Search Results (3,776)

In the era of information and communication technology (ICT), the advancement of science and technology has led to a trend of diversification in map representation. However, the lack of professional knowledge means that there is still a challenge in determining the appropriate type of thematic map for land use expression. To address this issue, this paper proposes a knowledge recommendation method for land use thematic maps based on the theory of visualization dimensions. Firstly, we establish a knowledge ontology of land use thematic maps centered on spatial data, data characteristics, visualization dimensions, thematic map forms, and application scenarios. A land use thematic map knowledge graph is constructed through knowledge extraction and storage operations. Secondly, knowledge embedding is performed on the knowledge graph to enable the knowledge-based expression of map visualization elements. Finally, based on the knowledge elements of land use thematic expression, a similarity calculation model is established to calculate the similarity between input data and the spatial data characteristics, visualization dimensions, and application scenarios within the knowledge graph, deriving a comprehensive similarity result to achieve precise recommendation for land use thematic map forms. The results show that the method can provide a more accurate visualization reference for the selection of land use themes, meeting the diversified needs of land use thematic expression to a certain extent. Full article

Recently, thermal regulators based on adsorption in a heat pipe have been proposed. The advantage of these so-called “switchpipes” over similar approaches is their low on state thermal resistance. In this paper, we propose a methodology to calculate and adjust the activation temperature of such switchpipes. For this purpose, we use a mass balance-based model that considers both the heat transfer properties of the heat pipe itself, which depend on the amount of working fluid, and the adsorption equilibrium of the adsorbent used. This model can be used not only to describe the activation behavior of a given heat pipe but also to optimize the configuration of a heat pipe for specific operating conditions and to select appropriate adsorbents. In this paper, we also propose definitions for basic indicators of the activation properties of the heat pipe, such as the activation temperature and the activation temperature span. Finally, a simplified calculation method is presented that allows the selection of the correct adsorbent among all adsorbents with Type IV and Type V adsorption isotherms. Full article

This study investigated the tolerance of resting eggs of Eurytemora pacifica to storage under low temperatures, which is of particular interest in light of the recent use of nauplii as living food in aquaculture, other than conditions experienced also in the wild during winter cold events in the Northern Hemisphere. Sediment samples collected in August 2020 were used to store the resting eggs at two different freezing temperatures (−5 and −20 °C) for five different durations (1, 3, 6, 9, and 12 months). The mean hatching success rates of the resting eggs after one month of storage were 85.3% (−5 °C) and 85.0% (−20 °C), with no significant difference between freezing temperatures. However, significant differences emerged over time, with hatching success dropping to 65.3% at −5 °C and to 32.7% at −20 °C after 12 months. For the non-freezing conditions, the hatching success at 10 °C increased gradually over the one-month incubation period, ultimately reaching 71.0%. These findings demonstrate the remarkable cold tolerance of E. pacifica but also indicate a limit to this tolerance at longer durations. These results underscore the importance of considering the adoption of storage freezing for resting eggs to be used for aquaculture and also suggest the possibility of the species better surviving the extreme weather events in comparison with other species. Full article

Educational institutions are increasingly using audio-based learning resources and technologies nowadays, especially for students who are auditory learners and visually impaired. The ability to design and create online educational talking books with a pedagogical foundation has become essential for students studying instructional and information technology in the age of digital learning. With the need to enhance such skills to target students in higher educational institutions, instructional and information technology students have no specialized platform for designing and producing an online educational talking book without web programming challenges. This study suggests a new specialized, web-based platform that can assist students in developing online educational talking books. In this study, fourteen instructional technology experts evaluated the proposed platform’s usability. An online questionnaire was utilized to gather data, applying qualitative and quantitative methodologies. The results show that the proposed platform is appropriate for creating and developing an online educational talking book for the intended audience of students. Furthermore, the suggested platform’s current version had a workable design that was appropriate for helping students acquire the necessary abilities. Full article

The research determines the level of financial risk in the Russian healthcare system and identifies prospects for improving the current Russian practice of financial risk management in healthcare when providing high-tech medical care for sustainable development (using Russia as an example). The author summarizes the advanced experience of the top 20 largest healthcare organizations in Russia by revenue in 2022. Based on this experience, the author developed an SEM model of the financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. The theoretical significance of the developed model lies in uncovering the previously unknown causal relationships between the implementation of the ICT, sustainable development support, and financial risks in healthcare. The model reveals a new market dimension of financial risks for healthcare organizations in Russia. The main conclusion is that implementing the ICT and support for sustainable development helps to reduce the financial risks in healthcare. The identified potential for reducing financial risks in providing high-tech medical care in Russia until 2026 is practically significant. This prospect can be practically applied as a roadmap for the digital modernization and sustainable development of healthcare until 2026, enhancing the state healthcare policy in Russia. The established systemic relationship between ICT implementation, sustainable development support, and financial risks in healthcare is of managerial importance because it will increase the predictability of the financial risks in the market dimension of healthcare in Russia. The newly developed approach to risk management in healthcare during the provision of high-tech medical care in Russia has expanded the instrumental framework of risk management for healthcare organizations in Russia and revealed further opportunities for improving its efficiency. Full article

Key–value stores (KV stores) are becoming popular in both academia and industry due to their high performance and simplicity in data management. Unlike traditional database systems such as relational databases, KV stores manage data in key–value pairs and do not support relationships between the data. This simplicity enables KV stores to offer higher performance. To further improve the performance of KV stores, high-performance storage devices such as solid-state drives (SSDs) and non-volatile memory express (NVMe) SSDs have been widely adopted. These devices are intended to expedite data processing and storage. However, our studies indicate that, due to a lack of multi-thread-oriented programming, the performance of KV stores is far below the raw performance of high-performance storage devices. In this paper, we analyze the performance of existing KV stores utilizing high-performance storage devices. Our analysis reveals that the actual performance of KV stores is below the potential performance that these storage devices could offer. According to the profiling results, we argue that this performance gap is due to the coarse-grained locking mechanisms of existing KV stores. To alleviate this issue, we propose a multi-threaded compaction operation that leverages idle threads to participate in I/O operations. Our experimental results demonstrate that our scheme can improve the performance of KV stores by up to 16% by increasing the number of threads involved in I/O operations. Full article

The precise segmentation of different regions of the prostate is crucial in the diagnosis and treatment of prostate-related diseases. However, the scarcity of labeled prostate data poses a challenge for the accurate segmentation of its different regions. We perform the segmentation of different regions of the prostate using U-Net- and Vision Transformer (ViT)-based architectures. We use five semi-supervised learning methods, including entropy minimization, cross pseudo-supervision, mean teacher, uncertainty-aware mean teacher (UAMT), and interpolation consistency training (ICT) to compare the results with the state-of-the-art prostate semi-supervised segmentation network uncertainty-aware temporal self-learning (UATS). The UAMT method improves the prostate segmentation accuracy and provides stable prostate region segmentation results. ICT plays a more stable role in the prostate region segmentation results, which provides strong support for the medical image segmentation task, and demonstrates the robustness of U-Net for medical image segmentation. UATS is still more applicable to the U-Net backbone and has a very significant effect on a positive prediction rate. However, the performance of ViT in combination with semi-supervision still requires further optimization. This comparative analysis applies various semi-supervised learning methods to prostate zonal segmentation. It guides future prostate segmentation developments and offers insights into utilizing limited labeled data in medical imaging. Full article

Causal Consistency has been proven to be the strongest type of consistency that can be achieved in a fault-tolerant, distributed system. This paper describes an implementation of D-Thespis, which is an approach that employs the actor mathematical model of concurrent computation to establish a distributed middleware that enforces causal consistency on a widely used relational database management system (RDBMS). D-Thespis prioritises developer experience by encapsulating the intricacies of causal consistency behind an interface that is accessible over standard REST protocol. Here, we discuss several novel results. Firstly, we define a method that builds a causally consistent DBMS supporting elastic horizontal scalability. Secondly, we deliver a cloud-native implementation of the middleware and provide results and insights on 6804 benchmark configurations executed on our implementation while running on a public cloud infrastructure across several data centres. The evaluation concerns transaction processing performance, an evaluation of our implementation’s update visibility latency, and a memory profiling exercise. The results of our evaluation show that under a transactional workload, a single-node installation of our implementation of D-Thespis is 1.5 times faster than a relational DBMS running serialisable transaction processing, while the performance of the middleware can improve by more than three times when scaled horizontally within the same data centre. Our study of the memory profile of the D-Thespis implementation shows that the system distributes its memory requirements evenly across all the available machines, as it is scaled horizontally. Finally, we also illustrate how our middleware propagates data changes across geographically-distributed infrastructures in a timely manner: our tests show that most of the effects of data change operations in one data centre are available in a remote data centre within less than 300 ms over and above the network round trip latency between the two data centres. Full article

This article seeks to reflect on the opportunities that mobile smartphones (MSPs) present as ICT integration tools in teaching geography. The more extensive study, underpinned by the Professional Development Framework for Digital Learning (PDFDL) in ICT integration, employed a qualitative research approach. Lensed by the Professional Development Framework for Digital Learning (PDFDL), the article used the qualitative approach to garner insights from the participants regarding using MSPs as tools to integrate ICT in geography teaching. Data collection tools included interviews, observations, and document reviews. Researchers sampled (n = 4) schools, interviewed and observed (n = 13) teachers, and interviewed (n = 10) learners and (n = 8) parents in the province of KwaZulu-Natal. Furthermore, they used a purposive sampling technique to access the participants, basing the research on the premise that MSPs promote virtual reality for an array of learners. As the findings revealed, although some participants viewed the use of MSPs as a distractor in the learning space, teachers felt compelled to heed the call to modify their teaching pedagogies, such that they integrated mobile phones fruitfully in their teaching. The findings further revealed that such a paradigm shift would benefit homeschooling and facilitate a dual teaching mode at learning institutions. Curriculum planners are responsible for helping teachers accept that uncertainty is the only certainty about the future, considering the volatility, uncertainty, complexity, and augmentation (VUCA) challenges brought on by the COVID-19 pandemic. Extended lockdown periods accelerated the use of MSPs in teaching, requiring every stakeholder in the educational space to become a life-long learner by using a range of technologies and platforms. Full article

Accurate skin diagnosis through end-user applications is important for early detection and cure of severe skin diseases. However, the low quality of dermoscopic images hampers this mission, especially with the presence of hair on these kinds of images. This paper introduces DM–AHR, a novel, self-supervised conditional diffusion model designed specifically for the automatic generation of hairless dermoscopic images to improve the quality of skin diagnosis applications. The current research contributes in three significant ways to the field of dermatologic imaging. First, we develop a customized diffusion model that adeptly differentiates between hair and skin features. Second, we pioneer a novel self-supervised learning strategy that is specifically tailored to optimize performance for hairless imaging. Third, we introduce a new dataset, named DERMAHAIR (DERMatologic Automatic HAIR Removal Dataset), that is designed to advance and benchmark research in this specialized domain. These contributions significantly enhance the clarity of dermoscopic images, improving the accuracy of skin diagnosis procedures. We elaborate on the architecture of DM–AHR and demonstrate its effective performance in removing hair while preserving critical details of skin lesions. Our results show an enhancement in the accuracy of skin lesion analysis when compared to existing techniques. Given its robust performance, DM–AHR holds considerable promise for broader application in medical image enhancement. Full article

This article explores the evolution of road freight transport in the context of Industry 4.0, focusing on management practices and technological advancements in transport and logistics companies’ management information systems. By analyzing the latest international practices in road freight quality management within Industry 4.0 through regression and correlation methods, a model highlighting the significant influence of quality over price and institutional factors on the development of information and communication technology (ICT) goods exports was developed. It showcases how digital frameworks, alongside AI and big data, can enhance road freight quality in Industry 4.0, establishing a digital ecosystem for transport and logistics quality management. This study introduces a novel perspective on managing road freight transport as a digital ecosystem, offering insights into improving ICT goods exports in Kazakhstan by enhancing management information systems. It suggests a new management information system organization scheme to increase road freight quality management efficiency and ensure quality in Industry 4.0 settings. Full article

One of the main Frequently Asked Questions (FAQs) in project management for built environment or physical infrastructure projects is “How will this project scope be delivered on time and under budget, addressing health and safety in a sustainable way?” This article presents a parallel point of view summarised in a competing question: “Have you followed a systems engineering methodology to detail interfaces and integrations in the business case?” Megaprojects face multiple risks that incur project delays and cost overruns; hence, this article proposes a simple but nevertheless innovative model that incorporates a systems engineering framework at the start of the built environment or physical infrastructure project: the business case phase. This proposed approach seeks to derisk megaprojects composed of complex systems of systems (SoSs) in their earliest stage when financial decisions based on cost estimations have to be made. The scope of this article covers built environment and physical infrastructure projects and their associated ICT, digital, and technology programmes, rather than purely IT developments. The inconvenient truth is this additional systems engineering task embedded in the business case comes at a further project CAPEX cost that decision makers or stakeholders should be willing to accept as it provides a wider technical vision of the project and better quantifies the Return on Investment (ROI). Full article

In today’s power systems, electric vehicles (EVs) constitute a significant factor influencing electricity dynamics, with their important role anticipated in future smart grid systems. An important feature of electric vehicles is their dual capability to both charge and discharge energy to/from their battery storage. Notably, the discharge capability enables them to offer vehicle-to-grid (V2G) services. However, most V2G research focuses on passenger cars, which typically already have their own specific usage purposes and various traveling schedules. This situation may pose practical challenges in providing ancillary services to the grid. Conversely, electric school buses (ESBs) exhibit a more predictable usage pattern, often deployed at specific times and remaining idle for extended periods. This makes ESBs more practical for delivering V2G services, especially when prompted by incentive price signals from grid or utility companies (UC) requesting peak shaving services. In this paper, we introduce a V2G energy sharing model focusing on ESBs in various schools in a single community by formulating the problem as a leader–follower game. In this model, the UC assumes the role of the leader, determining the optimal incentive price to offer followers for discharging energy from their battery storage. The UC aims to minimize additional costs from generating energy during peak demand. On the other hand, schools in a community possessing multiple ESBs act as followers, seeking the optimal quantity of discharged energy from their battery storage. They aim to maximize utility by responding to the UC’s incentive price. The results demonstrate that the proposed model and algorithm significantly aid the UC in reducing the additional cost of energy generation during peak periods by 36% compared to solely generating all electricity independently. Furthermore, they substantially reduce the utility bills for schools by up to 22.6% and lower the peak-to-average ratio of the system by up to 9.5%. Full article

Icaritin (ICT), a natural compound extracted from the dried leaves of the genus Epimedium, possesses antitumor and immunomodulatory properties. However, the mechanisms through which ICT modulates pyroptosis and immune response in hepatocellular carcinoma (HCC) remain unclear. This study demonstrated that ICT exhibits pyroptosis-inducing and anti-hepatocarcinoma effects. Specifically, the caspase1-GSDMD and caspase3-GSDME pathways were found to be involved in ICT-triggered pyroptosis. Furthermore, ICT promoted pyroptosis in co-cultivation of HepG2 cells and macrophages, regulating the release of inflammatory cytokines and the transformation of macrophages into a proinflammatory phenotype. In the Hepa1-6+Luc liver cancer model, ICT treatment significantly increased the expression of cleaved-caspase1, cleaved-caspase3, and granzyme B, modulated cytokine secretion, and stimulated CD8⁺ T cell infiltration, resulting in a reduction in tumor growth. In conclusion, the findings in this research suggested that ICT may modulate cell pyroptosis in HCC and subsequently regulate the immune microenvironment of the tumor. These observations may expand the understanding of the pharmacological mechanism of ICT, as well as the therapy of liver cancer. Full article

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen is essential for any water quality management structure. This research was conducted to develop a novel Nitrate Portable Measurement System (NPMS) to monitor nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on the Beer–Lambert law for measuring nitrate concentrations in water samples through light absorption in the spectral range of 295–315 nm. The system is equipped with a ready-to-use ultraviolet sensor, light emission diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box, which allows a very compact self-contained equipment with high portability, enabling field and near-real-time measurements. The proposed methodology and the developed instrument were used to analyze multiple nitrate standard solutions. The performance was evaluated in comparison to the Nicolet Evolution 300, a classical UV–Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO₃⁻/L. Full article