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As digital sports video becomes increasingly pervasive, semantic video summary becomes one of the important components for the next generation of multimedia applications. Ontology is a feasible way to mine the semantic information from the video stream. However, current ontology-based methods did not concentrate on the effectiveness and soundness of semantic reasoning. Here, the authors propose a content-directed ontology reasoning approach to produce meaningful sports video summarisation. The proposed ontology can facilitate the metadata acquisition of video and the improvement of query performance. It also provides a flexible way to query the sports video database, which cannot be achieved by simple keyword search. For annotating, describing and managing the sports video content, we propose a sports video descriptive language (SVDL) based on the proposed ontology. Moreover, the semantically meaningful sports video abstraction is produced by reasoning engine which is based on the extension of the Tableau algorithm. Meanwhile, the soundness and completeness of the reasoning algorithm can be solidly proved. Subjective assessment experimental results reveal the reliability and efficiency of the propose scheme.

Anesthetic gases contribute to global warming. We described a two-year performance improvement project to examine the association of individualized provider dashboard feedback of anesthetic gas carbon dioxide equivalent (CDE 20 ) production and median perioperative fresh gas flows (FGF) during general anesthetics during perioperative management. Using a custom structured query language (SQL) query, hourly CDE 20 for each anesthetic gas and median FGF were determined. During the first year, practitioners were not given any feedback on their use of anesthetic gases. During the second year of the study protocol, a commercially available business intelligence platform was used to deliver individualized monthly dashboard of these parameters to each practitioner. Continuous values are expressed as median [first quartile, third quartile]. During the study period, 53,294 patients managed by 79 anesthesiologists were available for analysis. Bivariate analysis revealed an overall decrease in median FGF from 2.0 [1.9, 3.0] liters/minute (l/min) to 1.9 [1.7, 2.0] l/min ( p  < 0.001). There was a significant decrease in the overall total CDE 20 from 5.10 [0,12.3] to 3.59 [0,8.78] kg/hr ( p  < 0.001). Multivariate analysis demonstrated an initial decrease in monthly practitioner total CDE 20 production with the intervention (odds ratio (OR) 0.875 95% confidence interval (CI) 0.809–0.996, p  < 0.001) and a faster decrease rate in monthly total CDE 20 (OR 0.986, 95% CI 0.976—0,996, p  < 0.001). Dashboard distribution initially decreased isoflurane (intervention OR 0.97 95% CI 0.96–0.99, p  = 0.001) and N 2 O (OR 0.82 95% CI 0.73–0.94, p  = 0.003) CDE 20 production and was associated with a steeper declining rate of isoflurane (OR 0.87, CI 0.79–0.94, p  < 0.001) and desflurane (OR 0.9, 0.84—0.97, p  = 0.005) CDE 20 production. The intervention did not have a significant effect on the monthly rate of decline of sevoflurane or N 2 O CDE 20 . The average practitioner FGF decreased by 0.3 l/m (95% confidence interval (CI): -0,011, -0.5, p  = 0.002) with dashboard distributions. Dashboard distribution may be an effective tool to decrease FGF as well as components of anesthetic greenhouse gas emissions.

PurposeThe purpose of this paper is to analyze the readability and level of word complexity of search engine results pages (SERPs) snippets and associated web pages between Google and Bing.Design/methodology/approachThe authors employed the Readability Test Tool to analyze the readability and word complexity of 3,000 SERPs snippets and 3,000 associated pages in Google and Bing retrieved on 150 search queries issued by middle school children.FindingsA significant difference was found in the readability of SERPs snippets and associated web pages between Google and Bing. A significant difference was also observed in the number of complex words in snippets between the two engines but not in associated web pages. At the engine level, the readability of Google and Bing snippets was significantly higher than associated web pages. The readability of Google SERPs snippets was at a much higher level than those of Bing. The readability of snippets in both engines mismatched with the reading comprehension of children in grades 6–8.Research limitations/implicationsThe data corpus may be small. Analysis relied on quantitative measures.Practical implicationsPractitioners and other mediators should mitigate the readability issue in SERPs snippets. Researchers should consider text readability and word complexity simultaneously with other factors to obtain the nuanced understanding of young users’ web information behaviors. Additional theoretical and methodological implications are discussed.Originality/valueThis study measured the readability and the level of word complexity embedded in SERPs snippets and compared them to respective web pages in Google and Bing. Findings provide further evidence of the readability issue of SERPs snippets and the need to solve this issue through system design improvements.

Bio-based fertilisers (BBFs) are gaining attention as sustainable alternatives to mineral fertilisers due to their potential for nutrient recovery, reduced environmental emissions, and improved soil health. However, their broader adoption is hindered by regulatory uncertainty, quality inconsistencies, and methodological variability in assessing their environmental impacts. This study can reveal about the body of research on bio-based fertilisers (BBFs), using a hybrid methodology that combines bibliometric and content analysis. A total of 247 publications from 2001 to 2024 were reviewed to identify research trends, environmental concerns, and assessment approaches. Results show a sharp increase in BBF-related publications after 2016, driven primarily by European and North American research, with growing focus on life cycle assessment (LCA) and nutrient recovery. The in-depth analysis of the ten most cited LCA and non-LCA studies highlights key methodological differences: non-LCA studies frequently rely on empirical fieldwork and generate primary data, whereas LCA studies typically synthesise secondary data to provide broader system-level insights. Despite this complementarity, the lack of methodological harmonisation poses a barrier to consistent comparison and interpretation. The findings highlight the need for a unified, standardised assessment framework to reliably evaluate the environmental performance of BBFs and support their effective implementation within circular and sustainable agricultural systems.

Background Central monitoring, which typically includes the use of key risk indicators (KRIs), aims at improving the quality of clinical research by pro-actively identifying and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. However, there has to-date been a relative lack of direct quantitative evidence published supporting the claim that central monitoring actually leads to improved quality. Material and Methods Nine commonly used KRIs were analyzed for evidence of quality improvement using data retrieved from a large central monitoring platform. A total of 212 studies comprising 1676 sites with KRI signals were used in the analysis, representing central monitoring activity from 23 different sponsor organizations. Two quality improvement metrics were assessed for each KRI, one based on a statistical score ( p -value) and the other based on a KRI’s observed value. Results Both KRI quality metrics showed improvement in a vast majority of sites (82.9% for statistical score, 81.1% for observed KRI value). Additionally, the statistical score and the observed KRI values improved, respectively by 66.1% and 72.4% on average towards the study average for those sites showing improvement. Conclusion The results of this analysis provide clear quantitative evidence supporting the hypothesis that use of KRIs in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Data-intensive applications are those that explore, query, analyze, and, in general, process very large data sets. Generally, these applications can be naturally implemented in parallel but, in many cases, these implementations show severe performance problems mainly due to load imbalances, inefficient use of available resources, and improper data partition policies. It is worth noticing that the problem becomes more complex when the conditions causing these problems change at run time. This paper proposes a methodology for dynamically improving the performance of certain data-intensive applications based on: adapting the size and number of data partitions, and the number of processing nodes, to the current application conditions in homogeneous clusters. To this end, the processing of each exploration is monitored and gathered data is used to dynamically tune the performance of the application. The tuning parameters included in the methodology are: (i) the partition factor of the data set, (ii) the distribution of the data chunks, and (iii) the number of processing nodes to be used. The methodology assumes that a single execution includes multiple related explorations on the same partitioned data set, and that data chunks are ordered according to their processing times during the application execution to assign first the most time consuming partitions. The methodology has been validated using the well-known bioinformatics tool—BLAST—and through extensive experimentation using simulation. Reported results are encouraging in terms of reducing total execution time of the application (up to a 40 % in some cases).

A growing number of governments are working to improve their performance by creating systems to measure and help them understand their performance.These systems for monitoring and evaluation (M&E) are used to measure the quantity, quality and targeting of the goods and services--the outputs--that the state provides and to measure the outcomes and.

The International Finance Corporation (IFC) has advanced systems to gather, analyze, and apply investment and advisory project information. It has made strides in developing, aggregating, disclosing, and strategically using its development indicators. The Multilateral Investment Guarantee Agency (MIGA) has made progress in upgrading its system of assessing its development performance. There are gaps in terms of measuring private sector development for investment projects and use of relevant standard indicators in advisory services projects. Reliability of data can be enhanced by adding more independent verification. Most self-evaluation has been project focused, but there is much that could be learned by extending evaluation to cover programs and strategies. The systems could be improved in several aspects to make evaluation more effective and to get more value from evaluation lessons. This biennial report on operations evaluation is an evaluation of these systems. It takes stock of the strengths and weaknesses of the development results frameworks in place for IFC investment services, IFC advisory services, and MIGA guarantees, and determines whether they: (1) provide mechanisms to generate credible, timely, and relevant information; (2) support evidence based decision making and learning; and (3) improve the performance and results of IFC's or MIGA's activities. Where they fall short, this report offers recommendations for improvements.

This report provides some practical guidance on how utilities can define their own smart grid vision, identify priorities, and structure investment plans. While most of these strategic aspects apply to any area of the electricity grid, the document focuses on the segment of distribution. The guidance includes key building blocks that are needed to modernize the distribution grid and provides examples of grid modernization projects. Potential benefits that can be achieved (in monetary terms) for a given investment range are also discussed. The concept of the smart grid is relevant to any grid regardless of its stage of development. What varies are the magnitude and type of the incremental steps toward modernization that will be required to achieve a specific smart grid vision. Importantly, a utility that is at a relatively low level of grid modernization may leap frog one or more levels of modernization to achieve some of the benefits offered by the highest levels of grid modernization. Smart grids impact electric distribution systems significantly and sometimes more than any other part of the electric power grid. In developing countries, modernizing the distribution grid promises to benefit the operation of electric distribution utilities in many and various ways. These benefits include improved operational efficiency (reduced losses, lower energy consumption, amongst others), reduced peak demand, improved service reliability, and ability to accommodate distributed generating resources without adversely impacting overall power quality. Benefits of distribution grid modernization also include improved asset utilization (allowing operators to 'squeeze' more capacity out of existing assets) and workforce productivity improvement. These benefits can provide more than enough monetary gain for electric utility stakeholders in developing countries to offset the cost of grid modernization. Finally the report describes some funding and regulatory issues that may need to be taken into account when developing smart grid plans.