Decision-making through a fuzzy hybrid AI system for selection of a third-party operations and maintenance provider

With the outsourcing and the increasing demand of facilities management services, we observe the growing of multi-technical contracts in real estate operations and maintenance (O&M). Selection of one or more contractors is actually complex and important financial and quality of service challenges depend on it. The present paper proposes a multiple-criteria decision-making tool whose objective is to predict contractors\u27 performances and to select the one who can best respond to O&M demands. In order to build the heuristic between technical, commercial and quality criteria and the expected performances, a neuro-fuzzy system (NFS) associated with a hybrid and adaptive genetic algorithms (GA) method has been developed. Important problems are considered: data pre-processing, problem of data scarcity to provide a sufficient number of data to the NFS and optimisation of hybridisation or adaptation parameters for GA. A case study, concerning the clients\u27 satisfaction levels for O&M contractors as a final indicator for decision-making will prove the relevance of this approach

Mediating punitiveness: understanding public attitudes towards work-related fatality cases

This paper concerns an empirical investigation into public attitudes towards work-related fatality cases, where organizational offenders cause the death of workers or members of the public. This issue is particularly relevant following the introduction of the Corporate Manslaughter and Corporate Homicide Act 2007 into UK law. Here, as elsewhere, the use of criminal law against companies reflects governmental concerns over public confidence in the law’s ability to regulate risk. The empirical findings demonstrate that high levels of public concern over these cases do not translate into punitive attitudes. Such cases are viewed rationally and constructively, and lead to instrumental rather than purely expressive enforcement preferences

Predicting the public health benefit of vaccinating cattle against Escherichia coli O157

Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle–human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human–animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases

Comprehensive Genetic Landscape of Uveal Melanoma by Whole-Genome Sequencing.

Uveal melanoma (UM) is a rare intraocular tumor that, similar to cutaneous melanoma, originates from melanocytes. To gain insights into its genetics, we performed whole-genome sequencing at very deep coverage of tumor-control pairs in 33 samples (24 primary and 9 metastases). Genome-wide, the number of coding mutations was rather low (only 17 variants per tumor on average; range 7-28), thus radically different from cutaneous melanoma, where hundreds of exonic DNA insults are usually detected. Furthermore, no UV light-induced mutational signature was identified. Recurrent coding mutations were found in the known UM drivers GNAQ, GNA11, BAP1, EIF1AX, and SF3B1. Other genes, i.e., TP53BP1, CSMD1, TTC28, DLK2, and KTN1, were also found to harbor somatic mutations in more than one individual, possibly indicating a previously undescribed association with UM pathogenesis. De novo assembly of unmatched reads from non-coding DNA revealed peculiar copy-number variations defining specific UM subtypes, which in turn could be associated with metastatic transformation. Mutational-driven comparison with other tumor types showed that UM is very similar to pediatric tumors, characterized by very few somatic insults and, possibly, important epigenetic changes. Through the analysis of whole-genome sequencing data, our findings shed new light on the molecular genetics of uveal melanoma, delineating it as an atypical tumor of the adult for which somatic events other than mutations in exonic DNA shape its genetic landscape and define its metastatic potential

Genomic and transcriptomic landscape of conjunctival melanoma.

Conjunctival melanoma (CJM) is a rare but potentially lethal and highly-recurrent cancer of the eye. Similar to cutaneous melanoma (CM), it originates from melanocytes. Unlike CM, however, CJM is relatively poorly characterized from a genomic point of view. To fill this knowledge gap and gain insight into the genomic nature of CJM, we performed whole-exome (WES) or whole-genome sequencing (WGS) of tumor-normal tissue pairs in 14 affected individuals, as well as RNA sequencing in a subset of 11 tumor tissues. Our results show that, similarly to CM, CJM is also characterized by a very high mutation load, composed of approximately 500 somatic mutations in exonic regions. This, as well as the presence of a UV light-induced mutational signature, are clear signs of the role of sunlight in CJM tumorigenesis. In addition, the genomic classification of CM proposed by TCGA seems to be well-applicable to CJM, with the presence of four typical subclasses defined on the basis of the most frequently mutated genes: BRAF, NF1, RAS, and triple wild-type. In line with these results, transcriptomic analyses revealed similarities with CM as well, namely the presence of a transcriptomic subtype enriched for immune genes and a subtype enriched for genes associated with keratins and epithelial functions. Finally, in seven tumors we detected somatic mutations in ACSS3, a possible new candidate oncogene. Transfected conjunctival melanoma cells overexpressing mutant ACSS3 showed higher proliferative activity, supporting the direct involvement of this gene in the tumorigenesis of CJM. Altogether, our results provide the first unbiased and complete genomic and transcriptomic classification of CJM

The Density Matrix Renormalization Group for finite Fermi systems

The Density Matrix Renormalization Group (DMRG) was introduced by Steven White in 1992 as a method for accurately describing the properties of one-dimensional quantum lattices. The method, as originally introduced, was based on the iterative inclusion of sites on a real-space lattice. Based on its enormous success in that domain, it was subsequently proposed that the DMRG could be modified for use on finite Fermi systems, through the replacement of real-space lattice sites by an appropriately ordered set of single-particle levels. Since then, there has been an enormous amount of work on the subject, ranging from efforts to clarify the optimal means of implementing the algorithm to extensive applications in a variety of fields. In this article, we review these recent developments. Following a description of the real-space DMRG method, we discuss the key steps that were undertaken to modify it for use on finite Fermi systems and then describe its applications to Quantum Chemistry, ultrasmall superconducting grains, finite nuclei and two-dimensional electron systems. We also describe a recent development which permits symmetries to be taken into account consistently throughout the DMRG algorithm. We close with an outlook for future applications of the method.Comment: 48 pages, 17 figures Corrections made to equation 19 and table

Dissociable effects of 5-HT2C receptor antagonism and genetic inactivation on perseverance and learned non-reward in an egocentric spatial reversal task

Cognitive flexibility can be assessed in reversal learning tests, which are sensitive to modulation of 5-HT2C receptor (5-HT2CR) function. Successful performance in these tests depends on at least two dissociable cognitive mechanisms which may separately dissipate associations of previous positive and negative valence. The first is opposed by perseverance and the second by learned non-reward. The current experiments explored the effect of reducing function of the 5-HT2CR on the cognitive mechanisms underlying egocentric reversal learning in the mouse. Experiment 1 used the 5-HT2CR antagonist SB242084 (0.5 mg/kg) in a between-groups serial design and Experiment 2 used 5-HT2CR KO mice in a repeated measures design. Animals initially learned to discriminate between two egocentric turning directions, only one of which was food rewarded (denoted CS+, CS−), in a T- or Y-maze configuration. This was followed by three conditions; (1) Full reversal, where contingencies reversed; (2) Perseverance, where the previous CS+ became CS− and the previous CS− was replaced by a novel CS+; (3) Learned non-reward, where the previous CS− became CS+ and the previous CS+ was replaced by a novel CS-. SB242084 reduced perseverance, observed as a decrease in trials and incorrect responses to criterion, but increased learned non-reward, observed as an increase in trials to criterion. In contrast, 5-HT2CR KO mice showed increased perseverance. 5-HT2CR KO mice also showed retarded egocentric discrimination learning. Neither manipulation of 5-HT2CR function affected performance in the full reversal test. These results are unlikely to be accounted for by increased novelty attraction, as SB242084 failed to affect performance in an unrewarded novelty task. In conclusion, acute 5-HT2CR antagonism and constitutive loss of the 5-HT2CR have opposing effects on perseverance in egocentric reversal learning in mice. It is likely that this difference reflects the broader impact of 5HT2CR loss on the development and maintenance of cognitive function

Depth-specific fluctuations of gene expression and protein abundance modulate the photophysiology in the seagrass <i>Posidonia oceanica</i>

Here we present the results of a multiple organizational level analysis conceived to identify acclimative/adaptive strategies exhibited by the seagrass Posidonia oceanica to the daily fluctuations in the light environment, at contrasting depths. We assessed changes in photophysiological parameters, leaf respiration, pigments, and protein and mRNA expression levels. The results show that the diel oscillations of P. oceanica photophysiological and respiratory responses were related to transcripts and proteins expression of the genes involved in those processes and that there was a response asynchrony between shallow and deep plants probably caused by the strong differences in the light environment. The photochemical pathway of energy use was more effective in shallow plants due to higher light availability, but these plants needed more investment in photoprotection and photorepair, requiring higher translation and protein synthesis than deep plants. The genetic differentiation between deep and shallow stands suggests the existence of locally adapted genotypes to contrasting light environments. The depth-specific diel rhythms of photosynthetic and respiratory processes, from molecular to physiological levels, must be considered in the management and conservation of these key coastal ecosystems

Tissue Specific Profiling of Females of Schistosoma japonicum by Integrated Laser Microdissection Microscopy and Microarray Analysis

Schistosomes are parasitic worms responsible for important human diseases in tropical and developing nations. There is urgent need to develop new drugs and vaccines to augment current treatments for this disease. In recent years, concerted efforts by many laboratories have led to extensive genetic sequencing of the parasites, and the publication of genome sequence for two agents of schistosomiasis appears imminent. This genetic information has revealed many molecules expressed by the schistosome parasites for which no functional information is available. This lack of information extends to ignorance of where in the complex multicellular schistosome parasites the genes are expressed. We integrated two molecular and cellular techniques to address these knowledge gaps. We used laser microdissection microscopy to dissect small but highly important tissues involved in nutrition and reproduction from sections of female Schistosoma japonicum. From these dissected tissues we then used a broad molecular biology method to identify the multiple genes active in these tissues. Our approach has allowed us to formulate the basis of a “gene atlas” for schistosome parasites, defining the expression repertoire of specific tissues. The better understanding of the roles of tissues in parasite biology, especially in development, reproduction and interactions with its human hosts, should promote future investigations into pathogenesis and control of these significant parasites