Limited Capacity Research Articles

Localized Microrobotic Delivery of Enzyme-Responsive Hydrogel-Immobilized Therapeutics to Suppress Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC), characterized by its aggressive metastatic propensity and lack of effective targeted therapeutic options, poses a major challenge in oncological management. A proof-of-concept neoadjuvant strategy aimed at inhibiting TNBC tumor growth and mitigating metastasis through a localized delivery of chemotherapeutics is reported in this paper. This approach addresses the limitations in payload capacity and stimuli responsiveness commonly associated with microrobotics in oncology. A hydrogel-based system is developed for the immobilization of chemotherapeutic agents, subsequently encapsulated within magnetically responsive microrobots. This design leverages external magnetic fields to facilitate the precise navigation and localization of the therapeutic agents directly to the tumor site. The efficacy of this approach is demonstrated in an animal model, in which a significant 14-fold reduction in tumor size and suppression of metastasis to critical organs such as the liver and lungs are observed. Crucially, the drug release mechanism is engineered to be responsive to the tumor microenvironment and is regulated by the overexpression of the enzymatic activity of matrix metalloproteinases (MMP2 and MMP9) in TNBC tumors, triggering the degradation of the hydrogel matrix, leading to controlled release of the immobilized therapeutic drug. This ensures that the therapeutic action is localized, reducing systemic toxicity and enhancing treatment efficacy. These findings suggest that this neoadjuvant approach holds promise for broader applications in other cancer types.

A dialectical behavior therapy skills training smartphone app for recurrent binge eating: a randomized clinical trial.

Dialectical behavior therapy (DBT) is a specialized treatment that has a growing evidence base for binge-spectrum eating disorders. However, cost and workforce capacity limit wide-scale uptake of DBT since it involves over 20 in-person sessions with a trained professional (and six sessions for guided self-help format). Interventions translated for delivery through modern technology offer a solution to increase the accessibility of evidence-based treatments. We developed the first DBT-specific skills training smartphone application (Resilience: eDBT) for binge-spectrum eating disorders and evaluated its efficacy in a randomized clinical trial. Participants reporting recurrent binge eating were randomized to Resilience (n = 287) or a waitlist (n = 289). Primary outcomes were objective binge eating episodes and global levels of eating disorder psychopathology. Secondary outcomes were behavioral and cognitive symptoms, psychological distress, and the hypothesized processes of change (mindfulness, emotion regulation, and distress tolerance). Intention-to-treat analyses showed that the intervention group reported greater reductions in objective binge eating episodes (incidence rate ratio = 0.69) and eating disorder psychopathology (d = -0.68) than the waitlist at 6 weeks. Significant group differences favoring the intervention group were also observed on secondary outcomes, except for subjective binge eating, psychological distress, and distress tolerance. Primary symptoms showed further improvements from 6 to 12 weeks. However, dropout rate was high (48%) among the intervention group, and engagement decreased over the study period. A novel, low-intensity DBT skills training app can effectively reduce symptoms of eating disorders. Scalable apps like these may increase the accessibility of evidence-based treatments.

A Robust joint coverless image steganography scheme based on two independent modules

With the development of deep learning technology, great progress has been made in the field of coverless steganography based on deep learning technology, including some selection-based steganography methods that use deep learning technology and all generation-based steganography methods, however both of which have their limitations. The former is difficult to meet actual communication requirements in terms of communication capacity and completeness due to the limit of the algorithm. Due to the irreversibility of the process of generating secret images from message codeword, the recovery accuracy of the latter is very poor. To this end, this paper designs a robust joint coverless image steganography scheme called Joint Coverless Image Steganography (JoCS). Firstly, this paper proposes the Semantic Factorization Fitting module (SeFF) and the Transform Domain Steganography module (TrDS). The former adds the secret message to the input vector of the low resolution layer in the StyleGAN generator network, which establishs a mapping rule between message codeword and the coarse feature of the generated image, and then the extractor is used to fit the above mapping rule, which has excellent robustness and completeness; the latter encodes the main content area of the image based on the encoder in VQGAN, and then adds secret message to the latent vector of the encoded image, which achieves the steganography in the latent domain of the image. Secondly, we demonstrate the independence between two modules and the advantages of connecting two modules. By using the image generated in the SeFF module as the cover image in the TrDS module, secondary steganography of a single image is achieved, based on which we design the JoCS scheme. The results show that our scheme breaks through the communication capacity limit in the selection-based coverless methods while guaranteeing 100% completeness, excellent image quality and outstanding robustness against various image attacks. Moreover, our scheme exhibits strong security against detection by multiple steganalysis tools and excellent practicality in practical communication. Finally, this paper also discusses the following three points as further elaboration of the scheme: (1) the advantages of the mapping rule in the SeFF module (2) the verification of the independence between the two modules (3) the flexibility of the joint steganography scheme.

Coordination strategies to improve COVID-19 PCR laboratory testing scale up in Nepal: An analysis.

During the COVID-19 pandemic, Nepal rapidly expanded its PCR testing capacity, essential for effective outbreak response. However, many laboratories faced overwhelming test volumes, resulting in delays that may have hindered containment efforts. This study aims to determine whether these challenges stemmed from capacity limitations and/or imbalanced sample distribution due to inadequate coordination. In this retro-perspective simulation of SARS-CoV-2 testing in Nepal during 2021, we evaluate the impact of coordinated sample transfers on reducing laboratory stress and wait times during demand peaks. Our findings reveal that centralized coordination and strategic partnerships for sample transfers significantly enhance diagnostic network performance, even under high demand. These insights offer valuable guidance for policymakers on implementing effective coordination strategies to strengthen diagnostic networks for future pandemics.

Karma economies for sustainable urban mobility – a fair approach to public good value pricing

City road infrastructure can be considered a public good, and congestion is the intersection of demand for mobility with the limited available transportation supply. Congestion pricing is effective in reducing demand to sustainable levels below network capacity limits, but also controversial, as it introduces equity issues and systematically discriminates against lower-income groups. Karma is a non-monetary, fair, and efficient resource allocation mechanism that employs an artificial currency different from money, incentivises cooperation amongst selfish individuals, and achieves a balance between giving and taking. Where money does not do its job, Karma achieves socially more desirable allocations by being aligned with consumers’ needs rather than their financial power. This work highlights the value proposition of Karma, provides guidance on Karma mechanism design, and equips the reader with a useful software framework to model Karma economies and predict consumers’ behaviour. A case study of road pricing demonstrates Karma’s potential.

Investigation on size effects of ultra-high-performance concrete: experimental and numerical study

ABSTRACT Test specimens with smaller sizes seem to be preferable because using standard specimen sizes for ultra-high-performance concrete (UHPC) can lead to issues owing to the current testing equipment’s capacity limitations. Therefore, the size effect investigation of the UHPC specimens is necessary. In this paper, the UHPC mix was used to explore the size effect on the compression and flexural response of the cylinder and beam specimens, respectively. The UHPC mix was cast into various-sized cylinders and beams with diameters ranging from 50 to 150 mm and heights/widths from 50 to 150 mm, respectively. A nonlinear 3D finite element (FE) model has been created in ABAQUS software for all UHPC specimens. Additionally, validation was done using the experimental findings of this study. The findings clearly revealed that the compressive and flexural strength decreases with increasing the size of the specimen. The larger specimens revealed a slight reduction in compressive strength between 1.4% and 9.5%, while a considerable reduction was recorded in flexural strength, where the larger specimens showed reduction ratios between 19.1% and 35.6%. Furthermore, the experimental and FE findings were in satisfactory agreement and exhibited virtually identical overall trends.

Distinct physiological, transcriptomic, and imaging characteristics of asthma-COPD overlap compared to asthma and COPD in smokers

The clinical and pathological features of asthma and chronic obstructive pulmonary disease (COPD) can converge in smokers and elderly individuals as asthma-COPD overlap (ACO). This overlap challenges the diagnosis and treatment of the distinct aetiologies underlying these conditions. We analysed 2453 smokers (≥10 pack-years), aged 45-80 years, from the Genetic Epidemiology of COPD (COPDGene) Study, stratified as Control, Asthma, COPD, and ACO based on Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria. A comprehensive assessment was performed, encompassing symptomatology, pulmonary function tests (PFTs), complete blood counts (CBCs), bulk RNA sequencing (RNA-seq), and high-resolution quantitative computed tomography (QCT) imaging to evaluate clinical impact, lung function, systemic inflammation, and structural alterations contributing to disease progression across respiratory phenotypes. Differential expression (DE) analysis was performed using whole blood RNA-seq (BH-corrected FDR < 0.01), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Group differences were assessed using the Mann-Whitney U-test (MWU) or Chi-squared test (χ2), with Bonferroni correction applied for multiple comparisons. Multivariate linear regression models were used to adjust the associations between disease status and specific clinical outcomes for confounders, with one-way ANOVA and Tukey's Honest Significant Difference (HSD) post-hoc test applied for pairwise comparisons. Our analysis aimed to delineate the extent and variability of clinical features among disease phenotypes to guide targeted therapeutic strategies. Our study highlights distinct yet overlapping profiles across ACO, asthma, and COPD. We effectively isolated disease-specific mechanisms by comparing each phenotype to smoking controls (GOLD 0) while accounting for baseline smoking-related inflammation. ACO exhibited the most severe symptom burden, with significantly higher COPD Assessment Test (CAT) score (18.32, 95% CI: [17.02, 19.63], P<0.0001) and Modified Medical Research Council (mMRC) Dyspnea score (2.14, 95% CI: [1.92, 2.35], P<0.0001) compared to COPD and asthma. ACO also displayed reduced lung capacity (forced expiratory volume in 1s [FEV1]: 52.5%, 95% CI: [50.08, 54.93], P<0.0001) and airflow limitation (FEV1/forced vital capacity [FVC]: 0.55, 95% CI: [0.5471, 0.5546], P<0.0001), closely resembling COPD but significantly worse than asthma. The inflammatory profile of ACO exhibited a mixed response, featuring elevated neutrophil counts (4.57K/μL, 95% CI: [4.28, 4.86], P<0.0001) and eosinophil levels (0.22K/μL, 95% CI: [0.20, 0.25], P<0.01), contrasting with the predominantly neutrophilic inflammation in COPD and the absence of systemic inflammation in asthma. Structurally, ACO demonstrated significant airway remodelling (Pi10: 2.87, 95% CI: [2.83, 2.91], P<0.0001), intermediate emphysema (5.66%, 95% CI: [4.72, 6.60], P<0.0001), and moderate small airway disease (parametric response mapping for functional small airway disease [PRMfSAD]: 22.94%, 95% CI: [21.53, 24.34], P<0.0001), reflecting features of both asthma and COPD. COPD was characterised by more extensive emphysema (8.9%, 95% CI: [8.34, 9.45], P<0.0001), small airway disease (PRMfSAD: 27.09%, 95% CI: [26.51, 27.66], P<0.0001), and gas trapping (37.34%, 95% CI: [36.33, 38.35], P<0.0001), alongside moderate airway remodelling. At a molecular level, DE analysis revealed enrichment of the Hypoxia-Inducible Factor 1 (HIF-1) pathway in ACO, highlighting unique hypoxia-driven metabolic adaptations, while COPD was associated with neutrophil extracellular trap (NET) formation and necroptosis. In contrast, asthma exhibited significant airway remodelling (Pi10: 2.09, 95% CI: [2.05, 2.13], P<0.0001), minimal parenchymal damage, and no systemic gene expression changes. Collectively, our findings underscore the lung function impairments, systemic inflammation, molecular mechanisms, and structural correlates distinguishing ACO from COPD and asthma, emphasising the need for precise clinical management and the potential for novel therapeutic interventions. This work was supported by National Heart, Lung, and Blood Institute (NHLBI) grants U01 HL089897 and U01 HL089856, as well as by National Institutes of Health (NIH) contract 75N92023D00011. Additional support was provided by grants R01 HL166231 (C.P.H.) and K01 HL157613 (A.S.).

Optimal control for an SIR model with limited hospitalised patients

This paper analyses the optimal control of infectious disease propagation using a classic susceptible-infected-recovered (SIR) model characterised by permanent immunity and the absence of available vaccines. The control is performed over a time-dependent mean reproduction number, in order to minimise the cumulative number of ever-infected individuals (recovered), under different constraints. We consider constraints on non-pharmaceutical interventions ranging from partial lockdown to non-intervention, as well as the social and economic costs associated with such interventions, and the capacity limitations of intensive care units that limits the number of infected individuals to a maximum allowed value. We rigorously derive an optimal quarantine strategy based on necessary optimality conditions. The obtained optimal strategy is of a boundary-bang type, comprising three phases: an initial phase with no intervention, a second phase maintaining the infected population at its maximum possible value, and a final phase of partial lockdown applied over a single interval. The optimal policy is further refined by optimising the transition times between these phases. We show that these results are in excellent agreement with the numerical solution of the problem.

Queuing Theory-Based Model for Optimization of Covid-19 Vaccination and Booster Delivery

Although queuing theory is commonly utilized in businesses to analyze and model processes involving waiting lines, the healthcare sector sees a difference from other industries when it comes to optimizing fixed resources under alterable demand conditions. To enhance operational effectiveness and cut down on waiting times, hospital operation managers need to be informed on the state of business processes. A scientific method to reduce systemic inefficiencies and raise patient satisfaction is the queuing theory. The objective of this study is to use queuing theory to optimize COVID-19 vaccination and booster delivery. This study discussed two distinct models, one for bigger MV hubs and the other for smaller GP vaccination clinics. The current study demonstrated how these models may be used to anticipate staffing needs to prevent bottlenecks, predict daily throughput given staff capacity limits, and simulate the queuing process. With respectable face validity, we produced accurate estimates of the distributions of given service times and overall processing times. In the future, this may be improved by carrying out a time-use survey to get empirical data on total processing time, which could be compared to the projected processing time of the model and service times for each station, which would help guide the model's inputs.

Power Conversion from Solar Panels using a 3000-watt Inverter

The advancement of inverter technology has seen rapid growth and widespread adoption across various industrial and commercial sectors. The output wave of the inverter has seen significant development since the introduction of the multilevel inverter. By utilizing multilevel inverters, the strain on switch components can be alleviated due to the low frequency of the power wave. This results in generating a voltage that closely resembles the desired output of the AC voltage. The study demonstrated the efficient utilization of resistive loads by the transformer, with the average sinusoid voltage source measuring 103.6%. When conducting inverter testing with a 60 Volt resource, the current input, output, voltage, and input and output efficiency measurements are obtained using a 10 Amper resource. After analyzing the data collected from the tests, it was found that the system's output voltage fell short of the anticipated 220 Volt. When a load of 60 W/220V is added, the system's output voltage is affected, resulting in an output of 740.5 Volts. When the light load is decreased to 60W/220V, the output voltage rises to 786.9 Volt with an average inverter efficiency of 77%. The input power efficiency ranges from 25.5% to 80.0% when calculated based on the inverter power capacity limit.

Understanding Rate and Capacity Limitations in Li-S Batteries Based on Solid-State Sulfur Conversion in Confinement.

Li-S batteries with an improved cycle life of over 1000 cycles have been achieved using cathodes of sulfur-infiltrated nanoporous carbon with carbonate-based electrolytes. In these cells, a protective cathode-electrolyte interphase (CEI) is formed, leading to solid-state conversion of S to Li2S in the nanopores. This prevents the dissolution of polysulfides and slows capacity fade. However, there is currently little understanding of what limits the capacity and rate performance of these Li-S batteries. Here, we aim to deepen our understanding of the capacity and rate limitation using a variety of structure-sensitive and electrochemical techniques, such as operando small-angle neutron scattering (SANS), operando X-ray diffraction (XRD), electrochemical impedance spectroscopy, and galvanostatic charge/discharge. Operando SANS and XRD data give direct evidence of CEI formation and solid-state sulfur conversion occurring inside the nanopores. Electrochemical measurements using two nanoporous carbons with different pore sizes suggest that charge transfer at the active material interfaces and the specific CEI/active material structure in the nanopores play the dominant role in defining capacity and rate performance. This work helps define strategies to increase the sulfur loading while maximizing sulfur usage, rate performance, and cycle life.

A convenient viral transduction based method for advanced multi-engineering of primary human (CAR) T-cells

The past decades have illustrated the power of T-cell engineering in the development of new and successful cell therapies, such as chimeric antigen receptor (CAR) T-cells. Despite clinical success in hematological malignancies, it also becomes increasingly clear that additional T-cell engineering will be required to improve efficacy and safety and expand the application to solid tumors. Engineering is most often achieved by viral delivery of transgenes, however, viral vector capacity limitations make efficient and reproducible generation of multi transgene expressing T-cell therapeutics technically challenging. We here describe a convenient and efficient method for the delivery of up to three γ-retroviral CAR vectors in T-cells. We achieved this using virus vector mixtures that are simultaneously produced at high titers by double- or triple- transduced stable virus producer cells. We show that this method is superior in overall efficiency and reproducibility to conventional double or triple CAR transductions, in which separate viral batches are used. Due to its robustness, this method can facilitate the research and the development for advanced T-cell engineering towards more effective and safe therapies.

POLYGAUSSIAN DESCRIPTION OF PROBABILITY DISTRIBUTIONS OF PROCESSES GENERATED BY A NONLINEAR LORENZ SYSTEM IMPLEMENTED IN FIXED-POINT NUMBERS

The article is aimed at analyzing the probability distributions of pseudorandom processes generated on the basis of the Lorentz system solution in fixed-point numbers. Numerical solution of the Lo-renz system by the Euler method in single- and double-precision floating-point numbers with a lim-ited number capacity can lead to a breakdown in signal generation. The use of fixed-point numbers contributes to the reduction of computational complexity in the digital implementation of such sys-tems, which ultimately leads to the simplification of their practical implementation on modern chips of programmable logic. This allows to use resources in more efficient way, and increases productiv-ity in the creation and maintenance of such digital systems. The study of approximation of Lorenz system signals using mixtures of Gaussian distributions is of great importance for predictive analyt-ics and stability of the system. Elimination of signal generation failure also contributes to the for-mation of stable modes of generation of chaotic signals with required statistical characteristics.

Connectivity-Enhanced 3D Deployment Algorithm for Multiple UAVs in Space–Air–Ground Integrated Network

The space–air–ground integrated network (SAGIN) can provide extensive access, continuous coverage, and reliable transmission for global applications. In scenarios where terrestrial networks are unavailable or compromised, deploying unmanned aerial vehicles (UAVs) within air network offers wireless access to designated regions. Meanwhile, ensuring the connectivity between UAVs as well as between UAVs and ground users (GUs) is critical for enhancing the quality of service (QoS) in SAGIN. In this paper, we consider the 3D deployment problem of multiple UAVs in SAGIN subject to the UAVs’ connection capacity limit and the UAV network’s robustness, maximizing the coverage of UAVs. Firstly, the horizontal positions of the UAVs at a fixed height are initialized using the k-means algorithm. Subsequently, the connections between the UAVs are established based on constraint conditions, and a fairness connection strategy is employed to establish connections between the UAVs and GUs. Following this, an improved genetic algorithm (IGA) with elite selection, adaptive crossover, and mutation capabilities is proposed to update the horizontal positions of the UAVs, thereby updating the connection relationships. Finally, a height optimization algorithm is proposed to adjust the height of each UAV, completing the 3D deployment of multiple UAVs. Extensive simulations indicate that the proposed algorithm achieves faster deployment and higher coverage under both random and clustered distribution scenarios of GUs, while also enhancing the robustness and load balance of the UAV network.

Comparison of Commercial REBCO Tapes Through Flux Pinning Energy

This work presents a comparison of different commercial tapes belonging to the second-generation High-Temperature Superconductors (2G HTS) produced by SuNAM Co., Ltd., SuperOx, and Shanghai Superconductors Technology Co., Ltd. (SST) companies. The aim is to investigate pinning mechanisms responsible for best performances, looking at the anisotropy of the irreversibility field and of the flux pinning energy. The irreversibility line states the upper limit of current-carrying capacity, whereas the flux pinning energy explores the ability of material defects to act as weak collectively or strong single vortex pinning centers. All investigated samples have artificial pinning centers (APCs) included in the superconducting matrix: BHO-doped EuBCO for SST, Y2O3 in YBCO for SuperOx, and Gd2O3 particles trapped in GdBCO for SuNAM. Resistive transition curves were measured in high magnetic fields up to 16 T for magnetic field orientations parallel and perpendicular to the tape surface. We found that the anistropy of SST tape shows an overall independence both on temperature and magnetic field, while the other two samples show a more complex behavior. This leads to the conclusion that properly engineered APC optimization in coated conductors can further reduce anisotropy of superconducting properties.

Reducing the blocking effect in the airport slot allocation problem with seasonal flexibility

Capacity limitations, combined with increased air-traffic, continue to drive the need for better resource management at airports. At congested airports, the allocation of resources for flights to take-off and land is governed through the use of slots. Slots are allocated twice a year according to the Worldwide Airport Slot Guidelines (WASG). A principle of WASG is to allocate slots to a request at the same time and day of the week over a given period, to maintain regularity in a schedule. Adhering to this principle can result in blocking, where requests are displaced to an alternative time period due to lack of available capacity. This paper addresses blocking by allowing a request to be allocated to slightly different times on different operating days. We present a novel integer linear programming (ILP) model and develop a two-stage framework, incorporating the Late Acceptance Hill Climbing metaheuristic, to increase flexibility across a complete scheduling season to mitigate the effect of blocking on three real-world congested airport instances. Results show that exact methods are not tractable for larger problems, as they are unable to find a solution in reasonable computational time, resulting in the need for heuristic methods to solve such problems in practice. Schedules created using the proposed framework are directly compared to an existing state-of-the-art model which aims to mitigate the effect of blocking through seasonal segmentation. The proposed approach is demonstrated to be able to reduce the effect of blocking, reduce the total number of displaced requests, and the maximum displacement within slot schedules when compared with non-flexible schedules.

Innovation Through the Titip Bandaku Program at Library and Archives Services of Klaten Regency, Indonesia

Background: Concerning archival services, local government agencies are responsible for managing archives within the regions. The Klaten Regency Government has adopted technology to produce innovation in public archives services, focusing on the management and preservation of archival records. To achieve this objective, the Titip Bandaku (Titip Berkas Arsip Digitalku) archival innovation program was established, facilitating the digital conversion of physical documents. However, in the implementation of program which has been running for approximately 5 years, the volume of digitized documents has not met the targets set by Library and Archives Services as the implementing government agency. Purpose: Therefore, This study aimed to examine the implementation of the Titip Bandaku program in protecting and preserving archives, identifying the obstacles included, and how the Klaten Regency Library and Archives Services addressed these challenges. Method: A qualitative-descriptive method was used to describe the implementation of the Titip Bandaku innovation based on the theory of innovation (State Administration Institute, 2017) with two dimensions of innovation namely output and outcome5. Data collection methods included observation, interviews, and documentation. The collected data further underwent stages of analysis through data collection, reduction, presentation, and conclusion. Result: The implementation of the Titip Bandaku Innovation Program positively impacted the preservation of community archives against disasters by digitizing records. On the Output indicator, program was a pioneering effort within Klaten Regency to protect archives in disaster-prone areas, offering swift and customized services despite capacity limitations. On the Outcome indicator, program improves the security of community archives, lowers transportation costs through a mobile services system, and shows sustainability with the backing of regulations, funding, and continuous enhancement of facilities and services. Conclusion: The Titip Bandaku program at the Klaten Regency Library and Archives Services did not achieve optimal functionality. Factors hindering progress included limited human resources, inadequate facilities and infrastructure, and the poor condition of some archives. To improve program’s effectiveness, several measures were recommended, such as forming a dedicated Titip Bandaku team, increasing public outreach through community activities, and fostering partnerships with relevant stakeholders.

Optimization of Reclaiming–Loading Scheduling in Dry Bulk Terminals Based on Knowledge-Driven Memetic Algorithm

Reclaiming–loading operations in dry bulk terminals often face conflicts and delays due to limitations in equipment processing capacity and operational line accessibility, which significantly compromise the safety and efficiency of these operations. This paper aims to optimize the reclaiming–loading schedule for each incoming vessel by considering parallel equipment operations and potential conflicts, with the goal of enhancing both the safety and efficiency of the loading processes. Through a detailed analysis of bulk reclaiming and reclaiming–loading mechanisms, we formulate the dry bulk terminal loading scheduling problem to minimize the total operational time for all loading tasks, taking into account constraints such as parallel reclaiming, collaborative loading, operational conflicts, and line accessibility. In order to obtain a good solution, including task execution sequences and allocation of reclaimers and shiploaders, a knowledge-driven memetic algorithm is developed by integrating knowledge-driven mechanisms with problem-specific operators within a memetic computing framework. Finally, numerical experiments for various scales are conducted using the layout and operational data from the Huanghua Port’s coal port area. The experimental results demonstrate the effectiveness of the proposed optimization algorithm.

Ultrafast Sintering of Dense Li7La3Zr2O12 Membranes for Li Metal All‐Solid‐State Batteries

AbstractUltrafast sintering (UFS) is a compelling approach for fabricating Li7La3Zr2O12 (LLZO) solid‐state electrolytes (SSEs), paving the way for advancing and commercializing Li‐garnet solid‐state batteries. Although this method is commonly applied to the sintering of LLZO ceramics, its use for producing dense, phase‐pure LLZO SSEs has thus far been primarily limited to millimeter‐thick pellets, which are unsuitable for commercial solid‐state batteries. This study presents ultrafast sintering as a highly effective approach for fabricating self‐standing, dense, 45 µm‐thick LLZO membranes. The chemical and structural evolution of LLZO membranes during the UFS process is characterized through in situ synchrotron X‐ray diffraction and thermogravimetric analysis‐mass spectrometry, complemented by an in‐depth investigation of surface chemistry using X‐ray photoelectron spectroscopy. The membranes in Li/LLZO/Li symmetrical cell configuration exhibit a high critical current density of up to 12.5 mA cm−2 and maintain superior cycling stability for 250 cycles at a current density of 1 mA cm−2, with an areal capacity limit of 1 mAh cm−2. The electrochemical performance of LLZO membranes is also assessed in full cell configuration using a pyrochlore‐type iron (III) hydroxy fluoride cathode.

Targeting Full-Hydrogen Operation on Industrial-Scale Gas Turbines: Impact of Unconventional Fuels on Turbine Module Performance and Aeromechanics

Abstract With the trend to full decarbonization, a full hydrogen economy development is a key industrial objective. Gas turbines, currently one of the cleanest fossil fuel-based power generation solutions, provide reliable and on-demand power. The introduction of hydrogen into the fuel mix of existing gas turbines represents a solution with great potential to provide low-carbon or even carbon-free energy. High-hydrogen content fuels, however, challenge the efficient operation of the gas turbine expander, as crucial aspects such as increased flow rate, different gas properties and temperature operating range may affect performance and structural integrity. To evaluate the impact of this conversion, a numerical investigation of five cases with increasing percentages of hydrogen in the fuel was carried out for an industrial four stages gas turbine module. The variation of turbine inlet temperature distribution from combustion chamber was considered, to assess the impact of the unconventional fuel on the well-known aeromechanical behavior of the last stage blades. Variations in capacity, efficiency, power and potential limits due to aeroelasticity were evaluated, identifying the most relevant differences with respect to the full methane case. All these analyses confirm the possibility to employ high-hydrogen fuel operation in a current gas turbine without the need of a further redesign, while maintaining acceptable performance levels.