Acinetobacterlwoffii Induced Cellulitis with Allergy-like Symptoms

Few reports document the misdiagnosis of Acinetobacterlwoffii skin infections for allergic reactions. In addition, A. lwoffii is frequently misidentified when applying conventional diagnostic methods. The bacterium has been reported to cause a multitude of diseases including skin and wound infections. The application of the newly established method “The Universal Method” allowed definite identification of the bacterium isolated from a leg and foot cellulitis case (Isolate QUBC mk1) that was misdiagnosed as an allergic reaction and was treated with intramuscular injections of diclofeneac sodium, anonsteroidal antiinflammatory drug.The isolate was identified as A. lwoffii, it failed to grow on MacConkey agar, and it was sensitive to ciprofloxacin but resistant to cefazolin. The 51-year old male patient was successfully treated with intravenous administration of ciprofloxacin, doxacillin, and cefazolin. He was released in good health after ten days.This work emphasizes the importance of distinguishing between skin infections and allergies. It also stresses the importance of prompt and accurate identification of A. Lwoffii and its possible relationship to allergic reactions. Misdiagnosis isdiscussed in the context of “The Hygiene Hypothesis”

Probabilistic forecasting of remotely sensed cropland vegetation health and its relevance for food security

In a world where climate change, population growth, and global diseases threaten economic access to food, policies and contingency plans can strongly benefit from reliable forecasts of agricultural vegetation health. To inform decisions, it is also crucial to quantify the forecasting uncertainty and prove its relevance for food security. Yet, in previous studies both these aspects have been largely overlooked. This paper develops a methodology to anticipate the agricultural Vegetation Health Index (VHI) while making the underlying prediction uncertainty explicit. To achieve this aim, a probabilistic machine learning framework modelling weather and climate determinants is introduced and implemented through Quantile Random Forests. In a second step, a statistical link between VHI forecasts and monthly food price variations is established. As a pilot implementation, the framework is applied to nine countries of South-East Asia (SEA) with consideration of national monthly rice prices. Model benchmarks show satisfactory accuracy metrics, suggesting that the probabilistic VHI predictions can provide decision-makers with reliable information about future cropland health and its impact on food price variation weeks or even months ahead, albeit with increasing uncertainty as the forecasting horizon grows. These results - ultimately allowing to anticipate the impact of weather shocks on household food expenditure - contribute to advancing the multidisciplinary literature linking vegetation health, probabilistic forecasting models, and food security policy

15-03 Real Time Bicycle Simulation Study of Bicyclists\u27 Behaviors and their Implication on Safety

The main goal of this study was to build a bicycle simulator and study the interaction between cyclists and other roadway users. The simulator developed was used in conjunction with Oculus Rift googles to create a virtual cycling environment. The virtual riding environment contained roadway infrastructures and features such as intersections, crosswalks, bicycle lanes, shared-lanes, etc. It also contained both motor vehicles and pedestrians that interacted with cyclists. The rider’s perception and reactions to different situations were investigated based on their performance during four virtual simulation scenarios with an electroencephalogram (EEG) readings. In addition to the results on interactions of cyclists and other roadway users and the infrastructure obtained from this study, the simulator developed can be used for future studies

CMS Monte Carlo production in the WLCG computing Grid

Monte Carlo production in CMS has received a major boost in performance and scale since the past CHEP06 conference. The production system has been re-engineered in order to incorporate the experience gained in running the previous system and to integrate production with the new CMS event data model, data management system and data processing framework. The system is interfaced to the two major computing Grids used by CMS, the LHC Computing Grid (LCG) and the Open Science Grid (OSG). Operational experience and integration aspects of the new CMS Monte Carlo production system is presented together with an analysis of production statistics. The new system automatically handles job submission, resource monitoring, job queuing, job distribution according to the available resources, data merging, registration of data into the data bookkeeping, data location, data transfer and placement systems. Compared to the previous production system automation, reliability and performance have been considerably improved. A more efficient use of computing resources and a better handling of the inherent Grid unreliability have resulted in an increase of production scale by about an order of magnitude, capable of running in parallel at the order of ten thousand jobs and yielding more than two million events per day

Erratum to: An Entropy Functional for Riemann-Cartan Space-Times

We correct the entropy functional constructed in Int. J. Theor. Phys. 51:362 (2012). The 'on-shell' functional one obtains from this correct functional possesses a holographic structure without imposing any constraint on the spin-angular momentum tensor of matter, in contrast to the conclusion made in the above paper.Comment: 15 pages. These are the preprints of the original paper and its erratum published in Int. J. Theor. Phy