Journal articles: 'Prediction of future progress of project' – Grafiati (2024)

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IntroductionDuring the last twenty years, international efforts advanced the prevention of psychosis considerably. However, improved predictions as well as well-tolerated and needs-tailored interventions are still required.ObjectivesPrediction and Prevention of PsychosisAims Presenting the current state and new developments, including the European Union funded multi-center project PRONIA with regard to prediction (www.pronia.eu, 7th Framework Programme grant agreement n° 602152) and the German multi-center trial ESPRIT funded by the Federal Ministry of Education and Research (BMBF grants 01EE1407 C and 01EE1407I) with regard to prevention.MethodsResults of meta-analyses will be presented and discussed with regard to achievements and challenges. Possible advances by current projects will be discussed.ResultsPharmacological as well as psychological prevention has been shown to reduce the incidence rate of psychosis in the respective samples considerably. However, particularly social and role functioning, which are prognostically most important, are still an unsolved challenge. Furthermore, new interventions providing an improved tolerability and acceptance by the patients are required. On the level of prediction, a further improvement of predictive validity, particularly with regard to individualized risk estimation is desired.ConclusionsThe achievements in the field of prevention of psychosis are impressive, but further progress is needed. This should be achieved by studies like PRONIA, which aims at improving risk estimation by an advanced assessment concept as well as a sophisticated data analysis, and ESPRIT, which compares the effects of N-Acetylcysteine with an innovative, modular psychological prevention program focusing not only stress and symptom management, but also social cognitive domains.Disclosure of interestConsultant to Boehringer Ingelheim lecture fees by Boehringer Ingelheim, Otsuka travel grant by Servier.

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IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society’s ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.

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Progress management of a construction project can detect changes early by visualizing the progress of the project, as it is important to be capable of predicting the success or failure of future project objectives. However, to perform reliable progress management tasks, accurate measurement data is required. In this study, the basic principle of the evaluation of project progress was performed through the 3D point cloud and the 4D attributes of BIM. The evaluation of project progress proposed in this study was based on as-built data to assess the progress of the project site. The specific improvements via the proposed process for this study in the construction project-progress control area were as follows: (1) visualization of construction project progress, (2) calculation of project as-built quantity, and (3) evaluation of a project’s progress. This study improved the efficiency and productivity in the management of a construction project through detection of the progress process. It provided easy monitoring of the overall project status, such as productivity analysis, progress rate and quality verifications, and easy identification of the problems created and foreseeable engineering tasks.

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In their pavement management decision-making processes, U.S. state highway agencies are required to develop performance-based approaches by the Moving Ahead for Progress in the 21st Century (MAP-21) federal transportation legislation. One of the performance-based approaches to facilitate pavement management decision-making processes is the use of remaining service life (RSL) models. In this study, a detailed step-by-step methodology for the development of pavement performance and RSL prediction models for flexible and composite (asphalt concrete [AC] over jointed plain concrete pavement [JPCP]) pavement systems in Iowa is described. To develop such RSL models, pavement performance models based on statistics and artificial intelligence (AI) techniques were initially developed. While statistically defined pavement performance models were found to be accurate in predicting pavement performance at project level, AI-based pavement performance models were found to be successful in predicting pavement performance in network level analysis. Network level pavement performance models using both statistics and AI-based approaches were also developed to evaluate the relative success of these two models for network level pavement performance modeling. As part of this study, in the development of pavement RSL prediction models, automation tools for future pavement performance predictions were developed and used along with the threshold limits for various pavement performance indicators specified by the Federal Highway Administration. These RSL models will help engineers in decision-making processes at both network and project levels and for different types of pavement management business decisions.

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Objective: To review specific literature that aimed to predict the future of US pharmacy, beginning in the late 1980s. Data Sources: Articles were identified from searching MEDLINE, CINAHL, Google Scholar, and references of relevant articles. The following combinations of search terms were used: future, pharmacy, prediction, and forecast. Study Selection and Data Extraction: The following inclusion criteria were applied: (1) full-text commentary, review, or original research and (2) focused predominantly on the pharmacy in the United States. Data on predictions for the future of pharmacy were extracted. Data Synthesis: We selected 3 articles published between 1988 and 2006, with each aiming to project the future for the following decade. We examined each prediction in light of the current knowledge. Relevance to Patient Care and Clinical Practice: Educators, practitioners, and other stakeholders should consider reflecting on the changes in pharmacy for the past 3 decades and applying both historical and emerging trends to improve patient care and sustain practice in the third decade of the 21st century and beyond. Conclusion: Most of the predictions for the future of pharmacy from the past 3 decades materialized, with some still in progress (reimbursem*nt for pharmacy services), whereas others manifested in unexpected ways (transition from shortage to excess of pharmacists). Current forces shaping pharmacy include, but are not limited to, growing spending and use of specialty drugs, automation of pharmacy operations, growth of pharmacy in the digital health enterprise, and growing consumer interest in the use of analytical pharmacy that tests drugs before dispensing.

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We review earthquake observation and strong motion seismology in Japan over the three decades starting in 1975. Preceding the 1995 Kobe earthquake, earthquake prediction research programs played an important role in earthquake observation research. The devastating damage from this earthquake, however, forced a change in emphasis from empirical shortterm prediction to long-term forecasting of earthquakes and the prediction of strong ground motion. Nationwide observation networks were set up, and progress in strong motion seismology was applied to projects of national seismic hazard maps. The next disastrous earthquake may even force their reexamination in the near future.

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The Earned Value Method allows the prediction of future values of the total cost and duration of the construction project realization, and also it allows the early detection of the collisions between the schedule and the construction project budget. It is more often indicated its usefulness for monitoring and controlling the construction work progress in the time and cost formulation. It is used, in the indirect way, to control the risk in terms of the cost overruns of the construction project realization and in case of the failure to meet the deadline for completion of the construction project. The authors’ goal was not only to indicate the advantages of the method (widely discussed in the literature) but also to indicate some inaccuracies in the application of the Earned Value Method, which may affect the costs forecasting and the date of completion of the construction project. The conclusions are based on the analysis of several construction project realizations.

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The progress made over the past three decades in the key elements of pavement management systems was evaluated, and the significant improvements expected over the next 10 years were projected. Eight specific elements of a pavement management system were addressed: functions, data collection and management, pavement performance prediction, economic analysis, priority evaluation, optimization, institutional issues, and information technology. Among the significant improvements expected in pavement management systems in the next decade are improved linkage among, and better access to, databases; systematic updating of pavement performance prediction models by using data from ongoing pavement condition surveys; seamless integration of the multiple management systems of interest to a transportation organization; greater use of geographic information and Global Positioning Systems; increasing use of imaging and scanning and automatic interpretation technologies; and extensive use of formal optimization methods to make the best use of limited resources.

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Aim: Development of a new, practically applicable computational method to monitor progress in lead optimization. Computational approaches that aid in compound optimization are discussed and the Compound Optimization Monitor (COMO) method is introduced and put into scientific context. Methodology & calculations: The methodological concept and the COMO scoring scheme are described in detail. Results & discussions: Calculation parameters are evaluated, and profiling results reported for an ensemble of analog series. Future perspective: The dual role of virtual analogs as diagnostic tools for progress evaluation and as potential candidates for lead optimization is discussed. In light of this dual role, interfacing COMO with machine learning for compound activity prediction and prioritization of candidates is highlighted as a future research objective.

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With the progress of science and technology, the advent of VR panorama, the era of Big Data has arrived, which has set off a revolution in the development and future destiny of Internet companies. Human resource management (HRM) is an important department of Internet companies. This paper introduces the principle and value of Big Data and related theories of HRM. This paper discusses three aspects of HRM in our company using Big Data theory: employee turnover prediction, salary comparison, and talent evaluation method, and puts forward suggestions for optimization and improvement of the company’s HRM. The results show that, through the company’s project manager’s ability to quantify data and analyze a set of data quantitative research, comparative analysis of the ability of three candidates Q, W, and E showed that W is the most suitable for the company’s project manager staff.

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Soils have critical relevance to global issues, such as food and water security, climate regulation, sustainable energy, desertification and biodiversity protec-tion. As a consequence, soil is becoming one of the top priorities for the global environmental policy agenda. Conventional soil maps suffer from large limita-tions, i.e. most of them are static and often obsolete, are often generated at coarse scale, and can be uneasy to handle. Digital Soil Mapping has been developed as a solution to generate high-resolution maps of soil properties over large areas. Two projects, GlobalSoilMap and SoilGrids, presently aim at delivering the first generation of global, high-resolution soil property fine grids. In this paper, we briefly describe the GlobalSoilMap history, its present status and present achievements, and illustrate some of these with (mainly) French examples. At given moment there is still an enormous potential for forthcoming research and for delivering products more helpful for end users. Key here is the continuous progress in available covariates, in their spatial, spectral and temporal coverage and resolution through remote sensing products. All over the world, there is still a very large amount of point soil data still to be rescued and this effort should be pursued and encouraged. Statistically advances are expected by exploring and implementing new models. Especially relevant are spatial-temporal models and contemporary Artificial Intelligence for handling the complex big data. Advances should be made and research efforts are needed on estimating the uncertainties, and even on estimating uncertainties on uncertainties. Attempts to merge different model strategies and products (for instance deriving from different covariates, spatial extents, soil data sources, and models) should be made in order to get the most useful information from each of these predictions, and to identify how controlling factors may change depending on scales.

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For at least a decade, researchers at the Army Research Laboratory (ARL) have predicted mental workload using human performance modeling (HPM) tools, primarily IMPRINT. During this timeframe their projects have matured from simple models of human behavior to complex analyses of the interactions of system design and human behavior. As part of this maturation process, the researchers learned: 1) to develop a modeling question that incorporates all aspects of workload, 2) to determine when workload is most likely to affect performance, 3) to build multiple models to represent experimental conditions, 4) to connect performance predictions to an overall mission or system capability, and 5) to format results in a clear, concise format. By implementing the techniques they developed from these lessons learned, the researchers have had an impact on major Army programs with their workload predictions. Specifically, they have successfully changed design requirements for future concept Army vehicles, substantiated manpower requirements for fielded Army vehicles, and made Soldier workload the number one item during preliminary design review for a major Army future concept vehicle program. The effective techniques the ARL researchers developed for their IMPRINT projects are applicable to other HPM tools. In addition, they can be used by students and researchers who are doing human performance modeling projects and are confronted with similar problems to help them achieve project success.

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AbstractThe Bovine Respiratory Disease Coordinated Agricultural Project (BRD CAP) is a 5-year project funded by the United States Department of Agriculture (USDA), with an overriding objective to use the tools of modern genomics to identify cattle that are less susceptible to BRD. To do this, two large genome wide association studies (GWAS) were conducted using a case:control design on preweaned Holstein dairy heifers and beef feedlot cattle. A health scoring system was used to identify BRD cases and controls. Heritability estimates for BRD susceptibility ranged from 19 to 21% in dairy calves to 29.2% in beef cattle when using numerical scores as a semi-quantitative definition of BRD. A GWAS analysis conducted on the dairy calf data showed that single nucleotide polymorphism (SNP) effects explained 20% of the variation in BRD incidence and 17–20% of the variation in clinical signs. These results represent a preliminary analysis of ongoing work to identify loci associated with BRD. Future work includes validation of the chromosomal regions and SNPs that have been identified as important for BRD susceptibility, fine mapping of chromosomes to identify causal SNPs, and integration of predictive markers for BRD susceptibility into genetic tests and national cattle genetic evaluations.

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Abstract The goal of the Canadian Arctic Weather Science (CAWS) project is to conduct research into the future operational monitoring and forecasting programs of Environment and Climate Change Canada in the Arctic where increased economic and recreational activities are expected with enhanced transportation and search and rescue requirements. Due to cost, remoteness and vast geographical coverage, the future monitoring concept includes a combination of space-based observations, sparse in situ surface measurements, and advanced reference sites. A prototype reference site has been established at Iqaluit, Nunavut (63°45'N, 68°33'W), that includes a Ka-band radar, water vapor lidars (both in-house and commercial versions), multiple Doppler lidars, ceilometers, radiation flux, and precipitation sensors. The scope of the project includes understanding of the polar processes, evaluating new technologies, validation of satellite products, validation of numerical weather prediction systems, development of warning products, and communication of their risk to a variety of users. This contribution will provide an overview of the CAWS project to show some preliminary results and to encourage collaborations.

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Progress in the development and adoption of the Meat Standards Australia system has encouraged substantial change and an improved consumer awareness at all points of the Australian beef production chain. The system is moving from niche to mainstream market application with the exciting potential to transform many industry practices and build a more direct consumer focus. The system aims to accurately predict consumer satisfaction levels for individual cooked beef portions. This is a major advance on grading systems that classify carcasses into groups of like appearance. A prediction model was developed based on consumer testing and has proved to be useful in categorising a wide range of beef into consumer grades within cooking methods. These provide a basis to ensure a predictable eating quality result for the consumer and a mechanism to align product description and pricing throughout the production chain. When used in value-based marketing systems financial reward can be directly linked to consumer satisfaction encouraging a consumer-focussed industry. Research is proceeding to extend and improve the accuracy of the prediction model encompassing additional cattle types and cooking methods. Several projects in other countries are adding insights into the relative response of consumers from varied cultural backgrounds. It is hoped that further international collaboration will facilitate use of the developed technology to improve consumer value and industry returns through improved product consistency in global markets.

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Since 1970 age at death has much increased. This is greatly due to quick diminishing of old age mortality rates and sheds a new light on the analysis of the probable and possible variations to be expected regarding mortality. Projected numbers of elderly people depend a great deal on the choices made regarding future mortality. When comparing forecasted hypothetical mortality with recent actual achievements it is obvious that a certain amount of pessimism prevails in the forecasts. This prompts us to show greater boldness when forecasting. However, will the present rise in life expectancy, especially at higher ages, continue at the same pace or will it tend to reach its zenith (the biological limit of human life) and when? According to some experts, we are already approaching the limits of average human longevity, whereas for others, scientific progress will amply enable us to push back the age of 85 years determined by the former group. Improvement in the understanding of the multifactorial process of ageing will feed the debate but the economic, social and behavioural constraints of lengthning life spans should not be overlooked. Nevertheless and whatever age limit is set to define elderly people, based on a fixed or a varying age, as the age at which remaining life expectancy is constant, a sharp increase in numbers of elderly people is to be expected.

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Wastewater infrastructure systems deteriorate over time due to a combination of aging, physical, and chemical factors, among others. Failure of these critical structures cause social, environmental, and economic impacts. To avoid such problems, infrastructure condition assessment methodologies are developing to maintain sewer pipe network at desired condition. However, currently utility managers and other authorities have challenges when addressing appropriate intervals for inspection of sewer pipelines. Frequent inspection of sewer network is not cost-effective due to limited time and high cost of assessment technologies and large inventory of pipes. Therefore, it would be more beneficial to first predict critical sewers most likely to fail and then perform inspection to maximize rehabilitation or renewal projects. Sewer condition prediction models are developed to provide a framework to forecast future condition of pipes and to schedule inspection frequencies. The objective of this study is to present a state-of-the-art review on progress acquired over years in development of statistical condition prediction models for sewer pipes. Published papers for prediction models over a period from 2001 through 2019 are identified. The literature review suggests that deterioration models are capable to predict future condition of sewer pipes and they can be used in industry to improve the inspection timeline and maintenance planning. A comparison between logistic regression models, Markov Chain models, and linear regression models are provided in this paper. Artificial intelligence techniques can further improve higher accuracy and reduce uncertainty in current condition prediction models.

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Abstract An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge.

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Abstract Arctic sea ice has undergone significant change with large reductions in thickness and areal extent over the historical record. Numerical models project sea ice loss to continue for the foreseeable future, with the possibility of September ice-free conditions later this century. Understanding the mechanisms behind ice loss and its consequences for the larger Arctic and global systems is important if we are to anticipate and plan for the future. Meeting this challenge requires the collective and collaborative insights of scientists investigating the system from numerous perspectives. One impediment to progress has been a disconnect between the observational and modeling research communities. Advancing the science requires enhanced integration between these communities and more collaborative approaches to understanding Arctic sea ice loss. This paper discusses a successful effort to further these aims: a weeklong sea ice summer camp held in Barrow, Alaska (now known as Utqiaġvik), in May 2016. The camp brought together 25 participants who were a heterogeneous mix of observers and modelers from 13 different institutions at career stages from graduate students to senior researchers. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. A dialogue with Barrow community members was initiated in order to further understand the local consequences of Arctic sea ice loss. The discussion herein describes lessons learned from this activity and paths forward to advance the understanding and prediction of Arctic climate change.

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Pavement management systems assist engineers in the analysis of road network pavement condition data and subsequently provide input to the planning and prioritization of road infrastructure works programs. The data also provide input to a variety of engineering and economic analyses that assist in determining the future road network condition for a range of infrastructure-funding scenarios. The fundamental calculation of future pavement condition is commonly based on a pavement age versus pavement roughness relationship. However, roughness–age relationships commonly do not take into account the pavement’s historical performance; rather, an “average” rate of roughness progression is assigned to each pavement based on its current age or current roughness measurement. Results of a research project are documented; the project involved a comprehensive evaluation of pavement performance by examining roughness progression over time with other related variables. A method of calculating and effectively displaying roughness progression and the effects of pavement maintenance was developed. The method provides a better understanding of pavement performance, which in turn led to a methodology of calculating and reporting road network performance for application to the pavement design and delivery system in Queensland, Australia. Means of using this information to improve the accuracy of roughness progression prediction were also investigated.

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Background. Self-admitted technical debt (SATD) is a special kind of technical debt that is intentionally introduced and remarked by code comments. Those technical debts reduce the quality of software and increase the cost of subsequent software maintenance. Therefore, it is necessary to find out and resolve these debts in time. Recently, many automatic approaches have been proposed to identify SATD. Problem. Popular IDEs support a number of predefined task annotation tags for indicating SATD in comments, which have been used in many projects. However, such clear prior knowledge is neglected by existing SATD identification approaches when identifying SATD. Objective. We aim to investigate how far we have really progressed in the field of SATD identification by comparing existing approaches with a simple approach that leverages the predefined task tags to identify SATD. Method. We first propose a simple heuristic approach that fuzzily Matches task Annotation Tags ( MAT ) in comments to identify SATD. In nature, MAT is an unsupervised approach, which does not need any data to train a prediction model and has a good understandability. Then, we examine the real progress in SATD identification by comparing MAT against existing approaches. Result. The experimental results reveal that: (1) MAT has a similar or even superior performance for SATD identification compared with existing approaches, regardless of whether non-effort-aware or effort-aware evaluation indicators are considered; (2) the SATDs (or non-SATDs) correctly identified by existing approaches are highly overlapped with those identified by MAT ; and (3) supervised approaches misclassify many SATDs marked with task tags as non-SATDs, which can be easily corrected by their combinations with MAT . Conclusion. It appears that the problem of SATD identification has been (unintentionally) complicated by our community, i.e., the real progress in SATD comments identification is not being achieved as it might have been envisaged. We hence suggest that, when many task tags are used in the comments of a target project, future SATD identification studies should use MAT as an easy-to-implement baseline to demonstrate the usefulness of any newly proposed approach.

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Each country needs to monitor progress on their Sustainable Development Goals (SDGs) to develop strategies that meet the expectations of the United Nations. Data envelope analysis (DEA) can help identify best practices for SDGs by setting goals to compete against. Automated machine learning (AutoML) simplifies machine learning for researchers who need less time and manpower to predict future situations. This work introduces an integrative method that integrates DEA and AutoML to assess and predict performance in SDGs. There are two experiments with different data properties in their interval and correlation to demonstrate the approach. Three prediction targets are set to measure performance in the regression, classification, and multi-target regression algorithms. The back-propagation neural network (BPNN) is used to validate the outputs of the AutoML. As a result, AutoML can outperform BPNN for regression and classification prediction problems. Low standard deviation (SD) data result in poor prediction performance for the BPNN, but does not have a significant impact on AutoML. Highly correlated data result in a higher accuracy, but does not significantly affect the R-squared values between the actual and predicted values. This integrative approach can accurately predict the projected outputs, which can be used as national goals to transform an inefficient country into an efficient country.

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Background Diabetes-related foot ulcers give rise to considerable morbidity, generate a high monetary cost for health and social care services and precede the majority of diabetes-related lower extremity amputations. There are many clinical prediction rules in existence to assess risk of foot ulceration but few have been subject to validation. Objectives Our objectives were to produce an evidence-based clinical pathway for risk assessment and management of the foot in people with diabetes mellitus to estimate cost-effective monitoring intervals and to perform cost-effectiveness analyses and a value-of-information analysis. Design We developed and validated a prognostic model using predictive modelling, calibration and discrimination techniques. An overview of systematic reviews already completed was followed by a review of randomised controlled trials of interventions to prevent foot ulceration in diabetes mellitus. A review of the health economic literature was followed by the construction of an economic model, an analysis of the transitional probability of moving from one foot risk state to another, an assessment of cost-effectiveness and a value-of-information analysis. Interventions The effects of simple and complex interventions and different monitoring intervals for the clinical prediction rules were evaluated. Main outcome measure The main outcome was the incidence of foot ulceration. We compared the new clinical prediction rules in conjunction with the most effective preventative interventions at different monitoring intervals with a ‘treat-all’ strategy. Data sources Data from an electronic health record for 26,154 people with diabetes mellitus in one Scottish health board were used to estimate the monitoring interval. The Prediction Of Diabetic foot UlcerationS (PODUS) data set was used to develop and validate the clinical prediction rule. Review methods We searched for eligible randomised controlled trials of interventions using search strategies created for Ovid® (Wolters Kluwer, Alphen aan den Rijn, the Netherlands), MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials. Randomised controlled trials in progress were identified via the International Standard Randomised Controlled Trial Number Registry and systematic reviews were identified via PROSPERO. Databases were searched from inception to February 2019. Results The clinical prediction rule was found to accurately assess the risk of foot ulceration. Digital infrared thermometry, complex interventions and therapeutic footwear with offloading devices were found to be effective in preventing foot ulcers. The risk of developing a foot ulcer did not change over time for most people. We found that interventions to prevent foot ulceration may be cost-effective but there is uncertainty about this. Digital infrared thermometry and therapeutic footwear with offloading devices may be cost-effective when used to treat all people with diabetes mellitus regardless of their ulcer risk. Limitations The threats to the validity of the results in some randomised controlled trials in the review and the large number of missing data in the electronic health record mean that there is uncertainty in our estimates. Conclusions There is evidence that interventions to prevent foot ulceration are effective but it is not clear who would benefit most from receiving the interventions. The ulceration risk does not change over an 8-year period for most people with diabetes mellitus. A change in the monitoring interval from annually to every 2 years for those at low risk would be acceptable. Future work recommendations Improving the completeness of electronic health records and sharing data would help improve our knowledge about the most clinically effective and cost-effective approaches to prevent foot ulceration in diabetes mellitus. Study registration This study is registered as PROSPERO CRD42016052324. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 62. See the NIHR Journals Library website for further project information.

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In the Maasai Steppe, public health and economy are threatened by African Trypanosomiasis, a debilitating and fatal disease to livestock (African Animal Trypanosomiasis -AAT) and humans (Human African Trypanosomiasis—HAT), if not treated. The tsetse fly is the primary vector for both HAT and AAT and climate is an important predictor of their occurrence and the parasites they carry. While understanding tsetse fly distribution is essential for informing vector and disease control strategies, existing distribution maps are old and were based on coarse spatial resolution data, consequently, inaccurately representing vector and disease dynamics necessary to design and implement fit-for-purpose mitigation strategies. Also, the assertion that climate change is altering tsetse fly distribution in Tanzania lacks empirical evidence. Despite tsetse flies posing public health risks and economic hardship, no study has modelled their distributions at a scale needed for local planning. This study used MaxEnt species distribution modelling (SDM) and ecological niche modeling tools to predict potential distribution of three tsetse fly species in Tanzania’s Maasai Steppe from current climate information, and project their distributions to midcentury climatic conditions under representative concentration pathways (RCP) 4.5 scenarios. Current climate results predicted that G. m. morsitans, G. pallidipes and G swynnertoni cover 19,225 km2, 7,113 km2 and 32,335 km2 and future prediction indicated that by the year 2050, the habitable area may decrease by up to 23.13%, 12.9% and 22.8% of current habitable area, respectively. This information can serve as a useful predictor of potential HAT and AAT hotspots and inform surveillance strategies. Distribution maps generated by this study can be useful in guiding tsetse fly control managers, and health, livestock and wildlife officers when setting surveys and surveillance programs. The maps can also inform protected area managers of potential encroachment into the protected areas (PAs) due to shrinkage of tsetse fly habitats outside PAs.

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The purpose of the current study was to examine the type and form of future jobs, in light of the modern technological trends of the NEOM project. To achieve its objectives, the study utilized descriptive statistics with the Delphi method. The researchers convened a sample of ten experts in the fields of Science and Technology, Human Resources Planning, and Educational Administration and Planning, who participated in three scientific rounds. The findings from these rounds provide a suggested model for future jobs in the Kingdom of Saudi Arabia, in light of the modern technological trends of the NEOM project. This proposed model consists of twenty types of future jobs expected to achieve high degrees of importance over the next decade. Examining the study hypothesis yielded no statistically significant differences at the level (α ≥0.05) between the second and third scientific-round averages, confirming the stability of the experts' responses and their approval of this list of future jobs. The study recommends directing Saudi universities to develop academic programs to meet the needs of the NEOM project in the disciplines of Mechatronics Engineering, Using Technology in Surgery, and Software Engineering. Building academic programs with specific learning outcomes will ensure that graduates can acquire the necessary entrepreneurial skills, especially in disciplines such as Computerized Quantity Encrypted Engineering, Virtual Reality Technologies Design, and Three-Dimensional Printing Specialization. These programs will reduce acceptance of traditional academic programs that do not match the future requirements of the labor market, the Saudi 2030 Vision initiatives, and projects such as the NEOM project. The benefit from seats in more closely related programs will include the development of all programs in various universities and colleges to be entrepreneurial, supporting the new and expected technical trends in the labor market and all promising sectors of investment, such as the NEOM project.

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Solar thermal power technologies require storage systems to mitigate the natural variability of solar irradiation. Packed bed thermal storage systems (PBTES) offer a cost-effective solution using air as heat transfer fluid and rocks as a storage medium. Compared to its alternatives, however, PBTES presents a limited flexibility of operation due to the conventional unidirectional flow, which involves the progressive reduction of the outlet temperature during discharge and thus lowers the thermodynamic efficiency of the power cycle. The present study summarizes the progress on the design and optimal operation of a novel multi-extraction PBTES, a project that aims at mitigating its typically poor operational flexibility for solar power applications. To this end, a one-dimensional model with a high spatial resolution of a PBTES was developed, which includes four intermediate outlet points along the axial direction to investigate the benefits of optimal extraction operation. In order to reduce the computational burden, a coarser model of the storage system is used in combination with non-linear model predictive control (NLMPC). Through the optimal manipulation of the extraction valves, the output temperature is maintained close to a prescribed temperature throughout the discharge. The control admits not only constant temperature targets, but also time-varying scheduled profiles. This work describes the limitation of such a design and control approach and sets the direction for the future, more detailed analyses needed to demonstrate its applicability.

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In Model Schools Project West-Netherlands the Free University of Amsterdam (Department of Cognitive Psychology) and the State University of Utrecht (Researchgroup on Mathematics Education and Educational Computer Centre) study the way the computer can be used as an aid in secondary education. In the model school (Cals College Nieuwegein) five departments (Dutch Language, Mathematics, Foreign Languages, Geography, Home Economics) are developing and trying series of experimental lessons in which the computer is used as an aid to students and teachers. Existing (educational) software is elaborated with worksheets and teacher guidelines, aimed at an optimal integration of the software into the curriculum. During the schoolyear 1987/1988 the English Language teacher, supported by researcher and subject matter experts, has given a series of lessons on "reading and prediction", viz. the use of function words in a text. In four lessons the students worked on (a) choosing an appropriate consecutive phrase given a main phrase with function word (supported by the program "Sequitur"), (b) identifying the meaning of function words in a text (without computer), (c) learning the meaning of the major function words (supported by a Dutch program "Word Meanings"), and (d) completing sentence with a function word (supported by the Dutch program "Doka"). The experimental lessons indicated the contributions to be expected of the programs used and also the shortcomings to be remedied in future releases.

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Abstract Clostridium difficile (CDI) is the most common healthcare associated infection (HAI), and it causes particularly high morbidity and mortality among older adults. While risk factors for this deadly HAI have been explored at the patient and facility levels, less is known about transmission between facilities. Recent literature suggests that more patient transfers to a hospital are correlated with elevated CDI levels. However, this work excludes skilled nursing facilities (SNFs), although SNFs are a major contributor of older adult patients to hospitals. We use multiple large data sets to make progress in filling several existing knowledge gaps. First, we construct and analyze healthcare facility networks using transfers of Medicare beneficiaries in the Minimum Data Set 3.0 and Medicare claims data from New Mexico, New York, Connecticut, and Colorado. We evaluate the role of SNFs in networks through the volume and frequency of patient flows in and out of individual hospitals. We also assess the level of interaction (i.e., transfers) between facilities of different sizes, locations, and types. Second, using the Healthcare Cost and Utilization Project State Inpatient Databases, we examine whether a hospital CDI outbreak is predictive of CDI incidence across a network of hospitals, using multiple existing metrics of CDI incidence, noting strengths and weaknesses for each. These two aims lay the foundation for future work to examine the relationship between patient transfers and the distribution of outbreaks. Such work may be able to identify facilities that present the greatest CDI risk to older adults across a facility network.

Abstract:

Aim. JSC RZD is one of the largest and most advanced companies in Russia who actively deploys and uses best practices in asset and risk management. In 2010, the railway industry initiated the project for the management of resources, risks and dependability at lifecycle stages of railway facilities (URRAN) that is currently under way. The aims of this paper are to overview the asset management tasks covered by URRAN; examine the marketed IT tools designed to address such problems; present the progress of the URRAN project in terms of process automation implemented by JSC RZD in light of the international best practice and the specificity of the Company. Methods. The preparation of this paper involved empirical and theoretical research. The authors analysed the URRAN project’s package of guidelines and regulations, public information on the globally available software products enabling asset management, as well as the program documentation of the EKP URRAN automated system. They analysed the functionalities and and engineering solutions used in the development of this automated system. The results of the EKP URRAN deployment and practical application by units and branches of JSC RZD were evaluated. Results. Asset management involves using Enterprise Asset Management Systems (EAMS) specially designed to suit the needs of specific companies or mass-produced “out-of-the-box” systems, e.g. SAP ERP, IBM MAXIMO, ABB AbilityТМ and SimeoTM that are examined in the paper. The EKP URRAN implements a single information space that is a decision support tool for the asset management system as it possesses the required regulatory and procedural resources, hardware and software assets intended for comprehensive management of assets and processes for the purpose of efficient railway service. In the future, the EKP URRAN is to become part of the Digital Platform for Risk and Traffic Safety Management deployed in JSC RZD and will comprise modules that implement dynamic predictive analytics models for the purpose of predicting undesirable events involving infrastructure and rolling stock that may disrupt traffic safety. Conclusions. Further development of the EKP URRAN will soon provide all levels of company management with an efficient tool that allows, in the context of limited resources, making substantiated managerial decisions and rational investment allocation. The EKP URRAN is an asset of JSC RZD designed to be used by the managers and specialists of various JSC RZD units. It can be implemented as a standalone IT product for the purpose of developing and deploying an asset management system in various railway companies.

Abstract:

AbstractVector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal ‘gold standard’ method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Abstract:

Objective - This paper reviews developments in the consolidation and diversification of the evidence based library and information practice (EBLIP) paradigm since publication of the authors’ book Evidence Based Practice for Information Professionals: a Handbook in 2004. Methods - The authors provide an updated narrative review of key themes in the development of evidence based librarianship within the context of the new consensual term ‘EBLIP.’ Sources for this thematic framework included professional literature, Internet searches, and the authors’ personal experiences. Results - While considerable achievements have been realized within a three-year period, most notably the instigation of the journal known as EBLIP, a broadening of the paradigm to other library sectors, and increased availability of implementation studies, many challenges remain. Of particular concern is the lack of international strategic foresight in determining rotation of the biennial international conferences and distribution of influential EBLIP infrastructures and initiatives. Conclusion - While the enthusiasms and energies of individual practitioners and work teams have made considerable progress in meeting short-term objectives, uncertainty remains concerning how longer-term objectives requiring infrastructure and resources might be realized. From its faltering steps as a toddler EBLIP has developed to a ‘pre-pubescent’ stage with the promise of ‘growth spurts’ and ‘emotional crises.’ The next three years should prove both challenging and demanding.

Abstract:

OBJECTIVES/SPECIFIC AIMS: The Rockefeller University-Center for Clinical and Translational Science and Clinical Directors Network (RU-CCTS/CDN) community-academic-partnership engaged with Carter Burden Center for the Aging (CBCA), a multisite senior community services organization serving Upper Eastside and East Harlem, NY, to develop community-engaged research. Many seniors served by CBCA are racial/ethnic minorities, live in poverty, suffer from multiple chronic conditions, depression, and food insecurity; there is no simple measure routinely used to characterize the health/health risks of program participants. Multiple biological, musculoskeletal, psychosocial and nutritional factors collectively contribute to frailty a construct that is variously defined, and has been used as a surrogate or predictor for health outcomes. Aim 1: We will engage seniors, CBCA leadership, New York City Department for the Aging, staff and other stakeholders in research priority-setting, joint protocol writing, research conduct, analysis and dissemination to cultivate a population of elder stakeholders interested in designing and participating in this and future research. Aim 2: We will characterize the health status of the resident and nonresident populations by collecting data across 3 sessions to include validated cardio-metabolic, musculoskeletal, chronic condition prevalence, quality of life, psychosocial, and nutritional assessments. METHODS/STUDY POPULATION: Stakeholders will be engaged through the process of Community Engaged Research Navigation and a series of meetings and exercises to refine priorities and research design, co-write the protocol, provide feedback on conduct, analyze and disseminate results of the project. RESULTS/ANTICIPATED RESULTS: Outcomes will include rates of participation and retention in assessments and engagement activities, themes from qualitative research, contributions to study design, placement of aims on the T0-T48 spectrum, social network analysis, classification of engagement on the spectrum of Community-based Participatory Research (CBPR) and partnership assessment. The primary outcome is frailty (6-minute walk test); We will examine associations among these measures with services utilization data captured electronically by CBCA. A key deliverable of this project will be a REDCap data capture platform that integrates and displays these measures that will be sustainable for CBCA. DISCUSSION/SIGNIFICANCE OF IMPACT: This practice-based research partnership will allow us to extract, replicate and extend the lessons learned about engaging stakeholders in generating hypotheses, operationalizing research, collecting and analyzing data, and disseminating results. The collaboration is built around generating and testing rigorous clinical an health services hypotheses that are derived from real-world practice-based needs and also incorporate basic science measures to embed and examine mechanistic hypotheses. Testing a simple to implement validated surrogate frailty measure will accelerate progress on evidence-based practices to test interventions that enhance healthy aging and serve as a model for future similar partnerships to form a network for community-based senior research. This work aligns with the RU-CCTS grant Hub Research goal to engage populations across the life span, including hard-to-reach and underserved populations, such as minority seniors.

Abstract:

The Organisation for Economic Co-operation and Development (OECD) is in the midst of a project intended to tackle the tax challenges arising from the digitalization of the economy. As initially laid out in its program of work released in May 2019, the goal is to develop consensus on a new taxing right that would allow countries to tax multinationals even in the absence of traditional physical presence. In this paper, the authors argue that upon inspection, the plan seems primarily focused on rebalancing taxing rights mostly among a number of OECD member states plus a few other key non-OECD states, and that, viewed from this perspective, the urgent effort to forge a new global tax deal for the digital age risks deferring a much-needed discussion on the broader distributive implications of the current global tax deal to some unspecified future time. The first part of the paper offers a brief survey of some of the main factors that prompted the OECD to turn its attention to this topic. The second part considers the origins and development of nexus in the international tax regime, showing why this concept is amenable to broad expansion. The third part examines the range of reforms currently under consideration, arguing that the framing on digitalization misses a necessary connection to other pressing international policy programs that are also under development, most notably a global commitment to building institutions that support sustainable economic development. The paper concludes with a prediction that on its current trajectory, the program of work on digitalization is likely to produce a new global tax deal that looks much like the old global tax deal, with a relatively modest redistribution of taxing rights among a few key states, thus missing an opportunity for meaningful reform.

Abstract:

The University of Missouri–St Louis Partnerships for Progress, Project Compete partnership programme was initiated in 1986 between the University and the St Louis School District, stimulated by a large grant from one major St Louis-based international corporation. Initially, the project involved only one major programme element, known as the ‘Bridge’ programme, which operated in two St Louis city high schools (grades 9–12). A second programme for high-school youth – the Engelmann Institute – was added in 1987, and a third programme, Access to Success, was added in 1988 to extend the programme to the middle school (grades 6–8). Each programme is discussed in this article, as are the lessons learned from Project Compete and its potential for future development.

Abstract:

AbstractLocated in central Poland, the Kłodawa salt dome is 26 km long and about 2 km wide. Exploitation of the dome started in 1956, currently rock salt extraction is carried out in 7 mining fields and the 12 mining levels at the depth from 322 to 625 meters below sea level (m.b.s.l.). It is planned to maintain the mining activity till 2052 and extend rock salt extraction to deeper levels. The dome is characterised by complex geological structure resulted from halokinetic and tectonic processes.Projection of the 3D numerical analysis took into account the following factors: mine working distribution within the Kłodawa mine (about 1000 rooms, 350 km of galleries), complex geological structure of the salt dome, complicated structure and geometry of mine workings and distinction in rocks mechanical properties e.g. rock salt and anhydrite. Analysis of past mine workings deformation and prediction of future rock mass behaviour was divided into four stages: building of the 3D model (state of mine workings in year 2014), model extension of the future mine workings planned for extraction in years 2015-2052, the 3D model calibration and stability analysis of all mine workings.The 3D numerical model of Kłodawa salt mine included extracted and planned mine workings in 7 mining fields and 14 mining levels (about 2000 mine workings). The dimensions of the model were 4200 m × 4700 m × 1200 m what was simulated by 33 million elements. The 3D model was calibrated on the grounds of convergence measurements and laboratory tests. Stability assessment of mine workings was based on analysis of the strength/stress ratio and vertical stress. The strength/stress ratio analysis enabled to indicate endangered area in mine workings and can be defined as the factor of safety. Mine workings in state close to collapse are indicated by the strength/stress ratio equals 1. Analysis of the vertical stress in mine workings produced the estimation of current state of stress in comparison to initial (pre-mining) conditions.The long-term deformation analysis of the Kłodawa salt mine for year 2014 revealed that stability conditions were fulfilled. Local disturbances indicated in the numerical analysis were connected with high chambers included in the mining field no 1 and complex geological structure in the vicinity of mine workings located in the mining fields no 2 and 3. Moreover, numerical simulations that projected the future extraction progress (till year 2052) showed positive performance. Local weakness zones in the mining field no 7 are associated with occurrence of carnallite layers and intensive mining which are planned in the mining field no 6 at the end of rock salt extraction.

Abstract:

The Environmental Assessment (EA) process should involve the generation of testable predictions generated using clearly stated methods and followed by the collection of environmental monitoring data. Follow-up programs should aim to determine the accuracy of the initial predictions. We examined the follow-up process for six oil and gas extraction projects in eastern Canada with respect to assessing batch spill (< 50 barrels of hydrocarbons and synthetic hydrocarbons) predictions. For three projects we compared oil spill frequency predictions to observed data. All three projects exceeded their predicted frequencies and two projects by ratios (actual to predicted) greater than six. Spill histories from earlier projects, clearly exceeding predictions of future projects, are not provided in subsequent oil and gas EAs for the region, when there were opportunities to do so. We provide recommendations on how to strengthen the quality of EAs and increase protection of the marine environment in Canada.

Abstract:

AbstractSpectra of exoplanets, cool stars and brown dwarfs contain features due to molecular absorptions. Modelling these requires extensive line lists which are provided by the ExoMol project. Here we report on current progress and future prospects for the project.

Abstract:

Abstract. A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU-project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity) with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT) event, encountered during the STACCATO period on 20–21 June 2001, could be followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20–21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one reaching almost a height of 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent measurements of the cosmogenic radionuclides 10Be and 7Be and their ratio 10Be/7Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures with many details the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October 1999) from the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model is shown to be in very good agreement with the observations during this case study, which provides the first successful validation of a chemical tracer that is used operationally in a weather forecast model. This suggests that coupling chemistry and weather forecast models may significantly improve both weather and chemical forecasts in the future.

Abstract:

Abstract. A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity) with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT) event, encountered during the STACCATO period on 20-21 June 2001, was followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20-21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one descending to nearly 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent surface measurements of the cosmogenic radionuclides 10Be and 7Be and their ratio 10Be/7Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures many details of the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October 1999) from the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model is shown to be in very good agreement with the observations during this case study, which provides the first successful validation of a chemical tracer that is derived operationally from a weather forecast model. This suggests that coupling chemistry and weather forecast models may significantly improve both weather and chemical forecasts in the future.

Abstract:

AbstractPosttranslational modifications (PTMs) play an important role in regulating protein folding, activity and function and are involved in almost all cellular processes. Identification of PTMs of proteins is the basis for elucidating the mechanisms of cell biology and disease treatments. Compared with the laboriousness of equivalent experimental work, PTM prediction using various machine-learning methods can provide accurate, simple and rapid research solutions and generate valuable information for further laboratory studies. In this review, we manually curate most of the bioinformatics tools published since 2008. We also summarize the approaches for predicting ubiquitination sites and glycosylation sites. Moreover, we discuss the challenges of current PTM bioinformatics tools and look forward to future research possibilities.

Abstract:

AbstractClark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models).

Abstract:

In order to implement the central government’s major deployment of preventing and punishing statistical falsification, improving the authenticity of statistical data, and further improving the science and accuracy of power grid project funding forecasts. By studying the fund payment law of power grid infrastructure project and constructing the theoretical capital progress curve model of power grid infrastructure project, the progress and time point of fund payment in each link of the whole process of the project can be effectively controlled. Scientific prediction of the project life cycle at all stages of the fund demand, financing arrangements and payment control to provide a reference.

Abstract:

IntroductionThis research project addresses the lack of screening tools for the early detection of high-risk individuals for long-term care, through four individual studies.Study 1 investigates the predictive ability of the ‘Kihon Check List’, study 2 the ‘Cognitive Function instrument’ and EuroQol-5 Dimension (EQ-5D) and study 3 the ‘Cognitive Function instrument’ and EQ-5D as well as the ‘Frail Kenshin’ health check-up, for incident long-term care certification over a follow-up period of up to 4 years. This is the first large prospective study to evaluate the predictive ability of these tools for the outcome measure long-term care certification. The last subsection of this project study four aims to explore a mixed methods intervention for delaying the need for long-term care. This section is purely exploratory, looking for clues for further studies.Methods and analysisBaseline data have been collected through local government programs, as well as through postal self-reported questionnaires. The primary outcome variable for all studies is long-term care certification data. Statistical analysis will be carried out using Kaplan-Meier, Multiple Cox regression as well as logistic regression.ConclusionThis project hopes to identify tools effective in predicting long-term care need. This will enable identification of citizens that are of higher risk for long-term care in the near future. This subset of high-risk individuals can in the future be addressed for extra support/intervention.Ethics and disseminationAll studies have been approved by respective institutional ethical committees and the WHO ethical committee ERC.0002899. In addition, all studies conform to the provisions of the Declaration of Helsinki and are conducted in accordance with Japan’s ‘Ethical Guidelines for Medical and Health Research Involving Human Subjects’. All findings will be disseminated at conferences and published in peer-reviewed journals.Trial registration numberUMIN000023283.