Experimental Study on Fiber Reinforced Concrete (FRC) Beams with splices

This paper presents the results of an experimental study involving nine simply supported beams featuring lap-spliced bars within the constant moment zone. All beams shared identical reinforcement details, including three longitudinal reinforcement bars (12 mm diameter) and two top reinforcement bars (8 mm diameter) for shear stirrup hanging. The lap-spliced specimens were created with a splice length of thirty times the bar diameter (360 mm). The study focused on two key parameters: the fiber content of hooked-end steel fibers used in the concrete mix and the presence of stirrups in the lap-splice region. The hooked-end steel fiber used was with an aspect ratio of 50 (Lf = 50 mm and df = 1.0 mm) and was incorporated into the concrete mix at varying volumetric contents ranging from 0% to 2%. For specimens with stirrups, two approaches were examined: only three closed stirrups in the splice zone (spaced at 180 mm) or seven closed stirrups (spaced at 90 mm) in the splice region. To assess the behavior and ductility of the beams, four-point loading tests were conducted, during these experiments, beam deflection, steel strains, crack propagation, and failure modes were observed and recorded, and then all these results were compared to those of conventional concrete specimens with and without lap splice. The results revealed that increasing the fiber content in the concrete mix led to higher yielding and ultimate loads in the beams, as well as increasing beam ductility. Notably, lap splice beams with a fiber content starting from 1.5% showed a comparable behavior to the reference RC beam without lap splice

Assessing the effects of data selection and representation on the development of reliable E. coli sigma 70 promoter region predictors

As the number of sequenced bacterial genomes increases, the need for rapid and reliable tools for the annotation of functional elements (e.g., transcriptional regulatory elements) becomes more desirable. Promoters are the key regulatory elements, which recruit the transcriptional machinery through binding to a variety of regulatory proteins (known as sigma factors). The identification of the promoter regions is very challenging because these regions do not adhere to specific sequence patterns or motifs and are difficult to determine experimentally. Machine learning represents a promising and cost-effective approach for computational identification of prokaryotic promoter regions. However, the quality of the predictors depends on several factors including: i) training data; ii) data representation; iii) classification algorithms; iv) evaluation procedures. In this work, we create several variants of E. coli promoter data sets and utilize them to experimentally examine the effect of these factors on the predictive performance of E. coli σ70 promoter models. Our results suggest that under some combinations of the first three criteria, a prediction model might perform very well on cross-validation experiments while its performance on independent test data is drastically very poor. This emphasizes the importance of evaluating promoter region predictors using independent test data, which corrects for the over-optimistic performance that might be estimated using the cross-validation procedure. Our analysis of the tested models shows that good prediction models often perform well despite how the non-promoter data was obtained. On the other hand, poor prediction models seems to be more sensitive to the choice of non-promoter sequences. Interestingly, the best performing sequence-based classifiers outperform the best performing structure-based classifiers on both cross-validation and independent test performance evaluation experiments. Finally, we propose a meta-predictor method combining two top performing sequence-based and structure-based classifiers and compare its performance with some of the state-of-the-art E. coli σ70 promoter prediction methods.NPRP grant No. 4-1454-1-233 from the Qatar National Research Fund (a member of Qatar Foundation).Scopu

Social Accounting Matrix for Egypt 1976

A Social Accounting Matrix (SAM) is presented for Egypt for 1976. It is based on the data available to the authors up to early 1978. While some parts may be improved as new data becomes available, the current matrix sheds light on a number of policy issues in Egypt. This work forms a basic part of the overall Egyptian model which is being constructed as part of the Food and Agriculture Program at IIASA

A Model-Scale Investigation for Microbially Induced Calcite Precipitation in Sand

New, exciting opportunities for utilizing biological processes to modify the engineering properties of the soil (e.g. strength, stiffness, permeability) have recently emerged. Enabled by interdisciplinary research at the confluence of microbiology, geochemistry, and civil engineering, this new field has the potential to meet society's ever-expanding needs for innovative treatment processes that improve soil supporting new and existing infrastructure. Ureolytic bacteria are one of the most efficient organisms in producing amounts of carbonate that easily react with the free calcium ions available in the environment. Sporosarcina pasteurii, a robust microbial alkaline environment was used in this work for its high potential in the biocementation process that involves the biomediated calcite precipitation. This study presents the results of a model-scale laboratory investigation conducted on bio-cemented siliceous sand. Chemicals used in this study are commercially available in order investigate the viability of implementing this technique in the field at larger scales. To make it more practical, the microbial cells are directly used with neither sterilization nor utilization of a centrifuge process for the growth medium. Blocks of the bio-treated soil were excavated from the model and were tested to examine the strength and durability parameters of the improved soil. The results show that the unconfined compressive strength (UCS) and slake durability index significant increased upon biological treatment. However, due to the downwards permeation of the fluid due to gravity, samples obtained from the bottom and the center of the treated column gave larger UCS and slake durability indices than those obtained from the top and the sides of the column

Excess Spin and the Dynamics of Antiferromagnetic Ferritin

Temperature-dependent magnetization measurements on a series of synthetic ferritin proteins containing from 100 to 3000 Fe(III) ions are used to determine the uncompensated moment of these antiferromagnetic particles. The results are compared with recent theories of macroscopic quantum coherence which explicitly include the effect of this excess moment. The scaling of the excess moment with protein size is consistent with a simple model of finite size effects and sublattice noncompensation.Comment: 4 pages, 3 Postsript figures, 1 table. Submitted to PR

Arbitral awards of the Cairo Regional Centre for International Commercial Arbitration

xx, 258 p.; 24 c