Limited Capacity Research Articles

Metal chloride‐graphite intercalation compounds for rechargeable metal‐ion batteries

AbstractThe typical metal chloride‐graphite intercalation compounds (MC‐GICs) inherit intercalation capacity, high charge conductivity, and high tap density from graphite, and these are considered as one of the promising alternatives of graphite anode in rechargeable metal‐ion batteries (MIBs). Notably, the special interlayer decoupling effects and the introduction of extra conversion capacity by metal chloride could greatly break the capacity limitation of graphite anodes and achieve higher energy density in MIBs. The optimization of both graphite host and metal chloride species with specific structures endows MC‐GICs with design feasibility for different application requirements of different MIBs, such as several times the actual capacity compared to graphite anodes, rapid migration of large carriers, and other properties. Herein, a brief review has been provided with the latest understanding of conductivity characteristics and energy storage mechanisms of MC‐GICs and their interesting performance features of full potential application in rechargeable MIBs. Based on the existing research of MC‐GICs, necessary improvements and prospects in the near future have been put forward.

Determining calf traceability and cow–calf relationships in extensive farming using geolocation collars and BLE ear tags

Extensive farming is often considered very beneficial to animals for its potential to enhance animal welfare, providing animals with free-range access to their natural environment where they can engage in innate behaviors like grazing and exploration. However, despite these benefits, extensive production still faces welfare and health challenges due to unpredictable weather conditions and limited supervision by stockholders. Moreover, increasing consumer demand for information regarding food quality, safety, and production conditions poses a challenge for extensive farming, where animals are less controlled. Precision livestock farming (PLF) emerges as a possible solution by enabling the continuous real-time monitoring of the health, welfare, and behavior of animals. A novel approach combining geolocation collars for cows and Bluetooth low energy (BLE) ear tags for calves appears promising to enhance traceability and monitoring in extensive farming. Nevertheless, challenges persist, including limitations in the data transmission capacity and associated costs. This study evaluated the effectiveness of combining geolocation collars and BLE ear tags for monitoring calf traceability and cow–calf relationships across three scenarios: 1) Equilibrated: same collar/ear tag ratio; good coverage; 2) intermediate: more collars than ear tags; fair coverage; 3) worst: more ear tags than collars; lousy coverage. Our results indicate that the equilibrated scenario (ES) with an equal number of geolocation collars and BLE ear tags, was the best scenario, demonstrating the highest fix rate (22%) and the longest mean consecutive days of detecting the same ear tag (22.30 days), followed by the intermediate scenario (IS) and the worst scenario. In all scenarios, there was a mean period of 14–15 d without detecting a calf. However, this shortcoming can be overcome as calves usually graze alongside their mothers, ensuring comprehensive traceability in farm breeding. Additionally, by comparing differences in the number of ear tags received from offspring compared to other calves, the BLE ear tags successfully associated every mother with their calf in the ES and IS. Finally, this valuable information, would enable the development of a traceability system that ensures transparency and reliability throughout the supply chain and could allow consumers to access to product information related to animal welfare.

According to Which Criteria Should We Determine Whether and When IACUCs Are Sufficient for Protecting the Welfare of Nonhuman Animals Used in Research?

Nonhuman animals used in biomedical research frequently suffer and are harmed as part of their use as experimental models. The Institutional Animal Care and Use Committee (IACUC) of a given institution is meant to ensure that research protocols follow federal guidelines, but research protocols such as those described in this case can generate unnecessary suffering; this problem suggests limitations of IACUCs' capacity to protect nonhuman animals' welfare. This commentary on the case considers how to more fully protect nonhuman animals used in scientific research and identifies barriers to more comprehensive protection of nonhuman animals' welfare.

Dissociable functional responses along the posterior-anterior gradient of the frontal and parietal cortices revealed by parametric working memory and training.

While the storage capacity is limited, accumulating studies have indicated that working memory (WM) can be improved by cognitive training. However, understanding how exactly the brain copes with limited WM capacity and how cognitive training optimizes the brain remains inconclusive. Given the hierarchical functional organization of WM, we hypothesized that the activation profiles along the posterior-anterior gradient of the frontal and parietal cortices characterize WM load and training effects. To test this hypothesis, we recruited 51 healthy volunteers and adopted a parametric WM paradigm and training method. In contrast to exclusively strengthening the activation of posterior areas, a broader range of activation concurrently occurred in the anterior areas to cope with increased memory load for all subjects at baseline. Moreover, there was an imbalance in the responses of the posterior and anterior areas to the same increment of 1 item at different load levels. Although a general decrease in activation after adaptive training, the changes in the posterior and anterior areas were distinct at different memory loads. Particularly, we found that the activation gradient between the posterior and anterior areas was significantly increased at load 4-back after adaptive training, and the changes were correlated with improvement in WM performance. Together, our results demonstrate a shift in the predominant role of posterior and anterior areas in the frontal and parietal cortices when approaching WM capacity limits. Additionally, the training-induced performance improvement likely benefits from the elevated neural efficiency reflected in the increased activation gradient between the posterior and anterior areas.

Design of Nested Linear/Lattice Code using Field-size Reduction

Abstract It has been demonstrated that lattice-code based communication strategies are beneficial to multi-user multi-hop networks. This paper considers a practical nested linear/lattice code design that achieves near-capacity performance. We propose a new field-size reduction method to realize code nesting for users with different rates. Then, a multi-code extrinsic information transfer (EXIT) chart is executed to design optimized degree distributions. Simulation results demonstrate enhanced BER performance compared to the existing method, and the nested code is less than 0.8 dB to capacity limits. The performance improvement in multi-user systems is demonstrated with linear physical-layer network coding multiple access (LPNC-MA) framework.

Multi-chamber parenteral nutrition (PN) bags are safe and cost-effective in replacing compounded PN regimens in hospitalised patients

Background & AimsThere is varied international practice in the use of ready-made multi-chamber bags (MCBs) and compounded parenteral nutrition (PN). Recent national aseptic pharmacy capacity limitations have restricted compounded PN production so we aimed to explore outcomes associated with the increased use of MCB vs compounded regimens during a period of change in PN supplies. MethodsThis was a point prevalence study conducted over two time periods, Period 1: 01.01.2022 – 31.03.2022 and Period 2: 01.10.2022 – 31.12.2022. Data were collected on PN regimen, outcomes, cost and aseptic time required to prepare PN bags. Results263 patients were included: 132 in Period 1 and 131 in Period 2. Overall, 2263 PN bags were utilised; 1179 in Period 1 and 1084 in Period 2. In Period 1, of all utilised bags, 138 (11.7%) were compounded PN, 356 (30.2%) supplemented MCBs and 685 (58.1%) manipulated MCBs whereas in Period 2, 0 were compounded PN, 546 (50.3%) supplemented MCBs and 538 (49.6%) manipulated MCBs. There were no significant differences in the proportion of patients with deranged blood tests between the study periods. In both periods there were only two episodes of catheter-related blood stream infection. The total cost saved in Period 2 compared to Period 1 was £20,684 and total aseptic staff time saved was 191 hours. ConclusionWider use of in-hospital MCB PN regimens could lead to a reduction in the need for compounded PN produced by aseptic pharmacy facilities, saving costs while maintaining good patient outcomes.

Comprehensive evaluation of malaria reactive surveillance and response strategies in Lao People’s Democratic Republic: a mixed-methods study

ObjectivesTo achieve malaria elimination by 2030, the Lao People’s Democratic Republic (PDR) adopted a reactive surveillance and response (RASR) strategy of malaria case notification within 1 day, case investigation and...

An improved similarity method for stiffened plates subjected to combined loads of longitudinal compression and lateral pressure

Structures’ ultimate strength has been increasingly valued in the past few decades. The model test is an important and reliable way to estimate the ultimate strength. For large and complex structures, like ship hull structures, the test subject is usually scale models due to the limitation of loading capacity and space of laboratories. Therefore, the similarity method and the design of scale models are of great importance. The stiffened plate is the minimum unit that makes up thin-walled structures. The similarity method of the ultimate strength of stiffened plates is the base of the similarity method of large and complex structures. This paper is a further study of an existing similarity method proposed in our previous work. A stiffened plate from a real ship is taken as the subject. 22 combinations of scale ratios are used to design scale models. The 23 models (including the original model) are subjected to a combined load of longitudinal compression and lateral pressure. The non-linear finite element method is used to analyze these models. The results revealed that the previous method is only suitable for scale models with small degrees of geometrical distortion. It didn't consider the effect of geometrical distortions. An improved similarity method and scale model design method are proposed to solve these problems. The improved methods consider the geometrical distortion of scale models and are applicable to more geometrically distorted scale models. More numerical examples are performed to verify the correctness and advantage of the improved methods.

A fuzzy multi-objective programming model for the delivery and distribution of humanitarian relief materials

Disaster relief presents many unique logistics challenges, including damaged transportation infrastructure, multiple conflicting goals, and secondary disasters caused by spontaneous disaster relief. The delivery and distribution of humanitarian relief materials faced by nonprofit organizations (NPOs) poses a critical challenge due to the highly unpredictable nature of disasters, conflicting missions, and the need to navigate government regulations in disaster management. In this paper, we propose a novel multi-objective disaster relief modeling system for NPOs, considering (1) prioritization (providing medical services to seriously injured victims), (2) effectiveness (degree of satisfaction), (3) efficiency (operational costs), and (4) equity (cost of maintaining order). To incorporate the practical constraints of disaster relief operations, we include factors such as road damage, transportation capacity limitations, and route flow saturation as part of the model formulation. We then utilize fuzzy multi-objective programming to optimize the proposed disaster relief model, considering two relief distribution schemes: a common NPOs' spontaneous relief scheme and a newly designed traffic control scheme with government regulation. Based on the real-world scenario of the 2008 Wenchuan earthquake, we demonstrate that the designed traffic control scheme exhibited remarkable improvement among the NPOs' four objectives compared to the spontaneous relief scheme. Moreover, in the process of solving fuzzy multi-objective programming problems, artificial intelligence technology is employed to handle the fuzziness in multi-objective and automatically adjust parameters, making the solution results better and in line with practical situations. And we also validate the proposed model can be solved in polynomial time, meeting the engineering practice requirements, and can be easily extend to most disaster relief distribution scenarios.

Fast and accurate modelling of twin-screw compressors: A generalised low-order approach

Twin-screw compressors (TSC) are commonly used in heat pump processes due to their robustness and flexibility. They exhibit two core properties, i.e. the swept volume and the built-in volume ratio (BVR), which heavily influence their capacity limits and off-design efficiency. This work presents a new low-order model (i.e. a polynomial model), which can accurately predict a TSC’s behaviour. The model uses the external pressure ratio and volumetric compressor inlet flow rate to calculate isentropic efficiency and compressor speed. The input parameters are normalised with a reference flow rate (calculated from the swept volume) and the BVR, respectively. This results in a generalised model of low numerical cost, which can be used for explorative studies independent of the specific machine size and BVR. A gain in computational speed by a factor of 375 is achieved compared to a semi-empiric reference model. The model displays very good predictive accuracy when used to predict the performance of machines with similar BVRs, but different sizes. A mean deviation from the manufacturer data of 4.29%, 0.88°C and 1.38% for the shaft power, the outlet temperature and the compressor speed can be observed, respectively. When there is a difference in size and BVR, the prediction accuracy is still reasonable but significantly declines for small and very large pressure ratios. Nevertheless, the proposed new approach extends the state-of-the-art by introducing a low-order model, which combines the advantages of low computational cost, high accuracy, physically correct predictions over a wide operational range and scalability to different machine capacities and BVRs. The validation for different fluids indicates a good general prediction accuracy relatively independent of the used fluid.

Source‐load cooperative frequency regulation based on virtual synchronous/asynchronous machine concept

AbstractDue to the absence of inertia, the high proportion of electronic power equipment is a great threat to the stability of the power system. Previous studies have proposed the virtual synchronous machine (VSM) control method for the inverter‐based distributed generators (DG). However, due to the capacity limitations of DG, the capability of the inverter to provide the inertia action is limited. At the same time, some controllable loads also have the ability to provide inertial support but are still not fully utilised. To get a better grid frequency response, this paper proposes a source‐load coordination strategy based on the VSM and virtual asynchronous machine (VAM) concept. For that purpose, a detailed VAM model is firstly derived for the rectifier on power demand side. Not only the virtual inertia and frequency oscillation damping can be provided, but also the synchronisation units are not needed to obtain the unknown grid frequency. After that, a distributed consensus‐based secondary control is present to regulate the frequency to converge to a reference value based on VSM and VAM. Compared with the existing frequency regulation method, the proposed scheme makes full use of the ability of the load side to participate in frequency modulation. Finally, some numerical simulations are performed to validate the feasibility of the proposed method on MATLAB/Simulink.

Energy Minimization for IRS-Assisted SWIPT-MEC System.

With the rapid development of the internet of things (IoT) era, IoT devices may face limitations in battery capacity and computational capability. Simultaneous wireless information and power transfer (SWIPT) and mobile edge computing (MEC) have emerged as promising technologies to address these challenges. Due to wireless channel fading and susceptibility to obstacles, this paper introduces intelligent reflecting surfaces (IRS) to enhance the spectral and energy efficiency of wireless networks. We propose a system model for IRS-assisted uplink offloading computation, downlink offloading computation results, and simultaneous energy transfer. Considering constraints such as IRS phase shifts, latency, energy harvesting, and offloading transmit power, we jointly optimize the CPU frequency of IoT devices, offloading transmit power, local computation workload, power splitting (PS) ratio, and IRS phase shifts. This establishes a multi-variate coupled nonlinear problem aimed at minimizing IoT devices energy consumption. We design an effective alternating optimization (AO) iterative algorithm based on block coordinate descent, and utilize closed-form solutions, Dinkelbach-based Lagrange dual method, and semidefinite relaxation (SDR) method to minimize IoT devices energy consumption. Simulation results demonstrate that the proposed scheme achieves lower energy consumption compared to other resource allocation strategies.

Optimizing the bidding strategy and assessing profitability of over-install renewable plants equipped with battery energy storage systems

The over-installation of renewable energy sources (RES) can enhance the profits of RES producers by increasing the total exporting energy; however, RES power curtailments must be applied under over-production of RES plants to ensure their contracted maximum export capacity limits. Battery energy storage systems (BESSs) can be used to reduce the RES curtailments and therefore enhance the profits of producers. This work develops a bidding strategy as a scenario-based stochastic optimization scheme to maximize the expected profits of producers in electricity markets considering battery degradation and maximum export capacity constraints. Using the proposed scheme, a financial analysis is performed to assess the profitability for over-installing hybrid RES plants by calculating the net present value and internal rate of return of the project under different BESS costs. Simulation results, using real data from a wind and photovoltaic plant, demonstrate the effectiveness of the proposed stochastic scheme in enhancing the profit of producers compared to the corresponding deterministic scheme. The performed financial analysis, using the net present value metric, indicates that a maximum over-installation of 150%–170% and 160%–180% for the wind and photovoltaic plant, respectively, is profitable, while the usage of a BESS is profitable when its cost is under 200,000 €/MWh.

Experimental and numerical investigation of the cyclic behaviour of coupled balloon-type CLT shear walls with high-capacity base connections

Mass timber buildings have gained global popularity due to the increasing availability and affordability of mass timber products and an increasing awareness of the sustainability of timber construction. This paper presents an experimental and numerical study on coupled balloon-type cross-laminated timber (CLT) shear walls with the aim of overcoming the capacity limitations of platform CLT shear walls. Using self-tapping screws to create innovative hold-down solutions, three two-storey coupled CLT shear walls were cyclically tested and the results demonstrated that the proposed coupled wall systems could achieve significantly higher lateral strength (over 400 kN) and initial stiffness (up to 14 kN/mm) compared to platform CLT shear walls in literature. The cyclic test results were used to validate a finite element CLT shear wall model in CLTWALL2D. The calibrated model was then used to run a parametric study of a series of balloon-type CLT shear walls up to twelve storeys (42 m) in height. This study provided evidence that coupled balloon-type CLT shear walls with high-capacity screwed connections have the potential of reaching high strength and stiffness with the displacement ductility factor μ = 2–4.

Forecasting of functional readiness and construction of variable tactics of elite single combatants on the basis of assessment of psychophysiological state

The goal is to substantiate and experimentally verify the effectiveness of using the results of the tapping test to assess readiness for a match. Methodology: analysis and synthesis of data from modern scientific and scientific and methodical literature as well as Internet on the problem being studied, dynamic tapping testing, forecasting. Scientific novelty. The article provides new data on the generalization of the results of the informativeness and effectiveness of the assessment of the current psychophysiological state for predicting changes in the functional preparedness of elite single combatants and the possibility of forming strategies and tactics for future matches taking into account the individual dynamics of changes in the studied parameters of the tapping test. Conclusions. In the course of the conducted research and generalization of the obtained individual results, it was established that the state of "strength - weakness" is the limit of physical and mental capacity, i.e., the time during which excitement in the brain cells can be maintained during long-term actions of the enemy. It was also found that the most informative for monitoring the psychophysiological state and functional abilities of martial artists are the indicators of the maximum frequency of movements in 30 sec. When choosing the time of the examination, it is necessary to take into account that the dynamics of the pace of hand movements are affected by the peculiarities of not only the nervous system, but also the muscular system, therefore, in the presence of weak muscle development or during particularly long examinations, the presence of fatigue may affect the results. It is very important that tapping metrics allows you to determine: the level of the total amount of work performed, or the most favorable time for the match, an indicator of the level of activity of attacking and defensive actions for the entire period of the fight; a favorable time for carrying out a series of actions; stability of the battle; the speed of single action, and also simplifies the process of selection and selection of the national team for participation in competitions. The use of the method of controlling the psychophysiological state by conducting a tapping test to assess functional abilities optimizes the process of forming a strategy and tactics of fighting a match depending on the state and stability of the central nervous system of the wrestler.

Joint optimization of truck-drone routing for last-mile deliveries in urban areas

This paper presents a joint routing optimization model to satisfy the on-demand customer requirements by minimising the transportation and time penalty costs of trucks and drones, considering the constraints on paths and delivery time of trucks and drones, the drone battery capacity limit, and the customer demands. The improved genetic algorithm is proposed to solve the optimization model followed by the computational experiments demonstrating the superiority of the improved genetic algorithm over the original genetic algorithm in computational efficiency, economy, and punctuality. Further, the comparative analysis demonstrates that the multi-drone joint delivery mode considering the customer demands performs better than the other delivery modes and that the delivery routes can be re-optimised promptly to satisfy the real-time customer demands. The sensitivity analysis on the drone design parameters provides theoretical insights into deploying the size and speed of drone platoons when promoting truck-drone joint delivery in applications.

A dynamic ensemble model for short-term forecasting in pandemic situations.

During the COVID-19 pandemic, many hospitals reached their capacity limits and could no longer guarantee treatment of all patients. At the same time, governments endeavored to take sensible measures to stop the spread of the virus while at the same time trying to keep the economy afloat. Many models extrapolating confirmed cases and hospitalization rate over short periods of time have been proposed, including several ones coming from the field of machine learning. However, the highly dynamic nature of the pandemic with rapidly introduced interventions and new circulating variants imposed non-trivial challenges for the generalizability of such models. In the context of this paper, we propose the use of ensemble models, which are allowed to change in their composition or weighting of base models over time and could thus better adapt to highly dynamic pandemic or epidemic situations. In that regard, we also explored the use of secondary metadata-Google searches-to inform the ensemble model. We tested our approach using surveillance data from COVID-19, Influenza, and hospital syndromic surveillance of severe acute respiratory infections (SARI). In general, we found ensembles to be more robust than the individual models. Altogether we see our work as a contribution to enhance the preparedness for future pandemic situations.

StarCross: Redactable blockchain-based secure and lightweight data sharing framework for satellite-based IoT

Due to limitations in network coverage and capacity, terrestrial networks cannot meet the growing demand for widespread intelligent applications in recent years. The increasingly popular Satellite-based Internet of Things (S-IoT), with its extensive and boundless coverage, has emerged as the optimal solution. However, the large-scale distributed communication and services have led to significant challenges in scalability and security. Blockchain can help mitigate security and privacy issues in data sharing of S-IoT. To address these challenges, we propose StarCross, a secure and lightweight data sharing framework for S-IoT based on redactable blockchain. Firstly, we develop a space-ground collaborative sharding blockchain network architecture. Low Earth Orbit (LEO) satellite network serves as the communication intermediary between shards. Secondly, StarCross employs an improved Proof of Work (PoW) consensus based on dynamic difficulty to mitigate the challenges of uneven computing power and centralization within each shard. To ensure the atomicity of cross-shard transactions, StarCross introduces a blockchain rewriting mechanism called RBCVC, which combines chameleon hash and voting-based consensus. Thirdly, we conducted theoretical analysis and experimental evaluations of StarCross. The results indicate that compared to existing solutions, StarCross achieves better scalability and security in S-IoT. StarCross’s TPS increased to 260.9% of the baseline, while the transaction confirmation latency decreased by 79.7%.

On the impact of Open RAN Fronthaul Control in scenarios with XR Traffic

Through extensive research and standardization efforts, mobile networks have rapidly evolved, offering improved services and allowing the establishment of new use cases, such as autonomous vehicles, smart cities, Industry 4.0, among others. While 5G networks have brought advancements that can support a broad spectrum of such new use cases, the requirements imposed by time-critical services as the eXtended Reality (XR) and Cloud Gaming (CG) applications still remain a challenge. Next generation networks are envisioned to adopt technologies that will allow them to surpass such barriers. Open Radio Access Network (RAN), utilizing the disaggregation paradigm, stands out as a pivotal technology thanks to its potential to endow the network with flexibility, automation, and intelligence. In fact, Open RAN is considered as one of the key enabling technologies for XR and CG applications. However, disaggregation of the RAN may result in bottlenecks in the links connecting the various parts of the network, like the Open Fronthaul link, especially when considering time-critical traffic. In this paper, we perform an analysis of the impact that the Open Fronthaul capacity limitations can have in the XR and CG traffic under 3GPP defined scenarios. Moreover, to address these limitations, we implement and extend a Fronthaul Control mechanism combined with modulation compression, using the open-source ns-3 based 5G-LENA network simulator. Results showcase that the Open Fronthaul capacity limitation can drastically reduce the performance of the XR and CG applications, and demonstrate the necessity for such mechanisms to be employed in order to meet their requirements in terms of latency and throughput.

Coordination and Hydrogen Bond Chemistry in Tungsten Oxide@Polyaniline Composite toward High-Capacity Aqueous Ammonium Storage.

Aqueous ammonium ion batteries (AAIBs) have garnered significant attention due to their unique energy storage mechanism. However, their progress is hindered by the relatively low capacities of NH4 + host materials. Herein, the study proposes an electrodeposited tungsten oxide@polyaniline (WOx@PANI) composite electrode as a NH4 + host, which achieves an ultrahigh capacity of 280.3 mAh g-1 at 1 A g-1, surpassing the vast majority of previously reported NH4 + host materials. The synergistic interaction of coordination chemistry and hydrogen bond chemistry between the WOx and PANI enhances the charge storage capacity. Experimental results indicate that the strong interfacial coordination bonding (N: →W6+) effectively modulates the chemical environment of W atoms, enhances the protonation level of PANI, and thus consequently the conductivity and stability of the composites. Spectroscopy analysis further reveals a unique NH4 +/H+ co-insertion mechanism, in which the interfacial hydrogen bond network (N-H···O) accelerates proton involvement in the energy storage process and activates the Grotthuss hopping conduction of H+ between the hydrated tungsten oxide layers. This work opens a new avenue to achieving high-capacity NH4 + storage through interfacial chemistry interactions, overcoming the capacity limitations of NH4 + host materials for aqueous energy storage.