ASSESSMENT OF WATER QUALITY OF THATIPUDI RESERVOIR OF VIZIANAGARAM DISTRICT OF ANDHRA PRADESH

The authors present work deals with the assessment of the water quality of the water samples collected from Thatipudi reservoir situated in Vizianagaram district of Andhra Pradesh, by analyzing some selected physico-chemical parameters and chosen heavy metals. Water quality parameters such as pH, EC, DO, COD, BOD, TDS, total hardness, calcium, magnesium, sodium, potassium, iron, chloride, nitrite, phosphate, carbonate, bicarbonate and heavy metals such as zinc, manganese, lead and chromium were analyzed for the water samples collected from the reservoir. The results were compared with the standard values prescribed by IS 10500. The parameters such as SAR, RSC, and Mg hazardous were analyzed and it was found that all these values were within the prescribed limit value. Saturation index values of the water samples analyzed were found to be in the range of 0.3-0.84 indicating, Water is supersaturated with respect to calcium carbonate (CaCO3) and scale forming may occur, but non corrosive..  KEYWORDS:Dams, Thatipudi reservoir water quality, physico-chemical charactersÂ

A study on the prevalence of obesity and metabolic syndrome among students of a medical college

Background: Obesity is emerging as a serious problem throughout the world. The overall life expectancy is significantly shortened and the quality of life decreased in those who are excessively overweight. Metabolic syndrome (MetS) is characterized by a constellation of individual risk factors of cardiovascular disease. Central obesity is a key feature of this syndrome, reflecting the fact that the syndrome’s prevalence is driven by strong relationship between waist circumference and increasing obesity. Awareness about MetS in medical students is the need of the hour.Methods: This cross-sectional study was conducted at Dr. PSIMS and RF, Chinnoutpalli, Andhra Pradesh, India involving 400 medical students. A pre-tested questionnaire, measurement of blood pressure, fasting glucose level, fasting lipid profile, anthropometric variables such as height, weight, waist circumference and hip circumference were taken. Metabolic syndrome was defined based on the International Diabetes Federation criteria. Data was processed using SPSS version 16. T-test, chi-square test, fisher’s exact test, anova and odd’s ratio were used for statistical analysis.Results: 59% of the study population was female. The prevalence of obesity was 4%, with majority being males (81.25%) The MetS prevalence as per the International diabetes federation (IDF) criteria was 6% (n=24). The prevalence of MetS in males was 12.19% (n=20) and in females 1.69%. (n=4). The risk of developing metabolic syndrome is high among those who smoke, consume alcohol, consume junk food and sleep for longer durations.Conclusions: The prevalence of metabolic syndrome is 6%. A significant association is established between life style habits like smoking, alcohol consumption, junk food consumption, sleep duration and MetS

Security enhanced sentence similarity computing model based on convolutional neural network

Deep learning model shows great advantages in various fields. However, researchers pay attention to how to improve the accuracy of the model, while ignoring the security considerations. The problem of controlling the judgment result of deep learning model by attack examples and then affecting the system decision-making is gradually exposed. In order to improve the security of sentence similarity analysis model, we propose a convolution neural network model based on attention mechanism. First of all, the mutual information between sentences is correlated by attention weighting. Then, it is input into improved convolutional neural network. In addition, we add attack examples to the input, which is generated by the firefly algorithm. In the attack example, we replace the words in the sentence to some extent, which results in the adversarial data with great semantic change but slight sentence structure change. To a certain extent, the addition of attack example increases the ability of model to identify adversarial data and improves the robustness of the model. Experimental results show that the accuracy, recall rate and F1 value of the model are due to other baseline models.This work was supported in part by the Major Scientific and Technological Projects of China National Petroleum Corporation (CNPC) under Grant ZD2019-183-006, in part by the Shandong Provincial Natural Science Foundation, China, under Grant ZR2020MF006, in part by the Fundamental Research Funds for the Central Universities of China University of Petroleum (East China) under Grant 20CX05017A, and in part by the Open Foundation of State Key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications) under Grant SKLNST-2021-1-17.Postprint (author's final draft

Observation of spin glass state in weakly ferromagnetic Sr2_2FeCoO6_6 double perovskite

We report the observation of spin glass state in the double perovskite oxide Sr$_{2}$FeCoO$_{6}$ prepared through sol-gel technique. Initial structural studies using x rays reveal that the compound crystallizes in tetragonal $I 4/m$ structure with lattice parameters, $a$ = 5.4609(2) \AA and $c$ = 7.7113(7) \AA. The temperature dependent powder x ray studies reveal no structural phase transition in the temperature range 10 -- 300 K. However, the unit cell volume shows an anomaly coinciding with the magnetic transition temperature thereby suggesting a close connection between lattice and magnetism. Neutron diffraction studies and subsequent bond valence sums analysis show that in Sr$_{2}$FeCoO$_{6}$, the $B$ site is randomly occupied by Fe and Co in the mixed valence states of Fe$^{3+}$/Fe$^{4+}$ and Co$^{3+}$/Co$^{4+}$. The random occupancy and mixed valence sets the stage for inhomogeneous magnetic exchange interactions and in turn, for the spin glass like state in this double perovskite which is observed as an irreversibility in temperature dependent dc magnetization at $T_f\sim$ 75 K. Thermal hysteresis observed in the magnetization profile of Sr$_{2}$FeCoO$_{6}$ is indicative of the mixed magnetic phases present. The dynamic magnetic susceptibility displays characteristic frequency dependence and confirms the spin glass nature of this material. Dynamical scaling analysis of $\chi'(T)$ yields a critical temperature $T_{ct}$ = 75.14(8) K and an exponent $z\nu$ = 6.2(2) typical for spin glasses. The signature of presence of mixed magnetic interactions is obtained from the thermal hysteresis in magnetization of Sr$_{2}$FeCoO$_{6}$. Combining the neutron and magnetization results of Sr$_2$FeCoO$_6$, we deduce the spin states of Fe to be in low spin while that of Co to be in low spin and intermediate spin.Comment: 23 pages, 6 figures, accepted in J. Appl. Phy

Modulation of Sn concentration in ZnO nanorod array: intensification on the conductivity and humidity sensing properties

Tin (Sn)-doped zinc oxide (ZnO) nanorod arrays (TZO) were synthesized onto aluminum-doped ZnO-coated glass substrate via a facile sonicated sol–gel immersion method for humidity sensor applications. These nanorod arrays were grown at different Sn concentrations ranging from 0.6 to 3 at.%. X-ray diffraction patterns showed that the deposited TZO arrays exhibited a wurtzite structure. The stress/strain condition of the ZnO film metamorphosed from tensile strain/compressive stress to compressive strain/tensile stress when the Sn concentrations increased. Results indicated that 1 at.% Sn doping of TZO, which has the lowest tensile stress of 0.14 GPa, generated the highest conductivity of 1.31 S cm− 1. In addition, 1 at.% Sn doping of TZO possessed superior sensitivity to a humidity of 3.36. These results revealed that the optimum performance of a humidity-sensing device can be obtained mainly by controlling the amount of extrinsic element in a ZnO film

Yeast expressed recombinant Hemagglutinin protein of Novel H1N1 elicits neutralising antibodies in rabbits and mice

Currently available vaccines for the pandemic Influenza A (H1N1) 2009 produced in chicken eggs have serious impediments viz limited availability, risk of allergic reactions and the possible selection of sub-populations differing from the naturally occurring virus, whereas the cell culture derived vaccines are time consuming and may not meet the demands of rapid global vaccination required to combat the present/future pandemic. Hemagglutinin (HA) based subunit vaccine for H1N1 requires the HA protein in glycosylated form, which is impossible with the commonly used bacterial expression platform. Additionally, bacterial derived protein requires extensive purification and refolding steps for vaccine applications. For these reasons an alternative heterologous system for rapid, easy and economical production of Hemagglutinin protein in its glycosylated form is required. The HA gene of novel H1N1 A/California/04/2009 was engineered for expression in Pichia pastoris as a soluble secreted protein. The full length HA- synthetic gene having α-secretory tag was integrated into P. pastoris genome through homologous recombination. The resultant Pichia clones having multiple copy integrants of the transgene expressed full length HA protein in the culture supernatant. The Recombinant yeast derived H1N1 HA protein elicited neutralising antibodies both in mice and rabbits. The sera from immunised animals also exhibited Hemagglutination Inhibition (HI) activity. Considering the safety, reliability and also economic potential of Pichia expression platform, our preliminary data indicates the feasibility of using this system as an alternative for large-scale production of recombinant influenza HA protein in the face of influenza pandemic threat

Relative Burden of Large CNVs on a Range of Neurodevelopmental Phenotypes

While numerous studies have implicated copy number variants (CNVs) in a range of neurological phenotypes, the impact relative to disease severity has been difficult to ascertain due to small sample sizes, lack of phenotypic details, and heterogeneity in platforms used for discovery. Using a customized microarray enriched for genomic hotspots, we assayed for large CNVs among 1,227 individuals with various neurological deficits including dyslexia (376), sporadic autism (350), and intellectual disability (ID) (501), as well as 337 controls. We show that the frequency of large CNVs (>1 Mbp) is significantly greater for ID–associated phenotypes compared to autism (p = 9.58×10−11, odds ratio = 4.59), dyslexia (p = 3.81×10−18, odds ratio = 14.45), or controls (p = 2.75×10−17, odds ratio = 13.71). There is a striking difference in the frequency of rare CNVs (>50 kbp) in autism (10%, p = 2.4×10−6, odds ratio = 6) or ID (16%, p = 3.55×10−12, odds ratio = 10) compared to dyslexia (2%) with essentially no difference in large CNV burden among dyslexia patients compared to controls. Rare CNVs were more likely to arise de novo (64%) in ID when compared to autism (40%) or dyslexia (0%). We observed a significantly increased large CNV burden in individuals with ID and multiple congenital anomalies (MCA) compared to ID alone (p = 0.001, odds ratio = 2.54). Our data suggest that large CNV burden positively correlates with the severity of childhood disability: ID with MCA being most severely affected and dyslexics being indistinguishable from controls. When autism without ID was considered separately, the increase in CNV burden was modest compared to controls (p = 0.07, odds ratio = 2.33)

Mechanical and Water Absorption Characterization of Mango Seed Shell/Epoxy Composite for Low Load Carrying Structures

The present work deals with the characterization of mango seed shell fiber reinforced epoxy composites by using hand layup method by varying the volume composition of the mango seed shell from 0 vol. % to 60 vol. % (M-0 to M-60). The physical density test, tensile test, flexural test, and water absorption test were conducted as per the American Society for Testing and Materials (ASTM) standards. Results revealed that the tensile strength of M-20 (20 vol. %) is 43% more than a neat epoxy, while the flexural strength of M-50 (50 vol. %) is greater than 10.85% more than a neat epoxy. The water absorption test was conducted by immersing the samples in distilled water at room temperature, and the weight of the specimens was measured and recorded at every 24-hour time interval. For all composite samples, saturation in water absorption and thickness swelling were observed after 432 hours of water immersion. The moisture absorption increases with the inclusion of reinforcements as compared to the neat epoxy samples. However, for the M-50 composite, the water absorption decreases due to the uniform mixing and stronger bonding between the matrix and the reinforcements. The scanning electron microscope (SEM) images of the composite specimens also depicted the particulate fiber distribution and the presence of micro-voids in the epoxy matrix

Experimental Investigation on Density and Volume Fraction of Void, and Mechanical Characteristics of Areca Nut Leaf Sheath Fiber-Reinforced Polymer Composites

Natural fiber-reinforced polymer composite is a rapidly growing topic of research due to the simplicity of obtaining composites that is biodegradable and environmentally friendly. The resulting composites have mechanical properties comparable to synthetic fiber-reinforced composites. In this regard, the present work is formulated with the objectives related to the development, characterization, and optimization of the wt% of reinforcements and the process parameters. The novelty of this work is related to the identification and standardization of the appropriate wt% of reinforcements and parameters for the processing of the areca nut leaf sheath fiber-based polymer composites for enhanced performance attributes. With this basic purview and scope, the composites are synthesized using the hand layup process, and the composite samples of various fiber compositions (20%, 30%, 40%, and 50%) are fabricated. The mechanical characteristics of biodegradable polymer composites reinforced with areca nut leaf sheath fibers are investigated in the present work, with a focus on the effect of fiber composition (tensile properties, flexural strength, and impact strength). The properties of composites are enhanced by combining the areca nut leaf sheath fiber and epoxy resin, with a fiber content of 50% being the optimal wt%. The Scanning electron microscopy (SEM) investigations also ascertain this by depicting the good interfacial adhesion between the areca nut leaf sheath fiber and the epoxy resin. The tensile strength of the composite specimen reinforced with 50% areca nut fiber increases to 44.6 MPa, while the young’s modulus increases to 1900 MPa, flexural strength increases to 64.8 MPa, the flexural modulus increases to 37.9 GPa, and impact strength increases to 34.1 k J/m2. As a result, the combination of areca nut leaf sheath fiber reinforced epoxy resin shows considerable potential as a renewable and biodegradable polymer composite. Furthermore, areca nut leaf sheath fiber-reinforced epoxy resin composites are likely to replace petroleum-based polymers in the future. The ecosustainability and biodegradability of the composite specimen alongside the improved mechanical characteristics serve as the major highlight of the present work, and can help the polymer composite industry to further augment the synthetic matrix and fiber-based composites with the natural fiber-reinforced composites