Citizen scientists have the potential to play a crucial role in the study of rapidly changing lady beetle (Coccinellidae) populations. We used data derived from three coccinellid-focused ...citizen-science programs to examine the costs and benefits of data collection from direct citizen-science (data used without verification) and verified citizen-science (observations verified by trained experts) programs. Data collated through direct citizen science overestimated species richness and diversity values in comparison to verified data, thereby influencing interpretation. The use of citizen scientists to collect data also influenced research costs; our analysis shows that verified citizen science was more cost effective than traditional science (in terms of data gathered per dollar). The ability to collect a greater number of samples through direct citizen science may compensate for reduced accuracy, depending on the type of data collected and the type(s) and extent of errors committed by volunteers.
Summary Background Neonatal interventions are largely focused on reduction of mortality and progression towards Millennium Development Goal 4 (child survival). However, little is known about the ...global burden of long-term consequences of intrauterine and neonatal insults. We did a systematic review to estimate risks of long-term neurocognitive and other sequelae after intrauterine and neonatal insults, especially in low-income and middle-income countries. Methods We searched Medline, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, and Embase for studies published between Jan 1, 1966, and June 30, 2011, that reported neurodevelopmental sequelae after preterm or neonatal insult. For unpublished studies and grey literature, we searched Dissertation Abstracts International and the WHO library. We reviewed publications that had data for long-term outcome after defined neonatal insults. We summarised the results with medians and IQRs, and calculated the risk of at least one sequela after insult. Findings Of 28 212 studies identified by our search, 153 studies were suitable for inclusion, documenting 22 161 survivors of intrauterine or neonatal insults. The overall median risk of at least one sequela in any domain was 39·4% (IQR 20·0–54·8), with a risk of at least one severe impairment in any insult domain of 18·5% (7·7–33·3), of at least one moderate impairment of 5·0% (0·0–13·3%), and of at least one mild impairment of 10·0% (1·4–17·9%). The pooled risk estimate of at least one sequela (weighted mean) associated with one or more of the insults studied (excluding HIV) was 37·0% (95% CI 27·0–48·0%) and this risk was not significantly affected by region, duration of the follow-up, study design, or period of data collection. The most common sequelae were learning difficulties, cognition, or developmental delay (n=4032; 59%); cerebral palsy (n=1472; 21%); hearing impairment (n=1340; 20%); and visual impairment (n=1228; 18%). Only 40 (26%) studies included data for multidomain impairments. These studies included 2815 individuals, of whom 1048 (37%) had impairments, with 334 (32%) having multiple impairments. Interpretation Intrauterine and neonatal insults have a high risk of causing substantial long-term neurological morbidity. Comparable cohort studies in resource-poor regions should be done to properly assess the burden of these conditions, and long-term outcomes, such as chronic disease, and to inform policy and programme investments. Funding The Bill & Melinda Gates Foundation, Saving Newborn Lives, and the Wellcome Trust.
The TENDL library is now established as one of the major nuclear data libraries in the world, striving for completeness and quality of nuclear data files for all isotopes, evaluation methods, ...processing and applied performance. To reach this status, some basic principles have been applied which sets it apart from other libraries: reproducible dedicated evaluations when differential data are available, through determination of nuclear models implemented in TALYS and their parameters, completeness (with or without experimental data), format and processing standardization, automation of production and reproducibility. In this paper, we will outline how such an approach has become a reality, and recall some of the past successes since the first TENDL release in 2008. Next, we will demonstrate the performance of the latest TENDL releases for different application fields, as well as new approaches for uncertainty quantification based on Bayesian inference methods and possible differential and integral adjustments. Also, current limitations of the library performances due to modelling and needs for new and more precise experimental data will be outlined.
Summary
The Common Data Element (CDE) Project was initiated in 2006 by the National Institute of Neurological Disorders and Stroke (NINDS) to develop standards for performing funded ...neuroscience‐related clinical research. CDEs are intended to standardize aspects of data collection; decrease study start‐up time; and provide more complete, comprehensive, and equivalent data across studies within a particular disease area. Therefore, CDEs will simplify data sharing and data aggregation across NINDS‐funded clinical research, and where appropriate, facilitate the development of evidenced‐based guidelines and recommendations. Epilepsy‐specific CDEs were established in nine content areas: (1) Antiepileptic Drugs (AEDs) and Other Antiepileptic Therapies (AETs), (2) Comorbidities, (3) Electrophysiology, (4) Imaging, (5) Neurological Exam, (6) Neuropsychology, (7) Quality of Life, (8) Seizures and Syndromes, and (9) Surgery and Pathology. CDEs were developed as a dynamic resource that will accommodate recommendations based on investigator use, new technologies, and research findings documenting emerging critical disease characteristics. The epilepsy‐specific CDE initiative can be viewed as part of the larger international movement toward “harmonization” of clinical disease characterization and outcome assessment designed to promote communication and research efforts in epilepsy. It will also provide valuable guidance for CDE improvement during further development, refinement, and implementation. This article describes the NINDS CDE Initiative, the process used in developing Epilepsy CDEs, and the benefits of CDEs for the clinical investigator and NINDS.
To describe the realities of conducting a cross‐jurisdictional data linkage project involving state and Australian Government‐based data collections to inform future national data linkage programs of ...work.
We outline the processes involved in conducting a Proof of Concept data linkage project including the implementation of national data integration principles, data custodian and ethical approval requirements, and establishment of data flows.
The approval process involved nine approval and regulatory bodies and took more than two years. Data will be linked across 12 datasets involving three data linkage centres. A framework was established to allow data to flow between these centres while maintaining the separation principle that serves to protect the privacy of the individual.
This will be the first project to link child immunisation records from an Australian Government dataset to other administrative health datasets for a population cohort covering 2 million births in two Australian states.
Although the project experienced some delays, positive outcomes were realised, primarily the development of strong collaborations across key stakeholder groups including community engagement. We have identified several recommendations and enhancements to this now established framework to further streamline the process for data linkage studies involving Australian Government data.
Recently, rapid deployment on the fifth-generation (5G) networks has brought great opportunities for enabling data-intensive applications and brings an extending expectation on the developments of ...6G. A basic requirement to develop 6G networks is to reach data with low latency, low cost, and high coverage in smart Internet of Things (IoT). Therefore, this article proposes a novel machine learning-based approach to collect data from multiple sensor devices by cooperation between vehicle and unmanned aerial vehicle (UAV) in IoT. First, a genetic algorithm is utilized to select vehicular collectors to collect massive data from sensor devices, which aims to maximize coverage ratio and to minimize employment cost. Second, we design a novel deep reinforcement learning (DRL)-based route policy to plan collection routes of UAVs with constrain energy, which simplifies the network model, accelerates training speeds, and realizes dynamic planning of flight paths. The optimal collection route of a UAV is a series of outputs based on the proposed DRL-based route policy. Finally, our extensive experiments demonstrate that the proposed scheme can comprehensively improve the coverage ratio of massive data collections and reduce collection costs in smart IoT for the future 6G networks.
Highlights ► Standard safety data collection methods for pIMDs in clinical trials are proposed. ► pIMD lists and disease-specific standard questionnaires will enhance data collection. ► The ...theoretical risk period is at least 6 months, up to 1 year after the last dose. ► Baseline biomarker measurement could eventually provide valuable information. ► Standard case definitions are useful tools for establishing diagnostic certainty.
In this paper, we present an unobtrusive cuffless blood pressure (BP) monitoring system based on pulse arrival time (PAT) for facilitating long-term home BP monitoring. The proposed system consists ...of an electrocardiograph (ECG), a photoplethysmograph (PPG), and a control circuit with a Bluetooth module, all of which are mounted on a common armchair to measure ECG and PPG signals from users while sitting on the armchair in order to calculate continuous PAT. Considering the good linear correlation of systolic BP (SBP) and the nonlinear correlation of diastolic BP (DBP) with PAT, a new BP estimation method was proposed. Ten subjects underwent BP monitoring experiments involving stationary sitting on a chair, lying on a bed, and pedaling using an ergometer in order to assess the accuracy of the estimated BP. A cuff-type BP monitor was used as reference in the experiments. Results showed that the mean difference of the estimated SBP and DBP was within 0.2 ± 5.8 mmHg (p <; 0.00001) and 0.4 ± 5.7 mmHg (p <; 0.00001), respectively, and the mean absolute difference of the estimated SBP and DBP were 4.4 and 4.6 mmHg, respectively, compared to references. Additionally, five subjects participated in data collections consisting of sitting on a chair twice a day for one month. Compared to the reference, the difference did not obviously increase along with time, even though individualized calibration was executed only once at the beginning. These results suggest that the proposed system has quite the potential for long-term home BP monitoring.
This study aimed to validate trial patient eligibility screening and baseline data collection using text-mining in electronic healthcare records (EHRs), comparing the results to those of an ...international trial.
In three medical centers with different EHR vendors, EHR-based text-mining was used to automatically screen patients for trial eligibility and extract baseline data on nineteen characteristics. First, the yield of screening with automated EHR text-mining search was compared with manual screening by research personnel. Second, the accuracy of extracted baseline data by EHR text mining was compared to manual data entry by research personnel.
Of the 92,466 patients visiting the out-patient cardiology departments, 568 (0.6%) were enrolled in the trial during its recruitment period using manual screening methods. Automated EHR data screening of all patients showed that the number of patients needed to screen could be reduced by 73,863 (79.9%). The remaining 18,603 (20.1%) contained 458 of the actual participants (82.4% of participants).
In trial participants, automated EHR text-mining missed a median of 2.8% (Interquartile range IQR across all variables 0.4–8.5%) of all data points compared to manually collected data. The overall accuracy of automatically extracted data was 88.0% (IQR 84.7–92.8%).
Automatically extracting data from EHRs using text-mining can be used to identify trial participants and to collect baseline information.
Purpose
To assess whether partitioning the elastance of the respiratory system (
E
RS
) between lung (
E
L
) and chest wall (
E
CW
) elastance in order to target values of end-inspiratory ...transpulmonary pressure (PPLAT
L
) close to its upper physiological limit (25 cmH
2
O) may optimize oxygenation allowing conventional treatment in patients with influenza A (H1N1)-associated ARDS referred for extracorporeal membrane oxygenation (ECMO).
Methods
Prospective data collection of patients with influenza A (H1N1)-associated ARDS referred for ECMO (October 2009–January 2010). Esophageal pressure was used to (a) partition respiratory mechanics between lung and chest wall, (b) titrate positive end-expiratory pressure (PEEP) to target the upper physiological limit of PPLAT
L
(25 cmH
2
O).
Results
Fourteen patients were referred for ECMO. In seven patients PPLAT
L
was 27.2 ± 1.2 cmH
2
O; all these patients underwent ECMO. In the other seven patients, PPLAT
L
was 16.6 ± 2.9 cmH
2
O. Raising PEEP (from 17.9 ± 1.2 to 22.3 ± 1.4 cmH
2
O,
P
= 0.0001) to approach the upper physiological limit of transpulmonary pressure (PPLAT
L
= 25.3 ± 1.7 cm H
2
O) improved oxygenation index (from 37.4 ± 3.7 to 16.5 ± 1.4,
P
= 0.0001) allowing patients to be treated with conventional ventilation.
Conclusions
Abnormalities of chest wall mechanics may be present in some patients with influenza A (H1N1)-associated ARDS. These abnormalities may not be inferred from measurements of end-inspiratory plateau pressure of the respiratory system (PPLAT
RS
). In these patients, titrating PEEP to PPLAT
RS
may overestimate the incidence of hypoxemia refractory to conventional ventilation leading to inappropriate use of ECMO.
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