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Ceramic filters for household water treatment can improve water quality and reduce diarrheal disease. Hydraulic performance is critical for quality control and user acceptability, and hydraulic models have previously been developed and tested with experimental full-scale filters. As filters are cumbersome, there is interest in using disks instead of filters in laboratory efficacy studies. To assess the validity of disk use, we collected experimental volume from three sets of full-scale frustum-shaped filters and matching disks with different burn-out material sieve sizes and firing temperatures. We compared the experimental and fitted data by calibrating hydraulic conductivities from filters and disks. Hydraulic conductivities increased with larger burn-out material and higher firing temperatures but were comparable between filters and disks (2.00-6.15 × 10-7m·s-1 and 2.69-6.32 × 10-7m·s-1, respectively). We found that previously described hydraulic models successfully predicted cumulative volumes for filters and disks with rRMSE ranging from 2.1 to 9.6% (filters) and 3.4 to 4.7% (disks). The error increased slightly (rRMSE: 5.0-15%) when predicting hydraulic parameters for filters from the hydraulic conductivity of disks. Our results validate a method to predict full-scale filter hydraulic performance from hydraulic conductivity of disks and can be used to simplify and increase testing capacity, resulting in higher quality, more acceptable filters that improve household drinking water quality.

Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling. We described the completeness of 103 variables for 22,792 outbreaks publicly reported by the United States Centers for Disease Control and Prevention’s (US CDC’s) electronic Foodborne Outbreak Reporting System (eFORS) and National Outbreak Reporting System (NORS). We compared monthly trends of completeness during eFORS (1998–2008) and NORS (2009–2019) reporting periods using segmented time series analyses adjusted for seasonality. We quantified the overall, annual, and monthly completeness as the percentage of outbreaks with blank records per our study period, calendar year, and study month, respectively. We found that outbreaks of unknown genus (n = 7401), Norovirus (n = 6414), Salmonella (n = 2872), Clostridium (n = 944), and multiple genera (n = 779) accounted for 80.77% of all outbreaks. However, crude completeness ranged from 46.06% to 60.19% across the 103 variables assessed. Variables with the lowest crude completeness (ranging 3.32–6.98%) included pathogen, specimen etiological testing, and secondary transmission traceback information. Variables with low (

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society.

The rapid expansion of food and nutrition information requires new ways of data sharing and dissemination. Interactive platforms integrating data portals and visualization dashboards have been effectively utilized to describe, monitor, and track information related to food and nutrition; however, a comprehensive evaluation of emerging interactive systems is lacking. We conducted a systematic review on publicly available dashboards using a set of 48 evaluation metrics for data integrity, completeness, granularity, visualization quality, and interactivity based on 4 major principles: evidence, efficiency, emphasis, and ethics. We evaluated 13 dashboards, summarized their characteristics, strengths, and limitations, and provided guidelines for developing nutrition dashboards. We applied mixed effects models to summarize evaluation results adjusted for interrater variability. The proposed metrics and evaluation principles help to improve data standardization and harmonization, dashboard performance and usability, broaden information and knowledge sharing among researchers, practitioners, and decision makers in the field of food and nutrition, and accelerate data literacy and communication.

Purpose To evaluate the usefulness of a high-magnification module (HMM) lens to visualize retinal photoreceptors, retinal nerve fiber layer (RNFL), and superficial retinal vasculature in physiologic and pathologic retinal conditions. Design Observational descriptive study. Participants Thirty-two participants with normal and pathologic retina examination results. Methods Normal and pathologic maculae were imaged in vivo using still and video HMM lens modes, with fixation and contrast adjustments to enhance visualization. The HMM images were classified qualitatively based on structures identified as either good (photoreceptors seen), average (photoreceptor mosaic cannot be visualized clearly, retinal vessels and other retinal changes can be seen), or poor (no identifiable structures). Selected eyes were imaged with fundus photography, OCT, OCT angiography, indocyanine green angiography, and fluorescein angiography for comparison with the pathologic maculae. Main Outcomes Measures Description of HMM module-obtained macula images. Results From 32 eyes imaged (16 normal and 16 pathologic retinas), 12 of 16 normal and 11 of 16 pathologic retinas demonstrated at least average image quality, in which retinal vasculature and landmarks could be visualized. The mosaic pattern of hexagonal shapes representing photoreceptors could not be resolved in most pathologic retinas. For the retinas in which the photoreceptor mosaics were visualized (12 of 16 normal and 2 of 16 pathologic retinas), parafoveal mosaic patterns appeared denser with better image quality for all participants compared with foveal photoreceptors. Difficulty in resolving the photoreceptors in the umbo, fovea, and perifovea was encountered, similar to what has been reported with adaptive optics devices. The RNFL was seen as arcuate hyperreflective bundles. Flow was observed in the macular microvasculature. Poorly resolved photoreceptors and scattered hyperreflective foci were correlated with changes in the retinal pigment epithelium in eyes with age-related macular degeneration or central serous chorioretinopathy. Macular striae were seen in eyes with epiretinal membrane. Conclusions In most eyes, regardless of whether retinal pathologic features were present, it was challenging to obtain average quality (or better) images. In the few participants with good-quality imaging, the parafoveal photoreceptor mosaic, vascular flow, and various features of pathologic eyes could be visualized.

The rapid development of nutrition science is embracing digital transformation to generate large amounts of data. Precision nutrition and "Big Data" place increasing demand for data repositories and visualization, which enhances the digital transformation. We defined the need for an integrated nutrition data platform as a web-based platform that can collect, store, track, analyze, monitor, and visually display key metrics in nutrition and health while allowing users to interact with visuals and download data provided in the platform. Interactive dashboards create new opportunities for scholars and practitioners to generate and test hypotheses. We present the development and implementation of the Global Nutrition and Health Atlas (GNHA; https://sites.tufts.edu/gnha/), an open-access online platform covering nutrition and health data with 26 themes and 500+ indicators from 190+ countries up to 30 y. We view GNHA as an interactive tool aiming to share information and perspectives and foster collaborations and innovations.

Given the rapid development within China, the inequality of available water resources has been increasingly of interest. Current methods for assessing water stress are inadequate for province-scale rapid monitoring. A more responsive indicator at a finer scale is needed to understand the distribution of water stress in China. This paper selected Defense Meteorological Satellite Program Operational Line-scan System night-time stable lights as a proxy for water stress at the province level in China from 2004 to 2012, as night-time lights are closely linked with population density, electricity consumption and other social, economic and environmental indicators associated with water stress. The linear regression results showed the intensity of night-time lights can serve as a predictive tool to assess water stress across provinces with an R2 from 0.797 to 0.854. The model worked especially well in some regions, such as East China, North China and South West China. Nonetheless, confounding factors interfered with the predictive relationship, including population density, level of economic development, natural resource endowment and industrial structures, etc. The model was not greatly improved by building a multi-variable linear regression including agricultural and industrial indicators. A straightforward predictor of water stress using remotely sensed data was developed.