Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Sintering behaviour of fluorapatite–silicate composites produced from natural fluorapatite and quartz

In this work, the sintering behaviour of fluorapatite (FAp)–silicate composites prepared by mixing variable amounts of natural quartz (2.5 wt% to 20 wt%) and FAp was studied. The composites were pressureless sintered in air at temperatures from 1000 °C to 1350 °C. The effects of temperatures on the densification, phase formation, chemical bonding and Vickers hardness of the composites were evaluated. All the samples exhibited mixed phase, comprising FAp and francolite as the major constituents along with some minor phases of cristobalite, wollastonite, dicalcium silicate and/or whitlockite dependent on the quartz content and sintering temperature. The composite containing 2.5 wt% quartz exhibited the best sintering properties. The highest bulk density of 3 g/cm³ and a Vickers hardness of >4.2 GPa were obtained for the 2.5 wt% quartz–FAp composite when sintered at 1100 °C. The addition of quartz was found to alter the microstructure of the composites, where it exhibited a rod-like morphology when sintered at 1000 °C and a regular rounded grain structure when sintered at 1350 °C. A wetted grain surface was observed for composites containing high quartz content and was believed to be associated with a transient liquid phase sintering.     

Colostrum source and passive immunity transfer in dairy bull calves

Colostrum is essential for good neonate health; however, it is not known whether different calves absorb the nutrients from colostrum equally well. In this study, the absorption of protein, IgG, and γ-glutamyl transferase was compared in newborn dairy bull calves for 1 wk after feeding colostrum from different sources. Thirty-five Holstein-Friesian bull calves were randomly allocated into 3 groups and fed colostrum within 4 h after birth. Group A calves (n = 12) were bottle fed colostrum from their own dam for 3 d. Colostrum from these group A cows was also used as foster cow colostrum for the group B calves (n = 12), such that each group A and B calf pair received identical colostrum from each milking of the respective group A dam (10% of birth weight per day). The group C calves (n = 11) were fed 1 bottle (2 L) of pooled colostrum and transition milk (referred to as pooled colostrum), as was the standard practice on the dairy farm. The pooled colostrum was collected from the other dairy cows on the farm 0 to 4 d postpartum and stored at 4°C for less than 12 h. Blood was sampled from calves before the first feeding and at 1, 2, 3, and 7 d after birth. Levels of total solids, total protein, and IgG were higher in the dam colostrum than in the pooled colostrum. At birth, there were no differences between the calf groups for any measurements, and all calves had very low IgG levels. After receiving colostrum, the glucose, plasma γ-glutamyl transferase, serum total protein, and IgG concentrations increased significantly in all calves. There were no differences in any blood measurements at any time point between the pairs of group A and group B calves that received colostrum from the same cow except for the IgG concentration 2 d after birth. However, the group A calves had a higher total serum protein level and IgG concentration than the group C calves for all the time points after the first feeding. The group B calves had a higher IgG concentration than the group C calves on d 1, 2, and 7 after birth. Compared with groups A and B, there was no difference in the proportion of calves in group C that failed to have passive immunity transferred adequately based on the IgG threshold (<10 g/L). Thus, the calves receiving identical colostrum from the same cow had the same levels of IgG, and even the pooled colostrum provided sufficient transfer of IgG as the calves were fed within 4 h after birth.     

Evaluation of the degree of rate control via automatic differentiation

The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady-state and transient kinetics. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high-quality results efficiently.     

Design of Trehalose-Based Amide/Sulfonamide C-type Lectin Receptor Signaling Compounds

Mincle agonists have been shown to induce inflammatory cytokine production, such as tumor necrosis factor-alpha (TNF) and promote the development of a Th1/Th17 immune response that might be crucial to development of effective vaccination against pathogens such as Mycobacterium tuberculosis. As an expansion of our previous work, a library of 6,6′-amide and sulfonamide α,α-d -trehalose compounds with various substituents on the aromatic ring was synthesized efficiently in good to excellent yields. These compounds were evaluated for their ability to activate the human C-type lectin receptor Mincle by the induction of cytokines from human peripheral blood mononuclear cells. A preliminary structure–activity relationship (SAR) of these novel trehalose diamides and sulfonamides revealed that aryl amide-linked trehalose compounds demonstrated improved activity and relatively high potency cytokine production compared to the Mincle ligand trehalose dibehenate adjuvant (TDB) and the natural ligand trehalose dimycolate (TDM) inducing dose-dependent and human-Mincle-specific stimulation in a HEK reporter cell line.     

Short-Term Creep of St3 Steel Under Low-Frequency Cyclic Loading

Strength of Materials - Creep constitutive equations have been derived for the materials that exhibit the properties of orthotropy (transversal isotropy) and transient creep under cyclic loading. A...