Cradle to Cradle and Whole-Life Carbon assessment - Barriers and opportunities towards a circular economic building sector

The general awareness of climate change has been increasing steadily while buildings continue to be the main contributors to greenhouse gas emissions. To address the need for change in the building industry and transform its hazardous impacts on the environment to a positive footprint, circular economic design approaches and Whole-Life Carbon (WLC) assessment have been introduced. This paper analyses the main barriers for a successful implementation of the regenerative Cradle to Cradle (C2C) concept and WLC evaluation, identifying the lack of unified and measurable framework along with the deficiency of detailed case studies and post occupancy evaluation. In the context of the increasing demand for carbon accounting, obtaining comprehensive information on embodied carbon in buildings is challenging despite the existing Life Cycle Assessment structure. To link theory with practice, the paper discusses the London School of Economics Centre Buildings Redevelopment by RSH+P as case study. It reveals barriers and opportunities for WLC evaluation as well as the potential of life cycle cost optimization in environmental and economic terms. The paper concludes with a reflection on how the certification of materials through material passports may not only achieve a higher transparency but lead to a circular economic building industry by comprehensive WLC assessment and a closer implementation of reversible building design corresponding to the C2C principles. The potential of combining WLC evaluation with C2C strategies and translating them into a comprehensive, unified assessment framework for a circular building sector is identified

Modulated structure in the martensite phase of Ni1.8Pt0.2MnGa: a neutron diffraction study

7M orthorhombic modulated structure in the martensite phase of Ni1.8Pt0.2MnGa is reported by powder neutron diffraction study, which indicates that it is likely to exhibit magnetic field induced strain. The change in the unit cell volume is less than 0.5% between the austenite and martensite phases, as expected for a volume conserving martensite transformation. The magnetic structure analysis shows that the magnetic moment in the martensite phase is higher compared to Ni2MnGa, which is in good agreement with magnetization measurement

Health profile of government aided private school children in urban slum of Solapur, Southern Maharashtra, India

Background: Malnutrition is a silent emergency and its prevalence is high among children under five years of age. The school children in present study belongs to lower middle income families and their parents are working in unorganised sectors like handloom textile mills, construction sites worker, domestic bidi worker. Hence the study was planned to understand their health profile including morbidity pattern and sociodemographic profile and their nutritional status and grade of malnutrition according to World Health Organisation (WHO) growth reference standards.Methods: The present descriptive cross sectional Study was carried out among 767 students from class Lower Kindergarten to 7th standard of government aided private school. A pre-designed and pre-tested questionnaire was used to interview and examine all the participated students. Grading of malnutrition was carried out using WHO reference tables. Chi square test of significance was applied.Results: A total of 767 students participated in this study. Boys were 513 (66%) and girls were 254 (33%).Most common morbidity found to be dental caries 55% .Out of 537 children 339 (63%) were underweight. Out of 767 children 302 (39%) had stunting, 272 (35%) had thinness and 26 (3%) were found to be obese. Two (0.32%) study subjects had suspect cardiac problems.Conclusions: The present study shows pattern of morbidities and malnutrition among school children. Comprehensive periodic health check-up should be carried out for early diagnosis and treatment of the common morbidities. Further studies should be carried out to assess the impact of health education.

Generalized Gravi-Electromagnetism

A self consistant and manifestly covariant theory for the dynamics of four charges (masses) (namely electric, magnetic, gravitational, Heavisidian) has been developed in simple, compact and consistent manner. Starting with an invariant Lagrangian density and its quaternionic representation, we have obtained the consistent field equation for the dynamics of four charges. It has been shown that the present reformulation reproduces the dynamics of individual charges (masses) in the absence of other charge (masses) as well as the generalized theory of dyons (gravito - dyons) in the absence gravito - dyons (dyons). key words: dyons, gravito - dyons, quaternion PACS NO: 14.80H

Origin of Ferroelectricity in Orthorhombic LuFeO3_3

We demonstrate that small but finite ferroelectric polarization ($\sim$0.01 $\mu$C/cm$^2$) emerges in orthorhombic LuFeO$_3$ ($Pnma$) at $T_N$ ($\sim$600 K) because of commensurate (k = 0) and collinear magnetic structure. The synchrotron x-ray and neutron diffraction data suggest that the polarization could originate from enhanced bond covalency together with subtle contribution from lattice. The theoretical calculations indicate enhancement of bond covalency as well as the possibility of structural transition to the polar $Pna2_1$ phase below $T_N$. The $Pna2_1$ phase, in fact, is found to be energetically favorable below $T_N$ in orthorhombic LuFeO$_3$ ($albeit$ with very small energy difference) than in isostructural and nonferroelectric LaFeO$_3$ or NdFeO$_3$. Application of electric field induces finite piezostriction in LuFeO$_3$ via electrostriction resulting in clear domain contrast images in piezoresponse force microscopy.Comment: 12 pages, 8 figure

Essential oil composition of petiole of Cinnamomum verum Bercht. & Presl.

Essential oil isolated from the petiole of  Cinnamomum verum was analysed by gaschromatography and gas chromatography-mass spectrometry. Twenty five compoundsaccounting for 87.31% of the total essential oil were identified. (E)-Cinnamaldehyde (33.04%)followed by eugenol (17.32%), linalool (16.85%) and (E)-cinnamyl acetate (11.78%) were themain components of the essential oil. This is the first report on the composition of essentialoil of petiole of C. verum. &nbsp

Silver nanoparticles green synthesis: A mini review

Nanotechnology is a significant field of contemporary research dealing with design, synthesis, and manipulation of particle structures ranging from in the region of 1-100 nm. Nanoparticles (NPs) have broad choice of applications in areas such as fitness care, cosmetics, foodstuff and feed, environmental health, mechanics, optics, biomedical sciences, chemical industries, electronics, space industries, drug-gene delivery, energy science, optoelectronics, catalysis, single electron transistors, light emitters, nonlinear optical devices, and photo-electrochemical applications. Nano Biotechnology is a speedily mounting scientific field of producing and constructing devices, an important area of research in nano biotechnology is the synthesis of NPs with different chemical compositions, sizes and morphologies, and controlled dispersities. Silver nanoparticles (NPs) have been the subjects of researchers because of their unique properties (e.g., size and shape depending optical, antimicrobial, and electrical properties). A variety of preparation techniques have been reported for the synthesis of silver NPs; notable examples include, laser ablation, gamma irradiation, electron irradiation, chemical reduction, photochemical methods, microwave processing, and biological synthetic methods. This assessment presents a general idea of silver nanoparticle preparation. The aim of this analysis article is, therefore, to replicate on the existing state and potential prediction, especially the potentials and limitations of the above mentioned techniques for industries

Exploration of multitrait antagonistic microbes against Fusarium oxysporum f.sp. lycopersici

Fusarium wilt is one of the major diseases of tomato causing extensive loss of production. Exploration of agriculturally important microbes (AIMs) for management of the tomato wilt is an ecofriendly and cost effective approach. In the present study, a total 30 Trichoderma and 30 bacterial isolates were screened in the laboratory for their biocontrol activity against Fusarium oxysporum f.sp. lycopersici (FOL). Out of all the isolates tested, Trichoderma asperellum BHU P-1 and Ochrobactrum sp. BHU PB-1 were found to show maximum inhibition of FOL in dual culture assay. Both the microbes also exhibited plant growth promoting activities such as phosphate solubilisation, production of siderophore, hydrogen cyanide (HCN), indole acetic acid (IAA) and protease activity. These microbes could be evaluated further in greenhouse and field studies for their potential use in management of Fusarium wilt of tomato

BI-69A11 enhances susceptibility of colon cancer cells to mda-7/IL-24-induced growth inhibition by targeting Akt

Background: Akt and its downstream signalling pathways contribute to the aetiology and progression of Colorectal Carcinoma (CRC). Targeting the Akt pathway is an attractive strategy but few chemotherapeutic drugs have been used to treat CRC with only limited success. BI-69A11, a small molecule inhibitor of Akt, efficiently inhibits growth in melanoma cells. Melanoma differentiation associated gene-7 (mda-7)/interleukin-24 promotes cancer-selective apoptosis when delivered by a tropism-modified replication incompetent adenovirus (Ad.5/3-mda-7). However, Ad.5/3-mda-7 displays diminished antitumour efficacy in several CRC cell lines, which correlates with the expression of K-RAS. Methods: The individual and combinatorial effect of BI-69A11 and Ad.5/3-mda-7 in vitro was studied by cell viability, cell cycle, apoptosis and invasion assays in HT29 and HCT116 cells containing wild type or mutant K-ras, respectively. In vivo HT29 tumour xenografts were used to test the efficacy of the combination treatment. Results: BI-69A11 inhibited growth and induced apoptosis in CRC. However, combinatorial treatment was more effective compared with single treatment. This combination showed profound antitumour and anti angiogenic effects in vitro and in vivo by downregulating Akt activity. Conclusions: BI-69A11 enhances the antitumour efficacy of Ad.5/3-mda-7 on CRC overexpressing K-RAS by inducing apoptosis and regulating Akt activity thereby warranting further evaluation in treating CRC

Analysis of Dimensionality Reduction Techniques on Big Data

Due to digitization, a huge volume of data is being generated across several sectors such as healthcare, production, sales, IoT devices, Web, organizations. Machine learning algorithms are used to uncover patterns among the attributes of this data. Hence, they can be used to make predictions that can be used by medical practitioners and people at managerial level to make executive decisions. Not all the attributes in the datasets generated are important for training the machine learning algorithms. Some attributes might be irrelevant and some might not affect the outcome of the prediction. Ignoring or removing these irrelevant or less important attributes reduces the burden on machine learning algorithms. In this work two of the prominent dimensionality reduction techniques, Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) are investigated on four popular Machine Learning (ML) algorithms, Decision Tree Induction, Support Vector Machine (SVM), Naive Bayes Classifier and Random Forest Classifier using publicly available Cardiotocography (CTG) dataset from University of California and Irvine Machine Learning Repository. The experimentation results prove that PCA outperforms LDA in all the measures. Also, the performance of the classifiers, Decision Tree, Random Forest examined is not affected much by using PCA and LDA.To further analyze the performance of PCA and LDA the eperimentation is carried out on Diabetic Retinopathy (DR) and Intrusion Detection System (IDS) datasets. Experimentation results prove that ML algorithms with PCA produce better results when dimensionality of the datasets is high. When dimensionality of datasets is low it is observed that the ML algorithms without dimensionality reduction yields better results