University of Virginia

About: University of Virginia is a education organization based out in Charlottesville, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 52543 authors who have published 113268 publications receiving 5220506 citations. The organization is also known as: U of V & UVa.

On The Computation of Equivalent Potential Temperature

Abstract: The computation of θE, the pseudo-quivalent potential temperature, ordinarily omits the contribution due to specific heats of water vapor. This may he an acceptable practice for temperate-latitude usages but a questionable one when applied in the tropics where lower layers, rich in moisture, may he several; degrees warmer and the vertical gradient larger when this factor is included. An inexpensive method of computing θE to include the beat capacities of water substance is presented aid the results compared with those derived from several tephigrams which ignore this contribution.

Flexible sequence similarity searching with the FASTA3 program package.

Abstract: The FASTA3 and FASTA2 packages provide a flexible set of sequence-comparison programs that are particularly valuable because of their accurate statistical estimates and high-quality alignments. Traditionally, sequence similarity searches have sought to ask one question: "Is my query sequence homologous to anything in the database?" Both FASTA and BLAST can provide reliable answers to this question with their statistical estimates; if the expectation value E is < 0.001-0.01 and you are not doing hundreds of searches a day, the answer is probably yes. In general, the most effective search strategies follow these rules: 1. Whenever possible, compare at the amino acid level, rather than the nucleotide level. Search first with protein sequences (blastp, fasta3, and ssearch3), then with translated DNA sequences (fastx, blastx), and only at the DNA level as a last resort (Table 5). 2. Search the smallest database that is likely to contain the sequence of interest (but it must contain many unrelated sequences for accurate statistical estimates). 3. Use sequence statistics, rather than percent identity or percent similarity, as your primary criterion for sequence homology. 4. Check that the statistics are likely to be accurate by looking for the highest-scoring unrelated sequence, using prss3 to confirm the expectation, and searching with shuffled copies of the query sequence [randseq, searches with shuffled sequences should have E approx 1.0]. 5. Consider searches with different gap penalties and other scoring matrices. Searches with long query sequences against full-length sequence libraries will not change dramatically when BLOSUM62 is used instead of BLOSUM50 (20), or a gap penalty of -14/-2 is used in place of -12/-2. However, shallower or more stringent scoring matrices are more effective at uncovering relationships in partial sequences (3,18), and they can be used to sharpen dramatically the scope of the similarity search. However, as illustrated in the last section, the E value is only the first step in characterizing a sequence relationship. Once one has confidence that the sequences are homologous, one should look at the sequence alignments and percent identities, particularly when searching with lower quality sequences. When sequence alignments are very short, the alignment should become more significant when a shallower scoring matrix is used, e.g., BLOSUM62 rather than BLOSUM50 (remember to change the gap penalties). Homology can be reliably inferred from statistically significant similarity. Whereas homology implies common three-dimensional structure, homology need not imply common function. Orthologous sequences usually have similar functions, but paralogous sequences often acquire very different functional roles. Motif databases, such as PROSITE (21), can provide evidence for the conservation of critical functional residues. However, motif identity in the absence of overall sequence similarity is not a reliable indicator of homology.

Infrared spectroscopy of proteins and peptides in lipid bilayers

Abstract: Infrared spectroscopy is a useful technique for the determination of conformation and orientation of membrane-associated proteins and lipids. The technique is especially powerful for detecting conformational changes by recording spectral differences before and after perturbations in physiological solution. Polarized infrared measurements on oriented membrane samples have revealed valuable information on the orientation of chemical groupings and substructures within membrane molecules which is difficult to obtain by other methods. The application of infrared spectroscopy to the static and dynamic structure of proteins and peptides in lipid bilayers is reviewed with some emphasis on the importance of sample preparation. Limitations of the technique with regard to the absolute determination of secondary structure and orientation and new strategies for structural assignments are also discussed.

Beyond Beliefs: Religions Bind Individuals Into Moral Communities

Abstract: Social psychologists have often followed other scientists in treating religiosity primarily as a set of beliefs held by individuals. But, beliefs are only one facet of this complex and multidimensional construct. The authors argue that social psychology can best contribute to scholarship on religion by being relentlessly social. They begin with a social-functionalist approach in which beliefs, rituals, and other aspects of religious practice are best understood as means of creating a moral community. They discuss the ways that religion is intertwined with five moral foundations, in particular the group-focused “binding” foundations of Ingroup/loyalty, Authority/respect, Purity/sanctity. The authors use this theoretical perspective to address three mysteries about religiosity, including why religious people are happier, why they are more charitable, and why most people in the world are religious.

The Empire of Chance: How Probability Changed Science and Everyday Life

Abstract: The Empire of Chance tells how quantitative ideas of chance transformed the natural and social sciences, as well as daily life over the last three centuries. A continuous narrative connects the earliest application of probability and statistics in gambling and insurance to the most recent forays into law, medicine, polling and baseball. Separate chapters explore the theoretical and methodological impact in biology, physics and psychology. Themes recur - determinism, inference, causality, free will, evidence, the shifting meaning of probability - but in dramatically different disciplinary and historical contexts. In contrast to the literature on the mathematical development of probability and statistics, this book centres on how these technical innovations remade our conceptions of nature, mind and society. Written by an interdisciplinary team of historians and philosophers, this readable, lucid account keeps technical material to an absolute minimum. It is aimed not only at specialists in the history and philosophy of science, but also at the general reader and scholars in other disciplines.