Variability in the Relationship Between Weight and Wing Length of Anopheles gambiae (Diptera: Culicidae)

The relationship between wing length and body weight of female Anopheles gambiae Giles reared at 3 densities and at 3 temperatures was examined. Although overall, weight was proportional to wing length raised to the 4th power, the relationship within treatments was linear. The slope of the regression line varied significantly among treatments. Therefore, wing length of mosquitoes caught from field populations may not be an adequate measure of body weight if the conditions under which the mosquitoes have developed are not know

Autotuning CUDA: Applying NLP Techniques to LS-CAT

The abstract relation between hardware parameters and program performance makes setting program parameters a difficult task. Without autotuning, software can miss low-level optimizations, resulting in lower performance. Traditionally, time-consuming trial and error search methods have been the staple of autotuning. Applying Natural language processing (NLP) based machine learning (ML) methods to source code as a means to perform autotuning-oriented tasks is a growing topic. Earlier research has, with success, performed a range of different autotuning tasks using multiple source code languages. However, most of the source code data is CPU-oriented, with very little GPU code. The LS-CAT (Large-Scale CUDA AutoTuning) dataset [BTE21] uses CUDA GPU-based kernels and generates a dataset to perform thread-coarsening. This paper implements several custom NLP-ML pipelines to evaluate ML-based thread-coarsening using the LS-CAT dataset, and a custom scoring function to ?nd the performance impact for any choice. Several model con?gurations were able to beat both random choice, 0.9400, and only selecting the largest thread-block (1024), 0.9437. Finally, the best model achieves a score of 0.9483, giving an average performance increase and speedup of 0.49 percent over the largest thread-block. Implementing self-attention mechanisms proved to counteract overfitting, while a multi-label based learning task outperformed other approaches. Compared to previous datasets [Cum+17], the LS-CAT dataset's higher thread-coarsening precision gives a more precise evaluation of the model's performance. The inst2vec embedding used in earlier works was unable to correctly parse the CUDA LLVM IR tokens, resulting in high data loss. Approaches to addressing this, and other ideas for future work, are also included

Comparative Efficacy of Serum Creatinine and Microalbuminuria in Detecting Early Renal Injury in Asphyxiated Babies in Calabar, Nigeria

Background: Microalbuminuria and serum creatinine are markers of acute kidney injury. Birth asphyxia is responsible for 50% of all newborn deaths and acute non-oliguric kidney injury is one of such complications. This study was undertaken to determine the efficacy of serum creatinine and microalbuminuria for the detection of early renal lesion in severely asphyxiated babies in Calabar, Nigeria. Materials and Method: This prospective cross-sectional investigational study was undertaken among severely asphyxiated babies admitted into the newborn units of the University of Calabar Teaching Hospital (UCTH), Calabar, Nigeria. Standard method for blood collection and determination of urea, electrolytes were used. Micral-test strips were used on samples negative only for albumin after using urine dipstick. Color comparison was done with the standardized color scale on test strip container after 5 minutes. Results: Fifty term newborn babies were enrolled, their serum electrolytes, creatinine and creatinine clearance were essentially normal. Six (12%) babies had positive microalbuminuria, while 44(88%) had negative microalbuminuria with specificity and negative predictive values of 100% and 88% respectively. Conclusion: Microalbuminuria was not useful for early detection of acute renal failure in babies with severe birth asphyxia, but further studies are recommended

Experimental and numerical studies on the shared activation anchoring of NSMR CFRP applied to RC beams

A shared activation anchoring method used for carbon fiber reinforced polymer (CFRP) near surface mounted reinforcement (NSMR) strengthening is hypothesized to provide a mean to exploit the full material capacity and to tailor desired responses. To investigate strengthening efficiency, failure control as well as ductility levels, the developed strengthening system were mounted on reinforced concrete T-beams with a length of 6400 mm. Initial activation stresses of 50% (1100 MPa) and 70% (1540 MPa) were applied to an 8 mm CFRP rod by the anchor system. Then, in some beams finite element simulations were carried out for better understanding the obtained results with regard to the overall structural behaviour. Good correlations between the FE-simulation and tested responses were observed, where a high utilization of the CFRP material (up to 3300MPa) was reached. Installation of the activated system worked well, without premature failure. Additionally it was possible to control the failure development, where intermediate crack de-bonding was achieved when testing the beams with an activation level of approximately 50%, while fibre rupture occurred at the level of 70% activation, thus providing a CFRP strain of approximately 0,02.SFRH/BSAB/150266/2019; S&P Denmark and Reinholdt W. Jorck and Hustrus foundation. FCT, respectively, financed by European Social Fund and by national funds through the FCT/MCTE