Limited Space Research Articles

Machine learning accelerated search for the impact limit of the graphene/aluminum alloy whipple structure

This paper proposes a Whipple structure to enhance the impact resistance of graphene/aluminum alloy composites by varying the interlayer spacing between graphene and aluminum alloy. The increased interlayer spacing provides more deformation space for the graphene to absorb more deformation energy, and enables the formation of a debris cloud from the bullet fragments and graphene fragments, significantly reducing the impact energy per unit area of the next material. The impact limit serves as a critical metric for assessing the impact resistance of the Whipple structure. Based on molecular dynamics simulations, we developed a machine learning model to predict the protection of aluminum alloy, and quickly determined the impact limits of velocity, bullet radius, and interlayer spacing by using the machine learning model. An empirical equation for the impact limit of interlayer spacing was established. The results showed that non-zero interlayer spacing can significantly improve the impact resistance of the hybrid structure; to fully exploit the superior impact resistance of this Whipple structure, the number of graphene layers should be at least 3. Furthermore, at high impact velocities and large bullet radii, the impact limit of the interlayer spacing exhibits a substantial correlation with the number of graphene layers. These results provide valuable information for the design of the impact resistance of the graphene/aluminum alloy composites.

Clinical Supervision Postpandemic: Providing a Continuity of Care and Supervision Using Zoom in the University Clinic Setting

Purpose: The COVID-19 pandemic necessitated the shift to telepractice by university clinics. Supervision then occurred through Zoom or other videoconferencing platforms. Although clinics have returned to in-person services, the use of telepractice still continues as a preferred form of service delivery for many clients. However, providing both telepractice and in-person supervision in one university clinic can present many challenges. This article describes how one pro bono university clinic is resolving supervisor observation issues and space limitations by implementing a cohesive, low-cost Zoom observation system that is used with both in-person and telepractice clients. Method: The history of the previous observation system is provided along with the factors that necessitated the shift to the videoconferencing platform. The authors describe the configuration of the clinic rooms, the equipment needed to implement a similar observation system, and recommendations for getting started. This article also discusses the benefits and challenges of using the Zoom observation system for supervision with graduate student clinicians and their clients. Conclusion: The information is relevant to programs seeking to implement an effective low-cost observation system for training graduate students in a university clinic.

Drug repositioning based on weighted local information augmented graph neural network.

Drug repositioning, the strategy of redirecting existing drugs to new therapeutic purposes, is pivotal in accelerating drug discovery. While many studies have engaged in modeling complex drug-disease associations, they often overlook the relevance between different node embeddings. Consequently, we propose a novel weighted local information augmented graph neural network model, termed DRAGNN, for drug repositioning. Specifically, DRAGNN firstly incorporates a graph attention mechanism to dynamically allocate attention coefficients to drug and disease heterogeneous nodes, enhancing the effectiveness of target node information collection. To prevent excessive embedding of information in a limited vector space, we omit self-node information aggregation, thereby emphasizing valuable heterogeneous and homogeneous information. Additionally, average pooling in neighbor information aggregation is introduced to enhance local information while maintaining simplicity. A multi-layer perceptron is then employed to generate the final association predictions. The model's effectiveness for drug repositioning is supported by a 10-times 10-fold cross-validation on three benchmark datasets. Further validation is provided through analysis of the predicted associations using multiple authoritative data sources, molecular docking experiments and drug-disease network analysis, laying a solid foundation for future drug discovery.

3D aerogel membrane-based evaporator with sandwich structure for superior solar-driven evaporation

Seawater desalination with solar-driven interfacial evaporators has emerged as a promising solution to alleviate global water scarcity. However, conventional two-dimensional (2D) planar evaporators have high reflectivity, which poses a challenge in achieving efficient light absorption. Herein, a sandwich-structured solar-driven interfacial evaporator (SSIE) assembled with three-dimensional (3D) cellulose aerogel membranes (modified with TiN nanoparticles) and an air-laid paper was proposed, which is significantly different from the previously reported 2D membrane-based evaporators. Cellulose aerogel membranes have excellent integrated properties, including extremely high flexibility, allowing for multiple folds, and a 3D porous structure that enables multiple light absorptions. Benefiting from special structural design, SSIE achieves an outstanding evaporation rate of 2.20 kg m−2 h−1 and an energy efficiency of 83.30%. Moreover, SSIE maintains a stable evaporation rate throughout a 10 h saltwater evaporation process. It also demonstrates excellent performance in seawater and simulated wastewater purification. Furthermore, SSIE exhibits a significant purification effect for dye wastewater, such as Rhodamine B (RhB). This study provides valuable insights into rational structural design for solar evaporators, as well as holding tremendous potential for carrying out seawater desalination in limited spaces.

RANCANG BANGUN LEARNING MANAGEMENT SYSTEM, STUDI KASUS: SMK WIPAMA CIKUPA

This study aims to design and develop an effective and efficient learning media at Wipama Cikupa Vocational School, because this Vocational School faces obstacles in terms of limited classroom space and learning time which is divided into two shifts. To overcome this problem, the development of an LMS (Learning Management System) was implemented as a solution to provide learning without distance, place and time limitations. E-learning was chosen as the main approach in this research, because of its flexibility, self-learning ability, and cost efficiency for both administrators and students. The development of this LMS includes the stages of system requirements analysis, user interface design, database design, coding using the PHP programming language, and testing. The development method used is the Waterfall model to ensure planned and systematic development. The testing phase is carried out using a black box approach to ensure compatibility between the system being developed and the desired requirements. The result of this research is the implementation of the LMS (Learning Management System) which allows online learning through a website platform, so that this school can overcome the limitations of classrooms and time, and increase the effectiveness and efficiency of the learning process in this school.

Possible approaches to the study of emissions from ships during their operations in ports

The emissions from ships are the key factor influencing the air quality near large ports. Although ship emissions are difficult to quantify, doing so can help port management find logistical solutions that can reduce the impact of having a large number of giant ships in a limited space. The joint study between the University of Naples and Istanbul Technical University, which focuses on the investigation of ship emissions in ports, is presented in this paper. It is expected that this study will lead to create new techniques for calculating, measuring, and validating emissions from ships at ports.

Análisis histórico de la formación de competencias profesionales en la carrera de Licenciatura en Enfermería

The history of the formation of professional competencies in the Bachelor's Degree in Nursing in Cuba is an exciting area of study. However, it is challenging to summarize in a limited space the historical evolution of this topic. The main objective of this study is to describe the process of formation of professional competencies in the Bachelor's Degree in Nursing. To achieve this objective, we carried out an exhaustive documentary and bibliographic review related to the topic, in addition to conducting interviews with professors prominent in the training of nursing professionals. Throughout the paper, the historical evolution of the formation of professional competencies in the Nursing career is presented. It is concluded that professional training in nursing requires both a theoretical and practical construction of the training process. In addition, it must be sensitive to the demands imposed by current social and economic policies. In this context, the commitment to integrate content related to professional competencies in the Bachelor's Degree in Nursing programs, with a focus on patient safety, is highlighted. The training of nurses is oriented towards the maintenance and recovery of health, the prevention of diseases and the rehabilitation of people with sequelae. These approaches will guide the content developed in the curriculum that prepares students to manage patient safety in acute care. In addition, the authors analyze how this training process is congruently adapted to the care model developed in health services.

Optimisation and analysis of an integrated energy system with hydrogen supply using solar spectral beam splitting pre-processing

The application of integrated energy systems (IES) in urban areas is gradually increasing, yet the constraint of limited building space poses a significant challenge to effective system planning. In this paper, to address the issue of area limitation from the perspective of improving solar energy utilization. A novel IES utilizing solar spectral beam splitting (SBS) for hydrogen production is proposed, which introduces SBS technology to make full use of the sun’s full-spectrum energy. Furthermore, the incorporation of photocatalytic hydrogen production introduces an innovative approach to meet the hydrogen needs of hydrogen refuelling stations, facilitating highly efficient co-generation of cooling, heating, electricity, and hydrogen supply. To determine the optimal system configuration, a comparison is made with a stand-alone solar system using a honey badger-simulated annealing optimization algorithm. The results show that the SBS-IES achieves a solar energy utilization rate of 37.72% and reduces equipment footprint by 20.48%. Furthermore, a sensitivity analysis is performed to analyse the impact of changes in floor space on the system. This innovative system is suitable for small-scale IES and serves as an efficient solution for urban energy systems.

Few-shot classification with multisemantic information fusion network

Metric-based methods aim to predict class labels by computing the similarity between samples using distance functions, which is the mainstream approach to few-shot learning. However, the limited representational space of feature vectors and appearance variations among congenetic samples still present challenges. We propose a Multisemantic Information Fusion Network (MIFN) to address these problems. A Lower-level Feature generator (LF-generator), which is an unsupervised module, adaptively activates high-response regions of objects to introduce discriminative semantic details. Meanwhile, a Higher-level Feature extractor (HF-extractor) learns global semantic information with human cognition to minimise the impact of appearance variations. We integrate the coarse outputs of these two modules, which complement each other to jointly promote more precise predictions. Furthermore, considering the importance of prototypes, we redefine the sampling strategy of the triplet loss and utilise it as an auxiliary loss to sharpen the decision boundary at the prototype level, facilitating subsequent classification. Our experimental results demonstrate the competitiveness of our approach in both general few-shot classification (mini-ImageNet and tiered-ImageNet) and cross-domain problems (CUB, Caltech-101, Stanford-dogs, and Stanford-cars) with minimal bells and whistles.

HPB O08 Championing benign biliary patients in Emergency General Surgery: A 3 year quality improvement project

Abstract Background A biliary quality improvement project (QuIP) was established in 2019 following 3 audit cycles highlighting delays to laparoscopic cholecystectomy (Lap-C) in patients with gallstone pancreatitis. Limited theatre space and other urgent care priorities hindered efforts to meet other biliary key performance indicator targets between 2015 and 2019. The last phase of the QuIP has introduced a dedicated consultant lead biliary service, a live biliary patient tracking system, increased in-patient Lap-C, implementation of ambulatory pathways and a patient centred integrated care approach. Methods Prospectively collected data from a live biliary tracking system was compared with retrospective audit data from 2015-2019. Key performance indicators were; average time to Lap-C, rate of Lap-C with-in 2 weeks following pancreatitis, inpatient Lap-C rate and out-patient appointments saved. Results 523 patients were managed through inpatient and ambulatory biliary pathways from November 2021-June 2023. 2 week Lap-C post pancreatitis improved from 27% to 79% (43% as inpatients) with average time to Lap-C improving from 68 days to 13 days. 191 outpatient appointments were saved by counselling and pre-assessing patients for Lap-C as inpatients, saving £22920 in outpatient costs. In-patient Lap-C rate improved from 2% to 19% for fit and consenting patients. Conclusions A higher quality of care can be achieved for biliary patients through; effective patient prioritisation, increasing inpatient Lap-C, the establishment of ambulatory pathways and a robust outpatient tracking system.

Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon

The first-of-its-kind use of the active learning (AL) framework in thermal spray is adapted to enhance the prediction accuracy of the in-flight particle characteristics. The successful AL framework implementation via Bayesian Optimisation is beneficial in, first, reducing the maximum uncertainty, which greatly improves the prediction accuracy and informativeness of the existing database. Second, it reduces local uncertainty around a contrived test point that offers the capability to find improvement in a limited search area, allowing an accurate prediction around a desired test point. The dataset for Machine Learning (ML) training consists of 26 atmospheric plasma spray (APS) parameters of silicon and a further six AL-guided spray runs carried out to reduce maximum uncertainty in the initial database. On average, a 52.9% improvement (error reduction) of RMSE and an R2 increase of 8.5% were reported on the predicted in-flight particle velocities and temperatures after the AL-driven optimisation. Furthermore, the contrived test point optimisation to predict the best possible characteristics in a limited search space resulted in a three-fold increase in prediction accuracy compared to the non-optimised prediction. The AL-driven optimisation proved to be greatly beneficial for resource-intensive thermal spraying, as the framework not only allowed an accurate prediction of the in-flight particle characteristics but also found expected improvement around a desired in-flight characteristic. Furthermore, the framework uses the Gaussian Process (GP) ML model as a surrogate that generalises a global solution without necessarily involving physical and underlying mechanisms, thus extending the framework to other thermal spraying methods.

Q-Learning and Efficient Low-Quantity Charge Method for Nodes to Extend the Lifetime of Wireless Sensor Networks

With the rapid development of the Internet of Things (IoT), improving the lifetime of nodes and networks has become increasingly important. Most existing medium access control protocols are based on scheduling the standby and active periods of nodes and do not consider the alarm state. This paper proposes a Q-learning and efficient low-quantity charge (QL-ELQC) method for the smoke alarm unit of a power system to reduce the average current and to improve the lifetime of the wireless sensor network (WSN) nodes. Quantity charge models were set up, and the QL-ELQC method is based on the duty cycle of the standby and active times for the nodes and considers the relationship between the sensor data condition and the RF module that can be activated and deactivated only at a certain time. The QL-ELQC method effectively overcomes the continuous state–action space limitation of Q-learning using the state classification method. The simulation results reveal that the proposed scheme significantly improves the latency and energy efficiency compared with the existing QL-Load scheme. Moreover, the experimental results are consistent with the theoretical results. The proposed QL-ELQC approach can be applied in various scenarios where batteries cannot be replaced or recharged under harsh environmental conditions.

Strategi Komunikasi Content Creator Podcast Disabilitas Sebagai Platform Peningkatan Disability Awareness

<p><em>This research aims to explore the communication strategies employed by disabled content creators in podcasts to enhance disability awareness among their audience. The utilization of podcast platforms for disseminating disability awareness by content creators Afif, Argya, and Dhani is motivated by various factors, such as ease of use and wider dissemination beyond the limitations of space and time. Their podcast content educates the general public about disability awareness, aiming to challenge the prevailing stigma surrounding disabled individuals. By employing their respective communication strategies to package the messages conveyed in their podcast content, they aspire to make their educational efforts accessible to a broader audience. This study adopts a qualitative approach with a case study method. Data collection involves observation and interviews with the three research subjects. The findings reveal that all three creators have communication strategies aligned with the developmental communication and empowerment perspectives. Additionally, the research identifies that the three creators engage in innovation diffusion to enhance disability awareness within society. The study also outlines the stages involved in the creation and dissemination of podcast content by these creators. The responses received after creating podcast content include both positive and negative feedback. Positive feedback includes increased knowledge and behavioral changes experienced by the listeners, indicating the effectiveness of the communication strategies employed. Consequently, the messages conveyed are not only well-received but also put into practice by the audience. On the other hand, negative feedback indicates the persistence of negative prejudices from some listeners concerning the experiences shared by disabled creators. </em></p>

A novel technique for constructing prefabricated subway stations under open excavation

Prefabricated construction is essential for realising green, efficient and sustainable development of rail transit. However, limited space in foundation pits and cross-interference with inner struts mean that the advantages of existing prefabrication technology cannot be leveraged effectively to build subway stations under open excavation with inner support. In this paper, this problem is addressed by introducing a modular design method and two novel connection technologies. The proposed modular design method is sufficiently adaptable to balance the use of space between the station structure and the inner struts. The two proposed connection technologies provide efficient ways to assemble different concrete segments with two newly developed joints – namely, a CHC joint (comprising two C-shaped and one H-shaped steel members) and a flexible lock joint – in the circumferential and longitudinal directions, respectively. The first application of this fully prefabricated scheme in the Shenzhen Metro shows the huge potential of this technology for constructing subway stations under open-cut conditions, and its advantages in technical, economic and social aspects reveal wide application prospects in rail transit.

Programmable mixed-signal circuits

A novel concept for programmable mixed-signal circuits is presented based on programmable transmission gates. For implementation, memristively switching devices are suggested as the most promising candidates for realization of fast and small-footprint signal routing switches with small resistance and capacity. As a proof-of-concept, LT Spice simulations of digital and analogue example circuits implemented by the new concept are demonstrated. It is discussed how important design parameters can be tuned in the circuity. Compared to competing technologies such as Field Programmable Analogue Arrays or Application-Specific Integrated Circuits, the presented concept allows for development of ultra-flexible, reconfigurable, and cheap embedded mixed-signal circuits for applications where only limited space is available or high bandwidth is required.

Quantum de Finetti Theorems as Categorical Limits, and Limits of State Spaces of C*-algebras

Quantum de Finetti Theorems as Categorical Limits, and Limits of State Spaces of C*-algebras

A Study on the Aesthetics of Chinese “Handscroll Films”

Abstract The handscroll, a traditional painting format in China, has had a profound impact on Chinese films. Handscrolls display not only lively landscape paintings, but also ingenious concepts. In Chinese cinema practice, a handscroll-like composition contributes to the combination of “immersion” (沉浸, Chenjin) and “understanding” (认识, Renshi), two different philosophical and aesthetic concepts. These are used to show a strong sense of history within the limited space of rectangular film scenes, reflecting dynamism and rich with soul. Combined with the technique of “looking back” (回眸, Huimou), handscroll-like compositions function as a chain of connectivity, further leading the audience into a reverie. Consequently, many young directors have applied this creative method to whole film structures in recent years, showing courage to push creative limits.

A novel control method for the automotive CO2 heat pumps under inappropriate refrigerant charge conditions

CO2 heat pumps are increasingly widely used in automotive air conditioning, and the demand for refrigerant charge varies greatly under different modes and operation conditions. However, due to the limited space in vehicles, the accumulator cannot fully meet the refrigerant balance requirements for the variable operating conditions, and states of inappropriate refrigerant charge were frequently observed. To enhance system performance and safety under inappropriate charge conditions, an experimental setup and a mathematical model with a maximum error of 6 % were established to investigate the operating characteristics under inappropriate charge conditions. An investigation into the interplay among discharge pressure, the appropriate refrigerant charge range, and refrigerant distribution was conducted. It elucidated how refrigerant charging states (undercharged, adequately charged, or overcharged) manifest in terms of refrigerant distribution and optimal discharge pressure. A novel control method based on refrigerant distribution regulation has been proposed. The proposed control logic could increase the system IPLV by 36.8 % when the refrigerant charge deviates from the appropriate range by 12.12 %, and the greater the dysregulation in the refrigerant charge, the greater the improvement. This control logic would be more enhanced if dysregulation was considered.

Design and Implementation of Experiment Online Teaching Platform for Oil and Gas Storage and Transportation Based on WeChat Mini-Program

With the emergence of “Internet + higher education,” online teaching platforms have become increasingly important, particularly for practical teaching courses. The study of oil and gas storage and transportation is a fundamental and essential course for students in this major. In light of the issues related to limited space, lack of openness, and low student enthusiasm for traditional experimental teaching methods, an online experimental teaching platform for oil and gas storage and transportation was developed. This platform is based on the WeChat mini-program and follows the principles of cross-platform computability, user friendliness, and low investment. Its aim is to explore effective learning models for mobile devices. This study compares and analyzes the differences in classroom effects before and after the implementation of the WeChat learning platform. The study examines the design of the platform, teaching session cases, and the analysis of application effects. The research utilizes questionnaires and statistical data as research methods. The results indicate that the WeChat online teaching platform has significantly improved the enthusiasm and learning outcomes of students in the independent learning of experimental courses. It has received high recognition from both teachers and students and has greatly enhanced the quality of teaching. This has considerable potential for further promotion.

Abbreviations in social media communication

Abbreviations form a large part of current social media communication, where messages are conditioned by time and space, allowing for fast communication in a limited space. Many abbreviations do not have an impact on language data, since they are just an alternative form of their corresponding non-abbreviated expression. However, they are a productive source of neologisms. This article presents an analysis of the trendy abbreviations used in social media by Portuguese youth and the associated neology phenomena. The lexicographic treatment of these abbreviations in the context of planning a dictionary designed to help people cope with these new trends is discussed, with a particular emphasis on neologisms. In considering the target audience and the main focus of users’ needs and profiles in modern lexicography, the decisions presented cover general options for data selection, and for the definition and design of the microstructure and macrostructure of the dictionary.