Biowaste Treatment and Waste-to-Energy - Environmental Benefits

Biowaste represents a significant fraction of municipal solid waste (MSW). Its separate collection is considered as a useful measure to enhance waste management systems in both the developed and developing world. This paper aims to compare the environmental performance of three market-ready technologies currently used to treat biowaste—biowaste composting, fermentation, and biowaste incineration in waste-to-energy (WtE) plants as a component of residual municipal solid waste (RES). Global warming potential (GWP) was applied as an indicator and burdens related to the operation of facilities and credits obtained through the products were identified. The environmental performance of a WtE plant was investigated in detail using a model, implementing an approach similar to marginal-cost and revenues, which is a concept widely applied in economics. The results show that all of the treatment options offer an environmentally friendly treatment (their net GWP is negative). The environmental performance of a WtE plant is profoundly affected by its mode of its operation, i.e., type of energy exported. The concept producing environmental credits at the highest rate is co-incineration of biowaste in a strictly heat-oriented WtE plant. Anaerobic digestion plants treating biowaste by fermentation produce fewer credits, but approximately twice as more credits as WtE plants with power delivery only

Integrated sliding-mode algorithms in robot tracking applications

An integrated solution based on sliding mode ideas is proposed for robotic trajectory tracking. The proposal includes three sliding-mode algorithms for speed auto-regulation, path conditioning and redundancy resolution in order to fulfill velocity, workspace and C-space constraints, respectively. The proposed method only requires a few program lines and simplifies the robot user interface since it directly deals with the fulfillment of the constraints to find a feasible solution for the robot trajectory tracking in a short computation time. The proposed approach is evaluated in simulation on the freely accessible 6R robot model PUMA-560, for which the main features of the method are illustrated.This research is partially supported by research project DPI2011-27845-C02-01 of the Spanish Government (Spain), research projects PAID-05-11-2640 and PAID-00-12-SP20120159 of the Universitat Polit'ecnica de Val'encia (Spain), and research projects ANPCyT PICT-2011-0888, CONICET PIP 112-2011-00361, and UNLP 1164 (Argentina).Gracia Calandin, LI.; Garelli, F.; Sala Piqueras, A. (2013). Integrated sliding-mode algorithms in robot tracking applications. Robotics and Computer-Integrated Manufacturing. 29(1):53-62. https://doi.org/10.1016/j.rcim.2012.07.007S536229

Data mining methods for the prediction of different forms of asthma

The article examines the diagnosis of bronchial asthma, cites the classification of the disease, proves the relevance of this research, and represents the result of primary data analysis by using a powerful tool for data analysis - Rapid Miner

Literacy in Lithuania. Country Report - Children and Adolescents

European Literacy policy network (ELINET

Sensitive Spectroscopic Detection of Large and Denatured Protein Aggregates in Solution by Use of the Fluorescent Dye Nile Red

The fluorescent dye Nile red was used as a probe for the sensitive detection of large, denatured aggregates of the model protein β-galactosidase (E. coli) in solution. Aggregates were formed by irreversible heat denaturation of β-galactosidase below and above the protein’s unfolding temperature of 57.4°C, and the presence of aggregates in heated solutions was confirmed by static light scattering. Interaction of Nile red with β-galactosidase aggregates led to a shift of the emission maximum (λmax) from 660 to 611 nm, and to an increase of fluorescence intensity. Time-resolved fluorescence and fluorescence correlation spectroscopy (FCS) measurements showed that Nile red detected large aggregates with hydrodynamic radii around 130 nm. By steady-state fluorescence measurements, it was possible to detect 1 nM of denatured and aggregated β-galactosidase in solution. The comparison with size exclusion chromatography (SEC) showed that native β-galactosidase and small aggregates thereof had no substantial effect on the fluorescence of Nile red. Large aggregates were not detected by SEC, because they were excluded from the column. The results with β-galactosidase demonstrate the potential of Nile red for developing complementary analytical methods that overcome the size limitations of SEC, and can detect the formation of large protein aggregates at early stages

Ex Vivo Metrics™, a preclinical tool in new drug development

Among the challenges facing translational medicine today is the need for greater productivity and safety during the drug development process. To meet this need, practitioners of translational medicine are developing new technologies that can facilitate decision making during the early stages of drug discovery and clinical development. Ex Vivo Metrics™ is an emerging technology that addresses this need by using intact human organs ethically donated for research. After hypothermic storage, the organs are reanimated by blood perfusion, providing physiologically and biochemically stable preparations. In terms of emulating human exposure to drugs, Ex Vivo Metrics is the closest biological system available for clinical trials. Early application of this tool for evaluating drug targeting, efficacy, and toxicity could result in better selection among promising drug candidates, greater drug productivity, and increased safety

Aβ40 Oligomers Identified as a Potential Biomarker for the Diagnosis of Alzheimer's Disease

Alzheimer's Disease (AD) is the most prevalent form of dementia worldwide, yet the development of therapeutics has been hampered by the absence of suitable biomarkers to diagnose the disease in its early stages prior to the formation of amyloid plaques and the occurrence of irreversible neuronal damage. Since oligomeric Aβ species have been implicated in the pathophysiology of AD, we reasoned that they may correlate with the onset of disease. As such, we have developed a novel misfolded protein assay for the detection of soluble oligomers composed of Aβ x-40 and x-42 peptide (hereafter Aβ40 and Aβ42) from cerebrospinal fluid (CSF). Preliminary validation of this assay with 36 clinical samples demonstrated the presence of aggregated Aβ40 in the CSF of AD patients. Together with measurements of total Aβ42, diagnostic sensitivity and specificity greater than 95% and 90%, respectively, were achieved. Although larger sample populations will be needed to confirm this diagnostic sensitivity, our studies demonstrate a sensitive method of detecting circulating Aβ40 oligomers from AD CSF and suggest that these oligomers could be a powerful new biomarker for the early detection of AD

Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p