The Importance of Time Congruity in the Organisation.

In 1991 Kaufman, Lane, and Lindquist proposed that time congruity in terms of an individual's time preferences and the time use methods of an organisation would lead to satisfactory performance and enhancement of quality of work and general life. The research reported here presents a study which uses commensurate person and job measures of time personality in an organisational setting to assess the effects of time congruity on one aspect of work life, job-related affective well-being. Results show that time personality and time congruity were found to have direct effects on well-being and the influence of time congruity was found to be mediated through time personality, thus contributing to the person–job (P–J) fit literature which suggests that direct effects are often more important than indirect effects. The study also provides some practical examples of ways to address some of the previously cited methodological issues in P–J fit research

Towards a population of HMXB/NS microquasars as counterparts of low-latitude unidentified EGRET sources

The discovery of the microquasar LS 5039 well within the 95% conficence contour of the Unidentified EGRET Source (UES) 3EG J1824-1514 was a major step towards the possible association between microquasars (MQs) and UESs. The recent discovery of precessing relativistic radio jets in LS I +61 303, a source associated for long time with 2CG 135+01 and with the UES 3EG J0241+6103, has given further support to this idea. Finally, the very recently proposed association between the microquasar candidate AX J1639.0-4642 and the UES 3EG J1639-4702 points towards a population of High Mass X-ray Binary (HMXB)/Neutron Star (NS) microquasars as counterparts of low-latitude unidentified EGRET sources.Comment: 12 pages, 7 figures. Proceedings of the Conference "The Multiwavelength Approach to Unidentified Gamma-ray Sources", to appear in the journal Astrophysics and Space Scienc

Chemostratigraphy of Neoproterozoic carbonates: implications for 'blind dating'

The delta C-13(carb) and Sr-87/Sr-86 secular variations in Neoproteozoic seawater have been used for the purpose of 'isotope stratigraphy' but there are a number of problems that can preclude its routine use. In particular, it cannot be used with confidence for 'blind dating'. The compilation of isotopic data on carbonate rocks reveals a high level of inconsistency between various carbon isotope age curves constructed for Neoproteozoic seawater, caused by a relatively high frequency of both global and local delta C-13(carb) fluctuations combined with few reliable age determinations. Further complication is caused by the unresolved problem as to whether two or four glaciations, and associated negative delta C-13(carb) excursions, can be reliably documented. Carbon isotope stratigraphy cannot be used alone for geological correlation and 'blind dating'. Strontium isotope stratigraphy is a more reliable and precise tool for stratigraphic correlations and indirect age determinations. Combining strontium and carbon isotope stratigraphy, several discrete ages within the 590-544 Myr interval, and two age-groups at 660-610 and 740-690 Myr can be resolved

A terminal assessment of stages theory : introducing a dynamic states approach to entrepreneurship

Stages of Growth models were the most frequent theoretical approach to understanding entrepreneurial business growth from 1962 to 2006; they built on the growth imperative and developmental models of that time. An analysis of the universe of such models (N=104) published in the management literature shows no consensus on basic constructs of the approach, nor is there any empirical confirmations of stages theory. However, by changing two propositions of the stages models, a new dynamic states approach is derived. The dynamic states approach has far greater explanatory power than its precursor, and is compatible with leading edge research in entrepreneurship

Self Organized Dynamic Tree Neural Network

Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partitional, hierarchical, density studies, probabilistic, etc. This article will present the SODTNN, which can perform clustering by integrating hierarchical and density-based methods. The network incorporates the behavior of self-organizing maps and does not specify the number of existing clusters in order to create the various groups

Complete breeding failures in ivory gull following unusual rainy storms in North Greenland

Natural catastrophic events such as heavy rainfall and windstorms may induce drastic decreases in breeding success of animal populations. We report the impacts of summer rainfalls on the reproductive success of ivory gull (Pagophila eburnea) in north-east Greenland. On two occasions, at Amdrup Land in July 2009 and at Station Nord in July 2011, we observed massive ivory gull breeding failures following violent rainfall and windstorms that hit the colonies. In each colony, all of the breeding birds abandoned their eggs or chicks during the storm. Juvenile mortality was close to 100% at Amdrup Land in 2009 and 100% at Station Nord in 2011. Our results show that strong winds associated with heavy rain directly affected the reproductive success of some Arctic bird species. Such extreme weather events may become more common with climate change and represent a new potential factor affecting ivory gull breeding success in the High Arctic

Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine

OBJECTIVE Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD. RESEARCH DESIGN AND METHODS We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial. RESULTS Four distinct phenotypes were identified: Cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29–3.29]). Similar phenotypes and outcomes were identified in EXSCEL. CONCLUSIONS In patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs

Tree-based Partition Querying: A Methodology for Computing Medoids in Large Spatial Datasets

Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous emerging fields, such as location based services and sensor networks. Since the k-medoid problem is NP-hard, all existing work deals with approximate solutions on relatively small datasets. This paper aims at efficient methods for very large spatial databases, motivated by: (1) the high and ever increasing availability of spatial data, and (2) the need for novel query types and improved services. The proposed solutions exploit the intrinsic grouping properties of a data partition index in order to read only a small part of the dataset. Compared to previous approaches, we achieve results of comparable or better quality at a small fraction of the CPU and I/O costs (seconds as opposed to hours, and tens of node accesses instead of thousands). In addition, we study medoid-aggregate queries, where k is not known in advance, but we are asked to compute a medoid set that leads to an average distance close to a user-specified value. Similarly, medoid-optimization queries aim at minimizing both the number of medoids k and the average distance. We also consider the max version for the aforementioned problems, where the goal is to minimize the maximum (instead of the average) distance between any object and its closest medoid. Finally, we investigate bichromatic and weighted medoid versions for all query types, as well as, maximum capacity and dynamic medoids