Capability Of System Research Articles

Advances in Intelligent Sports Based on Triboelectric Nanogenerators

In the realm of intelligent sports, the integration of triboelectric nanogenerators (TENGs) marks a transformative approach toward energy sustainability and more advanced athletic monitoring. By leveraging the principle of triboelectricity, TENGs ingeniously convert mechanical energy from athletes’ movements into electrical energy, which offers a green and efficient power solution for wearable technology. This paper presents an innovative study on the application of TENG technology in sports science, with the results illustrating the potential utility of TENGs in revolutionizing the way we monitor, analyze, and enhance athletic performance. Through the development of self-powered wearables and equipment, TENGs facilitate real-time data collection on physiological and biomechanical parameters, ultimately enabling personalized training adjustments and injury prevention strategies. Our findings underscore the dual benefit of TENGs in promoting environmental sustainability by reducing the overall reliance on traditional energy sources and growing the capabilities of intelligent sports systems. This research contributes to the burgeoning field of nano-energy sports applications while setting the stage for future explorations into the optimization of TENG integration in athletic performance enhancement. Finally, the paper concludes by discussing remaining challenges in this area and opportunities for further research.

A facile method to fabricate cell‐laden hydrogel microparticles of tunable sizes using thermal inkjet bioprinting

AbstractThis study investigates the application of a drop‐on‐demand (DOD) thermal inkjet (TIJ)‐based bioprinting system for the fabrication of cell‐laden hydrogel microparticles (HMPs) with tunable sizes. The TIJ bioprinting technique involves the formation of vapor bubbles within the print chamber through thermal energy, expelling small droplets of bio‐ink onto a substrate. The study employs a heat‐treated saponified gelatin‐based bio‐ink, HSP‐GelMA. This bio‐ink is modified through methacrylic anhydride functionalization and undergoes subsequent saponification and heat treatment processes. Various concentrations of SPAN 80 surfactant in mineral oil were evaluated to assess their influence on HMP size and stability. The results indicate a direct correlation, with higher SPAN 80 concentrations resulting in smaller and more stable HMPs. The study further investigates the influence of jetting volume on HMP size distribution, revealing that larger jetting volumes lead to increased HMP sizes, attributed to droplet coalescence. This is supported by our further study via a Monte Carlo simulation, which shows that the mean droplet diameter grows approximately linear with the number of dispensed droplets. In addition, the study demonstrates the capability of the TIJ bioprinting system to achieve multimaterial encapsulation within HMPs, exemplified by staining living cells with distinct cytoplasmic membrane dyes. The presented approach provides insights into the controlled fabrication of cell‐laden HMPs, highlighting the versatility of the TIJ bioprinting system for potential applications in tissue engineering and drug delivery.

Research on the Design of Multi-Rope Friction Hoisting System of Vertical Shaft Gravity Energy Storage System

Renewable energy generation methods such as wind power and photovoltaic power have problems of randomness, intermittency, and volatility. Gravity energy storage technology can realize the stable and controllable conversion of gravity potential energy and electric energy by lifting and lowering heavy loads. The hoisting system is an important component of a gravity energy storage system, and its lifting capacity and speed seriously restrict its energy storage capacity, energy conversion efficiency, and operational safety and reliability. In this paper, a design method for a multi-rope friction hoisting system of a vertical shaft gravity energy storage system is proposed. The parameter design and calculation of the hoisting rope, balance rope, and friction wheel of the friction hoisting system under typical conditions were carried out. The static and dynamic anti-slip capabilities of the friction hoisting system under the typical condition were explored. The results show that the maximum acceleration and deceleration speed of the compacted strand wire rope scheme is the largest, and the lifting and lowering time is the shortest. The maximum acceleration and deceleration speed of the triangular strand wire rope scheme is the lowest, and the lifting and lowering time is the longest. The dynamic tension of the hoisting rope at the heavy-load end is positively correlated with the acceleration, and the maximum value occurs in the accelerated lifting stage and decelerated lowering stage of the heavy load. The static anti-slip safety factor between the hoisting rope and the friction lining and the specific pressure between the hoisting rope and the friction lining comply with the requirements of China’s Safety Regulations for Coal Mines. The dynamic anti-slip safety factor of the hoisting system under different rope selection schemes is greater than the minimum value of 1.25 stipulated in the Safety Regulations for Metal and Nonmetal Mines. The research results are of great significance for the safety, reliability, and stable and efficient energy storage of a gravity energy storage system.

How to choose mobile energy storage or fixed energy storage in high proportion renewable energy scenarios: Evidence in China

With the large-scale integration of renewable energy and changes in load characteristics, the power system is facing challenges of volatility and instability. Therefore, enhancing the safe and stable operation capability of the power system is an urgent problem that needs to be solved. Mobile energy storage can improve system flexibility, stability, and regional connectivity, and has the potential to serve as a supplement or even substitute for fixed energy storage in the future. However, there are few studies that comprehensively evaluate the operational performance and economy of fixed and mobile energy storage systems. To comprehensively evaluate the economic benefits of large-scale mobile energy storage systems, this paper constructs an overall horizontal cost model for energy storage systems that considers the power system and train transportation system. This model not only introduces the traditional concept of lifecycle cost of energy storage systems, but also considers the costs of traditional transmission lines and battery transportation. Secondly, to achieve simulation of large-scale mobile energy storage system planning and operation, this paper establishes a multi-region power planning and operation simulation (MPO) model and a battery transportation and logistics (BTL) model to accurately reflect the operation mode of fixed energy storage and mobile energy storage in the power system. Finally, taking the actual power grids and railway networks in Northeast and North China as case studies, this article provides an in-depth analysis of the technical, economic, and environmental performance of large fixed and mobile energy storage systems, and conducts a detailed comparison. The research results indicate that under high grid connection ratios (using 75% and 66% as examples), the overall cost of mobile energy storage systems continues to decrease to 1.42 CNY/kWh and 0.98 CNY/kWh. Compared to fixed energy storage at 5.45 CNY/kWh and 4.79 CNY/kWh, it has an absolute economic advantage and shows significant carbon reduction capabilities, reaching 241,800 to 1,394,600 tons. This discovery fully confirms the enormous potential and application value of mobile energy storage in high proportion renewable energy scenarios, providing strong technical support and economic analysis basis for the sustainable development of the power system.

Advancing Refugee Health Data Management: The Implementation of ICD-11 in UNRWA's Primary Care System.

The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) was one of the earliest healthcare systems globally to implement the International Classification of Diseases, Eleventh Revision (ICD-11) across its 140 clinics serving 5.9 million Palestine refugees. This paper discusses the integration of ICD-11 into UNRWA's cloud-based electronic medical record (EMR) system, identifying both the barriers and facilitators involved and analyzing trends in clinical documentation and healthcare utilization. The key challenges included data privacy provisions, integration into a coordinated care model, complex classification schema for primary care settings, frequent staff turnover, and limited data analysis capabilities. Conversely, facilitators included physician-tailored training and on-site support, system compatibility, a multidisciplinary team approach, policy support from UNRWA and the World Health Organization (WHO), and leadership commitment and effective change management. Medical officers (MOs) using ICD-11 reported greater satisfaction with the system's capabilities in managing and visualizing health information. This article contributes to the discourse on health data management in complex humanitarian settings, offering insights into the benefits and challenges of implementing advanced classification systems like ICD-11. Future research should explore longitudinal impacts and further integration with global health systems, ensuring that the advancements in classification continue to support the overarching goal of health equity and access in vulnerable and hard-to-reach populations.

Intelligent Gesture Recognition Based on Screen Reflectance Multi-Band Spectral Features.

Human-computer interaction (HCI) with screens through gestures is a pivotal method amidst the digitalization trend. In this work, a gesture recognition method is proposed that combines multi-band spectral features with spatial characteristics of screen-reflected light. Based on the method, a red-green-blue (RGB) three-channel spectral gesture recognition system has been developed, composed of a display screen integrated with narrowband spectral receivers as the hardware setup. During system operation, emitted light from the screen is reflected by gestures and received by the narrowband spectral receivers. These receivers at various locations are tasked with capturing multiple narrowband spectra and converting them into light-intensity series. The availability of multi-narrowband spectral data integrates multidimensional features from frequency and spatial domains, enhancing classification capabilities. Based on the RGB three-channel spectral features, this work formulates an RGB multi-channel convolutional neural network long short-term memory (CNN-LSTM) gesture recognition model. It achieves accuracies of 99.93% in darkness and 99.89% in illuminated conditions. This indicates the system's capability for stable operation across different lighting conditions and accurate interaction. The intelligent gesture recognition method can be widely applied for interactive purposes on various screens such as computers and mobile phones, facilitating more convenient and precise HCI.

In situ tracking anisotropic photocarrier dynamics in two-dimensional ternary Ta2NiSe5 via digital micromirror device-based pump-probe microscopy

In two-dimensional (2D) material studies, tracking the anisotropic ultrafast carrier dynamics is essential for the development of optoelectronic nano-devices. Conventionally, the anisotropic optical and electronic properties are investigated via either polarization-dependent Raman spectroscopy or field-effect transistors measurements. However, study of the anisotropic transient carrier behaviors is still challenging, due largely to the lack of picosecond-resolved acquisition or programmable scanning capabilities in the current characterization systems. In this work, we select Ta2NiSe5 as a model system to investigate the ultrafast anisotropic transportation properties of photo-excited carriers and transient polarized responses via a digital micromirror device (DMD)-based pump-probe microscope, where the probe beam scans along the armchair and zigzag directions of a crystal structure via binary holography to obtain distinct carrier diffusion coefficients, respectively. The results reveal the nonlinear diffusion behaviors of Ta2NiSe5 in tens of picoseconds, which are attributed to the interplay between excited electrons and phonons. The trend of the measured local polarization-dependent transient reflectivity is consistent with the polarized Raman spectra results. These results show that the DMD-based pump-probe microscope is an effective and versatile tool to study the optoelectronic properties of 2D materials.

Feasibility study of fast-ion velocity-space tomography in KSTAR via phantom tests

The fast-ion velocity distribution function is crucial for understanding fast-ion behavior and transport in future burning plasmas. However, direct measurements of this distribution are difficult due to its high-dimensional nature, necessitating inference from diagnostic data. To infer fast-ion velocity distributions in KSTAR experimental conditions, we explored the feasibility of using measurements from fast-ion Dα (FIDA) diagnostics. We assessed the reconstruction quality for two phantoms, representing a possible fast-ion distribution scenario and local velocity-space structures. We calculated the phase-space weight function of FIDA measurements, required for tomographic inversion, by modeling the measurements, and also developed a tomography code with Phillips–Tikhonov regularization. The phantom test results revealed limitations in the reconstruction capability of current FIDA systems in KSTAR, particularly near low-pitch regions. We also identified the influence of spatial bias of the weight function of the current FIDA systems. Introducing a new FIDA system to tomographic inversion process provided wider coverage in velocity space and the weight function with reduced spatial bias, thereby improving reconstruction capability, especially in low-pitch regions. We also scanned noise levels in the phantom tests and observed the benefits of using prior information to mitigate degradation of the reconstruction quality caused by noise.

Optimization of crashworthiness design of foam-filled crash boxes under oblique loading for electric vehicles

To increase the energy-absorbing capability of frontal collision management systems and improve vehicle crash safety, foam-filled crash boxes should be optimized. On the basis of a double tubular construction, a novel foam-filled crash box with a different design is developed. The energy absorption capacity, initial peak force, and deformation modes of the original and improved crash boxes were examined using impact models. As opposed to the full-filling design, it is demonstrated that the filling design may utilize less foam while increasing specific energy absorption. The stability of continuing deformation after the first buckling is determined by the foam-filled crash box. For the foam-filled crash box, a better-optimized design technique is suggested using the Taguchi method and principal component analysis (PCA). Compression tests are used to validate the design concept. Therefore, the optimal design technique of the crash box is suitable and practical for the crashworthiness design of crash boxes, considering the combined effect of significant indicators for electric vehicles.

An optimal design of battery thermal management system with advanced heating and cooling control mechanism for lithium-ion storage packs in electric vehicles

Battery thermal management is crucial for the efficiency and longevity of energy storage systems. Thermoelectric coolers (TECs) offer a compact, reliable, and precise solution for this challenge. This study proposes a system that leverages TECs to actively regulate temperature and dissipate heat using transformer oil, known for its excellent thermal conductivity and electrical insulation properties. A thermal management system utilizing liquid immersion cooling was developed, providing both cooling and heating functionalities. The system was tested on a 48 V 26 Ah NMC Li-ion battery pack at charging rates of 0.5C and discharging rates of 0.5C and 1C. Maximum temperatures recorded were: natural convection (NC) at 42.8 °C and 54.9 °C, forced convection (FC) at 33.2 °C and 45.2 °C, and liquid immersion cooling (LIC) at 29.3 °C and 37.7 °C. LIC significantly lowered temperatures compared to NC and FC, while maintaining acceptable misbalance and capacity levels. Additionally, the liquid immersion heating setup effectively heated the battery from −25 °C to 0 °C before charging, demonstrating the system's capability to maintain optimal battery performance.

An intelligent garment for long COVID-19 real-time monitoring

As monitoring and diagnostic tools for long COVID-19 cases, wearable systems and supervised learning-based medical image analysis have proven to be useful. Current research on these two technical roadmaps has various drawbacks, despite their respective benefits. Wearable systems allow only the real-time monitoring of physiological parameters (heart rate, temperature, blood oxygen saturation, or SpO2). Therefore, they are unable to conduct in-depth investigations or differentiate COVID-19 from other illnesses that share similar symptoms. Medical image analysis using supervised learning-based models can be used to conduct in-depth analyses and provide precise diagnostic decision support. However, these methods are rarely used for real-time monitoring. In this regard, we present an intelligent garment combining the precision of supervised learning-based models with real-time monitoring capabilities of wearable systems. Given the relevance of electrocardiogram (ECG) signals to long COVID-19 symptom severity, an explainable data fusion strategy based on multiple machine learning models uses heart rate, temperature, SpO2, and ECG signal analysis to accurately assess the patient's health status. Experiments show that the proposed intelligent garment achieves an accuracy of 97.5 %, outperforming most of the existing wearable systems. Furthermore, it was confirmed that the two physiological indicators most significantly affected by the presence of long COVID-19 were SpO2 and the ST intervals of ECG signals.

A compact meta-learned neuro-fuzzy technique for noise-robust nonlinear control

Neuro-fuzzy systems show promise for adaptive control but can become complex due to the need to learn many parameters. This paper presents a resilient nonlinear controller that combines a simplified neuro-fuzzy system (Simp_NFS) and simplified neural network (Simp_NN) with only two meta-learnable parameters. This architecture enables fast and stable adaptation in uncertain nonlinear discrete-time systems. Simp_NFS utilizes interpretable hyperplane-based rules without antecedent parameters, simplifying the learning process to consequent weights. Simp_NN reduces complexity by replacing hidden-output weights with their mean. The hybrid auto-adaptive controller (HAC) combines the advantages of Simp_NFS and Simp_NN, significantly reducing the number of adaptive parameters compared to standard neuro-fuzzy methods for real-time control with limited resources. Simp_NFS provides structural adaptivity to handle uncertainties, while Simp_NN ensures reliable disturbance attenuation. The stability of HAC is proven using Lyapunov analysis. Extensive testing on challenging single-input single-output (SISO) and multi-input multi-output systems (MIMO) demonstrates that HAC improves performance by up to 82.55% compared to existing techniques. Key innovations include an ultra-compact meta-learned architecture, transparent online evolution of hyperplane clusters, and enhanced modeling capability for nonlinear uncertain systems. This interpretable neuro-fuzzy approach could enhance autonomy and safety by maintaining model transparency. The implementation of HAC is publicly available on GitHub at https://github.com/m-ferdaus/HAC.

An improved histogram algorithm for DOA estimation based on single vector acoustic system

The integration of a singular vector acoustic system onto an unmanned underwater platform can lead to achieving unambiguous direction finding across the entire space. To enhance the direction-finding capabilities of the single vector acoustic system for low noise target, a refined histogram algorithm utilizing coherent spectrum weighting is suggested. A comparative evaluation and analysis of the target azimuth estimation performance of the enhanced histogram algorithm, traditional frequency-weighted histogram algorithm, and energy-weighted histogram algorithm are carried out. Through computer simulations, it is observed that the three Direction of Arrival (DOA) algorithms exhibit comparable direction-finding capabilities for wideband signals, whereas for single-frequency signals, the improved histogram algorithm surpasses the two conventional algorithms in direction-finding accuracy. Specifically, at a signal-to-noise ratio (SNR) of −40 dB, the azimuth estimation root mean square error (RMSE) is approximately 2°. Findings from sea trials indicate that the improved histogram algorithm displays a narrower spectral peak width and robust resistance to noise interference, thereby substantiating the effectiveness of the enhanced histogram algorithm.

An assessment methodology for the flexibility capacity of new power system based on two-stage robust optimization

The inherent variability in wind and solar power output presents a significant challenge to the flexibility balance of power systems. This paper introduces an innovative method for evaluating the flexibility capacity of a new power system, employing a two-stage robust optimization approach. Firstly, a power system flexibility supply and demand balance mechanism model is constructed and quantitatively characterized for the power system flexibility shortfalls set. Subsequently, taking into account timescale characteristics and directionality, the time series production simulation technique is applied to establish the effective ramping and flexibility supply distribution model of thermal power and energy storage units, enabling an analysis of the power system's supply regulation capabilities. On this basis, a power system flexibility capacity assessment method is proposed, which divides the system regulation resources into demand set and supply set, and constructs a power system flexibility capacity assessment model to ensure that the maximum system flexibility margin and the lowest operating cost are taken as the optimization objectives under the system security operation constraints. The column and constraint generation (C&CG) robust optimization algorithm is used to decompose the master problem and the max-min dual-layer subproblems for iterative solving, and the optimal capacity of each unit of the system in terms of output and flexibility is derived. Finally, the effectiveness and superiority of the proposed method is verified through case analysis, which shows that the method can improve the flexibility capacity by 14.9% and reduce the operating cost by 15.83% compared with the traditional proportional allocation method.

A magnetic plucking frequency up-conversion piezoelectric energy harvester with nonlinear energy sink structure

In low and wide frequency vibration environments, the efficiency of vibration energy harvesters is relatively low. This paper presents a magnetic plucking frequency-up-conversion bistable Piezoelectric Energy Harvester (PEH) that features a Nonlinear Energy Sink (NES) structure for low and wide frequency vibration absorption. Based on the Euler-Bernoulli stepped beam theory, a theoretical model was derived from the Lagrange equation. The system's bandwidth and power generation capability were analyzed through frequency sweeping. This study thoroughly investigated the up-conversion working mechanism of the NES magnetically plucked PEH super-harmonic vibration. The results reveal that the system encompasses two power generation frequency bands: interwell periodic vibration and chaotic vibration. Under an excitation acceleration of 0.25 g, the interwell periodic vibration range during forward frequency sweep is from 3.30 to 4.31 Hz with an average power of 4.71 mW, and during reverse sweep, it is from 2.02 to 4.05 Hz with 2.43 mW. The coordination between NES and PEH is one of the crucial factors affecting power generation. Frequency mismatch can lead to asymmetrical displacement and alternating strong-weak voltage outputs.

Turn-table micro-CT scanner for dynamic perfusion imaging in mice: design, implementation, and evaluation

Objective.This study introduces a novel desktop micro-CT scanner designed for dynamic perfusion imaging in mice, aimed at enhancing preclinical imaging capabilities with high resolution and low radiation doses.Approach.The micro-CT system features a custom-built rotating table capable of both circular and helical scans, enabled by a small-bore slip ring for continuous rotation. Images were reconstructed with a temporal resolution of 3.125 s and an isotropic voxel size of 65µm, with potential for higher resolution scanning. The system's static performance was validated using standard quality assurance phantoms. Dynamic performance was assessed with a custom 3D-bioprinted tissue-mimetic phantom simulating single-compartment vascular flow. Flow measurements ranged from 1.51to 9 ml min-1, with perfusion metrics such as time-to-peak, mean transit time, and blood flow index calculated.In vivoexperiments involved mice with different genetic risk factors for Alzheimer's and cardiovascular diseases to showcase the system's capabilities for perfusion imaging.Main Results.The static performance validation confirmed that the system meets standard quality metrics, such as spatial resolution and uniformity. The dynamic evaluation with the 3D-bioprinted phantom demonstrated linearity in hemodynamic flow measurements and effective quantification of perfusion metrics.In vivoexperiments highlighted the system's potential to capture detailed perfusion maps of the brain, lungs, and kidneys. The observed differences in perfusion characteristics between genotypic mice illustrated the system's capability to detect physiological variations, though the small sample size precludes definitive conclusions.Significance.The turn-table micro-CT system represents a significant advancement in preclinical imaging, providing high-resolution, low-dose dynamic imaging for a range of biological and medical research applications. Future work will focus on improving temporal resolution, expanding spectral capabilities, and integrating deep learning techniques for enhanced image reconstruction and analysis.

The tasks of the stages of the annual cycle, the solution of which is the basis for improving physical qualities, which ensures the effectiveness of middle-distance running of athletes at the stage of specialized basic training

The current training method focuses on the athlete at the stage of specialized basic training to further achieve a consistent level of development of special strength, as well as basic strength and strength abilities, It is fundamentally necessary to thoroughly understand the technical and tactical abilities of a mid-distance runner in the minds of a high level for The highest level of basic tasks is to achieve a high level of diversity and the interconnection of all types of preparation - physical, technical, tactical, psychological, moral-volitional, etc. Based on periodization systems, we improved the annual training macrocycle for middle-distance runners in the third year of specialized basic training, which includes: 2 autumn-winter and spring-summer macrocycles, 6 main periods and 16 training stages, which include 18 mesocycles and 52 microcycles. Considering the stages of preparation of the annual training cycle as the basis of the training process of middle-distance runners at the stage of specialized basic training, we developed groups of exercises with different predominant orientation, and on this basis, model microcycles of each stage were built depending on the tasks. On the basis of the annual training macrocycle of qualified middle-distance runners in the third year of training at the stage of specialized basic training, the main tasks of the stages of the annual training cycle of different predominant orientations were developed, which are the basis for improving the components of physical qualities. The developed tasks of the stages of the annual training cycle are aimed at increasing the capabilities of the aerobic system, the aerobic-anaerobic system, as well as the anaerobic energy supply system, which will make it possible to lay an aerobic-anaerobic base on which middle-distance runners will successfully perform large volumes of special work, carry loads more easily, and recover faster after them at the stage of specialized basic training.

The structure of functional training of athletes as a ensuring factor competitive activities in sports games

Assessment of the level of structural components of the functional fitness of athletes' bodies is one of the priority factors for improving the training system in handball, because it allows you to create the necessary conditions for the rational management of the athletes' physical condition and the course of adaptive changes, which ensure that the level of preparedness corresponds to the given sports result in the competitive period. The goal was to study the peculiarities of the formation of the structure of the functional readiness of the body of young men aged 16-17 years who specialize in handball, within the preparatory period of the macrocycle. The analysis of integral indicators characterizing the level of the physical condition of the body of handball players revealed positive dynamics of the level of general physical capacity, the functional state of the cardiorespiratory system, the general level of functional preparedness and adaptive capabilities of the cardiovascular system. All indicators corresponded to the "above average" functional class. Experimental data confirmed the effectiveness of planning specialized training programs that are purposefully related to the volume and functional orientation of the training session in the structural components of the preparatory period of the macrocycle. The use of a computer program made it possible to determine the general level of functional fitness and the state of the cardiovascular and respiratory systems of athletes, which is important for monitoring their physical readiness for the competitive game season.

Characterization of pristine and aged NMC lithium-ion battery thermal runaway using ARC experiments coupled with optical techniques

Battery thermal runaway (TR) challenges battery applications due to safety considerations, potentially endangering consumers. Understanding the process is crucial to defining first alarm strategies that indicate the risk of TR and designing systems to mitigate this problem. For this reason, the present paper aims to characterise key variables of the venting and thermal runaway processes. Experimental tests were conducted in an accelerating rate calorimeter (ARC) using the heat wait seek (HWS) protocol, which tracks the battery temperature after detecting an exothermic reaction during the seek period. The maximum temperature rise rate and peak temperature that the calorimeter can achieve are 15 °C/min and 300 °C. Two optical accesses in the ARC were modified to use optical techniques such as Schlieren double pass and infrared. The results cover 3 different cell conditions: Pristine cells at state of charge (SOC) 100 %, pristine cells at SOC 50 %, and aged cells at SOC 100 %. For statical purposes, each cell condition was repeated 5 times. The aged battery was cycled to boost solid electrolyte interface growth. The images obtained were post-processed, with a specific methodology for each optical technique, and according to the parameters intended to be obtained. The main result shows that for higher SOC, the exothermic reaction is detected earlier than for SOC 50 %, which was only detected in an advanced TR stage (higher temperature rise rate). Therefore, the battery system capability to detect plays a crucial role in safety. Safety actuation time is reduced by ∼ 40 % for SOC 50 %. However, the energy to manage during this situation is lower (∼42 %), depending on the mass inside the battery, revealing the importance of a good venting cap design. Infrared images have shown higher particle temperatures for higher SOC, about 150 °C higher than the SOC 50 %. The particle velocity, in this case, achieved 30 m/s.

Supporting the Episodic Application of Clinical Guidelines over Significant Time Periods.

Medical errors contribute significantly to morbidity and mortality, emphasizing the critical role of Clinical Guidelines (GLs) in patient care. Automating GL application can enhance GL adherence, improve patient outcomes, and reduce costs. However, several barriers exist to GL implementation and real-time automated support. Challenges include creating a formalized, machine-comprehensible GL representation, and an episodic decision-support system for sporadic treatment advice. This system must accommodate the non-continuous nature of care delivery, including partial actions or partially met treatment goals. We describe the design and implementation of an episodic GL-based clinical decision support system and its retrospective technical evaluation using patient records from a geriatric center. Initial evaluation scores of the e-Picard system were promising, with a mean 94% correctness and 90% completeness based on 50 random pressure ulcer patients. Errors were mainly due to knowledge specification, algorithmic issues, and missing data. Post-corrections, scores improved to 100% correctness and a mean 97% completeness, with missing data still affecting completeness. The results validate the system's capability to assess guideline adherence and provide quality recommendations. Despite initial limitations, we have demonstrated the feasibility of providing, through the e-Picard episodic algorithm, realistic medical decision-making support for noncontinuous, intermittent consultations.