Physico-chemical study of cementitious materials based on binary and ternary binders

This research aims to study the physico-chemical phenomena occurring during hydration process of binary and ternary cementitious matrices, combining Portland cement (PC), blast furnace slag(BFS) and limestone filler (LF). For this purpose, measurements of the reaction rate and mechanical performances were performed on 12 mineral binders prepared with the same water-to-cementitious materials ratio (w/cm = 0.32) and various dosages of PC, BFS and LF. Three parameters are quantified using thermo-gravimetric analysis: the advancement of hydration characterized by the degree of hydration, the evolution of the chemically bound water as well as the quantity of Portlandite produced. Results show clearly that the knowledge of these parameters allows predicting correctly the evolution of compressive strength and young modulus at early age. The synergistic effects of ternary binders, formulated with moderate additions of BFS and LF, manifested in the form of an increased amount of hydration products compared to predictions based on the individual effects of BFS and the LF in the binary systems

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Deep learning regularization techniques to genomics data

Deep Learning algorithms have achieved a great success in many domains where large scale datasets are used. However, training these algorithms on high dimensional data requires the adjustment of many parameters. Avoiding overfitting problem is difficult. Regularization techniques such as L1 and L2 are used to prevent the parameters of training model from being large. Another commonly used regularization method called Dropout randomly removes some hidden units during the training phase. In this work, we describe some architectures of Deep Learning algorithms, we explain optimization process for training them and attempt to establish a theoretical relationship between L2-regularization and Dropout. We experimentally compare the effect of these techniques on the learning model using genomics datasets

Effects of land use and cultivation histories on the distribution of soil organic carbon stocks in the area of the Northern Nile Delta in Egypt

Precise knowledge of the soil organic carbon (SOC) stocks under various land uses is needed to meet the Kyoto Protocol and for the sustainability of natural resources. The purpose of the present study was to (1) gauge the depth and spatial distribution of the soil bulk density (BD), soil organic carbon (OC) stocks, and soil organic matter (OM) among the various land uses in the northern Nile Delta in Egypt; (2) estimate the soil carbon sequestration rate (CSR) under different land uses in the region; and (3) establish baseline data for SOC stocks in future studies on the dynamics of SOC. The study area was divided into ten sampling zones to represent each land use in the northern Nile Delta. Each sampling zone was further divided into four sampling sites to represent virgin lands and fish farms, and twelve sites were used to represent three crop types and four cultivation histories. The crops included clover, (Trifolium alexandrinum L.), sugar beet (Beta vulgaris L.), and rice, (Oryza sativa L.) and the years spanned were 5, 15, 30 and 50. The effects of the crop type on the SBD, SOC content, and SOC stocks were significant. In general, the SOC stocks increase as the number of years of cultivation increased. Thematic maps were produced using Geographical Information Systems (GIS) mapping. The Inverse Distance Weighted (IDW) technique in ArcGIS10.4 software revealed that the spatial pattern of the SBD, OC content, and stocks conformed to the soil analysis results. The SOC stocks of the croplands and fish farms were 1.6 and 1.5 times higher, respectively, compared to those of virgin land. Rice cropland had the lowest SBD (1.34 g cm−3) and the highest OC stocks (7.46 g C kg−1). The conversion of virgin land into croplands or fish farms actively contributed to the carbon storage rate (CSR)