Dark matter annihilation and decay in dwarf spheroidal galaxies: The classical and ultrafaint dSphs

Dwarf spheroidal (dSph) galaxies are prime targets for present and future gamma-ray telescopes hunting for indirect signals of particle dark matter. The interpretation of the data requires careful assessment of their dark matter content in order to derive robust constraints on candidate relic particles. Here, we use an optimised spherical Jeans analysis to reconstruct the `astrophysical factor' for both annihilating and decaying dark matter in 21 known dSphs. Improvements with respect to previous works are: (i) the use of more flexible luminosity and anisotropy profiles to minimise biases, (ii) the use of weak priors tailored on extensive sets of contamination-free mock data to improve the confidence intervals, (iii) systematic cross-checks of binned and unbinned analyses on mock and real data, and (iv) the use of mock data including stellar contamination to test the impact on reconstructed signals. Our analysis provides updated values for the dark matter content of 8 `classical' and 13 `ultrafaint' dSphs, with the quoted uncertainties directly linked to the sample size; the more flexible parametrisation we use results in changes compared to previous calculations. This translates into our ranking of potentially-brightest and most robust targets---viz., Ursa Minor, Draco, Sculptor---, and of the more promising, but uncertain targets---viz., Ursa Major 2, Coma---for annihilating dark matter. Our analysis of Segue 1 is extremely sensitive to whether we include or exclude a few marginal member stars, making this target one of the most uncertain. Our analysis illustrates challenges that will need to be addressed when inferring the dark matter content of new `ultrafaint' satellites that are beginning to be discovered in southern sky surveys.Comment: 19 pages, 14 figures, submitted to MNRAS. Supplementary material available on reques

Performance Enhancement of Deep Reinforcement Learning Networks using Feature Extraction

The combination of Deep Learning and Reinforcement Learning, termed Deep Reinforcement Learning Networks (DRLN), offers the possibility of using a Deep Learning Neural Network to produce an approximate Reinforcement Learning value table that allows extraction of features from neurons in the hidden layers of the network. This paper presents a two stage technique for training a DRLN on features extracted from a DRLN trained on a identical problem, via the implementation of the Q-Learning algorithm, using TensorFlow. The results show that the extraction of features from the hidden layers of the Deep Q-Network improves the learning process of the agent (4.58 times faster and better) and proves the existence of encoded information about the environment which can be used to select the best action. The research contributes preliminary work in an ongoing research project in modeling features extracted from DRLNs

Culture and Psychiatric Evaluation: Operationalizing Cultural Formulation for DSM-5

The Outline for Cultural Formulation (OCF) introduced with DSM-IV provided a framework for clinicians to organize cultural information relevant to diagnostic assessment and treatment planning. However, use of the OCF has been inconsistent, raising questions about the need for guidance on implementation, training, and application in diverse settings. To address this need, DSM-5 introduced a cultural formulation interview (CFI) that operationalizes the process of data collection for the OCF. The CFI includes patient and informant versions and 12 supplementary modules addressing specific domains of the OCF. This article summarizes the literature reviews and analyses of experience with the OCF conducted by the DSM-5 Cross-Cultural Issues Subgroup (DCCIS) that informed the development of the CFI. We review the history and contents of the DSM-IV OCF, its use in training programs, and previous attempts to render it operational through questionnaires, protocols, and semi-structured interview formats. Results of research based on the OCF are discussed. For each domain of the OCF, we summarize findings from the DCCIS that led to content revision and operationalization in the CFI. The conclusion discusses training and implementation issues essential to service delivery

Juvenile Hormone (JH) Esterase of the Mosquito Culex quinquefasciatus Is Not a Target of the JH Analog Insecticide Methoprene

Juvenile hormones (JHs) are essential sesquiterpenes that control insect development and reproduction. JH analog (JHA) insecticides such as methoprene are compounds that mimic the structure and/or biological activity of JH. In this study we obtained a full-length cDNA, cqjhe, from the southern house mosquito Culex quinquefasciatus that encodes CqJHE, an esterase that selectively metabolizes JH. Unlike other recombinant esterases that have been identified from dipteran insects, CqJHE hydrolyzed JH with specificity constant (kcat/KM ratio) and Vmax values that are common among JH esterases (JHEs). CqJHE showed picomolar sensitivity to OTFP, a JHE-selective inhibitor, but more than 1000-fold lower sensitivity to DFP, a general esterase inhibitor. To our surprise, CqJHE did not metabolize the isopropyl ester of methoprene even when 25 pmol of methoprene was incubated with an amount of CqJHE that was sufficient to hydrolyze 7,200 pmol of JH to JH acid under the same assay conditions. In competition assays in which both JH and methoprene were available to CqJHE, methoprene did not show any inhibitory effects on the JH hydrolysis rate even when methoprene was present in the assay at a 10-fold higher concentration relative to JH. Our findings indicated that JHE is not a molecular target of methoprene. Our findings also do not support the hypothesis that methoprene functions in part by inhibiting the action of JHE

European integration assessed in the light of the 'rules vs. standards debate'

The interplay of various legal systems in the European Union (EU) has long triggered a debate on the tension between uniformity and diversity of Member States' (MS) laws. This debate takes place among European legal scholars and is also paralleled by economic scholars, e.g. in the ambit of the 'theory of federalism'. This paper takes an innovative perspective on the discrepancy between 'centralized' and 'decentralized' law-making in the EU by assessing it with the help of the rules versus standards debate. When should the EU legislator grant the national legislator leeway in the formulation of new laws and when should all be fixed ex ante at European level? The literature on the 'optimal shape of legal norms' shall be revisited in the light of law-making in the EU, centrally dealing with the question how much discretion shall be given to the national legislator; and under which circumstances. This paper enhances the established decisive factors for the choice of a rule or a standard in a national setting (complexity, volatility, judges' specialization and frequency of application) by two new crucial factors (switching costs and the benefit of uniformity in terms of information costs) in order to assess law-making policies at EU level

Tire Defect Detection Based on Faster R-CNN

The tire defect detection method can help the rehabilitation robot to achieve autonomous positioning function and improve the accuracy of the robot system behavior. Defects such as foreign matter sidewall, foreign matter tread, and sidewall bubbles will appear in the process of tire production, which will directly or indirectly affect the service life of the tire. Therefore, a novel and efficient tire defect detection method was proposed based on Faster R-CNN. At preprocessing stage, the Laplace operator and the homomorphic filter were used to sharpen and enhance the data set, the gray values of the image target and the background were significantly different, which improved the detection accuracy. Moreover, data expansion was used to increase the number of images and improve the robustness of the algorithm. To promote the accuracy of the position detection and identification, the proposed method combined the convolution features of the third layer and the convolution features of the fifth layer in the ZF network (a kind of convolution neural network). Then, the improved ZF network was used to extract deep characteristics as inputs for Faster R-CNN. From the experiment, the proposed faster R-CNN defect detection method can accurately classify and locate the tire X-ray image defects, and the average test recognition rate is up to 95.4%. Moreover, if there are additional types of defects that need to be detected, then a new detection model can be obtained by fine-tuning the network

Clinical and cost-effectiveness of contingency management for cannabis use in early psychosis: the CIRCLE randomised clinical trial

Background Cannabis is the most commonly used illicit substance among people with psychosis. Continued cannabis use following the onset of psychosis is associated with poorer functional and clinical outcomes. However, finding effective ways of intervening has been very challenging. We examined the clinical and cost-effectiveness of adjunctive contingency management (CM), which involves incentives for abstinence from cannabis use, in people with a recent diagnosis of psychosis. Methods CIRCLE was a pragmatic multi-centre randomised controlled trial. Participants were recruited via Early Intervention in Psychosis (EIP) services across the Midlands and South East of England. They had had at last one episode of clinically diagnosed psychosis (affective or non-affective); were aged 18 to 36; reported cannabis use in at least 12 out of the previous 24 weeks; and were not currently receiving treatment for cannabis misuse, or subject to a legal requirement for cannabis testing. Participants were randomised via a secure web-based service 1:1 to either an experimental arm, involving 12 weeks of CM plus a six-session psychoeducation package, or a control arm receiving the psychoeducation package only. The total potential voucher reward in the CM intervention was £240. The primary outcome was time to acute psychiatric care, operationalised as admission to an acute mental health service (including community alternatives to admission). Primary outcome data were collected from patient records at 18 months post-consent by assessors masked to allocation. The trial was registered with the ISRCTN registry, number ISRCTN33576045. Results: 551 participants were recruited between June 2012 and April 2016. Primary outcome data were obtained for 272 (98%) in the CM (experimental) group and 259 (95%) in the control group. There was no statistically significant difference in time to acute psychiatric care (the primary outcome) (HR 1.03, 95% CI 0.76, 1.40) between groups. By 18 months, 90 (33%) of participants in the CM group, and 85 (30%) of the control groups had been admitted at least once to an acute psychiatric service. Amongst those who had experienced an acute psychiatric admission, the median time to admission was 196 days (IQR 82, 364) in the CM group and 245 days (IQR 99,382) in the control group. Cost-effectiveness analyses suggest that there is an 81% likelihood that the intervention was cost-effective, mainly resulting from higher mean inpatient costs for the control group compared with the CM group, however the cost difference between groups was not statistically significant. There were 58 adverse events, 27 in the CM group and 31 in the control group. Conclusions Overall, these results suggest that CM is not an effective intervention for improving the time to acute psychiatric admission or reducing cannabis use in psychosis, at least at the level of voucher reward offered

The Evolution of a Female Genital Trait Widely Distributed in the Lepidoptera: Comparative Evidence for an Effect of Sexual Coevolution

Sexual coevolution is considered responsible for the evolution of many male genital traits, but its effect on female genital morphology is poorly understood. In many lepidopterans, females become temporarily unreceptive after mating and the length of this refractory period is inversely related to the amount of spermatophore remaining in their genital tracts. Sperm competition can select for males that delay female remating by transferring spermatophores with thick spermatophore envelopes that take more time to be broken. These envelopes could select for signa, sclerotized sharp structures located within the female genital tract, that are used for breaking spermatophores. Thus, this hypothesis predicts that thick spermatophore envelopes and signa evolve in polyandrous species, and that these adaptations are lost when monandry evolves subsequently. Here we test the expected associations between female mating pattern and presence/absence of signa, and review the scant information available on the thickness of spermatophore envelopes.We made a literature review and found information on female mating pattern (monandry/polyandry), presence/absence of signa and phylogenetic position for 37 taxa. We built a phylogenetic supertree for these taxa, mapped both traits on it, and tested for the predicted association by using Pagel's test for correlated evolution. We found that, as predicted by our hypothesis, monandry evolved eight times and in five of them signa were lost; preliminary evidence suggests that at least in two of the three exceptions males imposed monandry on females by means of specially thick spermatophore envelopes. Previously published data on six genera of Papilionidae is in agreement with the predicted associations between mating pattern and the characteristics of spermatophore envelopes and signa.Our results support the hypothesis that signa are a product of sexually antagonistic coevolution with spermatophore envelopes

SnoRNA Snord116 (Pwcr1/MBII-85) Deletion Causes Growth Deficiency and Hyperphagia in Mice

Prader-Willi syndrome (PWS) is the leading genetic cause of obesity. After initial severe hypotonia, PWS children become hyperphagic and morbidly obese, if intake is not restricted. Short stature with abnormal growth hormone secretion, hypogonadism, cognitive impairment, anxiety and behavior problems are other features. PWS is caused by lack of expression of imprinted genes in a ∼4 mb region of chromosome band 15q11.2. Our previous translocation studies predicted a major role for the C/D box small nucleolar RNA cluster SNORD116 (PWCR1/HBII-85) in PWS. To test this hypothesis, we created a ∼150 kb deletion of the >40 copies of Snord116 (Pwcr1/MBII-85) in C57BL/6 mice. Snord116del mice with paternally derived deletion lack expression of this snoRNA. They have early-onset postnatal growth deficiency, but normal fertility and lifespan. While pituitary structure and somatotrophs are normal, liver Igf1 mRNA is decreased. In cognitive and behavior tests, Snord116del mice are deficient in motor learning and have increased anxiety. Around three months of age, they develop hyperphagia, but stay lean on regular and high-fat diet. On reduced caloric intake, Snord116del mice maintain their weight better than wild-type littermates, excluding increased energy requirement as a cause of hyperphagia. Normal compensatory feeding after fasting, and ability to maintain body temperature in the cold indicate normal energy homeostasis regulation. Metabolic chamber studies reveal that Snord116del mice maintain energy homeostasis by altered fuel usage. Prolonged mealtime and increased circulating ghrelin indicate a defect in meal termination mechanism. Snord116del mice, the first snoRNA deletion animal model, reveal a novel role for a non-coding RNA in growth and feeding regulation