A Rule-Based Approach to Analyzing Database Schema Objects with Datalog

Database schema elements such as tables, views, triggers and functions are typically defined with many interrelationships. In order to support database users in understanding a given schema, a rule-based approach for analyzing the respective dependencies is proposed using Datalog expressions. We show that many interesting properties of schema elements can be systematically determined this way. The expressiveness of the proposed analysis is exemplarily shown with the problem of computing induced functional dependencies for derived relations. The propagation of functional dependencies plays an important role in data integration and query optimization but represents an undecidable problem in general. And yet, our rule-based analysis covers all relational operators as well as linear recursive expressions in a systematic way showing the depth of analysis possible by our proposal. The analysis of functional dependencies is well-integrated in a uniform approach to analyzing dependencies between schema elements in general.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

Examination of the Relationship between In-Store Environmental Factors and Fruit and Vegetable Purchasing among Hispanics.

Retail food environments have received attention for their influence on dietary behaviors and for their nutrition intervention potential. To improve diet-related behaviors, such as fruit and vegetable (FV) purchasing, it is important to examine its relationship with in-store environmental characteristics. This study used baseline data from the "El Valor de Nuestra Salud" study to examine how in-store environmental characteristics, such as product availability, placement and promotion, were associated with FV purchasing among Hispanic customers in San Diego County. Mixed linear regression models indicated that greater availability of fresh FVs was associated with a $0.36 increase in FV purchasing (p = 0.01). Placement variables, specifically each additional square foot of display space dedicated to FVs (p = 0.01) and each additional fresh FV display (p = 0.01), were associated with a$0.02 increase and $0.29 decrease, respectively, in FV purchasing. Introducing FV promotions in the final model was not related to FV purchasing. Exploratory analyses indicated that men reported spending$3.69 fewer dollars on FVs compared to women, controlling for covariates (p = 0.02). These results can help inform interventions targeting in-store environmental characteristics to encourage FV purchasing among Hispanics

Resonance Raman scattering in bulk 2H-MX2 (M=Mo, W; X=S, Se) and monolayer MoS2

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Global Regulation on microRNA in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Recent work has revealed the causative links between deregulation of microRNAs (miRNAs) and cancer development. In hepatocellular carcinoma (HCC), aberrant expression of miRNAs has been observed, but the molecular mechanisms that contribute to such changes remains to be elucidated. Here, we reported the analysis of miRNA expression in 94 pairs of tumor and adjacent nontumor tissues from HBV-associated HCC in Chinese patients. We found miRNAs were aberrantly expressed in HCC tissues. To investigate the cause of such deregulation, we detected changes in DNA copy number by measuring locus-specific hybridization intensity, and found changes in expression of several miRNAs are correlated with genomic amplification or deletion. For example, the genomic regions of miR-30d and miR-151 were amplified in ∼50% of HCC tumor tissues, and the expressions of these miRNAs are significantly correlated with DNA copy number. We also employed cDNA microarray data, and provide evidence that key regulators of the miRNA biosynthetic pathway, including DROSHA, DGCR8, AGO1, and AGO2, are frequently overexpressed in HCC. This study provides molecular clues that may contribute to the global changes of miRNA expression in HCC. Copyright © 2011, Mary Ann Liebert, Inc.published_or_final_versio

Interactions in vivo between the Vif protein of HIV-1 and the precursor (Pr55GAG) of the virion nucleocapsid proteins

The abnormality of viral core structure seen in vif-defective HIV-1 grown in PBMCs has suggested a role for Vif in viral morphogenesis. Using an in vivo mammalian two-hybrid assay, the interaction between Vif and the precursor (Pr55GAG) of the virion nucleocapsid proteins has been analysed. This revealed the amino-terminal (aa 1–22) and central (aa 70–100) regions of Vif to be essential for its interaction with Pr55GAG, but deletion of the carboxy-terminal (aa 158–192) region of the protein had only a minor effect on its interaction. Initial deletion studies carried out on Pr55GAG showed that a 35-amino-acid region of the protein bridging the MA(p17)–CA(p24) junction was essential for its ability to interact with Vif. Site-directed mutagenesis of a conserved tryptophan (Trp21) near the amino terminus of Vif showed it to be important for the interaction with Pr55GAG. By contrast, mutagenesis of the highly conserved YLAL residues forming part of the BC-box motif, shown to be important in Vif promoting degradation of APOBEC3G/3F, had little or no effect on the Vif–Pr55GAG interaction

Increase in Weight in Low Birth Weight and Very Low Birth Weight Infants Fed Fortified Breast Milk versus Formula Milk: A Retrospective Cohort Study

There has been a dramatic rise in preterm births in developed countries owing to changes in clinical practices and greater use of assisted reproductive techniques. However, few studies have examined the growth and outcomes of preterm infants according to the type of feeding (with fortified breast milk or formula). The purpose of this study was to examine the effect of breast milk feedings and formula on the growth and short-term outcomes of preterm infants in Hong Kong. In a single-center retrospective cohort study, we included 642 preterm infants at gestational age <37 weeks with birth weights <2200 g. According to World Health Organization criteria, 466 were classified as low birth weight (LBW) infants (≥1500 g and <2200 g) and 176 were classified as very low birth weight (VLBW) infants (<1500 g). The mothers of approximately 80% of VLBW infants and 60% LBW infants initiated breast milk feeding. When compared with no breast milk intake, LBW infants that received breast milk were significantly more likely to have growth z-scores closer to the median of the reference population on admission and experienced slower weight gain from birth to discharge. When breast milk was categorized by percent of total enteral intake, significant differences were seen among LBW infants, with lower percentages of small-for-gestational-age (SGA) status at discharge with increased proportions of breast milk intake. Our results suggest that LBW infants fed breast milk had better growth z-scores and lower SGA status at discharge compared with those predominately fed preterm formula.published_or_final_versio

Sex knowledge, attitudes, and high-risk sexual behaviors among unmarried youth in Hong Kong

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Four patients with a history of acute exacerbations of COPD: implementing the CHEST/Canadian Thoracic Society guidelines for preventing exacerbations

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You turn me cold: evidence for temperature contagion

Introduction During social interactions, our own physiological responses influence those of others. Synchronization of physiological (and behavioural) responses can facilitate emotional understanding and group coherence through inter-subjectivity. Here we investigate if observing cues indicating a change in another's body temperature results in a corresponding temperature change in the observer. Methods Thirty-six healthy participants (age; 22.9±3.1 yrs) each observed, then rated, eight purpose-made videos (3 min duration) that depicted actors with either their right or left hand in visibly warm (warm videos) or cold water (cold videos). Four control videos with the actors' hand in front of the water were also shown. Temperature of participant observers' right and left hands was concurrently measured using a thermistor within a Wheatstone bridge with a theoretical temperature sensitivity of <0.0001°C. Temperature data were analysed in a repeated measures ANOVA (temperature × actor's hand × observer's hand). Results Participants rated the videos showing hands immersed in cold water as being significantly cooler than hands immersed in warm water, F(1,34) = 256.67, p0.1). There was however no evidence of left-right mirroring of these temperature effects p>0.1). Sensitivity to temperature contagion was also predicted by inter-individual differences in self-report empathy. Conclusions We illustrate physiological contagion of temperature in healthy individuals, suggesting that empathetic understanding for primary low-level physiological challenges (as well as more complex emotions) are grounded in somatic simulation

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur