A Precise Error Bound for Quantum Phase Estimation

Quantum phase estimation is one of the key algorithms in the field of quantum computing, but up until now, only approximate expressions have been derived for the probability of error. We revisit these derivations, and find that by ensuring symmetry in the error definitions, an exact formula can be found. This new approach may also have value in solving other related problems in quantum computing, where an expected error is calculated. Expressions for two special cases of the formula are also developed, in the limit as the number of qubits in the quantum computer approaches infinity and in the limit as the extra added qubits to improve reliability goes to infinity. It is found that this formula is useful in validating computer simulations of the phase estimation procedure and in avoiding the overestimation of the number of qubits required in order to achieve a given reliability. This formula thus brings improved precision in the design of quantum computers.Comment: 6 page

Community-Centered Responses to Ebola in Urban Liberia: The View from Below

The West African Ebola epidemic has demonstrated that the existing range of medical and epidemiological responses to emerging disease outbreaks is insufficient, especially in post-conflict contexts with exceedingly poor healthcare infrastructures. This study provides baseline information on community-based epidemic control priorities and identifies innovative local strategies for containing EVD in Liberia.In this study the authors analyzed data from the 2014 Ebola outbreak in Monrovia and Montserrado County, Liberia. The data were collected for the purposes of program design and evaluation by the World Health Organization (WHO) and the Government of Liberia (GOL), in order to identify: (1) local knowledge about EVD, (2) local responses to the outbreak, and (3) community based innovations to contain the virus. At the time of data collection, the international Ebola response had little insight into how much local Liberian communities knew about Ebola, and how communities managed the epidemic when they could not get access to care due to widespread hospital and clinic closures. Methods included 15 focus group discussions with community leaders from areas with active Ebola cases. Participants were asked about best practices and what they were currently doing to manage EVD in their respective communities, with the goal of developing conceptual models of local responses informed by local narratives. Findings reveal that communities responded to the outbreak in numerous ways that both supported and discouraged formal efforts to contain the spread of the disease. This research will inform global health policy for both this, and future, epidemic and pandemic responses

Extension of non-minimal derivative coupling theory and Hawking radiation in black-hole spacetime

We study the greybody factor and Hawking radiation with a non-minimal derivative coupling between the scalar field and the curvature in the background of the slowly rotating Kerr-Newman black hole. Our results show that both the absorption probability and luminosity of Hawking radiation of the scalar field increase with the coupling. Moreover, we also find that for the weak coupling $\eta<\eta_c$, the absorption probability and luminosity of Hawking radiation decrease when the black hole's Hawking temperature decreases; while for stronger coupling $\eta>\eta_c$, the absorption probability and luminosity of Hawking radiation increase on the contrary when the black hole's Hawking temperature decreases. This feature is similar to the Hawking radiation in a $d$-dimensional static spherically-symmetric black hole surrounded by quintessence \cite{chensong}.Comment: 17 pages, 6 figures, 1 table, Title changed, Appendix changed, accepted by JHE

Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA – a Bayesian approach

<p>Abstract</p> <p>Background</p> <p>Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge.</p> <p>Results</p> <p>A computing tool (ArrayLeaRNA) has been developed for gene expression analysis. It implements a Bayesian approach which is based on the Gumbel distribution and uses printed genomic DNA control features for normalization and for estimation of the parameters of the Bayesian model and prior knowledge from predicted operon structure. The method is compared with two other approaches: the classical LOWESS normalization followed by a two fold cut-off criterion and the OpWise method (Price, et al. 2006. BMC Bioinformatics. 7, 19), a published Bayesian approach also using predicted operon structure. The three methods were compared on experimental datasets with prior knowledge of gene expression. With ArrayLeaRNA, data normalization is carried out according to the genomic features which reflect the results of equally transcribed genes; also the statistical significance of the difference in expression is based on the variability of the equally transcribed genes. The operon information helps the classification of genes with low confidence measurements.</p> <p>ArrayLeaRNA is implemented in Visual Basic and freely available as an Excel add-in at <url>http://www.ifr.ac.uk/safety/ArrayLeaRNA/</url></p> <p>Conclusion</p> <p>We have introduced a novel Bayesian model and demonstrated that it is a robust method for analysing microarray expression profiles. ArrayLeaRNA showed a considerable improvement in data normalization, in the estimation of the experimental variability intrinsic to each hybridization and in the establishment of a clear boundary between non-changing and differentially expressed genes. The method is applicable to data derived from hybridizations of labelled cDNA samples as well as from hybridizations of labelled cDNA with genomic DNA and can be used for the analysis of datasets where differentially regulated genes predominate.</p

The Pediatric Obsessive-Compulsive Disorder Treatment Study II: rationale, design and methods

This paper presents the rationale, design, and methods of the Pediatric Obsessive-Compulsive Disorder Treatment Study II (POTS II), which investigates two different cognitive-behavior therapy (CBT) augmentation approaches in children and adolescents who have experienced a partial response to pharmacotherapy with a serotonin reuptake inhibitor for OCD. The two CBT approaches test a "single doctor" versus "dual doctor" model of service delivery. A specific goal was to develop and test an easily disseminated protocol whereby child psychiatrists would provide instructions in core CBT procedures recommended for pediatric OCD (e.g., hierarchy development, in vivo exposure homework) during routine medical management of OCD (I-CBT). The conventional "dual doctor" CBT protocol consists of 14 visits over 12 weeks involving: (1) psychoeducation, (2), cognitive training, (3) mapping OCD, and (4) exposure with response prevention (EX/RP). I-CBT is a 7-session version of CBT that does not include imaginal exposure or therapist-assisted EX/RP. In this study, we compared 12 weeks of medication management (MM) provided by a study psychiatrist (MM only) with two types of CBT augmentation: (1) the dual doctor model (MM+CBT); and (2) the single doctor model (MM+I-CBT). The design balanced elements of an efficacy study (e.g., random assignment, independent ratings) with effectiveness research aims (e.g., differences in specific SRI medications, dosages, treatment providers). The study is wrapping up recruitment of 140 youth ages 7–17 with a primary diagnosis of OCD. Independent evaluators (IEs) rated participants at weeks 0,4,8, and 12 during acute treatment and at 3,6, and 12 month follow-up visits

A qualitative study exploring perceptions and attitudes of community pharmacists about extended pharmacy services in Lahore, Pakistan

Background In recent decades, community pharmacies reported a change of business model, whereby a shift from traditional services to the provision of extended roles was observed. However, such delivery of extended pharmacy services (EPS) is reported from the developed world, and there is scarcity of information from the developing nations. Within this context, the present study was aimed to explore knowledge, perception and attitude of community pharmacists (CPs) about EPS and their readiness and acceptance for practice change in the city of Lahore, Pakistan. Methods A qualitative approach was used to gain an in-depth knowledge of the issues. By using a semi-structured interview guide, 12 CPs practicing in the city of Lahore, Pakistan were conveniently selected. All interviews were audio-taped, transcribed verbatim, and were then analyzed for thematic contents by the standard content analysis framework. Results Thematic content analysis yielded five major themes. (1) Familiarity with EPS, (2) current practice of EPS, (3) training needed to provide EPS, (4) acceptance of EPS and (5) barriers toward EPS. Majority of the CPs were unaware of EPS and only a handful had the concept of extended services. Although majority of our study respondents were unaware of pharmaceutical care, they were ready to accept practice change if provided with the required skills and training. Lack of personal knowledge, poor public awareness, inadequate physician-pharmacist collaboration and deprived salary structures were reported as barriers towards the provision of EPS at the practice settings. Conclusion Although the study reported poor awareness towards EPS, the findings indicated a number of key themes that can be used in establishing the concept of EPS in Pakistan. Over all, CPs reported a positive attitude toward practice change provided to the support and facilitation of health and community based agencies in Pakistan

Addressing vulnerability, building resilience:community-based adaptation to vector-borne diseases in the context of global change

Abstract Background The threat of a rapidly changing planet – of coupled social, environmental and climatic change – pose new conceptual and practical challenges in responding to vector-borne diseases. These include non-linear and uncertain spatial-temporal change dynamics associated with climate, animals, land, water, food, settlement, conflict, ecology and human socio-cultural, economic and political-institutional systems. To date, research efforts have been dominated by disease modeling, which has provided limited practical advice to policymakers and practitioners in developing policies and programmes on the ground. Main body In this paper, we provide an alternative biosocial perspective grounded in social science insights, drawing upon concepts of vulnerability, resilience, participation and community-based adaptation. Our analysis was informed by a realist review (provided in the Additional file 2) focused on seven major climate-sensitive vector-borne diseases: malaria, schistosomiasis, dengue, leishmaniasis, sleeping sickness, chagas disease, and rift valley fever. Here, we situate our analysis of existing community-based interventions within the context of global change processes and the wider social science literature. We identify and discuss best practices and conceptual principles that should guide future community-based efforts to mitigate human vulnerability to vector-borne diseases. We argue that more focused attention and investments are needed in meaningful public participation, appropriate technologies, the strengthening of health systems, sustainable development, wider institutional changes and attention to the social determinants of health, including the drivers of co-infection. Conclusion In order to respond effectively to uncertain future scenarios for vector-borne disease in a changing world, more attention needs to be given to building resilient and equitable systems in the present

Using social and behavioural science to support COVID-19 pandemic response

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behavior with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic, and also highlight important gaps researchers should move quickly to fill in the coming weeks and months

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior