3,411 research outputs found
Editorial: crime patterns in time and space: the dynamics of crime opportunities in urban areas
The routine activity approach and associated crime pattern theory emphasise how crime emerges from spatio-temporal routines. In order to understand this crime should be studied in both space and time. However, the bulk of research into crime patterns and related activities has investigated the spatial distributions of crime, neglecting the temporal dimension. Specifically, disaggregation of crime by place and by time, for example hour of day, day of week, month of year, season, or school day versus none school day, is extremely relevant to theory. Modern data make such spatio-temporal disaggregation increasingly feasible, as exemplified in this special issue. First, much larger data files allow disaggregation of crime data into temporal and spatial slices. Second, new forms of data are generated by modern technologies, allowing innovative and new forms of analyses. Crime pattern analyses and routine activity inquiries are now able to explore avenues not previously available. The unique collection of nine papers in this thematic issue specifically examine spatio-temporal patterns of crime to; demonstrate the value of this approach for advancing knowledge in the field; consider how this informs our theoretical understanding of the manifestations of crime in time and space; to consider the prevention implications of this; and to raise awareness of the need for further spatio-temporal research into crime event
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The application of cognitive dissonance theory to the acquisition of a Piagetian conservation task by selected elementary school children
Pancreatic cancer clusters and arsenic-contaminated drinking water wells in Florida
This is the final version of the article. Available from BioMed Central via the DOI in this record.BACKGROUND: We sought to identify high-risk areas of pancreatic cancer incidence, and determine if clusters of persons diagnosed with pancreatic cancer were more likely to be located near arsenic-contaminated drinking water wells. METHODS: A total of 5,707 arsenic samples were collected from December 2000 to May 2008 by the Florida Department of Health, representing more than 5,000 individual privately owned wells. During that period, 0.010 ppm (10 ppb) or greater arsenic levels in private well water were considered as the threshold based on standard of United States Environmental Protection Agency (EPA). Spatial modeling was applied to pancreatic cancer cases diagnosed between 1998-2002 in Florida (n = 11,405). Multivariable logistic regression was used to determine if sociodemographic indicators, smoking history, and proximity to arsenic-contaminated well sites were associated with residence at the time of pancreatic cancer diagnosis occurring within versus outside a cluster. RESULTS: Spatial modeling identified 16 clusters in which 22.6% of all pancreatic cancer cases were located. Cases living within 1 mile of known arsenic-contaminated wells were significantly more likely to be diagnosed within a cluster of pancreatic cancers relative to cases living more than 3 miles from known sites (odds ratio = 2.1 [95% CI = 1.9, 2.4]). CONCLUSIONS: Exposure to arsenic-contaminated drinking water wells may be associated with an increased risk of pancreatic cancer. However, case-control studies are needed in order to confirm the findings of this ecological analysis. These cluster areas may be appropriate to evaluate pancreatic cancer risk factors, and to perform targeted screening and prevention studies.The project was supported by grants from the James and Esther King Biomedical Research Foundation (#06TSP); the Bankhead-Coley Cancer Research Program (#1BG06-341963, #08BN-03), the Florida Department of Health (FDOH); the CDC National Program of Cancer Registries (CDC NPCR); and the European Union ERDF funding (University of Exeter)
Hsp70–Bag3 complex is a hub for proteotoxicity-induced signaling that controls protein aggregation
Protein abnormalities in cells are the cause of major pathologies, and a number of adaptive responses have evolved to relieve the toxicity of misfolded polypeptides. To trigger these responses, cells must detect the buildup of aberrant proteins which often associate with proteasome failure, but the sensing mechanism is poorly understood. Here we demonstrate that this mechanism involves the heat shock protein 70–Bcl-2–associated athanogene 3 (Hsp70–Bag3) complex, which upon proteasome suppression responds to the accumulation of defective ribosomal products, preferentially recognizing the stalled polypeptides. Components of the ribosome quality control system LTN1 and VCP and the ribosome-associated chaperone NAC are necessary for the interaction of these species with the Hsp70–Bag3 complex. This complex regulates important signaling pathways, including the Hippo pathway effectors LATS1/2 and the p38 and JNK stress kinases. Furthermore, under proteotoxic stress Hsp70–Bag3–LATS1/2 signaling regulates protein aggregation. We established that the regulated step was the emergence and growth of abnormal protein oligo-mers containing only a few molecules, indicating that aggregation is regulated at very early stages. The Hsp70–Bag3 complex therefore functions as an important signaling node that senses proteo-toxicity and triggers multiple pathways that control cell physiology, including activation of protein aggregation
On the existence and structure of a mush at the inner core boundary of the Earth
It has been suggested about 20 years ago that the liquid close to the inner
core boundary (ICB) is supercooled and that a sizable mushy layer has developed
during the growth of the inner core. The morphological instability of the
liquid-solid interface which usually results in the formation of a mushy zone
has been intensively studied in metallurgy, but the freezing of the inner core
occurs in very unusual conditions: the growth rate is very small, and the
pressure gradient has a key role, the newly formed solid being hotter than the
adjacent liquid. We investigate the linear stability of a solidification front
under such conditions, pointing out the destabilizing role of the thermal and
solutal fields, and the stabilizing role of the pressure gradient. The main
consequence of the very small solidification rate is the importance of
advective transport of solute in liquid, which tends to remove light solute
from the vicinity of the ICB and to suppress supercooling, thus acting against
the destabilization of the solidification front. For plausible phase diagrams
of the core mixture, we nevertheless found that the ICB is likely to be
morphologically unstable, and that a mushy zone might have developed at the
ICB. The thermodynamic thickness of the resulting mushy zone can be
significant, from km to the entire inner core radius, depending on
the phase diagram of the core mixture. However, such a thick mushy zone is
predicted to collapse under its own weight, on a much smaller length scale
( km). We estimate that the interdendritic spacing is probably
smaller than a few tens of meter, and possibly only a few meters
Faster Geometric Algorithms via Dynamic Determinant Computation
The computation of determinants or their signs is the core procedure in many
important geometric algorithms, such as convex hull, volume and point location.
As the dimension of the computation space grows, a higher percentage of the
total computation time is consumed by these computations. In this paper we
study the sequences of determinants that appear in geometric algorithms. The
computation of a single determinant is accelerated by using the information
from the previous computations in that sequence.
We propose two dynamic determinant algorithms with quadratic arithmetic
complexity when employed in convex hull and volume computations, and with
linear arithmetic complexity when used in point location problems. We implement
the proposed algorithms and perform an extensive experimental analysis. On one
hand, our analysis serves as a performance study of state-of-the-art
determinant algorithms and implementations. On the other hand, we demonstrate
the supremacy of our methods over state-of-the-art implementations of
determinant and geometric algorithms. Our experimental results include a 20 and
78 times speed-up in volume and point location computations in dimension 6 and
11 respectively.Comment: 29 pages, 8 figures, 3 table
Using a Temporal-Causal Network Model for Computational Analysis of the Effect of Social Media Influencers on the Worldwide Interest in Veganism
Srs2 removes deadly recombination intermediates independently of its interaction with SUMO-modified PCNA
Saccharomyces cerevisiae Srs2 helicase plays at least two distinct functions. One is to prevent recombinational repair through its recruitment by sumoylated Proliferating Cell Nuclear Antigen (PCNA), evidenced in postreplication-repair deficient cells, and a second one is to eliminate potentially lethal intermediates formed by recombination proteins. Both actions are believed to involve the capacity of Srs2 to displace Rad51 upon translocation on single-stranded DNA (ssDNA), though a role of its helicase activity may be important to remove some toxic recombination structures. Here, we described two new mutants, srs2R1 and srs2R3, that have lost the ability to hinder recombinational repair in postreplication-repair mutants, but are still able to remove toxic recombination structures. Although the mutants present very similar phenotypes, the mutated proteins are differently affected in their biochemical activities. Srs2R1 has lost its capacity to interact with sumoylated PCNA while the biochemical activities of Srs2R3 are attenuated (ATPase, helicase, DNA binding and ability to displace Rad51 from ssDNA). In addition, crossover (CO) frequencies are increased in both mutants. The different roles of Srs2, in relation to its eventual recruitment by sumoylated PCNA, are discussed
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