Polypropylene woven fabric: A good mulch material for young rubber plants

In young rubber   plantations, dry leaf, coco tree mat, polypropylene woven fabric and coir   pith were evaluated as agricultural mulch materials for their influence on   soil moisture conservation, weed control, soil temperature and microflora,   plant growth and durability in two field experiments. The experiments were   conducted in a drought susceptible clone (RRII 105) and a comparatively   drought tolerant clone (RRII 430) at Chimoni Estate, Thrissur district, a   drought-prone area in Kerala. The effects of different treatments were   similar in both the experiments irrespective of clones. Though dry leaf and   coir pith were effective in soil moisture conservation, they remained in the   field for one season only and failed to control weeds during rainy season.   Coco tree mat conserved moisture and also smothered weeds in plant basins. However,   it remained in the field for almost one year only before it was completely   decomposed. Polypropylene woven fabric improved soil moisture retention, as   well as suppressed weed growth and was found durable. Though mulching reduced   the adverse effects of summer, significant impact on soil microflora and   plant growth was not manifested. Polypropylene woven fabric appears to be a   good alternative mulch material for Hevea

Polychloroprene Rubber/Reduced Graphene Oxide (RGO) Nanomembranes for Pervaporation Separation of Azeotropic Mixtures

Chloroprene rubber is a high performance elastomer with remarkable ageing, heat and oil resistance. A new class of elastomeric nanocomposite was prepared by incorporating reduced graphene oxide (RGO) into chloroprene rubber (CR). RGO is synthesised from natural graphite, through GO route via Hummer's method. This paper focuses on the influence of reduced graphene oxide on chloroprene rubber based elastomeric composites and their pervaporation separation of azeotropic liquid mixtures. The effect of concentration of RGO on separation factor, pervaporation separation index (PSI) and flux of the membranes were analysed. Chloroprene loaded with 0.9 phr (parts per hundred rubber) RGO shows an improved permeation rate among all other membranes while chloroform/acetone (80/20) azeotropic liquid mixture was used as feed solution. Flux increases with increasing the concentration of filler, reaches an optimum value and then decreases. Interestingly PSI also shows similar trend

Hydrophilic Nanocomposite Membranes for the Pervaporation Separation of Water - Ethanol Azeotropic Mixtures

Bentonite nanoclay reinforced Poly (vinyl alcohol) (PVA) nanocomposite membranes were used for the separation of azeotropic composition of water – ethanol mixtures by pervaporation process. Fourier – transform infrared (FTIR) spectroscopic studies revealed the interaction of bentonite nanoclay and the PVA matrix. The dispersion and distribution of nanoclay in the polymer matrix was demonstrated by transmission electron microscopic analysis (TEM). The intrinsic membrane properties with filler loading were also investigated. The results indicate that the hydrophilic nature of the nanoclay influenced the pervaporation to a greater extent. The hydrophilic nature and surface roughness of the nanocomposite membranes was analyzed by atomic force microscopic (AFM) analysis. The pervaporation process illustrates that the permeation flux increases and the separation factor decreases with nanoclay loading. The instrinsic selectivity, which reflects the membrane performance was maximum for 1 wt% clay loaded membranes. PVA with 1 wt% nanoclay loading showed better pervaporation performance. The separation factor of the 1 wt% nanoclay membranes increased to 13, i.e. nearly 4 times more than that of neat PVA membranes. Membrane selectivity also increased to 254% than that of pristine PVA membranes. Thus at lower filler loading, maximum separation was achieved. The increase in nanoclay loading is favorable to improve intrinsic permeance at the cost of decrease in selectivit

Transport of organic solvents through natural rubber/nitrile rubber/organically modified montmorillonite nanocomposites

International audienceThe article describes the transport phenomenon of some commonly used laboratory organic solvents which differ in their solubility parameter value through polymer blend nanocomposites membrane prepared by melt mixing. The three solvents that were used are hexane, toluene and xylene which differed widely in their solubility parameter values. The motivation for the study was to know the effect of solubility parameter on the diffusion transport properties of NR/NBR (natural rubber/nitrile rubber) blends. The solvent uptake, diffusion, sorption and permeation constants were investigated and were found to decrease with organically modified montmorillonite (OMt) content at lower loading. The mode of transport through NR/NBR nano-composites was found to be anomalous. The difference in solubility parameter value greatly influenced the transport properties. The dependence of various properties on OMt content was supported by morphological analysis data. The effect of blend ratio, solvent size and OMt loading on the diffusion of aromatic and aliphatic solvents through NR/ NBR blend systems were investigated. The swelling coefficient values also decreased upon the addition of fillers indicating the presence of hindered path for solvents to diffuse into the polymer matrix. The better reinforcement at lower filler loading was confirmed from the cross-link density values and mechanical properties. The transport data obtained were applied to mathematical models for predicting the diffusion behaviour through nanocomposite membranes and to elucidate the physical mechanism of transport

Pattern of congenital abnormalities in a tertiary hospital and its impact on neonatal mortality

Background: Congenital abnormalities are major contributors of neonatal mortality and stillbirths. However, there is not sufficient data in our country on the prevalence of various congenital malformations and their impact on neonatal mortality. Objectives: To study the prevalence and pattern of congenital anomalies among neonates delivered in a tertiary hospital setting in 3 years and its impact on perinatal and neonatal mortality. Materials and Methods: This hospital based prospective descriptive study was undertaken at tertiary care hospital in Kerala. All babies born in the hospital from January 2013 to December 2015 (3 years) were included in the study. The baby was examined by a pediatrician during the first 24 h to identify any birth defects. A detailed history including familial and gestational factors was taken in babies with birth defects. Photographs, radiographs, ultrasound examination, echocardiography, and chromosomal studies were undertaken as required. The details were entered in a pro forma. The anomalies are classified as per ICD-10 criteria. Results were analyzed by simple statistical techniques recording number and percentage of cases. Results: The prevalence of birth defects in live born newborn was 1.9% whereas, in stillbirths, it was 15.3%. Congenital anomalies also contributed a major risk factor for neonatal death as 22% of the newborns, died in the immediate neonatal period, had some form of congenital anomaly. The major maternal risk factor found to be associated with congenital anomalies was gestational diabetes (21.3%). The patterns of congenital anomalies were musculoskeletal anomalies (25%), central nervous system (18%), genitourinary system (14%), congenital diaphragmatic hernia (12%), cardiovascular system (10%), gastrointestinal (7%), syndromes (6%), non-immune hydrops (5%), and others (3%). Conclusion: Prevalence of birth defects in this birth cohort was 1.9% comparable to other Indian data. In Kerala, one of the major causes of perinatal and neonatal mortality is congenital malformations

Synthesis of Carbon Nanoparticles and Study of Bioaccumulation in Seeds and its Application in Plant Fortification

The aim of the study is to carry out green synthesis of carbon nanoparticles and to study its applications in plant fortification and to analyze the bioaccumulation of minerals in the seeds. The synthesis of carbon nanoparticles was by pyrolysis of coconut milk. The average particle size and surface morphology was determined by scanning electron microscope, UV spectroscopy was used to find the optical spectra, Raman spectroscopy was conducted for comparing Raman shift and the crystallite size was calculated by (XRD) analysis. The soil used for cultivation was also analyzed before and after addition of carbon nanoparticles and the changes in pH and amount of minerals and organic matter was studied and showed improved soil characteristics after addition of carbon nanoparticles in a 1:10 ratio. The growth of a monocot and dicot plant species were analyzed as control and test for up to 22 days to study the effect of carbon nanoparticles on physical and chemical parameters of the plant. The results did show a significant rate of increase in root and shoot length of the test plants. Chemical parameters such as concentration of IAA, amount of protein and estimation of chlorophyll was determined by Salkowski test, Lowry’s test and Chlorophyll estimation test respectively which also showed positive results to the addition of carbon nanoparticles. There was also a significant increase in magnesium content in the seeds which proved mineral bioaccumulation in the soil as a result of carbon nanoparticle addition

Mechanics and Pervaporation Performance of Ionic Liquid Modified CNT Based SBR Membranes - A Case Study for the Separation of Toluene/Heptane Mixtures

SBR/ionic liquid modified CNT Nanocomposites were prepared using different concentration of CNT. Nano scale dispersion of CNT affected the properties of SBR. The results have been compared with the unfilled SBR films. Cure characteristics and mechanical properties such as tensile strength, modulus, abrasion resistance and hardness were measured for different composites. Morphological behaviour and structural characteristics of the composites were investigated by AFM, TEM, FTIR and Raman spectroscopy. Microstructural development in presence of filler and interfacial interaction between modified CNT and polymer matrix led to enhanced properties. The pervaporation performances of membranes were analysed using a toluene/heptane mixture. Membranes displayed high selectivity towards heptane. The influence of feed composition on pervaporation was also analysed. The 5 phr CNT loaded membrane showed enhanced membrane permeance and selectivity value, an improvement of 18% over the neat polymer. A drop in selectivity and an increase in permeation rate were observed at higher CNT loadings

Toxicity Evaluation and Biocompatibility of Nanostructured Biomaterials

Biomaterials have occupied a prominent place in regenerative procedures to restore human health. Moreover, there is a greater need in understanding, analyzing and establishing their toxicity profile. These, when made into nano-sized constructions called nanostructured biomaterials, their regenerative potential is enhanced, which could influence their toxicity nature. This chapter intends to give comprehensive information on their nanotoxicology pathways at the cellular level, their entry pathways into the human body, and their potential consequences on human health. It clearly explains the cytocompatibility and biocompatibility of various nanostructured biomaterials for potential human health applications like drug delivery and tissue engineering. A detailed overview of various in vitro and in vivo evaluation methods of biocompatibility of nanomaterials are outlined in this chapter that researchers should address as they move forward in developing new systems for the field of regeneration

Car Recommendation Using Machine Learning

<p>Abstract-- As the amounts of cars booking are exponentially Increasing because of that finding relevant cars are important to those who purchase cars, for this a Personal recommendation systems have been emerged to conduct effective search which mine most booked cars based on user rating and interest. This paper proposed an effective system for recommending cars for online users that rated a car using the content based filtering or collaborative filtering and then found out the best cars and suggest them. For this system, two datasets have been used one about the different cars and the other one about the rating for the cars by different users. In this work KNN algorithm is used to find best cars according to the user taste. To implement this system Pycharm is used as a developing software. Many python libraries like pandas, numpy, scipy, sklearn etc. is used.</p&gt

Prominence of seasonal water quality assessment in a tropical river using multivariate analysis: Kerala, India

Abstract An account of seasonal water quality variability has been taken as a proxy for the changes of environmental setting occurring in the catchment areas and helps to illustrate the ecological system processes associated with it. The present study in Meenachil River (L = 78 km, A = 1272 km2) comprising of stations from upstream to downstream for pre monsoon (PRM), monsoon (MON) and post monsoon (POM). Ca2+ and SO4 2− show an erratic trend while extreme deviations were observed at S6 and S7 stations. Na+, K+, Cl−, DIC and DOC showed a similar trend in most stations, i.e. (PRM > POM > MON). Significant rise of DIC and DOC at S7 during POM and PRM could explicate changes ensued in adjacent Vembanad lake system. Strong correlations of DIC and DOC for Na+, K+ and Cl− ions were noted in the study. HCA dendrogram reveals that ion chemistry in S6 and S7 was strictly controlled by neighbouring lake water dynamics. The results demonstrate high F1 variance of 73, 68 and 72% followed by F2 comprising of 17, 19 and 21% for PRM, MON and POM, respectively. General understanding into the autochthonous process associated within the river lake interface region was evident from the nutrient variability scenario