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Building Information Modeling (BIM) has attracted much attention as a vital information method in civil engineering. BIM data research has become increasingly important with the continuous understanding of BIM. The database designed especially for storing BIM data (IFC data) is called a BIM database. To realize centralized storage and sharing of complex building information, how to design and develop a BIM database will be a hot topic. However, the BIM database designed using an existing logical model (such as a relational model) is unsuitable for storing and managing a large amount of BIM data. To this end, we propose a database logical model for BIM database development called 'logical object structure'. Based on the database design methodology, the logical schema of the BIM database is discussed, and five relation forms are established to describe the feature of engineering information. According to the relation forms, the logical object structure is presented, and the corresponding system implementation process is discussed. Finally, four workloads are set to test the logical object structure. The results show that the logical object structure can well support interactive behaviors of BIM data and provide good performance for the BIM database. [ABSTRACT FROM AUTHOR]

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well‐studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land‐mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer‐reviewed literature with a survey of eDNA users including academics, end‐users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever‐increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward. [ABSTRACT FROM AUTHOR]

Purpose: To identify associations between systemic drugs and the incidence of diabetic macular oedema (DME). Of interest was to find beneficial and/or deleterious associations of used drugs. Methods: A historic cohort design based on administrative data. Study population consisted of 150 353 individuals with diabetes. Endpoint event was the development of DME (ICD‐10 H36.01), censoring events were death or study end December 2017. The follow‐up started between 1997 and 2010. The systemic medication consisted of 95 substances. We constructed a nested case–control study design comparing 2630 cases with DME to 13 144 age‐ and sex‐matched controls without DME. Results are reported as odds ratios (ORs) with 95% confidence intervals (CIs) based on conditional logistic regression models. Results: Incidence rate for DME was 1.80 per 1000 person‐years (95% CI 1.73–1.87). In all, we observed a lower incidence rate of DME in females (IRR 0.57; 95% CI 0.52–0.62) compared to males. Exposure to hormone replacement therapy estradiol (OR 0.42; 0.25–0.68), temazepam (0.23; 0.08–0.62) and allopurinol (0.61; 0.43–0.86) were associated with lower risk of DME, while use of insulin or insulin analogue (3.30; 2.99–3.64), sulfonylureas (1.21; 1.05–1.40), diuretic furosemide (1.90; 1.61–2.24), calcium channel blocker amlodipine (1.53; 1.34–1.75), ACE inhibitors ramipril (1.66; 1.46–1.89) and enalapril (1.38; 1.16–1.64) were associated with an increased risk of DME. Conclusions: Large‐scale studies examining the incidence of DME are lacking. Our findings suggest that associations of systemic medications with the incidence of DME may shed light on the pathogenesis of complex DME, encouraging further studies. [ABSTRACT FROM AUTHOR]

Summary: Global assessments of mycorrhizal symbiosis present large sampling gaps in rich biodiversity regions. Filling these gaps is necessary to build large‐scale, unbiased mycorrhizal databases to obtain reliable analyses and prevent misleading generalizations. Underrepresented regions in mycorrhizal research are mainly in Africa, Asia, and South America. Despite the high biodiversity and endemism in these regions, many groups of organisms remain understudied, especially mycorrhizal fungi. In this Viewpoint, we emphasize the importance of inclusive and collaborative continental efforts in integrating perspectives for comprehensive trait database development and propose a conceptual framework that can help build large mycorrhizal databases in underrepresented regions. Based on the four Vs of big data (volume, variety, veracity, and velocity), we identify the main challenges of constructing a large mycorrhizal dataset and propose solutions for each challenge. We share our collaborative methodology, which involves employing open calls and working groups to engage all mycorrhizal researchers in the region to build a South American Mycorrhizal Database. By fostering interdisciplinary collaborations and embracing a continental‐scale approach, we can create robust mycorrhizal trait databases that provide valuable insights into the evolution, ecology, and functioning of mycorrhizal associations, reducing the geographical biases that are so common in large‐scale ecological studies. [ABSTRACT FROM AUTHOR]

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species. [ABSTRACT FROM AUTHOR]

In the fast-paced fashion world, unique designs are like early birds, grabbing attention as online shopping surges. Fabric texture plays an immense role in selecting the perfect design. Indian Traditional textile motifs are pivotal, showing rich cultural origins and attracting worldwide art fanatics. Yet, technology-driven abstract forms are posing a challenge for them. The decline of handmade artistic ability due to computerization is concerning. Crafting new designs associated with the latest trends is time- consuming and requires diligence. In this work an interactive CBIR (content-based image retrieval) system is presented. It utilizes deep features from InceptionV3 and InceptionResNetV2 models to match query designs with a database of traditional Indian textiles. Its performance is tested with Caltech-101, Corel-1K state-of-the-art datasets, and Indian Textiles datasets and the results are shown to be finer than the existing approaches. The similarity-based fine-grained saliency maps (SBFGSM) approach is employed to visualize the importance of features. Our approach combines deep feature fusion with PCA dimensionality reduction and speeds up search using a clustering approach. Relevance feedback is employed to refine the retrievals. This tool is expected to benefit designers by accelerating the design cycles by bridging the gap between human creativity and A.I. assistance. [ABSTRACT FROM AUTHOR]

The High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases. However, practical applications like market basket analysis and business decision-making necessitate regular updates of the database with new transactions. As a result, researchers have developed incremental HAUIM (iHAUIM) algorithms to identify HAUIs in a dynamically updated database. Contrary to conventional methods that begin from scratch, the iHAUIM algorithm facilitates incremental changes and outputs, thereby reducing the cost of discovery. This paper provides a comprehensive review of the state-of-the-art iHAUIM algorithms, analyzing their unique characteristics and advantages. First, we explain the concept of iHAUIM, providing formulas and real-world examples for a more in-depth understanding. Subsequently, we categorize and discuss the key technologies used by varying types of iHAUIM algorithms, encompassing Apriori-based, Tree-based, and Utility-list-based techniques. Moreover, we conduct a critical analysis of each mining method's advantages and disadvantages. In conclusion, we explore potential future directions, research opportunities, and various extensions of the iHAUIM algorithm. [ABSTRACT FROM AUTHOR]

Background: Total iron (TI) intake and differentiation between heme iron (HI) and nonheme iron (NHI) are uncommon despite markedly different bioavailability. Objectives: To create a database compiling information from studies that directly assessed the HI content of animal products using the Hornsey method, and to explore differences in estimates of HI intake between the data compiled and the Monsen method. Methods: A literature search identified studies that chemically characterized the HI content of animal-based foods using the Hornsey method; HI, NHI, and TI contents (mg/100 g) were compiled. Information was grouped by animal type and cooking method, and mean (± SD) HI% was calculated. Using a 24-h dietary record, differences in HI and NHI intake using the compiled information and the Monsen approach were explored. Results: Actual HI% values ranged from 7% to 94%. Raw foods had the highest HI% [raw duck (94% ± 4%), raw blood curd (82% ± 4%), and raw beef (79% ± 9%)]. Boiled foods had the lowest HI% [boiled shrimp (11% ± 5%) and meatballs (15% ± 6%)]. Cooked foods with the highest HI% were beef (70% ± 10%) and lamb (70% ± 9%). In many instances, applying actual HI% from the complied database produced markedly different measures of the HI content of foods [cooked beef (Monsen: 1.3 mg/100 g); (Hornsey: 2.3 mg/100 g)]. Estimation of iron intake in a 24-h recall demonstrated that using animal-specific HI% results in different estimates of HI intake [Monsen: 1.2 mg HI (40%); Hornsey: 1.8 mg HI (59%)]. Conclusions: Animal-based foods have variable HI%. A fixed HI:NHI ratio does not reflect this variation and could give rise to inaccurate estimates of HI content in food and HI intake. Consideration of this variation in HI% may improve our ability to link dietary intake with iron status and important health outcomes. [ABSTRACT FROM AUTHOR]

The widespread use of non-nutritive sweeteners (NNSs) in the food and beverage industry has become a global trend. A study was undertaken to assess the level of awareness of South Africans of NNSs and to create a scientific product database of NNSs in a sample of packaged products in South Africa. A cross-sectional survey design was chosen. The study was carried out online in South Africa. The study participants were South African adults (n = 388). A consumer awareness survey on NNSs and a scientific product database were created to identify products formulated with NNSs. A large proportion of participants were unfamiliar with most NNSs by name; however, a significant 61% (n = 238) (p < 0.001) of participants were most aware of xylitol, and 45% (n = 174) were aware of aspartame. Despite this, a significant number of participants consumed products labelled 'sugar-free' and/or 'diet' (p < 0.001). Participants were aware of health concerns and health benefits associated with the consumption of NNSs. A scientific product database consisting of 419 products containing NNSs was created during the study. A combination of NNSs was used in the formulations of 65% (n = 273) of the products, while 35% (n = 146) of the products were formulated with a single NNS. The outcome of this research highlights key consumer insights into NNSs and their widespread use in product formulations in South Africa. The outcome of this study shows the need for continuous monitoring of the effects of the increasing use of NNSs in product formulation and their impact on health and diet. Consumer education would advance consumer awareness of NNSs. [ABSTRACT FROM AUTHOR]

The purpose of this study is to extend the mileage by improving the efficiency of the electric vehicle (EV) driving and thermal management system (TMS). The powertrain system and the TMS must be considered simultaneously from the architecture stage as complementary systems to maintain the driving performance of the EV. This paper proposes an EV architectural design method and a multi-physical EV modeling technique. The main components of the EV are standardized differently from those of the internal combustion engine (ICE) vehicle, and the TMS is designed by thermal system configuration. Therefore, instead of the traditional continuous variable-based design methodology, optimal combination design based on the component database (DB) and the configuration plot presents the combinational design method. The performance of an EV varies depending on the performance of driving components and TMS, and weather. This paper presents a Modelica-based vehicle modeling technique to integrate multiple physical phenomena. Finally, we implemented an automated design using the optimal combination design method and the multi-physical integrated vehicle model design framework. The design of the C-segment EV was carried out to review the validity of the proposed method. 2880 laboratories were planned and designed using design variables with 10 levels of mixing. As a result of the design, we have confirmed that the mileage increases by 5% compared to the previous one in NEDC mode. [ABSTRACT FROM AUTHOR]

There are growing public discussions about racism in Australia with renewed government commitment to addressing it. Robust evidence and high-quality data are important for informing anti-racism. However, current data have serious limitations that impact our knowledge about the nature, prevalence and impact of racism in Australia. To examine the state and limitations of data on racism in Australia, we conducted a stocktake review of quantitative racism data collected nationally until July 2022. This article reports on 32 survey-based research studies and six ongoing organisational reporting initiatives. We organise and classify existing data based on study designs and participant characteristics, as well as the settings, targets, perpetrators, responses to and effects of racism. We identify data gaps and recommend how they may be bridged. First, we recommend further analysis of existing, under-utilised data, to address outstanding questions about perpetrators' demographics, priority localities, and the health and socio-economic outcomes of racism. Second, we recommend new data collection on emerging settings where racism occurs, under-explored forms, cohorts experiencing racism, and responses to racism. We propose this study as a foundation for a national anti-racism research agenda and data management plan in Australia, and as a template for stocktakes in other countries. [ABSTRACT FROM AUTHOR]

Background: Genomic islands (GIs) are mobile genetic elements that integrate site-specifically into bacterial chromosomes, bearing genes that affect phenotypes such as pathogenicity and metabolism. GIs typically occur sporadically among related bacterial strains, enabling comparative genomic approaches to GI identification. For a candidate GI in a query genome, the number of reference genomes with a precise deletion of the GI serves as a support value for the GI. Our comparative software for GI identification was slowed by our original use of large reference genome databases (DBs). Here we explore smaller species-focused DBs. Results: With increasing DB size, recovery of our reliable prophage GI calls reached a plateau, while recovery of less reliable GI calls (FPs) increased rapidly as DB sizes exceeded ~500 genomes; i.e., overlarge DBs can increase FP rates. Paradoxically, relative to prophages, FPs were both more frequently supported only by genomes outside the species and more frequently supported only by genomes inside the species; this may be due to their generally lower support values. Setting a DB size limit for our SMAll Ranked Tailored (SMART) DB design speeded runtime ~65-fold. Strictly intra-species DBs would tend to lower yields of prophages for small species (with few genomes available); simulations with large species showed that this could be partially overcome by reaching outside the species to closely related taxa, without an FP burden. Employing such taxonomic outreach in DB design generated redundancy in the DB set; as few as 2984 DBs were needed to cover all 47894 prokaryotic species. Conclusions: Runtime decreased dramatically with SMART DB design, with only minor losses of prophages. We also describe potential utility in other comparative genomics projects. [ABSTRACT FROM AUTHOR]

The object of research is the traditional and universal approach of designing the database structure in systems of integrated monitoring of ecological, economic, energy and social parameters of the territory, which include diverse data from various subject areas. In the course of the study, an analysis was performed based on a set of criteria such as scalability, ease of updating data, absence of empty fields, volume of the database, number of tables and fields, ease and speed of execution of requests for a sample set of indicators of the research object. The comparison of these approaches took place on the example of water resources monitoring, since it has several subsystems and a large number of indicators that are used for assessment. It is established that the proposed universal approach to designing complex database structures made it possible to reduce the volume of the database by 2.25 times due to the absence of empty fields. In particular, in the considered example, the filling factor of the database with the traditional approach is 1.75 times less than with the proposed universal approach. It should be noted that the rate of table filling for the traditional design approach can vary depending on the number of indicator values, while the table filling rate for the universal approach is always close to 100 %. Also, the proposed database design approach makes it possible to speed up data loading and processing. For example, with the same volume of significant information, the minimum speed of sampling the characteristics of one research object is 3.87 times greater in a database developed according to the principles of the universal approach than according to the rules of the traditional approach. The proposed structure of the database is successfully used in the system of complex eco-energy-economic monitoring. The developed structure of the database can serve as an effective basis for the formation of an electronic data bank at the level of the enterprise, region and country. [ABSTRACT FROM AUTHOR]

With China's urbanization entering a stage of high-quality development, refined urban governance has become an important part in the modernization of governance capacity, in which urban design plays a major role. This paper briefly reviews the background of urban design digitalization and discusses the issues that need to be addressed in digital management and control of urban design in China. On this basis, the paper summarizes the practice of digital management and control of urban design in Zhuhai in three aspects: building a rule base for digital management and control, developing a 3D quantitative analysis method for urban space from the macro, meso, and micro perspectives, and establishing a digital urban design management platform and storing 2D and 3D urban design schemes in the database according to unified standards, so as to realize the standardized management, intelligent review, and scientific decision-making of urban design. [ABSTRACT FROM AUTHOR]

Fires resulting from antecedent fires, known as exposure fires, can manifest across diverse environments, including suburban, urban, and rural areas. Notably, exposure fires represented by structure-destroying fires within the wildland–urban interface (WUI) can extend into non-WUI suburban and urban regions, presenting significant challenges. Leveraging data from the United States National Fire Incident Reporting System (NFIRS) spanning 2002 to 2020, this study investigates 131,739 exposure fire incidents impacting 348,089 features (incidents). We analyze reported economic costs, affected feature types, and property utilization patterns for these exposure fires. We also compare these exposure fires to information documented in other databases. Finally, we examine structure separation distance at residential dwellings and describe ignition pathways for selected fires. Reported property losses for some fire incidents amounted to USD 5,647,121,172, with content losses totaling USD 1,777,345,793. Prominent fire incident categories include buildings, vehicles, and natural vegetation fires, predominantly occurring in residential, outdoor, and storage areas. While the NFIRS lacked information on most major structure-destroying WUI fires, highlighting this analysis's lack of statistical representation, it did provide insights into less extensive exposure fires, both WUI and non-WUI, unrecorded elsewhere. Our study reveals significant distinctions in the distribution of separation distances between damaged-to-damaged structures (average separation of 6.5 m) and damaged-to-not-damaged structures (average separation of 18.1 m). Notably, 84% of the incidents in exposure fires involved fire suppression defensive actions. These defensive actions contributed to the differences in structure separation distance distributions, highlighting the often-neglected role of these measures in assessing structure responses during WUI fires. We examined ignition pathways at select exposure fires, highlighting some common features involved in fire spread and challenges in documenting these pathways. Finally, we propose a set of idealized attributes for documenting exposure fires, accentuating the inherent difficulties in collecting such data across expansive geographical areas, particularly when striving for statistical representation. Our findings yield valuable insights into the multifaceted nature of exposure fires, informing future research and database development to aid in mitigating their impact on vulnerable communities. [ABSTRACT FROM AUTHOR]

Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields. [ABSTRACT FROM AUTHOR]

Based on the design and measured data of one actual tower, a three-dimensional numerical model for a natural draft dry cooling tower (NDDCT) was created and validated under constant heat load. This enabled the performance improvement mechanism of air equalizing on vertical delta-type radiators (VDRs) to be clarified by detailed analysis of key parameters, such as the exit water temperature, heat transfer coefficient, and mass airflow. Under the impact of typical ambient crosswind, all VDRs were retrofitted with air-side-equalizing devices. It was found that the exit water temperatures of the whole NDDCT decreased by 0.865 °C, 0.593 °C and 0.186 °C under the studied ambient crosswind speeds of 2.5 m/s, 4 m/s and 12 m/s, respectively. The performance improvement mechanism of air-side equalizing was investigated for three VDRs, which were located on the upwind, tower lateral, and downwind sides under crosswind impacts. Besides the studied VDRs, the performance of the neighboring VDRs behind them was also improved by the optimized aerodynamic field and the reduced hot wind recirculation around them. In addition, the average heat transfer coefficients of the VDRs were enhanced, which could lay the foundation for improving the cooling performance of thermodynamic devices with VDRs. [ABSTRACT FROM AUTHOR]

(1) Background: Our study explores the relationship between expected, perceived, and measured effects of botulinum toxin A (BoNT-A) treatment and saline (placebo) in children and adolescents with cerebral palsy (CP) in the calf muscles of 20 children and adolescents with cerebral palsy (CP), aged 4–15 years, using the Gross Motor Function Classification System (GMFCS) I–II. (2) Methods: A mixed methods parallel database design was used. Quantitative and qualitative data were collected at baseline and four weeks after treatment. The primary quantitative measure was gross energy cost (EC) during walking, obtained from a 5-Minute Walk Test (5MWT), while qualitative semi-structured interviews were performed with each parent and child/adolescent individually. (3) Results: Four weeks after treatment, we did not find any correspondence between expected, measured, and perceived effects. Interestingly, parental perceptions of treatment effects were more consistent than the measured outcomes. We also observed a connection between parental treatment expectations and perceived effects, often related to reduced energy expenditure. Children tended to view their parents as treatment experts and had fewer expectations and perceptions themselves. (4) Conclusions: These findings support the importance of child-centered care, which entails actively listening to children's expectations and perceptions during the treatment process. [ABSTRACT FROM AUTHOR]

The lumped element network model has been proven to be an efficient tool for the interpretation of transformer Frequency Response Analysis. However, it is challenging to obtain parameters of the model if transformer design information is unavailable. In such a case, optimisation algorithms can be used for gray‐box model parameter estimation. A methodology is developed by the authors to establish a transformer network model without winding design data, and instead, end‐to‐end open circuit Frequency Response and other terminal test results are utilised; and Genetic Algorithm is applied to approximate the unknown parameters of the model. The modelling approach developed is independent of the unit number of the network model and therefore guarantees the accuracy of optimisation. Furthermore, it can deal with transformers with a complicated winding structure such as interleaved disc type winding. Two single windings, helical and interleaved disc type, and a single‐phase 144/13 kV 60 MVA transformer are used to demonstrate the method. FRA spectra produced by the best estimated gray‐box model and the corresponding white‐box model are compared. The main features in amplitude and phase spectra are well matched, with low values of Relative Standard Deviation, for both single windings and transformer. Estimated electrical parameters show a high consistency with reference values, which are calculated based on winding design data. This validates the methodology and gives confidence to apply grey‐box modelling for FRA interpretation. [ABSTRACT FROM AUTHOR]

Background: Latin American and Caribbean Health Sciences Literature (LILACS) is the main reference database in the region; however, the way in which this resource is used in Cochrane systematic reviews has not been studied. Objectives: To assess the search methods of Cochrane reviews that used LILACS as a source of information and explore the Cochrane community's perceptions about this resource. Methods: We identified all Cochrane reviews of interventions published during 2019, which included LILACS as a source of information, and analysed their search methods and also ran a survey through the Cochrane Community. Results: We found 133 Cochrane reviews that reported the full search strategies, identifying heterogeneity in search details. The respondents to our survey highlighted many areas for improvement in the use of LILACS, including the usability of the search platform for this purpose. Discussion: The use and reporting of LILACS in Cochrane reviews demonstrate inconsistencies, as evidenced by the analysis of search reports from systematic reviews and surveys conducted among members of the Cochrane community. Conclusion: With better guidance on how LILACS database is structured, information specialists working on Cochrane reviews should be able to make more effective use of this unique resource. [ABSTRACT FROM AUTHOR]

The evolution of Internet technology has led to an increase in online users. This study focuses on the pivotal role of visual elements in web content conveyance and their impact on user browsing behavior. Therefore, the use of visual elements in web design based on big data has aroused widespread concern among web designers, they apply visual elements to their web design works to make the web more attractive. This study examines the composition and distribution characteristics of key visual elements identified through user behavior data in a big data environment and discusses the use of visual elements in web design in the era of network economy. In addition, this paper issued 200 questionnaires to investigate the degree of attention to visual elements in web pages for users of different occupations and different educational backgrounds. Our survey indicated that visual elements captured the attention of 41% of corporate employees, whereas a mere 1% of social welfare workers focused on web content; 36% of undergraduates pay attention to visual elements of web pages, but only 5% and 4% of postgraduates and doctoral degrees and above. Therefore, the visual elements of the designed web page need to conform to the user's cultural background and professional background. [ABSTRACT FROM AUTHOR]

Integrated systems of PEM water electrolyzers (PEMWE) and photovoltaic (PV) power plants are a promising method for the production of green hydrogen with zero-carbon emissions. Despite their potential, matching the intermittent nature of solar energy with the continuous demand for hydrogen production remains a challenge. In directly coupled PV-H 2 systems, the electrolyzer is operated dynamically with frequent load changes and shutdown (SD) periods whereas battery assisted systems enable steady operation at a fixed power rate. In this study, two accelerated stress tests (ASTs) were designed based on the data from a 100 kWp PV plant to mimic failure under real-life conditions in a single cell PEMWE. The first AST represents a time-accelerated PV-profile that depicts power imbalances during daytime and idle periods at night, where the cell is kept at open circuit voltage (OCV). In the second AST, the SD periods are compensated by a protective current of 0.3 A cm−2 to simulate a battery assisted system. A thorough electrochemical and physical characterization revealed a correlation between SD periods and the accelerated degradation of PEMWE components. With regard to the battery-supported AST, a lower degradation rate of ∼3 mV h−1 at 1 A cm−2 compared to ∼11 mV h−1 for the intermittent operation was recorded. [Display omitted] • A novel accelerated stress test for testing the impact of solar photovoltaic energy on electrolyzer operation is presented. • The role of OCV in PEM electrolyzer degradation is identified in a complementary investigation. • A thorough examination of the primary degradation mechanisms in PEMWE is caried out via various characterization techniques. [ABSTRACT FROM AUTHOR]

With the advent of ICT-based healthcare applications, various formats of health data are generated every day in huge volume. Such data, consisting of unstructured, semi-structured and structured data, has every characteristic of Big data. NoSQL databases are generally preferred for storing such type of health data with the objective of improving query performance. However, for efficient retrieval and processing of Big Health Data and for resource optimization, suitable data models and design of the NoSQL databases are important requirements. Unlike relational databases, no standard methods or tools exist for NoSQL database design. In this work, we adopt an ontology-based schema design approach. We propose that an ontology, which captures the domain knowledge, be used for developing a health data model. An ontology for primary healthcare is described in this paper. We also propose an algorithm for designing the schema of a NoSQL database, keeping in mind the characteristics of the target NoSQL store, using a related ontology, a sample query set, some statistical information of the queries, and performance requirements of the query set. The ontology proposed by us for primary healthcare domain and the above mentioned algorithm along with a set of queries are used for generating a schema targeting MongoDB datastore. The performance of the proposed design is compared with a relational model developed for the same primary healthcare data and the effectiveness of our proposed approach is demonstrated. The entire experiment has been carried out on MongoDB cloud platform. [ABSTRACT FROM AUTHOR]

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development. Highlights: Essential genes are crucial for organism survival and development, which have been identified using various experimental methods across different organisms, providing valuable resources for studying their characteristics and developing predictive algorithms.The database of essential genes (DEG) collects experimental results on essential genes and serves as a widely used resource for studying them. It enables quick access to essential gene information for specific species and has applications in essential gene analysis, prediction, drug and vaccine design, and artificial genome construction.The definition of essential genes is context‐dependent, not a simple binary classification. Integrating different experimental results of essential genes is challenging but offers opportunities to explore gene interaction mechanisms. [ABSTRACT FROM AUTHOR]

The topological relationship of spatial data is essential to GIS data processing and spatial analysis such as in analysis of pipe explosion in gas pipeline network. The existing browser-side JavaScript topology check library is inefficient and even crashes when checking the pipe network topology relationships for large amounts of data. In this paper, we present a topology checking and optimization method for pipeline vector data in browser-side using quadtree. Firstly, an algorithm mechanism that conforms to GIS data is designed based on JavaScript shared memory mechanism, topological check algorithm characteristics, and spatial data high-precision characteristics. Then using a fast rejection experiment and straddle test to realize the browser-side topology checking algorithm, through tolerance setting, improve the inspection efficiency and accuracy, which solves the problem that Turf and Jsts libraries cannot set tolerance. Based on the concept of quadtree spatial index, an optimization method of browser-side quadtree topology checking algorithm(BQTCA) is proposed. Without setting tolerance, the topology check of 114 point data and 1881 line data takes 487 milliseconds, and the efficiency of BQTCA is about 12 times and 39 times higher than that of the well-known public libraries Turf and Jsts, respectively. When the data volume increases to 912 point data and 15048 line data, BQTCA takes 6970 ms, which is about 65 times and 190 times more efficient than Turf and Jsts, respectively. The larger the data volume is, the more pronounced the efficiency improvement of BQTCA. Even when the data volume is so large that Turf and Jsts can- not calculate even crash, BQTCA can still complete the checking calculation. Through experiments, BQTCA can significantly improve the efficiency of browser-side vector pipeline topology relationship inspection under a large amount of data, and meet the commercial application requirements. [ABSTRACT FROM AUTHOR]

The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into novel technological solutions. To contribute to the resolution of this problem through multiple classifications by considering age and gender factors, in this study, two quadruple and one octal classifications were performed using a deep learning (DL) approach. Gender in one of the four classifications and age groups in the other were considered. In the octal classification, classes were created considering gender and age groups. In addition to the diagnosis of ASD (Autism Spectrum Disorders), another goal of this study is to find out the contribution of gender and age factors to the diagnosis of ASD by making multiple classifications based on age and gender for the first time. Brain structural MRI (sMRI) scans of participators with ASD and TD (Typical Development) were pre-processed in the system originally designed for this purpose. Using the Canny Edge Detection (CED) algorithm, the sMRI image data was cropped in the data pre-processing stage, and the data set was enlarged five times with the data augmentation (DA) techniques. The most optimal convolutional neural network (CNN) models were developed using the grid search optimization (GSO) algorism. The proposed DL prediction system was tested with the five-fold cross-validation technique. Three CNN models were designed to be used in the system. The first of these models is the quadruple classification model created by taking gender into account (model 1), the second is the quadruple classification model created by taking into account age (model 2), and the third is the eightfold classification model created by taking into account both gender and age (model 3).). The accuracy rates obtained for all three designed models are 80.94, 85.42 and 67.94, respectively. These obtained accuracy rates were compared with pre-trained models by using the transfer learning approach. As a result, it was revealed that age and gender factors were effective in the diagnosis of ASD with the system developed for ASD multiple classifications, and higher accuracy rates were achieved compared to pre-trained models. [ABSTRACT FROM AUTHOR]

This paper examines the concept of "terminological gaps" and strives to identify suitable methods for dealing with them during translation. The analysis begins with an investigation of the contended notion of gaps in terminology based on empirical examples drawn from a German-Italian terminological database specifically designed for translation purposes. Two macro categories of gaps are identified, conceptual and linguistic level gaps, which only partially correspond to previous observations in the literature. The paper uses examples to explore the advantages of ontological representations for detecting conceptual terminological gaps and identifying appropriate translation strategies. However, limitations are also observed and an attempt is made to resolve these using a frame-based approach. A frame-based analysis reveals that while certain designations may appear to refer to convergent conceptual units with matching distinctive features, differences also emerge due to the way the two language systems build designations. Examples from the corpus make it evident that a frame-based approach is helpful for identifying both kinds of terminological gaps, and then resolving them during translation. An important presupposition for this approach is that larger units of analysis need to be addressed rather than just terms themselves. There is confirmation of the existing idea that methods embracing entire segments or paragraphs as units of investigation are preferable during translation, and this is also seen to apply in terminological studies. [ABSTRACT FROM AUTHOR]

With the continuous development of the social economy, multimedia has been valued more and more as a computer technology with strong professional technology and high application level. The quality of multimedia professionals is predicted and analyzed for multimedia professional talent through the Internet according to a Chinese keyword extraction algorithm. It realizes the extraction of keywords through Internet intelligence information acquisition for solving the problem of Internet information explosion, aiming to solve the talent quality prediction analysis. The prediction and analysis of multimedia professional talent quality play a crucial role in talent recruitment and development in the ever-evolving multimedia industry. This paper constructed a Fuzzy Secured Hybrid Search (FSHS) for keyword extraction in the Chinese Language. The proposed FSHS model computes the features in the text for the computation of the talent quality prediction for the extraction of the keywords. Through the utilization of the fuzzy logic model, the features in the text are computed and classification is performed classification and extraction of the features. The simulation results show that the Chinese keyword extraction algorithm has a high recall rate and precision rate, and can effectively predict the quality of professional talents. [ABSTRACT FROM AUTHOR]

Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is, therefore, necessary to develop an efficient system for storing and managing multidimensional cadastral data. While there have been attempts to develop 3D cadastral database schemas, a comprehensive solution that meets all the requirements for effective data storage, manipulation, and retrieval has not yet been presented. This study aims to analyse the literature on 3D cadastral databases to identify approaches and technologies for storing and managing these data. Based on a systematic literature review integrated with a snowballing methodology, 108 documents were identified. During the analysis of the related documents, different parameters were extracted, including the conceptual data model, query type, and evaluation metrics, as well as the database management system (DBMS) used and technologies for visualisation, data preparation, data transformation, and the ETL (extract, transform, and load) process. The study emphasised the importance of adhering to database design principles and identified challenges associated with conceptual design, DBMS selection, logical design, and physical design. The study results provide insights for selecting the appropriate standards, technologies, and DBMSs for designing a 3D cadastral database system. [ABSTRACT FROM AUTHOR]

The need for sustainable urban growth management and preventive conservation of built elements constitute the key factors in today's increasing demand for the better understanding of subsoil. This information, mainly available from geotechnical surveys, can be integrated into spatial databases to produce operational models. Aiming to generate strategies that enable the visualisation of underground properties in highly anthropised environments, the following four-phase methodology has been proposed: (a) Gathering of geotechnical data; (b) Spatial and statistical analysis; (c) Database design; (d) Generation of 2D and 3D models. Following the aforementioned criteria and using open sources, a spatial dataset of 650 points located within the historical centre of Seville (Spain) has been developed. This urban area is characterised by the heterogeneous distribution of its soil layers and their geotechnical properties. The results show that the application of this method enables a prompt and efficient display of the distribution of geotechnical layers in urban and metropolitan environments, by considering the variations in their mechanical properties. This simplified approach therefore establishes a new starting point for the development of predictive strategies based on approaches of a more complex nature that facilitate the analysis of the interactions between subsoil, buildings, and infrastructures. [ABSTRACT FROM AUTHOR]

This study analyses the coverage of seven free‐access bibliographic databases (Crossref, Dimensions—non‐subscription version, Google Scholar, Lens, Microsoft Academic, Scilit, and Semantic Scholar) to identify the potential reasons that might cause the exclusion of scholarly documents and how they could influence coverage. To do this, 116 k randomly selected bibliographic records from Crossref were used as a baseline. API endpoints and web scraping were used to query each database. The results show that coverage differences are mainly caused by the way each service builds their databases. While classic bibliographic databases ingest almost the exact same content from Crossref (Lens and Scilit miss 0.1% and 0.2% of the records, respectively), academic search engines present lower coverage (Google Scholar does not find: 9.8%, Semantic Scholar: 10%, and Microsoft Academic: 12%). Coverage differences are mainly attributed to external factors, such as web accessibility and robot exclusion policies (39.2%–46%), and internal requirements that exclude secondary content (6.5%–11.6%). In the case of Dimensions, the only classic bibliographic database with the lowest coverage (7.6%), internal selection criteria such as the indexation of full books instead of book chapters (65%) and the exclusion of secondary content (15%) are the main motives of missing publications. [ABSTRACT FROM AUTHOR]

The development of facial expressions with sensing information is progressing in multidisciplinary fields, such as psychology, affective computing, and cognitive science. Previous facial datasets have not simultaneously dealt with multiple theoretical views of emotion, individualized context, or multi-angle/depth information. We developed a new facial database (RIKEN facial expression database) that includes multiple theoretical views of emotions and expressers' individualized events with multi-angle and depth information. The RIKEN facial expression database contains recordings of 48 Japanese participants captured using ten Kinect cameras at 25 events. This study identified several valence-related facial patterns and found them consistent with previous research investigating the coherence between facial movements and internal states. This database represents an advancement in developing a new sensing system, conducting psychological experiments, and understanding the complexity of emotional events. [ABSTRACT FROM AUTHOR]

The characterization system and automated database on vitrified high-level waste (VHLW) accumulated at the Mayak Production Association were developed for assessing and substantiating the waste disposal safety. All the available analytical data on VHLW are accumulated in the database. Calculations based on the developed integral algorithm for estimating the content of radiologically significant radionuclides (RSRNs) in containers with VHLW were made. [ABSTRACT FROM AUTHOR]

The absence of an integrated geospatial database hinders effective decision-making among various stakeholders in national projects and programs. The study aimed to create an integrated geospatial database for the Manesar tehsil, District Gurugram, Haryana. Another objective was to create a land use map to analyze the temporal change in land use patterns and its socioeconomic impact along the surrounding areas. The first stage of the study involved creating an integrated database after interviewing different stakeholders. In the second stage, the satellite imagery was georeferenced using Ground Control Points, and the land use patterns were digitized using Landsat imagery for 1987, 2011, 2014, and 2022. The study suggested that the construction area has grown up to 6% while cultivation has dropped significantly from 76% in 1987 to 50% in 2022. Likewise, the industrial area has grown up to 2% and natural vegetation dropped in coverage from 11% to 4%. The area witnessed a population growth rate of 3.2% per year and a decadal growth rate of 39.7%. Less than 50% of the land in the tehsil is used for agricultural purposes. It estimates that 4% of the tehsil's entire surface was covered by natural vegetation in 2019, down from 11% in 1987. The study recommends the creation of an integrated geospatial database that will help reduce duplication and speed up decision-making in government. This will pave the way for improving e-governance in local bodies. The framework created for developing the database system is universally applicable and can be used appropriately by other states, regions, and the entire country. [ABSTRACT FROM AUTHOR]

The adoption of agricultural machinery in countries with a developing economy can have a significant impact on improving well-being and pro-poor growth. However, this requires farmers to buy into mechanized farming, which is more likely to happen if the machinery meets their needs. The objective of this paper is to identify deciding factors for traditional farmers to adopt machinery and identify design requirements. Payback models were developed based on these design requirements, willingness to pay, and expected returns. Thirty-six farmers in Sudan were interviewed throughout 2019–2021. Six of these farmers were provided tractors during 2020 and 2021. Differences in net-profits between the 30 control and 6 treatment farms during the mechanized farming seasons were used in the models for expected profits. There were no significant differences in tractor design preferences between the treatment and control groups. Two cost models were estimated using a 95% confidence interval: entire Δ profit (entire additional profit from mechanized farming above nonmechanized) and percentage of total profit (percentage of total net-profits willing to spend). For the average farm size in this study (44.39 acres) and a market available tractor that satisfied all farmer needs, payback was 3.92 years [2.34, 8.54] and 4.57 years [3.39, 6.38] for the models, respectively. [ABSTRACT FROM AUTHOR]

As an important part of the industrial internet, identity analysis data are growing with the expansion of the field involved in the industrial internet. The management of industrial internet identity analysis data faces many problems, such as complex types, a wide range of information, rapid growth, reduced security, etc. In view of the above problems, a trusted management model of industrial internet identity analysis data based on blockchain is first designed. Meanwhile, the identity analysis data information is analyzed and classified, and industrial data are divided into three levels according to the degree of privacy for hierarchical encryption. Secondly, the "on-chain + off-chain" storage model combining the blockchain main-slave chain and the off-chain database is designed to improve the efficiency of the whole model. Then, a collaborative consensus mechanism suitable for the main-slave multi-chain of the industrial internet is also designed, including slave-chain CIPBFT consensus, inter-chain cross-chain transmission protocol and main chain KZKP consensus. Finally, a prototype system is built to analyze the correctness, security, scalability and consensus efficiency of the model proposed in this study. The results show that the model proposed in this study can be applied to trusted management of data information for industrial internet identity analysis, and also provides an optimized solution for the same problem in fields of the industrial internet. [ABSTRACT FROM AUTHOR]

Numerical models are used for detailed and site-specific tailings dam breach analyses (TDBAs) to estimate the downstream inundation and deposition resulting from a potential breach at a tailings dam. The results of TDBAs are key inputs into risk assessments, consequence classification, and emergency planning. This paper describes the research and development of a database of 12 tailings dam breach events with a specific focus on observations that are needed for numerical modelling, in conjunction with an assessment of existing dam breach conventions to improve consistency in reporting. The characteristics relevant to modelling include outflow volumes, breach processes, breach geometries, and runout observations local to the downstream area. This study and the new database shed light on the diversity of outflow materials, facility arrangements, breach processes, and downstream environments that affect the breach development and tailings runout. Familiarity with case studies is a crucial element of expert judgement for forward-analysis TDBAs, which this database supports. The database can also be used to define model inputs for back-analysis of additional tailings dam breach events, and simultaneously provides calibration or validation constraints with the runout observations. Continued review and critical assessments are needed to reduce uncertainties and to enhance case history data availability and quality in this database. [ABSTRACT FROM AUTHOR]

The UHPC flexural database: Validation of a design approach for bending with or without axial force In the present paper, test data of 228 ultra‐high performance concrete (UHPC) beams are consolidated in a database. Different shapes of cross‐section and reinforcement configurations are considered, including prestressing, exclusively fibre‐reinforced and exclusively bar reinforced members. The evaluation of the literature shows that in many cases important material parameters are inadequately documented. In addition, the use of different, often non‐standardised methods of material characterisation makes it difficult to compare the individual studies. Therefore, all data are first carefully checked, standardised, and partially complemented. Subsequently, the data sets of the database are used to validate an approach for the flexural design of beams with mixed reinforcement. This approach was developed with the participation of the authors and is presented here for the application to cross‐sections with complex geometry. When being evaluated with the mean values of the material parameters, the model fits well for both the universe of the tests and individual model parameters. An acceptable level of safety is obtained by limiting the characteristic value of the post‐cracking tensile strength to 0.6 times the mean value. The 5%‐quantile of the ratio between experimental and calculated moment resistance Mexp / Mcal is then Q0.05 = 0.97 for the universe of the 228 data sets. [ABSTRACT FROM AUTHOR]

Many special classes of simplicial sets, such as the nerves of categories or groupoids, the 2-Segal sets of Dyckerhoff and Kapranov, and the (discrete) decomposition spaces of Gálvez, Kock, and Tonks, are characterized by the property of sending certain commuting squares in the simplex category Δ to pullback squares of sets. We introduce weaker analogues of these properties called completeness conditions, which require squares in Δ to be sent to weak pullbacks of sets, defined similarly to pullback squares but without the uniqueness property of induced maps. We show that some of these completeness conditions provide a simplicial set with lifts against certain subsets of simplices first introduced in the theory of database design. We also provide reduced criteria for checking these properties using factorization results for pushouts squares in Δ , which we characterize completely, along with several other classes of squares in Δ . Examples of simplicial sets with completeness conditions include quasicategories, many of the compositories and gleaves of Flori and Fritz, and bar constructions for algebras of certain classes of monads. The latter is our motivating example. [ABSTRACT FROM AUTHOR]

Summary: This research presents a unified performance analysis methodology for the power domains of uplink non‐orthogonal multiple access (NOMA) system consisting of a base station and an arbitrary number of users over Rayleigh fading channels. The study derives exact closed‐form expressions for key performance metrics, such as outage probability (OP), symbol error rate (SER), outage capacity (OC), average channel capacity (AVC), and amount of fading, using binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulations. The analysis encompasses all necessary channel parameters for evaluating the performance of an uplink NOMA system. The theoretical and simulation results completely supported one another. Furthermore, the results were compared with experiments in the literature using similar parameters. The proposed system was determined to increase performance by 40% for OP, 62% for SER, and 4.74 times for AVC at SNR = 20 dB. Finally, this study introduced exact solutions that can significantly accelerate NOMA systems analysis by exploiting the information in the existing database for analytical design processes in communications theory. [ABSTRACT FROM AUTHOR]

Introduction: Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust training datasets including contrast enhanced images. Methods: NotIs CMR is a large UK, prospective, multicentre, observational cohort study to guide the development of a biventricular AI scar model. Patients with ischaemic heart disease undergoing clinically indicated contrast-enhanced cardiac magnetic resonance imaging will be recruited at Nottingham University Hospitals NHS Trust and Mid-Yorkshire Hospital NHS Trust. Baseline assessment will include cardiac magnetic resonance imaging, demographic data, medical history, electrocardiographic and serum biomarkers. Participants will undergo monitoring for a minimum of 5 years to document any major cardiovascular adverse events. The main objectives include (1) AI training, validation and testing to improve the performance, applicability and adaptability of an AI biventricular scar segmentation model being developed by the authors and (2) develop a curated, disease-specific imaging database to support future research and collaborations and, (3) to explore associations in clinical outcome for future risk prediction modelling studies. Conclusion: NotIs CMR will collect and curate disease-specific, paired imaging and clinical datasets to develop an AI biventricular scar model whilst providing a database to support future research and collaboration in Artificial Intelligence and ischaemic heart disease. [ABSTRACT FROM AUTHOR]