Recycling of EOL CRT glass into ceramic glaze formulations and its environmental impact by LCA approach

Background, Aims and Scope The interest in recycling materials at the end of their life is growing in the industry in general. As regards the Wastes of Electrical and Electronic Equipment (WEEE), an appreciable increase of these materials has been noticed in the last decades, 117 · 10³ tons of WEEE have been produced in Italy in 2002 according to Ecohitech [1] and the increase in this kind of waste is three times higher than that of the municipal waste according to the FISE ASSOAMBIENTE report [2]. Within WEEE, End-of-Life Cathode Ray Tube (EOL CRT) glass, the main part of TV sets and PC monitors, is here analysed using both a technical approach to establish a possible reuse of the glass in a open-loop recycling field (ceramic industry) and a methodology (LCA) capable of providing environmental evaluations. Methods The technological characterization was performed by chemical resistance tests (UNI EN ISO 10545-13), staining tests (UNI EN ISO 10545-14) with blue methylene and potassium permanganate (KMnO₄), and surface abrasion tests (UNI EN ISO 10545-7). The LCA study was conducted using the SimaPro 5.0 software and Eco-Indicator 99 as an evaluation method. Results and Discussion The good technical results, reached by using cleaned EOL CRT panel glass inside a ceramic glaze formulation instead of a commercial frit, are supported by the environmental impact evaluation, which shows a decrease of the overall potential damage (measured in Points) of 36% and, in particular, a reduction of 53% in ‘Human health’, 31% in ‘Eco-system quality’ and 24% in ‘Resources’. Conclusions This study has demonstrated that this new, open-loop recycling strategy for the CRT glass significantly reduces the environmental impact of the ceramic glaze production process. In fact, in all damage categories examined in this study, there is a minor impact. An improvement is evident in the respiratory inorganics sub-category related to the lowering of dusts mainly and to a lesser amount with NO_x and SO_x in the climate change sub-category, due mainly to the reduction of CO₂ emission correlated to the avoided combustion of the mixture which feeds melting furnaces in the frit production. Thus, the damage decrease in ‘Ecosystem quality’ is prevalently due to the lower NO_x emissions by the kilns in the frit production that is evident in the acidification/eutrophication sub-category. Finally, the significant saving in the ‘Resource’ category is principally linked to the fossil fuels sub-category, thanks to the methane saving which stokes the melting furnaces. Perspectives Furthermore, the decrease in CO₂ emission (94.4%) evident in the climate change sub-category is a very important topic because it is in line with the Kyoto protocol (1997), where significant efforts have been exerted for the reduction of the green house gases emission, notably CO₂. The CO₂ emission is correlated to the combustion of the mixture which feeds melting kilns in the frit production, therefore the recycling of secondary raw materials, already in a glass state, can reduce the emissions of this gas. This reduction can be termed as environmental credit and it is an example of an allocation of environmental loads in a open-loop recycling, where waste from one industrial system are used as raw materials in another product system.     

Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models

We consider a semiparametric regression model that relates a normal outcome to covariates and a genetic pathway, where the covariate effects are modeled parametrically and the pathway effect of multiple gene expressions is modeled parametrically or nonparametrically using least-squares kernel machines (LSKMs). This unified framework allows a flexible function for the joint effect of multiple genes within a pathway by specifying a kernel function and allows for the possibility that each gene expression effect might be nonlinear and the genes within the same pathway are likely to interact with each other in a complicated way. This semiparametric model also makes it possible to test for the overall genetic pathway effect. We show that the LSKM semiparametric regression can be formulated using a linear mixed model. Estimation and inference hence can proceed within the linear mixed model framework using standard mixed model software. Both the regression coefficients of the covariate effects and the LSKM estimator of the genetic pathway effect can be obtained using the best linear unbiased predictor in the corresponding linear mixed model formulation. The smoothing parameter and the kernel parameter can be estimated as variance components using restricted maximum likelihood. A score test is developed to test for the genetic pathway effect. Model/variable selection within the LSKM framework is discussed. The methods are illustrated using a prostate cancer data set and evaluated using simulations.     

iTIS-PseTNC: A sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition

Translation is a key process for gene expression. Timely identification of the translation initiation site (TIS) is very important for conducting in-depth genome analysis. With the avalanche of genome sequences generated in the postgenomic age, it is highly desirable to develop automated methods for rapidly and effectively identifying TIS. Although some computational methods were proposed in this regard, none of them considered the global or long-range sequence-order effects of DNA, and hence their prediction quality was limited. To count this kind of effects, a new predictor, called “iTIS-PseTNC,” was developed by incorporating the physicochemical properties into the pseudo trinucleotide composition, quite similar to the PseAAC (pseudo amino acid composition) approach widely used in computational proteomics. It was observed by the rigorous cross-validation test on the benchmark dataset that the overall success rate achieved by the new predictor in identifying TIS locations was over 97%. As a web server, iTIS-PseTNC is freely accessible at http://lin.uestc.edu.cn/server/iTIS-PseTNC. To maximize the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web server to obtain the desired results without the need to go through detailed mathematical equations, which are presented in this paper just for the integrity of the new prection method.     

Effects of bilateral medial knee osteoarthritis on intra- and inter-limb contributions to body support during gait

Patients with knee OA show altered gait patterns, affecting their quality of living. The current study aimed to quantify the effects of bilateral knee OA on the intra-limb and inter-limb sharing of the support of the body during gait. Fifteen patients with mild, 15 with severe bilateral knee OA, and 15 healthy controls walked along a walkway while the kinematic and kinetic data were measured. Compared with the controls, the patients significantly reduced their knee extensor moments and the corresponding contributions to the total support moment in the sagittal plane (p<0.05). For compensation, the mild OA group significantly increased the hip extensor moments (p<0.05) to maintain close-to-normal support and a more symmetrical inter-limb load-sharing during double-limb support. The severe OA group involved compensatory actions of both the ankle and hip, but did not succeed in maintaining a normal sagittal total support moment during late stance, nor a symmetrical inter-limb load-sharing during double-limb support. In the frontal plane, the knee abductor moments and the corresponding contributions to the total support moment were not affected by the changes in the other joints, regardless of the severity of the disease. The observed compensatory changes suggest that strengthening of weak hip muscles is essential for body support during gait in patients with knee OA, but that training of weak ankle muscles may also be needed for patients with severe knee OA.     

Functional annotation of putative hypothetical proteins from Candida dubliniensis

An extensive analysis of C. dubliniensis proteomics data showed that ~ 22% protein are conserved hypothetical proteins (HPs) whose function is still not determined precisely. Analysis of gene sequence of HPs provides a platform to establish sequence–function relationships to a more profound understanding of the molecular machinery of organisms at systems level. Here we have combined the latest versions of bioinformatics tools including, protein family, motifs, intrinsic features from the amino acid sequence, sequence–function relationship, pathway analysis, etc. to assign a precise function to HPs for which no any experimental information is available. Our results show that 27 HPs have well defined functions and we categorized them as enzyme, nucleic acid binding, transport protein, etc. Five HPs showed adhesin character that is likely to be essential for the survival of yeast and pathogenesis. We also addressed issues related to the sub-cellular localization and signal peptide identification which provides an idea about its colocalization and function. The outcome of the present study may facilitate better understanding of mechanism of virulence, drug resistance, pathogenesis, adaptability to host, tolerance for host immune response, and drug discovery for treatment of C. dubliniensis infections.     

从灾害救援特点看新时期心理卫生支援分队建设

根据自然灾害医学救援要求及组织体制,结合灾害救援过程中的心理压力来源及心理需求,提出心理卫生支援分队建设指导:人员需具备专业技能,兼顾全面技术;采取的工作方式主要为团体合作、小组协作和单人干预等;日常训练重点在于做好实战训练、预案、心理和物资方面的准备,力求使心理卫生支援分队满足新时期非战争军事任务的需要。     

Predicting rRNA-, RNA-, and DNA-binding proteins from primary structure with support vector machines

In the post-genome era, the prediction of protein function is one of the most demanding tasks in the study of bioinformatics. Machine learning methods, such as the support vector machines (SVMs), greatly help to improve the classification of protein function. In this work, we integrated SVMs, protein sequence amino acid composition, and associated physicochemical properties into the study of nucleic-acid-binding proteins prediction. We developed the binary classifications for rRNA-, RNA-, DNA-binding proteins that play an important role in the control of many cell processes. Each SVM predicts whether a protein belongs to rRNA-, RNA-, or DNA-binding protein class. Self-consistency and jackknife tests were performed on the protein data sets in which the sequences identity was < 25%. Test results show that the accuracies of rRNA-, RNA-, DNA-binding SVMs predictions are approximately 84%, approximately 78%, approximately 72%, respectively. The predictions were also performed on the ambiguous and negative data set. The results demonstrate that the predicted scores of proteins in the ambiguous data set by RNA- and DNA-binding SVM models were distributed around zero, while most proteins in the negative data set were predicted as negative scores by all three SVMs. The score distributions agree well with the prior knowledge of those proteins and show the effectiveness of sequence associated physicochemical properties in the protein function prediction. The software is available from the author upon request.     

The use of Silver-coated Ceramic Beads for Sterilization of Sphingomonas sp. in Drinking Mineral Water

Summary It has been established that certain heavy metals including silver have antibacterial properties, and that they may be useful components of antibacterial materials. This knowledge of the antibacterial activity of silver has already been put to use to decrease the occurrence of urinary catheter infections and to develop topical antibacterial agents for burn victims. In this study, the ability of silver-coated ceramic beads (Ag-CBs), sintered at 375, 400, 425, or 450 °C, to sterilize Sphingomonas sp. in commercial mineral water was evaluated. Over 3% (w/v) Ag-CBs in mineral water completely sterilized Sphingomonas sp. after 6 h, regardless of the sintering temperature. The Ag-CBs sintered at 400 °C were the most useful since they did not produce clouding in the water and the bacteria were effectively killed. The antimicrobial activity of the 400 °C-sintered Ag-CBs was comparable to that of free silver ions at 15 μg/l, showing that the silver ions released from the Ag-CBs resulted in the complete sterilization of the microbial cells in mineral water. These results suggest that Ag-CBs present an easy-to-use option for mineral water sterilization.     

麻醉电子病历是手术麻醉信息管理系统的核心

近几年来医院的信息化发展已经向"以患者诊疗为中心"的临床信息系统(Clinical Information System,CIS)进行转变,然而目前的手术麻醉信息管理系统(Anesthesia Information Management System,MMS)大多还停留在以麻醉记录单自动生成为中心,减轻医生的工作负担为目的,提供科室管理功能的麻醉科临床应用系统。这样的AIMS已经不适应医院信息化发展的需要,只有建立以麻醉电子病历为核心的手术麻醉信息管理系统才能更好的融入到临床信息系统当中。     

Predicting DNA-binding proteins: approached from Chou’s pseudo amino acid composition and other specific sequence features

Summary. DNA-binding proteins play a pivotal role in gene regulation. It is vitally important to develop an automated and efficient method for timely identification of novel DNA-binding proteins. In this study, we proposed a method based on alone the primary sequences of proteins to predict the DNA-binding proteins. DNA-binding proteins were encoded by autocross-covariance transform, pseudo-amino acid composition, dipeptide composition, respectively and also the different combinations of the three encoded methods; further, these feature matrices were applied to support vector machine classifiers to predict the DNA-binding proteins. All modules were trained and validated by the jackknife cross-validation test. Through comparing the performance of these substituted modules, the best result was obtained from pseudo-amino acid composition with the overall accuracy of 96.6% and the sensitivity of 90.7%. The results suggest that it can efficiently predict the novel DNA-binding proteins only using the primary sequences. Authors’ address: Menglong Li, College of Chemistry, Sichuan University, Chengdu, Sichuan 610064, P.R. China