantly reduced energy requirements. Our 3D-printed soft actuator leverages pressure-driven collapse for efficient retraction and pressure-enhanced rapid extension, achieving a power-to-weight ratio of 249 W/kg. The integration of a non-backdriveable clutch mechanism enables the system to hold positions with zero energy expenditure—a critical feature for space applications. Experimental characterisation and a subsequent optimisation methodology across various materials, dimensions, and pressures reveal that the robot can achieve jumping heights of up to 1.86 times its body length. The collapsible nature of the soft limb enables efficient stowage during spacecraft transit, while the integrated pumping system facilitates self-deployment upon arrival. This work demonstrates how biologically inspired design principles can be effectively applied to develop versatile robotic systems optimised for the unique constraints of extraterrestrial exploration. Full article

The aircraft fuel pump is a critical component of the aviation fuel supply system, and its fault diagnosis is essential in ensuring flight safety. However, in practical operating conditions, fault samples are scarce and data distributions are highly imbalanced, which severely limits the ability of traditional models to identify minority-class faults. To address this challenge, this paper proposes a fault diagnosis method for aircraft fuel pumps based on adaptive synthetic data augmentation using a Conditional Variational Autoencoder (CVAE). The CVAE generates semantically consistent and feature-diverse minority-class samples under class-conditional constraints, thereby enhancing the overall representational capacity of the dataset. Simultaneously, the Adaptive Synthetic (ADASYN) approach adaptively augments hard-to-classify samples near decision boundaries, enabling fine-grained control over sample distribution. The integration of these two techniques establishes a “broad coverage + focused refinement” augmentation strategy, effectively mitigating the class imbalance problem. Experimental results demonstrate that the proposed method significantly improves the recognition performance of minority-class faults on real-world aircraft fuel pump fault datasets. Full article

Optically pumped semiconductor disk lasers—known as vertical-external-cavity surface-emitting lasers (VECSELs)—are promising devices for ultrashort pulse formation. For it, a “SESAM-free” approach labeled “self-mode-locking” received considerable attention in the past decade, relying solely on a chip-related nonlinear optical property which can establish adequate pulsing conditions—thereby suggesting a reduced reliance on a semiconductor saturable-absorber mirror (the SESAM) in the cavity. Self-mode-locked (SML) VECSELs with sub-ps pulse durations were reported repeatedly. This motivated investigations on a Kerr-lensing type effect acting as an artificial saturable absorber. So-called Z-scan and ultrafast beam-deflection experiments were conducted to emphasize the role of nonlinear lensing in the chip for pulse formation. Recently, in addition to allowing stable ultrashort pulsed operation, self-starting mode-locked operation gave rise to another emission regime related to frequency comb formation. While amplitude-modulated combs relate to signal peaks in time, providing a so-called pulse train, a frequency-modulated comb is understood to cause quasi continuous-wave output with its sweep of instantaneous frequency over the range of phase-locked modes. With gain-bandwidth-enhanced chips, as well as with an improved understanding of the impacts of dispersion and nonlinear lensing properties and cavity configurations on the device output, an enhanced employment of SML VECSELs is to be expected. Full article

Background/Objectives: Effective diabetes self-management is critical for glycemic management and well-being, yet Latino youth face unique cultural and socioeconomic barriers that are insufficiently explored in the literature. This review mapped existing evidence on diabetes self-management for Latino youth. Methods: Searches were conducted in PubMed, CINAHL, SCOPUS, Web of Science, LILACS, ERIC, and The Cochrane Library, using the gray literature and reference lists, in September 2024, following JBI guidelines. The included studies were qualitative, quantitative, and mixed-methods studies and reviews on diabetes self-management for Latinos aged 0–30 with type 1 or 2 diabetes. Studies including participants over 30 or with gestational diabetes were excluded. Two reviewers independently extracted data using a standardized table and analyzed findings using the Association of Diabetes Care & Education Specialists framework (ADCES7) for self-care behaviors: healthy eating, being active, monitoring, taking medication, problem-solving, reducing risks, and healthy coping. Results: Forty-five studies (forty from the United States) were included from 860 citations. The findings highlighted challenges in adopting diabetes-friendly diets, including cultural preferences, food insecurity, and limited resources. Physical activity improved glycemic control but was hindered by family and school obligations. Continuous glucose monitoring (CGM) enhanced outcomes, though economic barriers limited access. Family-centered education improved medication adherence, while family support strengthened problem-solving. CGMs and insulin pumps reduced complications, and culturally adapted psychological support enhanced emotional well-being and glycemic management. Conclusions: This review underscores persistent disparities in diabetes self-management among Latino youth. While the study designs and settings were heterogeneous, the findings highlight the need for culturally tailored, family-centered interventions that address structural barriers and psychosocial needs to improve care. Full article

Background/Objectives: Up to 25–70% of proton-pump inhibitor (PPI) prescriptions worldwide lack an evidence-based indication, exposing patients to avoidable adverse events and unnecessary costs. Community pharmacists (CPs) are well-equipped to curb the misuse of PPIs. This study aimed to quantify CPs’ knowledge, attitudes, and practices (KAPs) regarding PPIs in two high-use Middle-Eastern markets and determine how demographic and professional factors influence guideline-adherent PPI use. Bridging this gap is crucial to ensure pharmacists can promote rational PPI use, provide accurate patient counseling, and reduce the likelihood of adverse outcomes. Methods: An online cross-sectional survey was undertaken between May 2024 and July 2024 to investigate the KAPs of CPs in Egypt and Iraq toward PPI use. The self-developed thirty-item questionnaire (17 knowledge, 11 attitude, and 6 practice items) was piloted with 30 CPs. A sample size of 385 CPs was required based on an estimated 93,000 community pharmacists in Egypt and 22,120 in Iraq; however, to improve statistical power, we aimed to include >500 CPs. Results: A total of 527 CPs from Egypt and Iraq completed the survey. The total median scores for knowledge, attitude, and practice were 11 out of 17 (IQR: 9–16), 9 out of 11 (IQR: 6–12), and 5 out of 6 (IQR: 3–8), respectively. CPs with >20 years of experience and those who relied on clinical guidelines as a primary information source demonstrated a median knowledge score significantly higher than those with fewer years of experience (p = 0.001 and 0.028, respectively). There was a significant positive association between knowledge and attitude, knowledge and practice, and attitude and practice scores (coefficients: 0.832, 0.701, and 0.445, respectively). Conclusions: Although their attitudes and practices regarding PPI use were satisfactory, the knowledge of CPs about the judicious use of PPIs requires improvement. Thus, a call for action targeting their tailored education and training is necessary to address these knowledge gaps regarding PPIs identified, including PPI adverse-effect profiles, evidence-based indications, and deprescribing criteria, and to foster informed medication attitudes and practices. Such education and training can reinforce guideline adherence, enhance patient counseling skills, and ultimately reduce inappropriate PPI use. Full article

We report a passively Q-switched self-Raman laser using a dual-end composite c-cut Nd:YVO₄ crystal, which generates switchable visible emissions at 533 nm, 560 nm, and 589 nm. A Cr⁴⁺:YAG/YAG composite crystal served the role of a saturable absorber to achieve passive Q-switching. An angle-tuned BBO crystal was used to achieve the frequency mixing between the first-tokes wave and the fundamental wave. At an incident pump power of 9.5 W, the maximum average output powers were 425 mW for the 589 nm yellow laser, 193 mW for the 560 nm lime laser, and 605 mW for the 533 nm green laser, with corresponding pulse widths of approximately 3.8, 3.6, and 35.1 ns, respectively. This result shows that a passive Q-switching operation with self-Raman crystals presents a promising approach for compact multi-wavelength pulse laser sources. Full article

In this study, we present a comprehensive numerical investigation of alternating-current electrothermal (ACET) pumping strategies tailored for energy-efficient microfluidic applications. Using coupled electrokinetic and thermal multiphysics simulations in narrow microchannels, we systematically explore the effects of channel geometry, electrode asymmetry and external heating on flow performance and thermal management. A rigorous mesh convergence study confirms velocity deviations below ±0.006 µm/s across the entire operating envelope, ensuring reliable prediction of ACET-driven flows. We demonstrate that increasing channel height from 100 µm to 500 µm reduces peak temperatures by up to 79 K at a constant 2 W heat input, highlighting the critical role of channel dimensions in convective heat dissipation. Introducing a localized external heat source beneath asymmetric electrode pairs enhances convective circulations, while doubling the fluid’s electrical conductivity yields a ~29% increase in net flow rate. From these results, we derive practical design guidelines—combining asymmetric electrode layouts, tailored channel heights, and external heat bias—to realize self-regulating, low-power microfluidic pumps. Such devices hold significant promises for on-chip semiconductor cooling, lab-on-a-chip assays and real-time thermal control in high-performance microelectronic and analytical systems. Full article

The European Union’s 2050 targets for decarbonization and electrification are promoting the widespread integration of heat pumps for space heating, cooling, and domestic hot water in buildings. However, their energy and environmental performance can be significantly compromised by soft faults, such as refrigerant leakage or heat exchanger fouling, which may reduce system efficiency by up to 25%, even with maintenance intervals every two years. As a result, the implementation of self-fault detection, diagnosis, and evaluation (FDDE) tools based on operational data has become increasingly important. The complexity and added value of these tools grow as they progress from simple fault detection to quantitative fault evaluation, enabling more accurate and timely maintenance strategies. Direct fault measurements are often unfeasible due to spatial, economic, or intrusiveness constraints, thus requiring indirect methods based on low-cost and accessible measurements. In such cases, overlapping fault symptoms may create diagnostic ambiguities. Moreover, the accuracy of FDDE approaches depends on the type and number of sensors deployed, which must be balanced against cost considerations. This paper provides a comprehensive review of current FDDE methodologies for heat pumps, drawing insights from the academic literature, patent databases, and commercial products. Finally, the role of artificial intelligence in enhancing fault evaluation capabilities is discussed, along with emerging challenges and future research directions. Full article

To improve hydrodynamic conditions and self-purification in plain river networks, this study optimized an existing hydrofoil-based pumping device and redesigned its flow channel. Using the finite volume method (FVM) and overset grid technique, a comparative numerical analysis was conducted on the pumping performance of hydrofoils operating under simple harmonic and quasi-harmonic flapping motions. Based on the tip vortex phenomenon observed at the channel outlet, the flow channel structure was further designed to inform the structural optimization of bionic pumping devices. Results show both modes generate reversed Kármán vortex streets, but the quasi-harmonic mode induces a displacement in vorticity distribution, whereas that of the simple harmonic motion extends farther downstream. Pumping efficiency under simple harmonic motion consistently outperforms that of quasi-harmonic motion, exceeding its peak by 20.2%. The pumping and propulsion efficiencies show a generally positive correlation with the outlet angle of the channel, both reaching their peak when the outlet angle α is −10°. Compared to an outlet angle of 0°, an outlet angle of −10° results in an 8.5% increase in pumping efficiency and a 10.2% increase in propulsion efficiency. Full article

The aim of this study was to evaluate machine learning algorithms’ capacity to improve prescriptive maintenance. A pumping system consisting of two hydraulic pumps with an electric motor from a Spanish petrochemical company was used as a case study. Sensors were used to record data on the variables, with the target variable being the bearing temperature of the electric motor. Several regression models and a neural network time series model were tested to model the system variables. A bearing temperature sensitivity analysis was conducted based on the coefficients obtained from the optimization of the regression model. To fully exploit the capabilities of these techniques for application in this field, we designed a reference framework intended to foster model deployment in an industrial context by promoting the self-monitoring and updating of the models when required. The impact on decision-making processes is explored using reinforcement learning in the context of this framework. Full article

Gas bubbles are one of the main disturbances encountered when dispensing drugs of microliter volumes using portable miniaturized systems based on piezoelectric diaphragm micropumps. The presence of a gas bubble in the pump chamber leads to the inaccurate administration of the required dose due to its impact on the flowrate. This is particularly important for highly concentrated drugs such as insulin. Different types of sensors are used to detect gas bubbles: inline on the fluidic channels or inside the pump chamber itself. These solutions increase the complexity, size, and cost of the microdosing system. To address these problems, a radically new approach is taken by utilizing the sensing capability of the piezoelectric diaphragm during micropump actuation. This work demonstrates the workflow to build a self-sensing micropump based on artificial intelligence methods on an embedded system. This is completed by the implementation of an electronic circuit that amplifies and samples the loading current of the piezoelectric ceramic with a microcontroller STM32G491RE. Training datasets of 11 micropumps are generated at an automated testbench for gas bubble injections. The training and hyper-parameter optimization of artificial intelligence algorithms from the TensorFlow and scikit-learn libraries are conducted using a grid search approach. The classification accuracy is determined by a cross-training routine, and model deployment on STM32G491RE is conducted utilizing the STM32Cube.AI framework. The finally deployed model on the embedded system has a memory footprint of 15.23 kB, a runtime of 182 µs, and detects gas bubbles with an accuracy of 99.41%. Full article

The transition toward sustainable and decentralized energy solutions necessitates the development of innovative bioelectronic systems capable of harvesting and converting renewable energy. Here, we present a novel photo-bioelectrochemical fuel cell architecture based on a biohybrid anode integrating laser-induced graphene (LIG), poly(3,4-ethylenedioxythiophene) (PEDOT), and isolated thylakoid membranes. LIG provided a porous, conductive scaffold, while PEDOT enhanced electrode compatibility, electrical conductivity, and operational stability. Compared to MXene-based systems that involve complex, multi-step synthesis, PEDOT offers a cost-effective and scalable alternative for bioelectrode fabrication. Thylakoid membranes were immobilized onto the PEDOT-modified LIG surface to enable light-driven electron generation. Electrochemical characterization revealed enhanced redox activity following PEDOT modification and stable photocurrent generation under light illumination, achieving a photocurrent density of approximately 18 µA cm⁻². The assembled photo-bioelectrochemical fuel cell employing a gas diffusion platinum cathode demonstrated an open-circuit voltage of 0.57 V and a peak power density of 36 µW cm⁻² in 0.1 M citrate buffer (pH 5.5) under light conditions. Furthermore, the integration of a charge pump circuit successfully boosted the harvested voltage to drive a low-power light-emitting diode, showcasing the practical viability of the system. This work highlights the potential of combining biological photosystems with conductive nanomaterials for the development of self-powered, light-driven bioelectronic devices. Full article

Breast cancer remains a leading cause of cancer-related morbidity and mortality among women worldwide. Its treatment is complicated by molecular heterogeneity and the frequent development of multidrug resistance (MDR). Conventional drug delivery approaches are often limited by poor aqueous solubility, rapid systemic clearance, non-specific biodistribution, and off-target toxicity. This review will critically explore the possibility of surfactant-based drug delivery systems (DDSs) in addressing the constraints of standard breast cancer treatments. It focuses on the mechanisms by which surfactants promote solubility, facilitate cellular uptake, and overcome drug resistance, while also analyzing current therapeutic success and future directions. A thorough review of preclinical and clinical investigations was undertaken, focusing on important surfactant-based DDSs such as polymeric micelles, nanoemulsions, liposomes, and self-emulsifying systems (SEDDSs). Mechanistic insights into surfactant functions, such as membrane permeabilization and efflux pump inhibition, were studied alongside delivery systems incorporating ligands and co-loaded medicines. Pluronic^® micelles, TPGS-based systems, biosurfactant-stabilized nanoparticles, and lipid-based carrier surfactant platforms improve medication solubility, stability, and delivery. Genexol^® are examples of formulations demonstrating effective use and FDA translational potential. These systems now incorporate stimuli-responsive release mechanisms—such as pH, temperature, redox, immuno- and photodynamic treatment—artificial intelligence treatment design, and tailored treatment advancement, and responsive tailoring. Surfactant-enabled DDSs can improve breast cancer care. Innovative approaches for personalized oncology treatment are countered by the enduring challenges of toxicity, regulatory hurdles, and diminished scalability. Full article

This paper presents a Virtualized Computational Radio Frequency Identification (VCRFID) solution that utilizes far-field UHF RF for sensing, computing, and self-powering at the edge. A standard UHF RFID system is asymmetric as it consists of a relatively large, complex “reader”, which acts as an RF transmitter and controller for a number of small simple battery-less “tags”, which work in passive mode as they communicate and harvest RF energy from the reader. Previously proposed Computational RFID (CRFID) solutions enhance the standard RFID tags with microcontrollers and sensors in order to gain enhanced functionality, but they end up requiring a relatively high level of power, and thus ultimately reduced range, which limits their use for many Internet-of-Things (IoT) application scenarios. Our VCRFID solution instead keeps the functionality of the tags minimalistic by only providing a sensor interface to be able to capture desired environmental data (temperature, humidity, vibration, etc.), and then transmit it to the RFID reader, which then performs all the computational load usually carried out by a microcontroller on the tag in prior work. This virtualization of functions enables the design of a circuit without a microcontroller, providing greater flexibility and allowing for wireless reconfiguration of tag functions over RF for a 97% reduction in energy consumption compared to prior energy-harvesting RFID tags with microcontrollers. The target application is Industry 4.0 where our VCRFID solution enables battery-less fine-grain monitoring of vibration and temperature data for pumps and motors for predictive maintenance scenarios. Full article