Online Data Portal Research Articles

Impacts of Climate Change on Rainfall ‘Seasonality Index’ and Its Potential Implications on Water Savings and Reliability through Household Rainwater Tanks

This study depicts potential climate change impacts on annual rainwater savings from household rainwater harvesting using two different climate projection models; ACCESS 1.0 and CSIRO-Mk3.6. This paper also investigates potential changes in the relationships of ‘water saving efficiency’ and reliability with rainfall ‘seasonality index’ under the mentioned climate change scenarios. The annual water savings were calculated for three weather conditions: dry, average, and wet. Historical daily rainfall amounts provided by the Australian Bureau of Meteorology were used for three locations within the city of Brisbane (Australia). For the same locations, projected future daily rainfall amounts were collected from an online data portal facilitated by the Australian government. Potential annual water savings, water saving efficiency, and reliability values for the selected locations were calculated through a widely used tool, eTank, developed on water balance methodology at a daily scale. It was found that for the coastal location, Manly, the future water savings are not likely to change significantly. However, for the inland location, Sunnybank, the future water savings are expected to decrease under all the weather conditions through both the considered climate projections. For the far inner location, Oxley, the water savings are likely to decrease in the dry year, whereas in wet year, they are likely to increase. Also, it was found that the overall average relationship of SI–water saving efficiency is steeper for ACCESS 1.0 projected data compared to that produced through CSIRO-Mk3.6 data, and that significant differences exist among individual relationships for each location. The overall reliabilities calculated through the model projected data show lower values compared to the reliabilities calculated using historical data.

Interrelationships Among the Rice Export Prices of Major Exporting Countries: In Search of the Leader and Followers

AbstractBy examining the econometric interrelationships of rice export prices of India, Thailand, Vietnam, Pakistan, the U.S., Argentina, Brazil, and Uruguay, this study examines the most influential rice-exporting countries in the international rice export market. The sampled countries are the source of more than 80% of the global rice exports. In the process, this study relies on online data portals of the United Nations and country-level sources for aromatic and non-aromatic rice export price information from India, Pakistan, and Thailand. This study employed the Prais-Winsten and Autoregressive Distributive Lag (ARDL) estimation processes with the error correction procedure. Combining the findings from both models, this study concludes that in terms of interactions, the non-aromatic long-grain rice price of the U.S., and the aromatic rice price of Pakistan are the most correlated prices in the international rice market. Considering the number of countries influenced by the price of a given country, our results indicate that Vietnam is the price leader in the non-aromatic long-grain market, followed by Argentina, Brazil, and India. India, the largest exporter, is the fourth top price leader. In the case of aromatic rice, Thailand is the absolute leader. Many countries in Asia and Africa rely on rice imports to meet domestic demand, where the food security situation is already precarious. Based on the findings, this study suggests closely monitoring rice production and export trends of Vietnam, Argentina, Brazil, India and Thailand to provide early warning when necessary to better manage supply shocks in the international rice market.

SAT105 Frequent Monitoring Of Blood Glucose Levels Via A Remote Patient Monitoring System Helps Improve Glycemic Control

Abstract Disclosure: I. Sachmechi: None. M. Amini: None. S. Salam: None. R. Khan: None. A. Spitznogle: None. T. Belen: None. Objective: This study aims to evaluate the effectiveness of the Vivovitals telehealth platform on improving glycemic control and reducing A1C in patients with uncontrolled type II diabetes mellitus by providing more accessible and frequent patient care under the monitoring by their physician. Methods: This 12-week, prospective, pragmatic, single-center, double-arm study assessed the impact of the Vivovitals diabetes platform on glycemic control among 78 adults ≥ 18 years of age, with A1C ≥ 7.5% (58 mmol/mol) at baseline. The participants were randomized into two groups. The control group received standard care, while the intervention group was assisted to install the application on their smartphones and connect it to a Bluetooth Glucometer, and access to an online data portal. Blood glucose measurements were transmitted to the provider daily. Patients were contacted twice weekly regardless of their blood sugar measurements and additional call was made if blood glucose levels were <70 mg/dL or >180 mg/dL and modifications were made to diet and medication. The control group was allowed to call the provider if they have questions regarding their blood sugar levels or their medications. The two groups were compared at baseline and 12 weeks using nonparametric tests with p<0.05 considered statistically significant. Results: The mean A1C in the intervention group (n=39) was 9.53 (81 mmol/mol) +1.68 at baseline. Post-trial, mean A1C decreased to 7.99 (64 mmol/mol) + 1.40 (p < 0.001). In comparison, the mean A1C in the control group (n=39) was 9.63 (64 mmol/mol) + 1.47 at baseline with little change in post-trial mean A1C averaging 9.16 (77 mmol/mol) + 1.51 (p = 0.87). Discussion: In this study, patients who utilized the Vivovitals platform saw a significant decrease in A1C at an average of 1.56% compared to the non-significant 0.47% A1C reduction in the control group participants. We believe the A1C-reducing effect in the intervention group was due to the more frequent interactions with the physician and subsequent medication adjustments based on the data provided. The Vivovitals platform allows an affordable closer monitoring of blood glucose levels, identification of the direction of glycemic trends, and earlier intervention. While not explored in this study, it is reasonable to believe that the use of the Vivovitals diabetes platform could reduce Emergency Department visits and inpatient hospitalizations for hypoglycemia or hyperglycemia as the clinician can intervene before a patient becomes symptomatic. Conclusion: We conclude that the Vivovitals platform may help to reduce A1C in adults with uncontrolled type 2 diabetes mellitus in conjunction with lifestyle modifications and anti-diabetic medications. Presentation: Saturday, June 17, 2023

Using Data Tools and Systems to Drive Change in Early Childhood Education for Disadvantaged Children in South Africa.

In line with United Nations Sustainable Development Goal (SDG) 4.2, South Africa's National Development Plan commits to providing high-quality early childhood education to all children by 2030 to drive improved child outcomes. Prior to 2016, South Africa lacked reliable, locally standardised, valid, and cross-culturally fair assessment tools for measuring preschool quality and child outcomes, suitable for use at scale within a resource-constrained context. In this paper we detail the development and evolution of a suite of early learning measurement (ELOM) tools designed to address this measurement gap. The development process included reviews of literature and other relevant assessment tools; a review of local curriculum standards and expected child outcomes; extensive consultation with government officials, child development experts, and early learning practitioners, iterative user testing; and assessment of linguistic, cultural, functional, and metric equivalence across all 11 official South African languages. To support use of the ELOM tools at scale, and by users with varying levels of research expertise, administration is digitised and embedded within an end-to-end data value chain. ELOM data collected since 2016 quantify the striking socio-economic gradient in early childhood development in South Africa, demonstrate the relationship between physical stunting, socio-emotional functioning and learning outcomes, and provide evidence of the positive impact of high-quality early learning programmes on preschool child outcomes. To promote secondary analyses, data from multiple studies are regularly collated into a shared dataset, which is made open access via an online data portal. We describe the services and support that make up the ELOM data value chain, noting several key challenges and enablers of data-driven change within this context. These include deep technical expertise within a multidisciplinary and collaborative team, patient and flexible capital from mission-aligned investors, a fit-for-purpose institutional home, the appropriate use of technology, a user-centred approach to development and testing, sensitivity to children's diverse linguistic and socio-economic circumstances, careful consideration of requirements for scale, appropriate training and support for a non-professional assessor base, and a commitment to ongoing learning and continuous enhancement. Practical examples are provided of ways in which the ELOM tools and data are used for programme monitoring and enhancement purposes, to evaluate the relative effectiveness of early learning interventions, to motivate for greater budget and inform more effective resource allocation, to support the development of enabling Government systems, and to track progress towards the attainment of national and global development goals. We share lessons learnt during the development of the tools and discuss the factors that have driven their uptake in South Africa.

Strategies for improving the communication of satellite-derived InSAR data for geohazards through the analysis of Twitter and online data portals

Abstract. Satellite-based earth observation sensors are increasingly able to monitor geophysical signals related to natural hazards, and many groups are working on rapid data acquisition, processing, and dissemination to data users with a wide range of expertise and goals. A particular challenge in the meaningful dissemination of Interferometric Synthetic Aperture Radar (InSAR) data to non-expert users is its unique differential data structure and sometimes low signal-to-noise ratio. In this study, we evaluate the online dissemination of ground deformation measurements from InSAR through Twitter, alongside the provision of open-access InSAR data from the Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR) processing system. Our aim is to evaluate (1) who interacts with disseminated InSAR data, (2) how the data are used, and (3) to discuss strategies for meaningful communication and dissemination of open InSAR data. We found that the InSAR Twitter community was primarily composed of non-scientists (62 %), although this grouping included earth observation experts in applications such as commercial industries. Twitter activity was primarily associated with natural hazard response, specifically following earthquakes and volcanic activity, where users disseminated InSAR measurements of ground deformation, often using wrapped and unwrapped interferograms. For earthquake events, Sentinel-1 data were acquired, processed, and tweeted within 4.7±2.8 d (the shortest was 1 d). Open-access Sentinel-1 data dominated the InSAR tweets and were applied to volcanic and earthquake events in the most engaged-with (retweeted) content. Open-access InSAR data provided by LiCSAR were widely accessed, including automatically processed and tweeted interferograms and interactive event pages revealing ground deformation following earthquake events. The further work required to integrate dissemination of InSAR data into longer-term disaster risk-reduction strategies is highly specific, to both hazard type and international community of practice, as well as to local political setting and civil protection mandates. Notably, communication of uncertainties and processing methodologies are still lacking. We conclude by outlining the future direction of COMET LiCSAR products to maximize their useability.

Arctic Specimens in the Zoological Collections at the Natural History Museum, University of Oslo, Norway (NHMO)

In the NHMO zoological collections, specimens from the Arctic include about 9,000 mammals and 7,100 birds, whereas the Insect Collection holds about 105,000 specimens plus more than hundred jars with unsorted material. The Fish Collection contains approximately 1,400 specimens, while the Herptile Collection (amphibians & reptiles) holds only thirty-one specimens of three taxa. Many of these specimens originate from expeditions to E Greenland, N Canada, Svalbard, Novaya Zemlya, Finnmark, and NE Siberia in the period 1898 to 1966. Furthermore, the DNA Bank has about 5,600 tissue and extracted DNA samples, mostly sampled from wild animals during the last decades but also from specimens in the voucher collections. Most of the Arctic specimens have been digitized and are available in online data portals like GBIF, except for the Insect Collection, where only the type material and about 30 percent of the total specimens are digitized.

Diversity and structure in California’s urban forest: What over six million data points tell us about one of the world's largest urban forests

Urban street trees provide many benefits to surrounding communities, but our ability to assess such benefits relies on the availability of high-quality urban tree data. While these data are numerous, they are not available in an easily accessible, centralized place. To fill this gap, we aggregated public and private data into a single, comprehensive inventory of urban trees in California called the California Urban Forest (CUF) Inventory. These data are offered to the public (aggregated to ZIP code) via an online data portal, which at the time of publication contained over 6.6 million urban tree records. In this study, we first describe the assembly and utility of the inventory. Then, we conduct the most comprehensive assessment of the diversity and structure of California’s urban forest to date at statewide, regional, and local spatial scales. These analyses demonstrate that California’s urban forests are highly diverse and among the most diverse urban forests in the world. We present a new and intuitive metric of species diversity, the top diversity or TD-50 index, which represents the cumulative number of species accounting for the top 50 % abundance of trees in an urban forest. We used species abundance data from 81 well-inventoried cities to demonstrate that the TD-50 index was a robust metric of diversity and a good predictor of comprehensive metrics like the Shannon Index. We also found that small-statured trees, such as crape myrtles (Lagerstroemia cv.) dominate California’s urban forests. This aggregated inventory of one of the world's largest urban forests provides the data necessary to assess the structure, diversity, and value of California’s urban forests at multiple spatial scales. The inventory’s presentation to the public and the information that can be gained from its analysis can be a model for urban forest management worldwide.

ALYREF associated with immune infiltration is a prognostic biomarker in hepatocellular carcinoma

BackgroundAlthough ALYREF has been demonstrated to have a role in a number of malignancies, its role in hepatocellular carcinoma (HCC) has received little attention. Our objective was to research at the prognostic value, biological role and relevance of ALYREF to the immune system in HCC. MethodsThe expression of ALYREF and its relationship with clinical parameters of HCC patients were analyzed by liver cancer cohort (LIHC) of The Cancer Genome Atlas. The expression and prognosis were verified by immunohistochemistry experiments. Gene transfection, CCK-8, scratch healing, transwell invasion and flow cytometry were used to assess the molecular function of ALYREF in vitro. The TIMER and TISIDB online data portals were used to assess the relevance of ALYREF to immunization. Stepwise regression analysis of ALYREF-related immune genes in the LIHC training set was used to construct a prognostic risk prediction model. Also, construct a nomogram to predict patient survival. The testing set for internal verification. ResultsKnockdown of ALYREF changed the biological phenotypes of HCC cells, such as proliferation, apoptosis, and invasion. In addition, the expression of ALYREF in HCC affected the level of immune cell infiltration and correlated with the overall survival time of patients. The constructed immune prognostic model allows for a valid assessment of patients. ConclusionALYREF is increased in HCC, has an impact on cellular function and the immune system, and might be used as a prognostic marker.

DSM-5 pathological personality domains as vulnerability factors in predicting COVID-19-related anxiety symptoms

Since the beginning of the coronavirus disease-2019 (COVID-19) outbreak, individuals worldwide have shown different anxiety-related reactions. Several vulnerability factors may play a role in individuals’ psychological reactions to the COVID-19 pandemic. Such factors include pathological personality traits which have been shown to contribute to the development of anxiety-related conditions. Consequently, the present study investigated the relationships between DSM-5 pathological personality domains and COVID-19-related anxiety symptoms. Using an online data portal, the relationships between DSM-5 pathological personality domains and COVID-19-related anxiety symptoms among a mixed university student and community sample (N = 612) were studied. The results showed that there was a positive and significant relationship between all DSM-5 pathological personality domains and COVID-19-related anxiety. The results of multiple linear regression analysis showed that DSM-5 pathological personality domains explained 21% of COVID-19-related anxiety variance. Based on standardized coefficients, the Personality Inventory for DSM-5 (PID-5) negative affect domain had the main role in COVID-19-related anxiety. The findings suggest that pathological personality domains can be predictors in the symptoms of anxiety in a viral outbreak. The novel findings add to the literature on individual differences in domains of personality in response to pandemic situations. Implications for future clinical applications and research investigations are discussed.

Recent confirmed records of Galictis vittata in the department of Sucre, Caribbean region of Colombia

Galictis vittata is a small carnivore distributed in all the natural regions of Colombia, but it is considered as a “demographic rarity” due to its low density throughout its range in the national territory. This note documents new records with some ecological data and compiles the existing evidence about the local distribution of G. vittata in the department of Sucre, Colombian Caribbean. The new records are the product of fieldwork aiming at evaluating mammal diversity in the region, among other ecological aspects, by applying camera-trapping and interviews. In addition, other confirmed records of the species in the department were compiled based on the available information in three online data portals. The new records of G. vittata presented include a camera-trap record in a disturbed area of tropical dry forest and one related to an event of attack by domestic dogs. The local distribution of the species is extended to the sub-regions of Golfo de Morrosquillo and San Jorge, based on that three preserved specimens confirm its presence in the Montes de Maria sub-region. This is among the first data compilation of G. vittata focused specifically to the department of Sucre, also confirming its current presence in disturbed zones of tropical dry forest. The new records contribute evidence to previous statements about the potential ecological tolerance of the species to landscape modifications and provide novel information on possible threats and habitat use, specially about the potential importance of some elements in fragmented landscapes.

Data managers' perspectives on OAIS designated communities and the FAIR principles: mediation, tools and conceptual models

PurposeThis paper presents results of a study on data managers' perspectives on the evolution of Designated Communities and the FAIR Principles using an example of a geological repository.Design/methodology/approachThe study employed 10 semi-structured interviews with data managers at a state geological survey and qualitative analysis of the interview transcripts.FindingsThe Designated Community for a collection in this data repository has evolved from petroleum industry users to include academic researchers and the public. This change was accompanied by significant user interaction changes from in-person, reference interview-style conversations to anonymous digital, automated interactions. The main factors driving these changes were developments in technology which allowed the data managers to shift data discovery and access into the online environment. The online data portal has seen increasing non-expert use, driving the data team to develop additional services for these new communities. Repository data team participants varied in their familiarity with the FAIR Principles and their perceptions of the FAIRness of the data in the repository.Research limitations/implicationsThe study was limited to one organization in the United States. However, the results are applicable to other data environments working through the tensions between high-level global frameworks such as FAIR, and continuing to serve the day-to-day needs of their designated communities. Continued work on how to assess success in this complex space is needed.Originality/valueThis paper lies at the nexus of two digital preservation frameworks and contributes to a limited extant literature providing guidance on implementing the concept of a Designated Community in practice.

LOOKING FORWARD: BEHAVIORAL RISK FACTOR SURVEILLANCE SYSTEMS (BRFSS) CAREGIVING DATA

The Centers for Disease Control and Prevention (CDC), through its Behavioral Risk Factor Surveillance System (BRFSS), collects data on caregivers and the caregiving situation as well as many health behaviors, annually. The BRFSS is the world’s largest ongoing health survey, administered in all 50 U.S. states, as well as the District of Columbia and the three U.S. territories, with data collected from more than 400,000 respondents. In 2015-2017, the 9-item caregiving module was administered in 44 states, DC, and Puerto Rico on the BRFSS. CDC’s Alzheimer’s Disease and Healthy Aging Program has developed many data for action resources for use by states and other partners to help identify populations and communities most at need. This presentation will describe future enhancements with the BRFSS caregiving module and the series CDC developed resources to facilitate date utilization, including state-specific infographics, data briefs, and the online data portal.

A web-based platform for terrestrial data repository from Chicken Creek catchment

Exploring hydrological and ecological processes plays a key role in understanding ecosystem developments. In this respect, the constructed catchment, Chicken Creek, has been established for fundamental and interdisciplinary scientific research. Since 2005, an ongoing monitoring program has been launched to measure hydrological, biological, meteorological, and pedological parameters during the ecological development of the site. This comprehensive and multidisciplinary monitoring program has produced a diverse large data set. Handling such complex data for research purposes can be a cumbersome task. Consequently, we developed an online data portal (https://www.b-tu.de/chicken-creek/apps/datenportal/) to efficiently handle the data from Chicken Creek catchment. The portal was constructed using Shiny package of the R programming language. This platform provides a web-based data repository allowing for data discovery, download, visualization, and analysis. The data include time series of different parameters from installed sensors, data from laboratory analyses, vegetation data, data from sampling campaigns, and aerial photos. This platform demonstrates the relevancy and potentiality of the R-Shiny for constructing an online data portal to be used for multidisciplinary scientific purposes. The Chicken Creek data portal thus provides a comprehensive and reliable database to give scientists a fast and easy access to all collected data.

Gigwa v2-Extended and improved genotype investigator.

BackgroundThe study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution.ResultsGigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data).ConclusionsThis new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.

Provider Experiences with a Payer-Based PCMH Program.

The patient-centered medical home (PCMH) is an enhanced primary care model that aims to improve quality of care. Over the past several years, the PCMH model has been adopted by Medicare and private payers, which offer financial resources and technical assistance to participating practices. However, few studies have examined provider experiences and perspectives on the adoption of payer-based PCMH models in different practice settings. The goal of this qualitative study was to analyze how providers experienced specific elements of a payer-based PCMH model and identify cross-cutting themes that can be applied to other payer-based PCMH initiatives. Observational qualitative study. A total of 65 individuals (which includes 57 primary care physicians) participated in focus group sessions. Telephone interviews were conducted with an additional 14 physicians and 2 practice administrators. Interviews and focus groups were recorded after obtaining the informed consent of participants. Written transcripts from the recordings were then imported into NVivo 11 for subsequent coding and qualitative analysis of themes. We found that nurse care coordinators (NCCs) were the single most valuable and visible program element. Individual care plans served as effective tools of communication between the NCC and physician on patient care management goals and issues. The online data portal was viewed as the least valuable element. With regard to cross-cutting themes, some providers expressed a strained relationship with CareFirst due to communication challenges, a lack of trust, and differing priorities in selecting patients for care plans. Nurse care coordinators and the targeted use of individualized care plans are essential components in a payer-based PCMH program. Improving communication and trust in data reports are critical for effective implementation. Future research should examine provider experiences in other payer-based PCMH programs to see how interactions with payers affect program implementation.

Distinct prognostic value of dynactin subunit 4 (DCTN4) and diagnostic value of DCTN1, DCTN2, and DCTN4 in colon adenocarcinoma.

BackgroundColon adenocarcinoma (COAD) is ranked as the third most commonly diagnosed cancer in both women and men, and it is the most frequently occurring malignant tumor. Dynactin is a protein compound based on multiple subunits, including dynactin 1–6 (DCTN1–6), in most categories of cytoplasmic dynein performance in eukaryotes. Nevertheless, correlations between the DCTN family and the prognosis and diagnosis of COAD remain unidentified.MethodsStatistics for DCTN mRNA expression in patients with COAD were acquired from The Cancer Genome Atlas. Kaplan–Meier analyses and a Cox regression model were applied to determine overall survival, with computation of HRs and 95% CIs. Several online data portals were used to assess the biological process, and pathway examination was performed using the Kyoto Encyclopedia of Genes and Genomes to predict the biological functionality of DCTN genes.ResultsWe found that high expression of DCTN4 was linked with satisfactory results for overall survival (P=0.042, HR=0.650, 95% CI 0.429–0.985). The expression of DCTN1, DATN2, and DCTN4 was closely correlated with the frequency of colon tumors (P<0.001, area under the curve [AUC]=0.8811, 95% CI 0.8311–0.9312; P<0.001, AUC=0.870, 96% CI 0.833–0.9071; and P=0.0051, AUC=0.6317, 95% CI 0.5725–0.6908, respectively). In the enrichment examination, the level of gene expression was related to the cell cycle, cell apoptosis, and the cell metastasis pathway.ConclusionThe expression levels of DCTN1, DCTN2, and DCTN4 could allow differentiation between cancer-bearing tissues and paracancerous tissue. These genes can be applied as biomarkers to predict the prognosis and diagnosis of COAD.

11P - The role of downregulated SIRT3 expression in patients with hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the fifth leading cause of cancer-related deaths worldwide. The only drug currently approved for clinical use in the treatment of advanced HCC is sorafenib, a tyrosine kinase inhibitor. However, many patients with HCC are resistant to sorafenib and sensitivity to sorafenib differs according to the progression of liver cancer. SIRT3, a member of the mammalian sirtuin family, is localized to the mitochondria and regulates metabolic activity. To date, a few studies have investigated the effects of SIRT3 on prognosis and drug resistance in patients with HCC. Methods: A correlation study between SIRT3 and other genes was conducted through the TCGA online data portal site (http://cancergenome.nih.gov). To determine the protein expression of SIRT3, immunohistochemistry (IHC) was performed with liver cancer tissue using various antibodies. To investigate whether the expression of SIRT3 in HCC is related to the resistance to sorafenib, we treated sorafenib after the modulation of SIRT3 levels in HCC cell lines (overexpression in Huh7, knockdown in HepG2 and Hep3B cells) and conducted functional assays. Results: We identified that SIRT3 expression is downregulated in patients with HCC and high GLUT1 (glucose metabolism index) and Ki67 (proliferation index) expression. In addition, analysis of Cancer Imaging Archive data (TCGA) revealed a negative correlation between GLUT1 and SIRT3 mRNA expression and also HIF1a and SIRT3 mRNA expression. There was also a negative correlation between Ki67 and SIRT3 mRNA expression. After sorafenib treatment, SIRT3 protein expression was highly downregulated in various HCC cell lines (HepG2/Hep3B/SK-Hep1/Huh7). These cells altered their therapeutic resistance to sorafenib via SIRT3 modulation through a 2 dimensional (D)/3D cell culture system. Conclusions: Taken together, our results show that SIRT3 acts as a tumor suppressor and plays an important role in therapy resistance for HCC. Legal entity responsible for the study: Misu Lee. Funding: The National Research Foundation of Korea (Seoul, Korea; Grant Nos. NRF-2015R1D1A1A01057737, NRF-2018R1C1B6003894). Disclosure: All authors have declared no conflicts of interest.

REBIOMA Data Portal, Tool for Conservation Planning in Madagascar

Recognizing the abundance and the accumulation of information and data on biodiversity that are still poorly exploited and even unfunded, the REBIOMA project (Madagascar Biodiversity Networking), in collaboration with partners, has developed an online dataportal in order to provide easy access to information and critical data, to support conservation planning and the expansion of scientific and professional activities in Madagascar biodiversity. The mission of the REBIOMA data portal is to serve quality-labeled, up-to-date species occurrence data and environmental niche models for Madagascar’s flora and fauna, both marine and terrestrial. REBIOMA is a project of the Wildlife Conservation Society Madagascar and the University of California, Berkeley. REBIOMA serves species occurrence data for marine and terrestrial regions of Madagascar. Following upload, data is automatically validated against a geographic mask and a taxonomic authority. Data providers can decide whether their data will be public, private, or shared only with selected collaborators. Data reviewers can add quality labels to individual records, allowing selection of data for modeling and conservation assessments according to quality. Portal users can query data in numerous ways. One of the key features of the REBIOMA web portal is its support for species distribution models, created from taxonomically valid and quality-reviewed occurrence data. Species distribution models are produced for species for which there are at least eight, reliably reviewed, non-duplicate (per grid cell) records. Maximum Entropy Modeling (MaxEnt for short) is used to produce continuous distribution models from these occurrence records and environmental data for different eras: past (1950), current (2000), and future (2080). The result is generally interpreted as a prediction of habitat suitability. Results for each model are available on the portal and ready for download as ASCII and HTML files. The REBIOMA Data Portal address is http://data.rebioma.net, or visit http://www.rebioma.netfor more general information about the entire REBIOMA project.

Identification of persistent benthic assemblages in areas with different temperature variability patterns through broad-scale mapping.

Ecosystem-based management is a place-based approach that considers the relationships between system parts. Due to the complexity of ecosystems in the marine environment it is often difficult to define these relationships in space and time. Maps illustrate spatial concepts. Here we promote ecosystem-based spatial thinking by layering datasets from a larger project that mapped benthic fauna, substrate characteristics, and oceanic conditions on monthly, annual and decadal time scales along the U.S. continental shelf. By combining maps of persistent benthic megafauna and bottom temperature variability over approximately 90,000 km2, we identified wide spread benthic animal assemblages and regional disparity in temperature variability. From a broad-scale perspective the locations of the assemblage appear to be related to sea scallop population dynamics and indicate potential regional differences in climate change resiliency. These findings offer information on a scale that correlates with marine spatial planning, and could be used as a starting point for further investigation. To spur additional analysis and facilitate their linkage to other datasets, these datasets are available through public, online data portals. Overall, this study demonstrates how the growth of maps from single to multiple elements can help promote and facilitate the multifactor, ecosystem-based thinking needed to support regional ocean planning.

Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms

Management of poultry farms in China mostly relies on manual labor. Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents, making it very difficult for data retrieve, processing and analysis. An integrated cloud-based data management system (CDMS) was proposed in this study, in which the asynchronous data transmission, distributed file system, and wireless network technology were used for information collection, management and sharing in large-scale egg production. The cloud-based platform can provide information technology infrastructures for different farms. The CDMS can also allocate the computing resources and storage space based on demand. A real-time data acquisition software was developed, which allowed farm management staff to submit reports through website or smartphone, enabled digitization of production data. The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center. All the valid historical data of poultry farms can be stored to the remote cloud data center, and then eliminates the need for large server clusters on the farms. Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide. Keywords: cloud-based data management system (CDMS), egg production, intensified laying-hen farms, asynchronous data transmission, metadata DOI: 10.3965/j.ijabe.20160904.2488 Citation: Chen H Q, Xin H W, Teng G H, Meng C Y, Du X D, Mao T T, et al. Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms. Int J Agric & Biol Eng, 2016; 9(4): 106－115.