Analytics for Everyone

Analyzing relational data typically involves tasks that facilitate gaining familiarity or insights and coming up with findings or conclusions based on the data. This process is usually practiced by data experts, such as data scientists, who share their output with a potentially less expert audience (everyone). Our goal is to enable everyone to participate in analyzing data rather than passively consuming its outputs (analytics democratization). With today’s increasing availability of data (data democratization) on the internet (web) combined with already widespread personal computing capabilities such a goal is becoming more attainable. With the recent increase of public data, i.e., Open Data, users without a technical background are keener than ever to analyze new data sets that are relevant to wide sectors of society. An important example of Open Data is the data released by governments all over the world, i.e., Open Government. This dissertation focuses on two main challenges that would face data exploration scenarios such as exploring open data found over the web. First, the infrastructure necessary for interactive data exploration is costly and hard to manage, especially by users who do not have technical knowledge. Second, the target users need guidance through the data exploration since there are too many starting points. To eliminate challenges related to managing infrastructure, we propose an in-browser SQL engine (serverless), i.e., a portable database, which we call Afterburner. Afterburner achieves comparable performance to native SQL engines given the same resources on modestly sized data sets. Afterburner uses code generation techniques that target an optimization-amenable subset of JavaScript and employs typed arrays for its columnar-based in-memory storage. In addition, for databases that are too large for the browser, we propose a hybrid architecture to accelerate the performance of data exploration tasks: a one-time SQL query that runs at the backend and SQL queries running in the browser as per user’s interactions. Based on a simple hint by the user, Afterburner automatically splits queries into two parts: a backend query that generates a materialized view that is shipped to the browser, and a frontend query per subsequent interaction occur locally against this view. Optimizing queries using local materialized views inside the browser accelerates query latency without adding any complexity to the backend or the frontend. One common theme among many data exploration tasks revolves around navigating the many different ways to group the data, i.e., exploring the data cube. Thus, to guide the user through data exploration, we apply an information-theoretic technique that picks the most informative parts from the entire data cube of a relational table, which is called Explanation Tables. We evaluate the efficiency and effectiveness of a sampling-based technique for generating explanation tables that achieves comparable quality to an exhaustive technique that considers the entire data cube, with a significant reduction in the run time. In addition, we introduce optimizations to explanation tables to fit the modest resources available in the browser without any external dependencies. In this, we present an SQL engine and a data exploration guidance tool that run entirely in the browser. We view the techniques and the experiments presented here as a fully functional and open-sourced proof of viability of our proposal. Our analytical stack is portable and works entirely in the browser. We show that SQL and exploration guidance can be as accessible as a web page, which opens the opportunity for more people to analyze data sets. Facilitating data exploration for everyone is one step closer towards analytics democratization where everyone can participate in data exploration, not just the experts

On the Coulomb interaction between spherical and deformed nuclei

AbstractA method is presented to calculate the exact HI Coulomb potential between spherical and deformed nuclei in the framework of the double folding model. We used realistic density distributions taking the deformations of the target into account. We have compared between our calculations and one of the more recent analytical expressions based on assuming sharp surface of the interacting nuclei. We have found that the finite surface diffuseness affects strongly the HI Coulomb interaction in the inner region and has a smaller effect in the tail region. Moreover, neglecting non-linear higher order terms in the analytical expressions produces errors in the outer region of the Coulomb interaction

Integrating IAEA’s Physical Model with JRC’s The Big Table document search tool

The Physical Model (PM) is an internal multi-Volume document for the IAEA’s Department of Safeguards describing the nuclear fuel cycle. This report describes work carried out by the JRC with the IAEA to prototype the integration of the PM with The Big Table (TBT), a document search tool developed by the JRC and in use at the IAEA. The core of TBT is an integrated collection of reference documents including regulatory documents, technical handbooks and trade nomenclatures. The documents are stored in a database. They are searchable by text in a structured way (i.e. on database fields) and also by correspondence tables that relate items by their meaning. To integrate the Physical Model into TBT, the IAEA/SG/SGIM has first turned the PM into a tabular format. JRC has then proposed and implemented a way of coding the PM in TBT tables to better reflect the PM structure. Eleven PM Volumes have been integrated in a TBT-PM database for use by the IAEA. The PM Volumes are linked by correspondence tables to other documents in the TBT collection. By coding the Physical Model into a TBT database format, the original intended uses of the PM are still supported. TBT can ease the consultation of the PM for evaluating States’ nuclear activities by IAEA’s analysts. TBT can be an aid for IAEA’s inspectors preparing for routine and ad hoc inspections, design information verification visits and complementary access operations. Further the PM integrated into TBT can be used as a tool for training inspectors on steps of the nuclear fuel cycle. Finally implementing the Physical Model multi-level structure into a database-coded format opens the possibility of linking the PM to other taxonomies and collections of open sources relevant for safeguards analyses.JRC.E.8-Nuclear securit

EFFECT OF SPROUTING USING SALINE WATER ON CHEMICAL COMPOSITION AND PROTEIN QUALITY AND FRACTIONATIONS OF EGYPTIAN CLOVER SPROUTS

The effect of salt stress on growth proximate analysis, amino acid profile, protein quality and fractionations in 3 days etiolated clover sprout samples was investigated. Sterilized and non-sterilized clover seeds were sprouting using tap water 1000 ppm and 2000 ppm NaCl solution. The results showed reduction effect of clover sprout characters with higher NaCl concentration. Clover seed sprouting increased the crude protein content using tap water or saline water for sprouting as compared with dry seeds. However using non-sterilized clover seeds for sprouting recorded the higher values of protein (44.73%), lipids (6.21%) and energy (318.51 kcal/g) in etiolated sprouts, while using sterilized seeds recorded higher carbohydrate (21.28%), fiber (14.57%) and  ash (4.46%). For amino acids, aspartic acid followed by glutamic acid were the most abundant, while Cysteine and methionine were the least in clover etiolated sprouts. Using saline water for clover seed sprouting caused increases in all amino acid compared with tap water except Methionine, aspartic acid and cysteine. For protein efficiency ratio (PER), essential amino acid index (EAAI%) and biological value (BV), from using saline water for sprouting had the higher values than sprouts from using tap water, but the values are less than dry seeds. On the other hand nutritional index (NI) recorded the higher values in salt stress compared with both using tap water and dry clover seeds. For protein fraction in etiolated clover sprouts albumin was the major protein fraction extracted from NaCl 2000ppm sprout fallowed by prolamin from tap water sprouts, glutelin from NaCl 1000 ppm sprout and globulin from tap water sprout. The clover sprout protein isolated and its fractions could have excellent applications for future product development by virtue of their nutritional and functional properties

Evaluation of Neonatal Sepsis Based on Measurement of Red Cell Distribution Width

Background: Infant morbidity as well as mortality are frequently caused by neonatal sepsis. Neonatal sepsis can be predicted using the red cell distribution width (RDW), according to several researches. Objective: To determine if RDW can be employed as a marker for the evaluation of newborn sepsis and the assessment of its severity. Patients and Methods: 40 newborns, 20 of whom were infected and the other 20 of whom were non infected, participated in this case-control research. Patients and controls were collected from neonatal intensive care unit (NICU), Zagazig University Hospitals. Full history was taken from all participants parent, with clinical and laboratory examination were done; complete blood picture, and creatinine, blood culture, and serum level of C-reactive protein(CRP). Results: We revealed significant link between RDW and all of total leukocyte count (TLC), immature to total neutrophil ratio (I/T ratio), absolute neutrophil count (ANC), CRP, procalcitonin, severity of sepsis, and mortality. RDW and platelet count, on the other hand, have a strong negative association. With a sensitivity of 83.3 percent, specificity of 50 percent, a positive predictive value (PPV) of 71.4 percent, and a negative predictive value (NPV) of 66.7 percent, accuracy of 70 percent (p>0.05), the best RDW cutoff for diagnosing newborn sepsis severity was ≥17.9. Conclusion: Predictors of illness severity and death in newborn sepsis may be accurately predicted using baseline RDW measurements, which is critical for treatment of neonates who are at great risk of sepsis

Assessment of Genotoxic and Cytotoxic Hazards in Brain and Bone Marrow Cells of Newborn Rats Exposed to Extremely Low-Frequency Magnetic Field

The present study aimed to evaluate the association between whole body exposure to extremely low frequency magnetic field (ELF-MF) and genotoxic , cytotoxic hazards in brain and bone marrow cells of newborn rats. Newborn rats (10 days after delivery) were exposed continuously to 50 Hz, 0.5 mT for 30 days. The control group was treated as the exposed one with the sole difference that the rats were not exposed to magnetic field. Comet assay was used to quantify the level of DNA damage in isolated brain cells. Also bone marrow cells were flushed out to assess micronucleus induction and mitotic index. Spectrophotometric methods were used to measure the level of malondialdehyde (MDA) and the activity of glutathione (GSH) and superoxide dismutase (SOD). The results showed a significant increase in the mean tail moment indicating DNA damage in exposed group (P<0.01,0.001,0.0001). Moreover ELF-MF exposure induced a significant (P<0.01,0.001) four folds increase in the induction of micronucleus and about three folds increase in mitotic index (P<0.0001). Additionally newborn rats exposed to ELF-MF showed significant higher levels of MDA and SOD (P<0.05). Meanwhile ELF-MF failed to alter the activity of GSH. In conclusion, the present study suggests an association between DNA damage and ELF-MF exposure in newborn rats