Search

Background: Managing repaired tetralogy of Fallot (TOF) patients is still challenging despite the fact that published studies identified prognostic clinical or imaging data with rather good negative predictive accuracy but weak positive predictive accuracy. Heterogeneity of the initial anatomy, the surgical approach, and the complexity of the mechanism leading to dilation and ventricular dysfunction explain the challenge of predicting the adverse event in this population. Therefore, risk stratification and management of this population remain poorly standardized. Design: The CMR/CT WG of the Italian Pediatric Cardiology Society set up a multicenter observational clinical database of repaired TOF evaluations. This registry will enroll patients retrospectively and prospectively assessed by CMR for clinical indication in many congenital heart diseases (CHD) Italian centers. Data collection in a dedicated platform will include surgical history, clinical data, imaging data, and adverse cardiac events at 6 years of follow-up. Summary: The multicenter repaired TOF clinical database will collect data on patients evaluated by CMR in many CHD centers in Italy. The registry has been set up to allow future research studies in this population to improve clinical/surgical management and risk stratification of this population. [ABSTRACT FROM AUTHOR]

At present, many budget companies have realized high-level computerized accounting and have high-speed and advanced database management systems. In order to adapt to the growth of budget entity informatization, the financial department must improve its own financial budget level. Introduce information technology, and develop corresponding financial budget software to better perform its own financial calculation function. This paper explores and analyzes the full collaborative matching algorithm of enabling big data financial budget and builds a financial big data financial budget platform through offline and online data collection. Combined with the matching algorithm and linear regression prediction algorithm in data analysis, the financial data is analyzed in depth. Finally, the PSO-SA algorithm runs 10 rounds on the datasets with matching scales d = 10 and 30, respectively. It is found that the fluctuation is large when d = 10 and relatively stable when d = 30. When d = 10 , the maximum value is 7.2354, and the minimum value is 6.9969. When d = 10 , the maximum value is 26.6403, and the minimum value is 23.9599. It can be concluded that when d = 0 , PSO-SA can obtain a relatively good matching scheme, but it is easy to fall into a local optimal solution. The superposition effect of "data + computing power + algorithm + scenario" can help enterprises make better decisions. Embed complex analysis into daily management and trading scenarios to build a financial empowerment platform. Make the increasingly complex work more automated and intelligent, and improve financial efficiency. [ABSTRACT FROM AUTHOR]

Clinical tuberculosis research, both within research groups and across research ecosystems, is often undertaken in isolation using bespoke data collection platforms and applying differing data conventions. This failure to harmonise clinical phenotype data or apply standardised data collection and storage standards in turn limits the opportunity to undertake meta-analyses using data generated across multiple research projects for the same research domain. We have developed the Tuberculosis DataBase Template (TBDBT), a template for the well-supported, free and commonly deployed clinical databasing platform, REDCap. This template can be used to set up a new tuberculosis research database with a built-in set of standardised data conventions, to ensure standardised data capture across research projects and programs. A modular design enables researchers to implement only the modules of the database template that are appropriate for their particular study. The template includes core modules for informed consent data, participant demographics, clinical symptoms and presentation, diagnostic imaging and laboratory tests. Optional modules have been designed for visit scheduling and calendar functionality, clinical trial randomisation, study logistics and operations, and pharmacokinetic data. Additional fields can be added as needed. This REDCap template can facilitate collection of high-quality data for tuberculosis research, providing a tool to ensure better data harmonisation, analysis and meta-analysis. [ABSTRACT FROM AUTHOR]

Optimal milking management leads to an increase in production efficiency while respecting animal welfare and health. Not all farms can equip themselves with high level technological systems for economic, generational and structural reasons. The aim of the study was to assess milking performances, cow behaviour and microclimatic condition in farm areas using an integrated data collection system based on surveys and low-cost sensors. The use of video recordings and mobile electronic flowmeters highlighted significant differences between farms that milked two and three times a day. Milking efficiency parameters (cow/hour; cows/stall per hour; milk/hour; milk/stall per hour) were calculated. In particular, the milk/stall per hour parameter emerged as the most interesting. Animal stay time, defined as the time running from when cows are moved from the housing to the beginning of the milking, was calculated and the highest value (76.3 minutes) was observed in farms with more than 10 stalls/row. Hobo pendant sensors were used in order to evaluate cows lying behaviour: no differences were observed between farms that milked two and three times a day (11.3 vs 11.0 h/d of lying). Microclimatic conditions were influenced by both the season (p <.001) and farm areas (p <.05) (holding area, milking parlour, housing area). Light intensity in milking parlour emerged as a critical point; further research is needed to understand the relation with udder hygiene and health. The integration of manual measurements with the use of low-cost sensors allowed to monitor the efficiency of the process and microclimatic condition in farm areas. The integration of manual measurements and low-cost sensors was tested Different parameters can be used to monitor milking efficiency Light intensity in milking parlour emerged as a critical point [ABSTRACT FROM AUTHOR]

This article aims to compose an analytical framework about the production of contemporary Brazilian geographers who have the indigenous theme as one of their central aspects, based on the research and data collection in texts and articles produced on this theme from 2004 to 2016, in congresses in this area. We work with the texts of the "Encontro Nacional de Geógrafos (ENG)" and the "Simpósio Internacional de Geografia Agrária (SINGA)", from which we organize quantitative data, in addition to analyzing which concepts and theoretical-methodological perspectives Brazilian geography has been addressing these issues. We identified an increase in production on indigenous themes in geography, but we highlight the need for greater convergence between studies in this area. This text constitutes a starting point in the sense of knowing and making visible the geographical productions in Brazil in the face of indigenous themes, as well as the protagonism and acting of geographers in this field in the last decades. [ABSTRACT FROM AUTHOR]

Applying computer technology and data mining technology in sports field plays an important role in improving the training effect and competition level of athletes. This paper focuses on the design and implementation of the beach volleyball big data analysis system based on computer technology. Using computer as the data collection and analysis platform, it adopts the sorting prediction algorithm and the Markov-based data mining algorithm to predict the cooperation success rate in the beach volleyball match and to search for key action transfer processes. The paper designs and implements a beach volleyball big data analysis system based on computer technology, and experimental results have verified the effectiveness of the data mining algorithm in beach volleyball matches. This study provides a scientific basis for coaches to formulate reasonable beach volleyball training programs and tactical decisions, which is of certain practical significance. [ABSTRACT FROM AUTHOR]

The article discusses the use of the PROCLIPI (PROspective Cutaneous Lymphoma International Prognostic Index) data collection system to research diagnostic delays in early-stage mycosis fungoides (MF) cancer. Topics include the inaccuracy of diagnostic tests for MF, survival prognosis for patients, and the use of biobanked tissue samples.

The problem of crowdsourced entity collection solicits people (a.k.a. workers) to complete missing data in a database and has witnessed many applications in knowledge base completion and enterprise data collection. Although previous studies have attempted to address the "open world" challenge of crowdsourced entity collection, they do not pay much attention to the "distribution" of the collected entities. Evidently, in many real applications, users may have distribution requirements on the collected entities, e.g., even spatial distribution when collecting points-of-interest. In this paper, we study a new research problem, distribution-aware crowdsourced entity collection (CrowdDEC): Given an expected distribution w.r.t. an attribute (e.g., region or year), it aims to collect a set of entities via crowdsourcing and minimize the difference of the entity distribution from the expected distribution. Due to the openness of crowdsourcing, the CrowdDEC problem calls for effective crowdsourcing quality control. We propose an adaptive worker selection approach to address this problem. The approach estimates underlying entity distribution of workers on-the-fly based on the collected entities. Then, it adaptively selects the best set of workers that minimizes the difference from the expected distribution. Once workers submit their answers, it adjusts the estimation of workers' underlying distributions for subsequent adaptive worker selections. We prove the hardness of the problem, and develop effective estimation techniques as well as efficient worker selection algorithms to support this approach. We deployed the proposed approach on Amazon Mechanical Turk and the experimental results on two real datasets show that the approach achieves superiority on both effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Population health data, collected worldwide in an effort to monitor mortality and morbidity of mothers and babies, namely, perinatal data, are mandated at a federal level within Australia. The data are used to monitor patterns in midwifery, obstetric and neonatal practice, health outcomes, used for research purposes, funding allocation and education. Accuracy in perinatal data is most often reported via quantitative validation studies of perinatal data collections both internationally and in Australia. These studies report varying levels of accuracy and suggest researchers need to be more aware of the quality of data they use. This article presents findings regarding issues of concern identified by midwives relating to their perceptions of how technology affects the accuracy of perinatal data records. Perinatal data records are perceived to be more complete when completed electronically. However, issues regarding system functionality, the inconsistent use of terminology, lack of data standards and the absence of clear, written records contribute to midwives’ perceptions of the negative influence of technology on the quality of perinatal data. [ABSTRACT FROM AUTHOR]

Conventional data collection methods lack real time information and involve excessive cost of installation and maintenance. A real-time, low cost travel time data collection system can be developed using mobile phones. This project examines the use of mobile phones for travel time prediction of public transit vehicles and develops a dynamic travel time prediction model. Personnel were employed in public transit vehicles with mobile phones and these mobile phones were tracked continuously. Space information of the mobile phones represents the position of the buses and movement pattern of these mobile phones in turn represents the movement pattern of the public buses. The starting and arrival time at sections obtained from the cellular database were used to get the travel time and speed. Results obtained were statistically significant and it shows that use of mobile phone for travel time data collection is a low cost data collection technique for Indian cities. [ABSTRACT FROM AUTHOR]

Objective: The National Children's Study is a long-term epidemiologic study of 100,000 children from 105 locations across the United States. It will require information on a large number of environmental variables to address its core hypotheses. The resources available to collect actual home and personal exposure samples are limited, with most of the home sampling completed on periodic visits and the personal sampling generally limited to biomonitoring. To fill major data gaps, extant data will be required for each study location. The Queens Vanguard Center has examined the extent of those needs and the types of data that are generally and possibly locally available. Data: In this review we identify three levels of data-national, state and county-and local data and information sets (levels 1-3, respectively), each with different degrees of availability and completeness, that can be used as a starting point for the extant data collection in each study location over time. We present an example on the use of this tiered approach, to tailor the data needs for Queens County and to provide general guidance for application to other NCS locations. Conclusions: Preexisting and continually evolving databases are available for use in the NCS to characterize exposure. The three levels of data we identified will be used to test a method for developing exposure indices for segments and homes during the pilot phase of NCS, as outlined in this article. [ABSTRACT FROM AUTHOR]

The following article covers the author's methodology and self research on psychic signals. As a main method of research the author recorded her psychic signals directly into her employment database and began collecting the data. The work environment offered the author multiple, repetitive opportunities to experience and confirm her personal signals in a straight forward way. Accumulated research results allowed for several early conclusions. The author's psychic signals appeared to occur independently of her state of mind, opinion, intuition and previous intraphysical knowledge. The article later covers the author's upcoming plans and efforts to expand hetero research on psychic signals through conducting exercises where individuals watch pre-selected films in order to enhance their ability to recognize their psychic signals. [ABSTRACT FROM AUTHOR]

Song, W.; Xu, M.-M., and Dolma, Y.-C., 2019. Design and implementation of beach sports big data analysis system based on computer technology. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 327–331. Coconut Creek (Florida), ISSN 0749-0208. Applying computer technology and data mining technology in sports field plays an important role in improving the training effect and competition level of athletes. This paper focuses on the design and implementation of the beach volleyball big data analysis system based on computer technology. Using computer as the data collection and analysis platform, it adopts the sorting prediction algorithm and the Markov-based data mining algorithm to predict the cooperation success rate in the beach volleyball match and to search for key action transfer processes. The paper designs and implements a beach volleyball big data analysis system based on computer technology, and experimental results have verified the effectiveness of the data mining algorithm in beach volleyball matches. This study provides a scientific basis for coaches to formulate reasonable beach volleyball training programs and tactical decisions, which is of certain practical significance. [ABSTRACT FROM AUTHOR]

A commentary is presented on a paper published within the journal's issue about the COLLECT database for research in obstetrics. The author believes that the COLLECT database will contribute to the goal of the Global Pregnancy Collaboration in facilitating collaboration and data sharing by standardising data collection. The importance of standardisation of data collection is discussed, along with the key issues in clinical research in obstetrics.

The author reflects on the promotion of data access and how to make it sustainable. The author says that a discussion regarding incentives to an effective ideas market is a must rather than restricting the discussion in open data deposition. The author suggests the construction of an open data commons filled with datasets which can be re-used by a larger community. The author also mentions linking the author and contributor roles to data accession as an incentive significant to data access.