Metal casting energy efficient metrics for material selection of automotive parts

The automotive sector is one of the main end-use markets for metal casting worldwide. The strong competitive pressure typical of this industry have been influenced in the recent years by sustainability as a new factor promoted by legislation, increased societal awareness of relevant instances and resource scarcity. Energy efficiency, although only a part of sustainability, is important for the metal casting practice because of its nature of large consumer of energy per unit product. Therefore, the effective use of appropriate energy efficient metrics in foundries is of great interest. In this work, a set of indicators developed by the authors (and derived by traditional metrics) to analyse the energy performance of foundries will be used to compare high pressure die casting processes producing car transfer cases with different suitable materials. On the basis of this analysis, it will be shown that the most energy efficient material can be identified whereas the traditional metrics cannot detect such opportunity

Gene and protein nomenclature in public databases

BACKGROUND: Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap. RESULTS: We compiled five gene and protein name dictionaries for each of the five model organisms (yeast, fly, mouse, rat, and human) from different organism-specific and general public databases. We analyzed the degree of ambiguity of gene and protein names within and between dictionaries, to a lexicon of common English words and domain-related non-gene terms, and we compared different data sources in terms of size of extracted dictionaries and overlap of synonyms between those. The study shows that the number of genes/proteins and synonyms covered in individual databases varies significantly for a given organism, and that the degree of ambiguity of synonyms varies significantly between different organisms. Furthermore, it shows that, despite considerable efforts of co-curation, the overlap of synonyms in different data sources is rather moderate and that the degree of ambiguity of gene names with common English words and domain-related non-gene terms varies depending on the considered organism. CONCLUSION: In conclusion, these results indicate that the combination of data contained in different databases allows the generation of gene and protein name dictionaries that contain significantly more used names than dictionaries obtained from individual data sources. Furthermore, curation of combined dictionaries considerably increases size and decreases ambiguity. The entries of the curated synonym dictionary are available for manual querying, editing, and PubMed- or Google-search via the ProThesaurus-wiki. For automated querying via custom software, we offer a web service and an exemplary client application

Building the process-drug–side effect network to discover the relationship between biological Processes and side effects

<p>Abstract</p> <p>Background</p> <p>Side effects are unwanted responses to drug treatment and are important resources for human phenotype information. The recent development of a database on side effects, the side effect resource (SIDER), is a first step in documenting the relationship between drugs and their side effects. It is, however, insufficient to simply find the association of drugs with biological processes; that relationship is crucial because drugs that influence biological processes can have an impact on phenotype. Therefore, knowing which processes respond to drugs that influence the phenotype will enable more effective and systematic study of the effect of drugs on phenotype. To the best of our knowledge, the relationship between biological processes and side effects of drugs has not yet been systematically researched.</p> <p>Methods</p> <p>We propose 3 steps for systematically searching relationships between drugs and biological processes: enrichment scores (ES) calculations, t-score calculation, and threshold-based filtering. Subsequently, the side effect-related biological processes are found by merging the drug-biological process network and the drug-side effect network. Evaluation is conducted in 2 ways: first, by discerning the number of biological processes discovered by our method that co-occur with Gene Ontology (GO) terms in relation to effects extracted from PubMed records using a text-mining technique and second, determining whether there is improvement in performance by limiting response processes by drugs sharing the same side effect to frequent ones alone.</p> <p>Results</p> <p>The multi-level network (the process-drug-side effect network) was built by merging the drug-biological process network and the drug-side effect network. We generated a network of 74 drugs-168 side effects-2209 biological process relation resources. The preliminary results showed that the process-drug-side effect network was able to find meaningful relationships between biological processes and side effects in an efficient manner.</p> <p>Conclusions</p> <p>We propose a novel process-drug-side effect network for discovering the relationship between biological processes and side effects. By exploring the relationship between drugs and phenotypes through a multi-level network, the mechanisms underlying the effect of specific drugs on the human body may be understood.</p

Effects of Compression and Collective Expansion on Particle Emission from Central Heavy-Ion Reactions

Conditions under which compression occurs and collective expansion develops in energetic reactions of heavy nuclei, are analyzed, together with their effects on emitted light baryons and pions. Within transport simulations, it is shown that shock fronts perpendicular to beam axis form in head-on reactions. The fronts separate hot compressed matter from normal. As impact parameter increases, the angle of inclination of the fronts relative to beam axis decreases, and in-between the fronts a weak tangential discontinuity develops. Hot matter exposed to the vacuum in directions perpendicular to shock motion (and parallel to fronts), starts to expand sideways, early within reactions. Expansion in the direction of shock motion follows after the shocks propagate through nuclei, but due to the delay does not acquire same strength. Expansion affects angular distributions, mean-energy components, shapes of spectra and mean energies of different particles emitted into any one direction, and further particle yields. Both the expansion and a collective motion associated with the weak discontinuity, affect the magnitude of sideward flow within reaction plane. Differences in mean particle energy components in and out of the reaction plane in semicentral collisions, depend sensitively on the relative magnitude of shock speed in normal matter and speed of sound in hot matter.Comment: 71 pages, 33 figures (available on request), report MSUCL-94

Normalizing biomedical terms by minimizing ambiguity and variability

<p>Abstract</p> <p>Background</p> <p>One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of the terms. Soft string matching is a possible solution to the problem, but its inherent heavy computational cost discourages its use when the dictionaries are large or when real time processing is required. A less computationally demanding approach is to normalize the terms by using heuristic rules, which enables us to look up a dictionary in a constant time regardless of its size. The development of good heuristic rules, however, requires extensive knowledge of the terminology in question and thus is the bottleneck of the normalization approach.</p> <p>Results</p> <p>We present a novel framework for discovering a list of normalization rules from a dictionary in a fully automated manner. The rules are discovered in such a way that they minimize the ambiguity and variability of the terms in the dictionary. We evaluated our algorithm using two large dictionaries: a human gene/protein name dictionary built from BioThesaurus and a disease name dictionary built from UMLS.</p> <p>Conclusions</p> <p>The experimental results showed that automatically discovered rules can perform comparably to carefully crafted heuristic rules in term mapping tasks, and the computational overhead of rule application is small enough that a very fast implementation is possible. This work will help improve the performance of term-concept mapping tasks in biomedical information extraction especially when good normalization heuristics for the target terminology are not fully known.</p

Stationary Black Holes: Uniqueness and Beyond

The spectrum of known black-hole solutions to the stationary Einstein equations has been steadily increasing, sometimes in unexpected ways. In particular, it has turned out that not all black-hole-equilibrium configurations are characterized by their mass, angular momentum and global charges. Moreover, the high degree of symmetry displayed by vacuum and electro-vacuum black-hole spacetimes ceases to exist in self-gravitating non-linear field theories. This text aims to review some developments in the subject and to discuss them in light of the uniqueness theorem for the Einstein-Maxwell system.Comment: Major update of the original version by Markus Heusler from 1998. Piotr T. Chru\'sciel and Jo\~ao Lopes Costa succeeded to this review's authorship. Significantly restructured and updated all sections; changes are too numerous to be usefully described here. The number of references increased from 186 to 32

Long-term follow-up after cancer rehabilitation using high-intensity resistance training: persistent improvement of physical performance and quality of life

The short-term beneficial effects of physical rehabilitation programmes after cancer treatment have been described. However, little is known regarding the long-term effects. The purpose of this study was to investigate the long-term effects of high-intensity resistance training compared with traditional recovery. A total of 68 cancer survivors who completed an 18-week resistance training programme were followed for 1 year. During the 1-year follow-up, 19 patients dropped out (14 due to recurrence of cancer). The remaining 49 patients of the intervention group were compared with a group of 22 patients treated with chemotherapy in the same period but not participating in any rehabilitation programme. Outcome measures were muscle strength, cardiopulmonary function, fatigue, and health-related quality of life. One year after completion of the rehabilitation programme, the outcome measures in the intervention group were still at the same level as immediately after rehabilitation. Muscle strength at 1 year was significantly higher in patients who completed the resistance training programme than in the comparison group. High-intensity resistance training has persistent effects on muscle strength, cardiopulmonary function, quality of life, and fatigue. Rehabilitation programmes for patients treated with chemotherapy with a curative intention should include high-intensity resistance training in their programme

Role for the Mammalian Swi5-Sfr1 Complex in DNA Strand Break Repair through Homologous Recombination

In fission yeast, the Swi5-Sfr1 complex plays an important role in homologous recombination (HR), a pathway crucial for the maintenance of genomic integrity. Here we identify and characterize mammalian Swi5 and Sfr1 homologues. Mouse Swi5 and Sfr1 are nuclear proteins that form a complex in vivo and in vitro. Swi5 interacts in vitro with Rad51, the DNA strand-exchange protein which functions during HR. By generating Swi5−/− and Sfr1−/− embryonic stem cell lines, we found that both proteins are mutually interdependent for their stability. Importantly, the Swi5-Sfr1 complex plays a role in HR when Rad51 function is perturbed in vivo by expression of a BRC peptide from BRCA2. Swi5−/− and Sfr1−/− cells are selectively sensitive to agents that cause DNA strand breaks, in particular ionizing radiation, camptothecin, and the Parp inhibitor olaparib. Consistent with a role in HR, sister chromatid exchange induced by Parp inhibition is attenuated in Swi5−/− and Sfr1−/− cells, and chromosome aberrations are increased. Thus, Swi5-Sfr1 is a newly identified complex required for genomic integrity in mammalian cells with a specific role in the repair of DNA strand breaks

Polymorphous adenocarcinoma of the salivary glands : reappraisal and update

Although relatively rare, polymorphous adenocarcinoma (PAC) is likely the second most common malignancy of the minor salivary glands (MiSG). The diagnosis is mainly based on an incisional biopsy. The optimal treatment comprises wide surgical excision, often with adjuvant radiotherapy. In general, PAC has a good prognosis. Previously, PAC was referred to as polymorphous low-grade adenocarcinoma (PLGA), but the new WHO classification of salivary gland tumours has also included under the PAC subheading, the so-called cribriform adenocarcinoma of minor salivary glands (CAMSG). This approach raised controversy, predominantly because of possible differences in clinical behaviour. For example, PLGA (PAC, classical variant) only rarely metastasizes, whereas CAMSG often shows metastases to the neck lymph nodes. Given the controversy, this review reappraises the definition, epidemiology, clinical presentation, diagnostic work-up, genetics, treatment modalities, and prognosis of PAC of the salivary glands with a particular focus on contrasting differences with CAMSG.Peer reviewe

ANK, a Host Cytoplasmic Receptor for the Tobacco mosaic virus Cell-to-Cell Movement Protein, Facilitates Intercellular Transport through Plasmodesmata

Plasmodesma (PD) is a channel structure that spans the cell wall and provides symplastic connection between adjacent cells. Various macromolecules are known to be transported through PD in a highly regulated manner, and plant viruses utilize their movement proteins (MPs) to gate the PD to spread cell-to-cell. The mechanism by which MP modifies PD to enable intercelluar traffic remains obscure, due to the lack of knowledge about the host factors that mediate the process. Here, we describe the functional interaction between Tobacco mosaic virus (TMV) MP and a plant factor, an ankyrin repeat containing protein (ANK), during the viral cell-to-cell movement. We utilized a reverse genetics approach to gain insight into the possible involvement of ANK in viral movement. To this end, ANK overexpressor and suppressor lines were generated, and the movement of MP was tested. MP movement was facilitated in the ANK-overexpressing plants, and reduced in the ANK-suppressing plants, demonstrating that ANK is a host factor that facilitates MP cell-to-cell movement. Also, the TMV local infection was largely delayed in the ANK-suppressing lines, while enhanced in the ANK-overexpressing lines, showing that ANK is crucially involved in the infection process. Importantly, MP interacted with ANK at PD. Finally, simultaneous expression of MP and ANK markedly decreased the PD levels of callose, β-1,3-glucan, which is known to act as a molecular sphincter for PD. Thus, the MP-ANK interaction results in the downregulation of callose and increased cell-to-cell movement of the viral protein. These findings suggest that ANK represents a host cellular receptor exploited by MP to aid viral movement by gating PD through relaxation of their callose sphincters