Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

Investigation of thermal residual stresses during laser ablation of tantalum carbide coated graphite substrates using micro-Raman spectroscopy and COMSOL multiphysics

Laser ablation of high-temperature ceramic coatings results in thermal residual stresses due to which the coatings fail by cracking and debonding. Hence, the measurement of such residual stresses during laser ablation process holds utmost importance from the view of performance of coatings in extreme conditions. The present research aims at investigating the effect of laser parameters such as laser pulse energy, scanning speed and line spacing on thermal residual stresses induced in tantalum carbide-coated graphite substrates. Residual stresses were measured using micro-Raman spectroscopy and correlated with Raman peak shifts. Transient thermal analysis was performed using COMSOL Multiphysics to model the single ablated track and residual stresses were reported at low, moderate and high pulse energy regimes. The results showed that the initial laser conditions caused higher tensile residual stresses. Moderate pulse energy regime comprised higher compressive residual stresses due to off centre overlapping of the laser pulses. Higher pulse energy (250 μJ), higher scanning speed (1000 mm/s) and moderate line spacing (20 μm) caused accumulation of tensile residual stresses during the final stage of laser ablation. The deviation of experimental residual stresses from COMSOL numerical model was attributed to unaccounted additional stresses induced during thermal spraying process and deformation potentials in the numerical model.     

Role of Zinc (Zn) in Human Reproduction: A Journey from Initial Spermatogenesis to Childbirth

Zinc (Zn), the second-most necessary trace element, is abundant in the human body. The human body lacks the capacity to store Zn; hence, the dietary intake of Zn is essential for various functions and metabolism. The uptake of Zn during its transport through the body is important for proper development of the three major accessory sex glands: the testis, epididymis, and prostate. It plays key roles in the initial stages of germ cell development and spermatogenesis, sperm cell development and maturation, ejaculation, liquefaction, the binding of spermatozoa and prostasomes, capacitation, and fertilization. The prostate releases more Zn into the seminal plasma during ejaculation, and it plays a significant role in sperm release and motility. During the maternal, labor, perinatal, and neonatal periods, the part of Zn is vital. The average dietary intake of Zn is in the range of 8–12 mg/day in developing countries during the maternal period. Globally, the dietary intake of Zn varies for pregnant and lactating mothers, but the average Zn intake is in the range of 9.6–11.2 mg/day. The absence of Zn and the consequences of this have been discussed using critical evidence. The events and functions of Zn related to successful fertilization have been summarized in detail. Briefly, our current review emphasizes the role of Zn at each stage of human reproduction, from the spermatogenesis process to childbirth. The role of Zn and its supplementation in in vitro fertilization (IVF) opens opportunities for future studies on reproductive biology.     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Simple schemes for parallel acquisition of spreading sequences inDS/SS systems

Suboptimal parallel schemes for the acquisition of spreading sequences in chip-asynchronous spread-spectrum systems are considered. These acquisition schemes estimate the unknown delay of the received signal with respect to a locally generated spreading code. Two schemes are presented which are considerably easier to implement than the optimal estimator. An analytical expression is given for the error probability of the simpler of the two schemes, and it is shown that the average error probability of this scheme decreases exponentially with the signal-to-noise ratio. Numerical results show that the performance of both suboptimal estimators is comparable to that of the optimal estimator     

Sulfated zirconia catalysts: Are Brønsted acid sites the source of the activity?

The thermal decomposition products of pyridinium sulfate differ from those of pyridinium sulfate supported on zirconia which in turn differs from that of pyridine adsorbed on a sulfated zirconia. Unsupported pyridinium sulfate decomposes to produce pyridine and sulfuric acid, and these subsequently react to produce oxides of carbon and sulfur. Zirconia that is sulfated and then exposed to pyridine does not release detectable amount of pyridine during heating in an inert gas; rather the pyridine undergoes oxidation reduction reactions simultaneously to release CO₂ and sulfur compounds. Pyridinium sulfate supported on zirconia decomposes upon heating to release pyridine and sulfuric acid, which reacts with the zirconia. The desorption of pyridine in one case and only CO₂/SO_x in the other case suggests that sulfated zirconia does not contain Brønsted acidity that can form pyridinium sulfate.