Digital Data Collection System Research Articles

Pathways from livestock to improved human nutrition: lessons learned in East Africa

AbstractThe Livestock CGIAR (Consultative Group on International Agricultural Research) Research Program (Livestock CRP) generated evidence on livestock-to-nutrition pathways through the implementation of nutrition-related livestock programs and research. In this analysis, we compiled lessons learned from Livestock CRP projects and identified recommendations for nutrition-sensitive livestock programming and research in the context of the literature and through the development of an updated livestock-to-nutrition pathways framework. The updated framework shows the interconnected nature of the three main pathways—own-consumption, income, and women’s empowerment—along with other pathways and includes contextual factors, which were lacking in previous frameworks. Eight Livestock CRP projects were reviewed, including five integrated livestock and human nutrition projects, two studies on drivers of food choice, and one study to develop and test a tool to measure nutrition outcomes among pastoralists. Key lessons learned were that women’s empowerment in livestock-to-nutrition pathways is important, but challenging to measure; engaging male partners improves nutrition in livestock-keeping households; nutrition-sensitive livestock programs and researchers should articulate and measure livestock-to-nutrition pathways they are addressing; livestock keeping does not guarantee access to animal source foods; context and livelihoods are not static and program design should be adapted accordingly; and digital data collection systems can provide accurate and timely nutrition information. Key recommendations include developing tools to fill measurement gaps; creating shorter versions of validated tools for ease of use; using complexity-aware evaluation methods to capture the interconnected nature of livestock-to-nutrition pathways and shifting livelihoods; and conducting pathways analyses to better understand linkages in the framework and further refine it.

Factors Affecting the Transition from Paper to Digital Data Collection for Mobile Tuberculosis Active Case Finding in Low Internet Access Settings in Pakistan.

Between September 2020 and March 2021, Mercy Corps piloted hybrid digital (CAPI) and paper-based (PAPI) data collection as part of its tuberculosis (TB) active case finding strategy. Data were collected using CAPI and PAPI at 140 TB chest camps in low Internet access areas of Punjab and Khyber Pakhtunkhwa provinces in Pakistan. PAPI data collection was performed primarily during the camp and entered using a tailor-performed CAPI tool after camps. To assess the feasibility of this hybrid approach, quality of digital records were measured against the paper “gold standard”, and user acceptance was evaluated through focus group discussions. Completeness of digital data varied by indicator, van screening team, and month of implementation: chest camp attendees and pulmonary TB cases showed the highest CAPI/PAPI completeness ratios (1.01 and 0.96 respectively), and among them, all forms of TB diagnosis and treatment initiation were lowest (0.63 and 0.64 respectively). Vans entering CAPI data with high levels of completeness generally did so for all indicators, and significant differences in mean indicator completeness rates between PAPI and CAPI were observed between vans. User feedback suggested that although the CAPI tool required practice to gain proficiency, the technology was appreciated and will be better perceived once double entry in CAPI and PAPI can transition to CAPI only. CAPI data collection enables data to be entered in a more timely fashion in low-Internet-access settings, which will enable more rapid, evidence-based program steering. The current system in which double data entry is conducted to ensure data quality is an added burden for staff with many activities. Transitioning to a fully digital data collection system for TB case finding in low-Internet-access settings requires substantial investments in M&E support, shifts in data reporting accountability, and technology to link records of patients who pass through separate data collection stages during chest camp events.

Infodemic Management Using Digital Information and Knowledge Cocreation to Address COVID-19 Vaccine Hesitancy: Case Study From Ghana.

BackgroundInfodemic management is an integral part of pandemic management. Ghana Health Services (GHS) together with the UNICEF (United Nations International Children's Emergency Fund) Country Office have developed a systematic process that effectively identifies, analyzes, and responds to COVID-19 and vaccine-related misinformation in Ghana.ObjectiveThis paper describes an infodemic management system workflow based on digital data collection, qualitative methodology, and human-centered systems to support the COVID-19 vaccine rollout in Ghana with examples of system implementation.MethodsThe infodemic management system was developed by the Health Promotion Division of the GHS and the UNICEF Country Office. It uses Talkwalker, a social listening software platform, to collect misinformation on the web. The methodology relies on qualitative data analysis and interpretation as well as knowledge cocreation to verify the findings.ResultsA multi-sectoral National Misinformation Task Force was established to implement and oversee the misinformation management system. Two members of the task force were responsible for carrying out the analysis. They used Talkwalker to find posts that include the keywords related to COVID-19 vaccine–related discussions. They then assessed the significance of the posts on the basis of the engagement rate and potential reach of the posts, negative sentiments, and contextual factors. The process continues by identifying misinformation within the posts, rating the risk of identified misinformation posts, and developing proposed responses to address them. The results of the analysis are shared weekly with the Misinformation Task Force for their review and verification to ensure that the risk assessment and responses are feasible, practical, and acceptable in the context of Ghana.ConclusionsThe paper describes an infodemic management system workflow in Ghana based on qualitative data synthesis that can be used to manage real-time infodemic responses.

Development of algorithm for implementation of technical condition-based repair program for generating equipment at energy enterprises

The use of modern digital technologies during the industrial revolution enables to revise a number of approaches to the organization of technological processes, in particular when introducing approaches to the implementation of repair programs of energy enterprises. Through the example of the network planning and control system, the use of the overhaul activity schedule for generating equipment is considered, taking into account the logging of asbuilt documentation in a digital system, which is a software and technical complex made up of a centralized data storage system and a decentralized registry. The improvement of equipment, the development of diagnostic tools and methods directly affects the maintenance and repair system. In the maintenance system under development, it is planned to make a transition from statistical empirical assessments of the technical condition of equipment to objective ones based on automated technical diagnostics systems. On the basis of an algorithm for implementing a technical condition-based equipment repair program for energy enterprises, the authors proposed an algorithm for conducting technical supervision and recording the stages of work performed in a distributed register, based on the capabilities of modern digital data collection and processing systems. Obtaining parameter values for further use in the operation of the proposed algorithm is carried out on the basis of the capabilities existing at energy facilities of information-measuring and control systems. The use of the network planning and management system in the form of a network schedule and the algorithm proposed by the authors for conducting technical supervision and recording the stages of work performed during repair activities will make it possible to objectively determine the amount of labor resources necessary to perform the planned scope of work within the specified period, identify critical works delaying the completion of repair, actively manage repair by analyzing the progress of repair work and making reasonable organizational and technical decisions that ensure the performance of work within the planned time frame and at the lowest possible costs.

Industry 4.0 driven statistical analysis of investment casting process demonstrates the value of digitalisation

The purpose of this research is to perform statistical data analysis of currently manually collected data in an area of the industrial manufacturing organisation employed in this study that is not digitalised to show the value that can be achieved through digitalisation. The insights gained through analysis of the data can be used to drive decision making in relation to the optimisation of input parameters to minimise the level of defective parts. The parts under investigation in this study were ceramic shells used in the manufacturing process of orthopaedic metal implants. The ceramic shell is a crucial element in the investment casting process because molten metal is poured into the ceramic shell to form the shape of the metal orthopaedic implant. Hence, by minimising the number of defective ceramic shells, there are fewer defective metal implants produced, resulting in cost savings and increased efficiency of the manufacturing process. A number of scientific questions to establish the relationship between the quantity of scrapped products and the level of the silica component in the ceramic slurry were defined and a series of independent t-tests were conducted to address these questions. The results from the t-tests showed the statistically optimal percentage of silica in the binder of the ceramic slurry to minimise the rate of a particular scrap type caused by thin or weak areas of the shell. These results demonstrate the value of analysing digital data relating to the manufacturing process to understand relationships between parameters in the manufacturing process and effectively root-cause scrap outputs. The results from the analysis gave rise to the implementation of a digitalised data collection system that allows continuous monitoring of the components in the ceramic slurry to ensure they are in the optimal specified range. Hence, the quality and yield rate of the orthopaedic implants are maintained at a high level. The digital data collection system also acts as a resource containing historical data for further potential scrap root-cause analysis.

Development of an Innovative Digital Data Collection System for Routine Mental Health Care Delivery in Rural Haiti.

Effective digital health management information systems (HMIS) support health data validity, which enables health care teams to make programmatic decisions and country-level decision making in support of international development targets. In 2015, mental health was included within the Sustainable Development Goals, yet there are few applications of HMIS of any type in the practice of mental health care in resource-limited settings. Zanmi Lasante (ZL), one of the largest providers of mental health care in Haiti, developed a digital data collection system for mental health across 11 public rural health facilities. We describe the development, implementation, and evaluation of the digital system for mental health data collection at ZL. To evaluate system reliability, we assessed the number of missing monthly reports. To evaluate data validity, we calculated concordance between the digital system and paper charts at 2 facilities. To evaluate the system's ability to inform decision making, we specified and then calculated 4 priority indicators. The digital system was missing 5 of 143 monthly reports across all facilities and had 74.3% (55/74) and 98% (49/50) concordance with paper charts. It was possible to calculate all 4 indicators, which led to programmatic changes in 2 cases. In response to implementation challenges, it was necessary to use strategies to increase provider buy-in and ultimately to introduce dedicated data clerks to keep pace with data collection and protect time for clinical work. While demonstrating the potential of collecting mental health data digitally in a low-resource rural setting, we found that it was necessary to consider the ongoing roles of paper records alongside digital data collection. We also identified the challenge of balancing clinical and data collection responsibilities among a limited staff. Ongoing work is needed to develop truly sustainable and scalable models for mental health data collection in resource-limited settings.

Improving Psychiatric Care Through Integrated Digital Technologies.

This manuscript provides an overview of our efforts to implement an integrated electronic monitoring and feedback platform to increase patient engagement, improve care delivery and outcome of treatment, and alert care teams to deterioration in functioning. Patients First utilizes CareSense, a digital care navigation and data collection system, to integrate traditional patient-reported outcomes monitoring with novel biological monitoring between visits to provide patients and caregivers with real-time feedback on changes in symptoms such as stress, anxiety, and depression. The next stage of project development incorporates digital therapeutics (computerized therapeutic interventions) for patients, and video resources for primary care physicians and nurse practitioners who serve as the de facto front line for psychiatric care. Integration of the patient-reported outcomes monitoring with continuous biological monitoring, and digital supports is a novel application of existing technologies. Video resources pushed to care providers whose patients trigger a symptom severity alert is, to our knowledge, an industry first.

Evaluation of Self-Care Activities and Quality of Life in Patients With Type 2 Diabetes Mellitus Treated With Metformin Using the 2D Matrix Code of Outer Drug Packages as Patient Identifier: Protocol for the DePRO Proof-of-Concept Observational Study.

BackgroundDiabetes mellitus (DM) is one of the most common noncommunicable diseases. DM has a substantial negative impact on patients’ quality of life, which is measured using a variety of diabetes-specific measures covering multiple aspects of patients’ psychological state, behavior, and treatment satisfaction. A fully digital data collection system, including patient identification, would represent a substantial advance in how these patient-reported outcome (PRO) data are measured. Within the European Union, one way to identify patients without the involvement of health care professionals is to use the unique 2D matrix codes on the packaging of prescription medication—for example, metformin, the recommended initial treatment for patients with type 2 DM (T2DM).ObjectiveIn the DePRO study we aim to (1) describe the self-care activities of patients with T2DM using metformin-containing medication; (2) describe the self-reported health status (eg, presence of diabetes complications and quality of life) of these patients; (3) describe associations between self-care activities and demographics and disease characteristics; and (4) assess the usability of the my ePRO app.MethodsDePRO is an observational, multicenter, cross-sectional, digital, patient-driven study conducted in Germany. Patients with a prescription for a metformin-containing medication will be given a postcard by their pharmacist, which will include a download link for the my ePRO app. In total, 12 diabetes-focused pharmacies, selected to represent urban and rural areas, will be recruited. Participants will use their own mobile device (bring your own device) to download the my ePRO app and access the DePRO study, for which they can register using the 2D matrix code on their medication. An electronic informed consent form will be displayed to the patients and only after giving consent will patients be able to complete the study questionnaires. The PRO instruments used in the study are the Summary of Diabetes Self-Care Activities Scale, the Diabetes Treatment Satisfaction Questionnaire, and the 5 level, 5-dimension EuroQol Questionnaire. Patients will also be asked to complete a questionnaire with items addressing demographics, patient characteristics, disease history, complications, and concomitant medications. Data will be transferred to the study database by the app upon completion of each questionnaire. Statistical analyses of primary and secondary endpoints will be exploratory and descriptive.ResultsEnrollment began in June 2020. The estimated study completion date is December 31, 2020, and the planned sample size is 300 patients.ConclusionsThe DePRO study uses completely digital data collection, including authentication of eligible patients and completion of the study questionnaires. Therefore, the design of the DePRO study represents a substantial advance in the evaluation of the digital capturing of PRO data.Trial RegistrationClinicalTrials.gov NCT04383041; https://clinicaltrials.gov/ct2/show/NCT04383041International Registered Report Identifier (IRRID)PRR1-10.2196/21727

Immediate impact of COVID-19 across tropical small-scale fishing communities

The volume and value of fish catches by Indonesia's small-scale fisheries have declined significantly since national government restrictions on travel and social distancing were imposed in response to the COVID-19 pandemic. Using a digital data collection system (OurFish), that records purchases by fish traders from small-scale fishers, data was collected across 82 coastal communities in Southeast Sulawesi. We found that the number of active fishers and traders declined by more than 90% after the onset of the pandemic and the average weight of catch per fishing trip increased across fishers. Although the average price per kilogram of fish declined after the pandemic began, fishers that were able to maintain fishing had on average higher catches and therefore daily catch value was maintained. High value fisheries that usually enter export supply chains were more negatively impacted compared with lower value species that are commonly sold to local markets. We interviewed 185 small scale fishers and fish traders across 20 of the 82 communities in Southeast Sulawesi province, recording the perceived level of impact on local fisheries and the fish trade, causes of this impact and proposed coping strategies. Over 50% of both fishers and fish traders believed low demand for fish from traders and a decline in the price received for fish were disrupting their lives. Approximately 75% of both male and female fishers are coping by continuing to fish, highlighting that there were few alternative livelihoods available at the time of the interviews. Our results provide key insights into the vulnerability of small-scale fishing communities to impacts of the COVID-19 pandemic.

Gift-exchange Game Theory for Gamification on Digital Data Collection Systems

Gamification is widely used to increase user motivation by applying game elements to things that are not game-based. For example, in a data collection system. Gamification is used to increase the motivation of users to want to get involved. The elements of the game that are often used are rewards, badges, and leaderboards. But some implementations have not been able to ensure increased user motivation. Gamification applied needs to consider the use of game theory. Game theory is used to determine the right gamification model for digital data collection. This paper discusses the application of gift-exchange-games (GEG) in the gamification of digital data collection systems. GEG is used to model player interactions in the gamification system. GEG implementation of Gamification can improve user involvement in the system. This theoretical model can later be used for a more efficient data collection system development platform.
 Keywords: gamification, game theory, data collection, gift-exchange-game, geg

P10 CAPTURE JIA: paper data collection feasibility and acceptability pilot

Abstract Background There is a challenging lack of evidence to inform best practice in the routine clinical care of juvenile idiopathic arthritis (JIA). Wide inter-centre variation in the definition and documentation of clinical data items is a major barrier to improvement. In response, we have developed a consensus agreed standardised core dataset called CAPTURE-JIA (n = 62 data items and a ‘data dictionary’ including agreed definitions of terms) designed to support routine collection of high-quality clinical data. The feasibility and acceptability of CAPTURE-JIA in clinical practice is not yet known and was the focus of this pilot study. Methods A purposeful sample of six paediatric rheumatology centres across England was invited to collect the CAPTURE-JIA dataset using paper collection forms (n = 20 patients/centre). The dataset was analysed for missing data. Six focus groups (n = 3-10) explored clinicians’ views on acceptability and feasibility. Results One hundred and twenty-one patients were recruited over three months. The completeness of the dataset was similar across centres, with minor variations. The majority of data items (eg demographics, dates, ILAR type and examination) were >80% completed. However, 14/62 data items received >40% missing data. (Table 1) Further descriptive analyses highlighted incorrect completion of paper forms. Three themes emerged from the focus groups: problematic data items (missing from >10% forms at > 1 centre), format of clinician data forms and the role of digital data collection. Suggested solutions included minor changes to data item definitions and formatting. There were no refinements to the data items. Development of a digital data collection system was identified by all as essential. Due to a lack of clear consensus, the original CAPTURE forms included a number of ways to record joint count data. This proved confusing and a unanimous decision was taken to collect joint count data on all 83 joints in a tabular format. P10 Table 1: CAPTURE JIA data items with >40% missing data Data item % forms with data item missing (if item required) Relevant co-morbidities? 60 Macrophage activation syndrome? 100 Has the ILAR subtype changed? 50 Morning stiffness lasting >15 minutes? 42 History of any form of uveitis? 52 Date started uveitis mediation? 50 Strength of uveitis medication? 83 Counselled prior to new DMARD / biologic? 56 Enrolled in BECS/BCRD if new DMARD / biologic? 48 Joint count (homunculus or table format) 48 Physician assessment of systemic disease activity (VAS) 75 ESR 74 CRP 92 Plasma viscosity 100 Conclusion Paper collection of the CAPTURE-JIA data items is feasible and acceptable in the routine clinical setting, but unlikely to be sustainable in the longer term if collected in duplicate with medical notes. A digital tool in the clinical domain, ideally interlocking with local systems, would offer many advantages, including more complete and time-efficient data collection. Conflicts of Interest The authors declare no conflicts of interest.

Digital data collection in paleoanthropology.

Understanding patterns of human evolution across space and time requires synthesizing data collected by independent research teams, and this effort is part of a larger trend to develop cyber infrastructure and e-science initiatives. At present, paleoanthropology cannot easily answer basic questions about the total number of fossils and artifacts that have been discovered, or exactly how those items were collected. In this paper, we examine the methodological challenges to data integration, with the hope that mitigating the technical obstacles will further promote data sharing. At a minimum, data integration efforts must document what data exist and how the data were collected (discovery), after which we can begin standardizing data collection practices with the aim of achieving combined analyses (synthesis). This paper outlines a digital data collection system for paleoanthropology. We review the relevant data management principles for a general audience and supplement this with technical details drawn from over 15 years of paleontological and archeological field experience in Africa and Europe. The system outlined here emphasizes free open-source software (FOSS) solutions that work on multiple computer platforms; it builds on recent advances in open-source geospatial software and mobile computing.

Using digital data collection tools to improve overall cost-efficiency and provide timely analysis for decision making during invasive species eradication campaigns

Context Worldwide, invasive vertebrate eradication campaigns are increasing in scale and complexity, requiring improved decision making tools to achieve and validate success. For managers of these campaigns, gaining access to timely summaries of field data can increase cost-efficiency and the likelihood of success, particularly for successive control-event style eradications. Conventional data collection techniques can be time intensive and burdensome to process. Recent advances in digital tools can reduce the time required to collect and process field information. Through timely analysis, efficiently collected data can inform decision making for managers both tactically, such as where to prioritise search effort, and strategically, such as when to transition from the eradication phase to confirmation monitoring. Aims We highlighted the advantages of using digital data collection tools, particularly the potential for reduced project costs through a decrease in effort and the ability to increase eradication efficiency by enabling explicit data-informed decision making. Methods We designed and utilised digital data collection tools, relational databases and a suite of analyses during two different eradication campaigns to inform management decisions: a feral cat eradication utilising trapping, and a rodent eradication using bait stations. Key results By using digital data collection during a 2-year long cat eradication, we experienced an 89% reduction in data collection effort and an estimated USD42 845 reduction in total costs compared with conventional paper methods. During a 2-month rodent bait station eradication, we experienced an 84% reduction in data collection effort and an estimated USD4525 increase in total costs. Conclusions Despite high initial capital costs, digital data collection systems provide increasing economics as the duration and scale of the campaign increases. Initial investments can be recouped by reusing equipment and software on subsequent projects, making digital data collection more cost-effective for programs contemplating multiple eradications. Implications With proper pre-planning, digital data collection systems can be integrated with quantitative models that generate timely forecasts of the effort required to remove all target animals and estimate the probability that eradication has been achieved to a desired level of confidence, thus improving decision making power and further reducing total project costs.

A SYSTEM FOR INTEGRATED SCAT DATA COLLECTION AND MANAGEMENT: ESCAT, SCATDB, AND PHOTOLOGGER

ABSTRACT During response, oiled shorelines must be surveyed to guide cleanup operations. The Shoreline Cleanup and Assessment Technique (SCAT) is a standard method for conducting these surveys. Multiple field teams often conduct SCAT. SCAT surveys quickly produce a large and complex dataset comprised of SCAT observations, GPS positions, and photographs. In order to guide response decision-making, SCAT field data must be processed and analyzed in a timely manner. Until recently, SCAT and GPS data were collected on standardized paper worksheets, transcribed to electronic form, and then incorporated into maps and other decision-making products. Photographs were not tightly managed alongside SCAT data. Today, with the emergence of robust handheld computing technology, the deficiencies inherent in paper data collection are no longer necessary or acceptable. Paper data collection can be slow, error prone, and lacking quality control and integration with GPS technology. Digital options are available to address these challenges. To improve methods, the Office of Response and Restoration is developing a digital field data collection and management system for SCAT data and photographs composed of: (1) specialized software for efficient SCAT data collection with GPS enabled handheld devices, (2) a relational SCAT database which expedites the synthesis of field data into decision making products, promotes community standards, and supports standard paper worksheet and digital data collection methods, and (3) an image database which allows for the processing, documenting, and sharing of large quantities of digital photographs. For this project, commonly used, readily available, and Open Source computing resources were chosen so that end-users could easily test, adopt, and improve this system.

40 YEARS AND 3-PLUS MILLION GALLONS LATER A CASE STUDY ON THE HARTFORD, ILLINOIS AREA GROUNDWATER PLUME SITE

ABSTRACT An estimated 3.4 million gallons of leaded gasoline, diesel fuel and other refined and unrefined products from buried pipeline systems and several refineries have affected a residential area of 200 plus homes and businesses. U.S. EPA tasked a consortium of energy companies to develop a rapid response program to quickly eliminate intermittent vapor intrusion problems and to ultimately remove the petroleum products plume. The project involved coordinating efforts between several energy companies, the U.S. EPA, the Illinois EPA, the Illinois Department of Public Health and ATSDR. Some of the innovative technologies utilized include the laser fluorescence Rapid Optical Screening Tool (ROST™), soil vapor extraction (SVE), oil skimming and bio slurping. Managing data decision uncertainties, through the compilation of historical data into a site conceptual model was used to develop a dynamic site cleanup strategy and managing rapidly evolving field data by GIS digital mapping and data collection systems.

Sensitivity and accuracy of CBED pattern matching

When establishing the feasibility of matching experimental and theoretical convergent-beam electron diffraction (CBED) patterns to recover structure-factor information it is important to investigate the accuracy of the results obtained and the effects of random and systematic errors. The effects of counting noise in a digital data-collection system are studied, together with various sources of systematic error. The sensitivity of parts of the pattern to specific structure-factor parameters is analysed via the calculation of analytic gradients of the intensity with respect to those parameters. All calculations are based on diffraction at the [110] axis of GaP, using simulated CBED patterns as idealesed “experimental” data. The results indicate that, provided care is taken to minimise the effects of systematic errors, low-order structure factors may be extracted from experimental data with an accuracy approaching 0.1%.

Scattering of ultrasonic pulses by a turbulent water jet

Experimental results are presented for the scattering of an acoustic pulse from a region of turbulent flow. The investigation was performed in the 7‐m‐deep section of the USNA Hydrodynamics TOW Tank facility. Turbulent flow is produced by a submerged nozzle of 4.8cm‐diam and 100‐cm/s exit velocity. Flow is directed perpendicular to the water's surface. The 1.9‐MHz acoustic pulse is generated from a 2.54‐cm‐diam ultrasonic transducer located 18‐nozzle diameters downstream from the jet exit and at a perpendicular distance of 84 cm from the jet axis. An identical transducer receiver located at the depth of the sender is positioned 217 cm from the jet axis. Angular scattering measurements are made in a plane parallel with the water's surface. Scattering results are presented for the temporal broadening, the spectral broadening, and the energy distribution of the incident pulse using a digital data collection and analysis system. Results are compared with theoretical predictions. [Work supported by NRL (Physical Acoustics Branch) and USNA.]

Automatic torque magnetometer for vacuum-to-high-pressure hydrogen environments

An automatic torque magnetometer has been developed for use in high-pressure hydeogen. It will contain pressures ranging from vacuum to 200 atm of hydrogen gas at sample temperatures greater than 400 degrees C. This magnetometer, which uses an optical lever postion sensor and a restoring force technique has an operating range of 2.0x10(3) dyn cm to l.6x10(-4) dyn cm. An accompanying digital data collection system extends the sensitivity to 1x10(-5) dyn cm as well as increasing the data handling capacity of the system. The magnetic properties of thin films in high-temperature and high-pressure hydrogen environments can be studied using this instruments.

Active, modular, digital data-collection system

Active, modular, digital data-collection system

The syndrome of closed-angle glaucoma.

Closed-angle glaucoma is the result of two mechanisms acting either separately or in combination: 1. Pupil block creates a greater pressure in the posterior than in the anterior chamber, pushing the iris on to the cornea. 2. Increased trabecular meshwork outflow in the presence of pupil block creates a lower pressure in the anterior chamber than in the posterior, pulling the iris on to the cornea. Three main groups of eyes manifest closed-angle glaucoma: (i) Mechanism (I) is necessary and sufficient, but (2) precludes the development of angle closure. (ii) Mechanism (I) is necessary but insufficient. Mechanism (2) must also be present. (iii) Mechanism (I) is necessary and sufficient but (I) and (2) may combine to produce an acute attack.