Application of the PRECEDE-PROCEED model in the development of evidence-informed interventions for drowning prevention: a mixed-methods study protocol

Introduction Drowning is a global public health threat, disproportionately impacting low-income and middle-income countries. In the Philippines, it is estimated that more than 5200 people die from drowning per annum. This number is likely to be higher than currently estimated with the inclusion of disaster-related and transportation-related drowning. Drowning is preventable if appropriate preventive interventions are put in place which redress known risk factors. Methods and analysis This study uses the PRECEDE-PROCEED model (PPM), an eight-step health promotion planning and evaluation model for building and improving intervention programmes. This mixed-methods study, which can be used in any location, will be implemented in Los BaÅ os, Laguna, Philippines, identified as an area of concern for drowning. Using the PPM, data on drowning will be collected from death records, community observation, key informant interviews, focus group discussions and community survey. A range of analytical methods will be used to explore drowning data including univariate and χ 2 analyses, analysis of variance, relative risk and calculating rates using population data. The quantitative data and themes drawn from qualitative data will be used to populate the first four phases of the PPM. Following the data collection, the remaining stages of the PPM will be designed and implemented in the barangay (village) with the highest drowning rate. Ethics and dissemination This study has obtained ethical clearance from the University of the Philippines Manila Research Ethics Board (UPMREB 2017-425-01). Study findings will be disseminated through workshops and presentations to the local community as well as through peer-reviewed literature and conference presentations. The PPM has rarely been applied to drowning prevention and it is the aim that the study described in this protocol is expanded across other areas of the Philippines and to other countries with a high drowning burden to inform prevention efforts

"I want to see a drowning-free Philippines": a qualitative study of the current situation, key challenges and future recommendations for drowning prevention in the Philippines

Drowning is described as a public health challenge by the World Health Organization. This challenge faces the Philippines where drowning claims an average of 3276 lives annually (3.50/100,000 population). However, no research comprehensively documents prevention strategies implemented by government and non-government agencies at a national or local level in the Philippines. This study aimed to qualitatively explore the current situation and key challenges of preventing drowning in the Philippines through key informant interviews and make recommendations to guide prevention efforts. Interviews were conducted among government and non-government agencies involved in drowning prevention using purposive sampling. Qualitative data collected were thematically analyzed. Findings indicate government and non-government agencies implement drowning prevention programs or strategies based on the mandate of their institutions. Most commonly cited were activities related to education or information awareness, emergency and disaster preparedness, and swimming skills. It was revealed that each agency was relatively unaware of the drowning prevention programs of other agencies. A multisector approach is needed to develop coordinated and comprehensive programs and activities aimed at preventing drowning. In this way, duplication will be avoided and the minimal resources available will be used effectively to reduce the burden of drowning in the Philippines

Solar fuel photoanodes prepared by inkjet printing of copper vanadates

Widespread deployment of solar fuel generators requires the development of efficient and scalable functional materials, especially for photoelectrocatalysis of the oxygen evolution reaction. Metal oxides comprise the most promising class of photoanode materials, but no known material meets the demanding photoelectrochemical requirements. Copper vanadates have recently been identified as a promising class of photoanode materials with several phases exhibiting an indirect band gap near 2 eV and stable photoelectrocatalysis of the oxygen evolution reaction in a pH 9.2 electrolyte. By employing combinatorial inkjet printing of metal precursors and applying both calcination and rapid thermal processing, we characterize the phase behaviour of the entire CuO–V_2O_5 composition space for different thermal treatments via automated analysis of approximately 100 000 Raman spectra acquired using a novel Raman imaging technique. These results enable the establishment of structure–property relationships for optical absorption and photoelectrochemical properties, revealing that highly active photoelectrocatalysts containing α-Cu_2V_2O_7 or α-CuV_2O_6 can be prepared using scalable solution processing techniques. An additional discovery results from the formation of an off-stoichiometric β-Cu_2V_2O_7 material that exhibits high photoelectroactivity in the presence of a ferri/ferrocyanide redox couple with excellent stability in a pH 13 electrolyte, demonstrating that copper vanadates may be viable photoanodes in strong alkaline electrolytes

Multi-component background learning automates signal detection for spectroscopic data

Automated experimentation has yielded data acquisition rates that supersede human processing capabilities. Artificial Intelligence offers new possibilities for automating data interpretation to generate large, high-quality datasets. Background subtraction is a long-standing challenge, particularly in settings where multiple sources of the background signal coexist, and automatic extraction of signals of interest from measured signals accelerates data interpretation. Herein, we present an unsupervised probabilistic learning approach that analyzes large data collections to identify multiple background sources and establish the probability that any given data point contains a signal of interest. The approach is demonstrated on X-ray diffraction and Raman spectroscopy data and is suitable to any type of data where the signal of interest is a positive addition to the background signals. While the model can incorporate prior knowledge, it does not require knowledge of the signals since the shapes of the background signals, the noise levels, and the signal of interest are simultaneously learned via a probabilistic matrix factorization framework. Automated identification of interpretable signals by unsupervised probabilistic learning avoids the injection of human bias and expedites signal extraction in large datasets, a transformative capability with many applications in the physical sciences and beyond

Philippine birds

9 p. ; 24 cm."Publications on Phillipine birds, 1945 through 1951": p. 7-9

Enabling Solar Fuels Technology With High Throughput Experimentation

The High Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP, http://solarfuelshub.org/) performs accelerated discovery of new earth-abundant photoabsorbers and electrocatalysts. Through collaboration within the DOE solar fuels hub and with the broader research community, the new materials will be utilized in devices that efficiently convert solar energy, water and carbon dioxide into transportation fuels. JCAP-HTE builds high-throughput pipelines for the synthesis, screening and characterization of photoelectrochemical materials. In addition to a summary of these pipelines, we will describe several new screening instruments for high throughput (photo-)electrochemical measurements. These instruments are not only optimized for screening against solar fuels requirements, but also provide new tools for the broader combinatorial materials science community. We will also describe the high throughput discovery, follow-on verification, and device implementation of a new quaternary metal oxide catalyst. This rapid technology development from discovery to device implementation is a hallmark of the multi-faceted JCAP research effort

Preventing child drowning in the Philippines: the need to address the determinants of health

Drowning is a public health issue in the Philippines, with children at significantly increased risk. Determinants of health (DoH) such as education, socio-economic status, ethnicity, and urbanization are factors that impact drowning risk. As drowning is a multisectoral issue, a national drowning prevention plan can drive collaboration with relevant stakeholders. This study reports trends in unintentional child (0–14 years) drowning in the Philippines (incidence, rates, and trends over time for fatal and non-fatal (years lived with a disability (YLDs) and disability adjusted life years (DALYs) from 2008–2017 and conducts an analysis of the Philippines’ Multisector Action Plan (MSAP) on Drowning Prevention. From 2008–2017, 27,928 (95%UI [Uncertainty Interval]: 22,794–33,828) children aged 0–14 years died from drowning (52.7% aged 5–14 years old). Rates of drowning have declined among both age groups, with greater reductions seen among 0–4 year olds (y = −0.3368x + 13.035; R2 = 0.9588). The MSAP has 12 child drowning-specific activities and 20 activities were identified where DoH will need to be considered during development and implementation. The MSAP activities, and work done to prevent drowning more generally, must consider DoH such as education, urbanization, water and sanitation health, and safe water transportation. A national drowning surveillance system and investment in research in the Philippines are recommended

Combinatorial Alloying Improves Bismuth Vanadate Photoanodes via Reduced Monoclinic Distortion

Improving the efficiency of solar-powered oxygen evolution is both critical for development of solar fuels technologies and challenging due to the broad set of properties required of a solar fuels photoanode. Bismuth vanadate, in particular the monoclinic clinobisvanite phase, has received substantial attention and has exhibited the highest radiative efficiency among metal oxides with a band gap in the visible range. Efforts to further improve its photoelectrochemical performance have included alloying one or more metals onto the Bi and/or V sites, with progress on this frontier stymied by the difficulty in computational modelling of substitutional alloys and the high dimensionality of co-alloying composition spaces. Since substitutional alloying concurrently changes multiple materials properties, understanding the underlying cause for performance improvements is also challenging, motivating our application of combinatorial materials science techniques to map photoelectrochemical performance of 948 unique bismuth vanadate alloy compositions comprising 0 to 8% alloys of P, Ca, Mo, Eu, Gd, and W along with a variety of compositions from each pairwise combination of these elements. Upon identification of substantial improvements in the (Mo,Gd) co-alloying space, structural mapping was performed to reveal a remarkable correlation between performance enhancement and a lowered monoclinic distortion. First-principles density functional theory calculations indicate that the improvements are due to a lowered hole effective mass and hole polaron formation energy, and collectively, our results identify the monoclinic distortion as a critical parameter in the optimization and understanding of bismuth vanadate-based photoanodes