Energy end-use flexibility of the next generation of decision-makers in a smart grid setting: an exploratory study

Demand Response (DR) mechanisms have been developed to reshape consumption patterns in face of price signals, enabling to deal with the increasing penetration of intermittent renewable resources and balance electricity demand and supply. Although DR mechanisms have been in place for some time, it is still unclear to what extent end-users are ready, or willing, to embrace DR programs that can be complex and imply adjustments of daily routines. This work aims to understand how the next generation of Portuguese decision makers, namely young adults in higher education, are prepared to deal with energy decisions in the context of the challenges brought by the smart grids. Results demonstrate that cost savings and the contribution to environmental protection are found to be important motivating factors to enroll into DR programs, which should be further exploited in future actions for the promotion of end-user engagement. Moreover, DR solutions are well-accepted by higher education students, although with limited flexibility levels. In addition, there is room to exploit the willingness to adopt time-differentiated tariffs, yet savings should be clearer and more attractive to end-users. Also, the framing effect should be considered when promoting this type of time-differentiated tariffs.This work was partially supported by project grants UID/MULTI/00308/2013 and UID/CEC/00319/2013 and by the European Regional Development Fund through the COMPETE 2020 Programme, FCT—Portuguese Foundation for Science and Technology with in projects ESGRIDS (POCI-01-0145-FEDER-016434), Learn2Behave (02/SAICT/2016-023651), MAnAGER (POCI-01-0145-FEDER-028040), and POCI-01-0145-FEDER-007043, as well as by the Energy for Sustainability Initiative of the University of Coimbra

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Neutrophils in cancer: neutral no more

Neutrophils are indispensable antagonists of microbial infection and facilitators of wound healing. In the cancer setting, a newfound appreciation for neutrophils has come into view. The traditionally held belief that neutrophils are inert bystanders is being challenged by the recent literature. Emerging evidence indicates that tumours manipulate neutrophils, sometimes early in their differentiation process, to create diverse phenotypic and functional polarization states able to alter tumour behaviour. In this Review, we discuss the involvement of neutrophils in cancer initiation and progression, and their potential as clinical biomarkers and therapeutic targets

Task-Specific Codes for Face Recognition: How they Shape the Neural Representation of Features for Detection and Individuation

The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing.Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area".OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information considered. More generally, these findings provide evidence for the computational utility and the neural validity of fragment-based visual representation and recognition

Interactive effects of mGlu5 and 5-HT2A receptors on locomotor activity in mice

RationaleMetabotropic glutamate (mGlu) receptors have been suggested to play a role in neuropsychiatric disorders including schizophrenia, drug abuse, and depression. Because serotonergic hallucinogens increase glutamate release and mGlu receptors modulate the response to serotonin (5-HT)(2A) activation, the interactions between serotonin 5-HT(2A) receptors and mGlu receptors may prove to be important for our understanding of these diseases.ObjectiveWe tested the effects of the serotonergic hallucinogen and 5-HT(2A) agonist, 2,5-dimethoxy-4-methylamphetamine (DOM), and the selective 5-HT(2A) antagonist, M100907, on locomotor activity in the mouse behavioral pattern monitor (BPM) in mGlu5 wild-type (WT) and knockout (KO) mice on a C57 background.ResultsBoth male and female mGlu5 KO mice showed locomotor hyperactivity and diminished locomotor habituation compared with their WT counterparts. Similarly, the mGlu5-negative allosteric modulator 2-methyl-6-(phenylethynyl)pyridine (MPEP) also increased locomotor hyperactivity, which was absent in mGlu5 KO mice. The locomotor hyperactivity in mGlu5 receptor KO mice was potentiated by DOM (0.5 mg/kg, subcutaneously (SC)) and attenuated by M100907 (1.0 mg/kg, SC). M100907 (0.1 mg/kg, SC) also blocked the hyperactivity induced by MPEP.ConclusionsThese studies demonstrated that loss of mGlu5 receptor activity either pharmacologically or through gene deletion leads to locomotor hyperactivity in mice. Additionally, the gene deletion of mGlu5 receptors increased the behavioral response to the 5-HT(2A) agonist DOM, suggesting that mGlu5 receptors either mitigate the behavioral effects of 5-HT(2A) hallucinogens or that mGlu5 KO mice show an increased sensitivity to 5-HT(2A) agonists. Taken together, these studies indicate a functional interaction between mGlu5 and 5-HT(2A) receptors

Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat

To accelerate genetic gains in breeding, physiological trait (PT) characterization of candidate parents can help make more strategic crosses, increasing the probability of accumulating favorable alleles compared to crossing relatively uncharacterized lines. In this study, crosses were designed to complement “source” with “sink” traits, where at least one parent was selected for favorable expression of biomass and/or radiation use efficiency—source—and the other for sink-related traits like harvest-index, kernel weight and grains per spike. Female parents were selected from among genetic resources—including landraces and products of wide-crossing (i.e. synthetic wheat)—that had been evaluated in Mexico at high yield potential or under heat stress, while elite lines were used as males. Progeny of crosses were advanced to the F4 generation within Mexico, and F4-derived F5 and F6 generations were yield tested to populate four international nurseries, targeted to high yield environments (2nd and 3rd WYCYT) for yield potential, and heat stressed environments (2nd and 4th SATYN) for climate resilience, respectively. Each nursery was grown as multi-location yield trials. Genetic gains were achieved in both temperate and hot environments, with most new PT-derived lines expressing superior yield and biomass compared to local checks at almost all international sites. Furthermore, the tendency across all four nurseries indicated either the superiority of the best new PT lines compared with the CIMMYT elite checks, or the superiority of all new PT lines as a group compared with all checks, and in some cases, both. Results support—in a realistic breeding context—the hypothesis that yield and radiation use efficiency can be increased by improving source:sink balance, and validate the feasibility of incorporating exotic germplasm into mainstream breeding efforts to accelerate genetic gains for yield potential and climate resilience

Bone turnover markers in sheep and goat: a review of the scientific literature

Bone turnover markers (BTMs) are product of bone cell activity and are generally divided in bone formation and bone resorption markers. The purpose of this review was to structure the available information on the use of BTMs in studies on small ruminants, especially for monitoring their variations related to diet, exercise, gestation and metabolic lactation state, circadian and seasonal variations, and also during skeletal growth. Pre-clinical and translational studies using BTMs with sheep and goats as animal models in orthopaedic research studies to help in the evaluation of the fracture healing process and osteoporosis research are also described in this review. The available information from the reviewed studies was systematically organized in order to highlight the most promising BTMs in small ruminant research, as well as provide a wide view of the use of sheep and goat as animal models in orthopaedic research, type of markers and commercial assay kits with cross-reactivity in sheep and goat, method of sample and storage of serum and urine for bone turnover markers determination and the usefulness and limitations of bone turnover markers in the different studies, therefore an effective tool for researchers that seek answers to different questions while using BTMs in small ruminants.José Arthur de A. Camassa acknowledges to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, for his PhD scholarship 202248/2015-1.info:eu-repo/semantics/publishedVersio

Genetic Dissection of Acute Ethanol Responsive Gene Networks in Prefrontal Cortex: Functional and Mechanistic Implications

Background Individual differences in initial sensitivity to ethanol are strongly related to the heritable risk of alcoholism in humans. To elucidate key molecular networks that modulate ethanol sensitivity we performed the first systems genetics analysis of ethanol-responsive gene expression in brain regions of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens, and ventral midbrain) across a highly diverse family of 27 isogenic mouse strains (BXD panel) before and after treatment with ethanol. Results Acute ethanol altered the expression of ~2,750 genes in one or more regions and 400 transcripts were jointly modulated in all three. Ethanol-responsive gene networks were extracted with a powerful graph theoretical method that efficiently summarized ethanol\u27s effects. These networks correlated with acute behavioral responses to ethanol and other drugs of abuse. As predicted, networks were heavily populated by genes controlling synaptic transmission and neuroplasticity. Several of the most densely interconnected network hubs, including Kcnma1 and Gsk3β, are known to influence behavioral or physiological responses to ethanol, validating our overall approach. Other major hub genes like Grm3, Pten and Nrg3 represent novel targets of ethanol effects. Networks were under strong genetic control by variants that we mapped to a small number of chromosomal loci. Using a novel combination of genetic, bioinformatic and network-based approaches, we identified high priority cis-regulatory candidate genes, including Scn1b,Gria1, Sncb and Nell2. Conclusions The ethanol-responsive gene networks identified here represent a previously uncharacterized intermediate phenotype between DNA variation and ethanol sensitivity in mice. Networks involved in synaptic transmission were strongly regulated by ethanol and could contribute to behavioral plasticity seen with chronic ethanol. Our novel finding that hub genes and a small number of loci exert major influence over the ethanol response of gene networks could have important implications for future studies regarding the mechanisms and treatment of alcohol use disorders

Following the genes: a framework for animal modeling of psychiatric disorders

The number of individual cases of psychiatric disorders that can be ascribed to identified, rare, single mutations is increasing with great rapidity. Such mutations can be recapitulated in mice to generate animal models with direct etiological validity. Defining the underlying pathogenic mechanisms will require an experimental and theoretical framework to make the links from mutation to altered behavior in an animal or psychopathology in a human. Here, we discuss key elements of such a framework, including cell type-based phenotyping, developmental trajectories, linking circuit properties at micro and macro scales and definition of neurobiological phenotypes that are directly translatable to humans