Branching Ratio and CP-asymmetry for B-> 1^{1}P_{1}gamma decays

We calculate the branching ratios for B_{d}^{0}->(b_{1},h_{1})gamma at next-to-leading order (NLO) of alpha_{s} where b_{1} and h_{1} are the corresponding radially excited axial vector mesons of rho and omega respectively. Using the SU(3)symmetry for the form factor, the branching ratio for B_{d}^{0}->(b_{1},h_{1})gamma is expressed in terms of the branching ratio of the B_{d}^{0}-> K_{1}gamma and it is found to be B(B_{d}^{0}->b_{1}gamma)=0.71* 10^{-6} and B(B_{d}^{0}-> h_{1}gamma) =0.74*10^{-6}. We also calculate direct CP asymmetry for these decays and find, in confirmity with the observations made in the literature, that the hard spectator contributions significantely reduces the asymmetry arising from the vertex corrections alone. The value of CP-asymmetry is 10% and is negative like rho and omega in the Standard Model.Comment: 10 pages, 2 figure

Use of untreated wastewater in peri-urban agriculture in Pakistan: risks and opportunities

Water reuse / Waste waters / Water quality / Groundwater / Irrigation practices / Soil properties / Environmental effects / Conjunctive use / Pakistan / Haroonabad

Deterministic and Probabilistic Binary Search in Graphs

We consider the following natural generalization of Binary Search: in a given undirected, positively weighted graph, one vertex is a target. The algorithm's task is to identify the target by adaptively querying vertices. In response to querying a node $q$, the algorithm learns either that $q$ is the target, or is given an edge out of $q$ that lies on a shortest path from $q$ to the target. We study this problem in a general noisy model in which each query independently receives a correct answer with probability $p > \frac{1}{2}$ (a known constant), and an (adversarial) incorrect one with probability $1-p$. Our main positive result is that when $p = 1$ (i.e., all answers are correct), $\log_2 n$ queries are always sufficient. For general $p$, we give an (almost information-theoretically optimal) algorithm that uses, in expectation, no more than $(1 - \delta)\frac{\log_2 n}{1 - H(p)} + o(\log n) + O(\log^2 (1/\delta))$ queries, and identifies the target correctly with probability at leas $1-\delta$. Here, $H(p) = -(p \log p + (1-p) \log(1-p))$ denotes the entropy. The first bound is achieved by the algorithm that iteratively queries a 1-median of the nodes not ruled out yet; the second bound by careful repeated invocations of a multiplicative weights algorithm. Even for $p = 1$, we show several hardness results for the problem of determining whether a target can be found using $K$ queries. Our upper bound of $\log_2 n$ implies a quasipolynomial-time algorithm for undirected connected graphs; we show that this is best-possible under the Strong Exponential Time Hypothesis (SETH). Furthermore, for directed graphs, or for undirected graphs with non-uniform node querying costs, the problem is PSPACE-complete. For a semi-adaptive version, in which one may query $r$ nodes each in $k$ rounds, we show membership in $\Sigma_{2k-1}$ in the polynomial hierarchy, and hardness for $\Sigma_{2k-5}$

OSCA: a comprehensive open-access system of analysis of posterior capsular opacification

BACKGROUND: This paper presents and tests a comprehensive computerised system of analysis of digital images of posterior capsule opacification (PCO). It updates and expands significantly on a previous presentation to include facilities for selecting user defined central areas and for registering and subsequent merging of images for artefact removal. Also, the program is compiled and thus eliminates the need for specialised additional software. The system is referred to in this paper as the open-access systematic capsule assessment (OSCA). The system is designed to be evidence based, objective and openly available, improving on current systems of analysis. METHODS: Principal features of the OSCA system of analysis are discussed. Flash artefacts are automatically located in two PCO images and the images merged to produce a composite free from these artefacts. For this to be possible the second image has to be manipulated with a registration technique to bring it into alignment with the first. Further image processing and analysis steps use a location-sensitive entropy based texture analysis of PCO. Validity of measuring PCO progression of the whole new system is assessed along with visual significance of scores. Reliability of the system is assessed. RESULTS: Analysis of PCO by the system shows ability to detect early progression of PCO, as well as detection of more visually significant PCO. Images with no clinical PCO produce very low scores in the analysis. Reliability of the system of analysis is demonstrated. CONCLUSION: This system of PCO analysis is evidence-based, objective and clinically useful. It incorporates flash detection and removal as well as location sensitive texture analysis. It provides features and benefits not previously available to most researchers or clinicians. Substantial evidence is provided for this system's validity and reliability

Energy-aware Theft Detection based on IoT Energy Consumption Data

With the advent of modern smart grid networks, advanced metering infrastructure provides real-time information from smart meters (SM) and sensors to energy companies and consumers. The smart grid is indeed a paradigm that is enabled by the Internet of Things (IoT) and in which the SM acts as an IoT device that collects and transmits data over the Internet to enable intelligent applications. However, IoT data communicated over the smart grid could however be maliciously altered, resulting in energy theft due to unbilled energy consumption. Machine learning (ML) techniques for energy theft detection (ETD) based on IoT data are promising but are nonetheless constrained by the poor quality of data and particularly its imbalanced nature (which emerges from the dominant representation of honest users and poor representation of the rare theft cases). Leading ML-based ETD methods employ synthetic data generation to balance the training the dataset. However, these are trained to maximise average correct detection instead of ETD. In this work, we formulate an energy-aware evaluation framework that guides the model training to maximise ETD and minimise the revenue loss due to mis-classification. We propose a convolution neural network with positive bias (CNN-B) and another with focal loss CNN (CNN-FL) to mitigate the data imbalance impact. These outperform the state of the art and the CNN-B achieves the highest ETD and the minimum revenue loss with a loss reduction of 30.4% compared to the highest loss incurred by these methods

Urban wastewater: A valuable resource for agriculture - A case study from Haroonabad, Pakistan

Waste waters / Irrigation water / Water reuse / Economic analysis / Soil properties / Households / Water availability / Water use / Water quality / Groundwater / Public health / Risks / Case studies

Gender differences in use and preferences of agricultural information sources in Pakistan

Purpose: Rural advisory services ensure agricultural information is disseminated to rural populations, yet they are less accessible to women. This research provides insight on gender differences in information access by investigating frequency of use and preference of agricultural information sources by gender in a rural setting, differentiated according to literacy and age. Design/Methodology/approach: This study interviewed 401 male/female individuals in farm households in Jhang and Bahawalpur district of Punjab, Pakistan in 2016. Findings: Men and women farmers’ use and preferences in accessing information sources are extremely different. Women hardly use sources for agricultural information, and value interpersonal communication from informal sources. In contrast, men use and value official agencies more. Radio, surprisingly, was very rarely used, contradicting previous findings of research elsewhere. Age and literacy affect differences between women more than it does between men, particularly for convenient locations to access information. Practical implications The study identified and refined major gender differences regarding use and preference for agricultural information in relation to age and literacy, and helps to articulate options to improve gender equality of access to agricultural information in Pakistan. Theoretical implications: The focus and outcomes regarding gender intersecting with age and literacy in agricultural information access imply the need for more refined socioeconomic models, discerning and interrelating gender and other social dimensions beyond the standard of male-headed households. Originality/value: This paper adds to the growing body of evidence on information access according to gender, highlighting the need to investigate deeper socio-cultural issues around age and literacy

Intelligence as a source of cold case homicide investigation : a cross national perspective

Cold case homicides are probably the most complex and difficult of cases to (re-) investigate. Each is different in terms of means and motives, method of killing, geographic location and weapon used. There is no single method of investigation that fully fits with each type of cold case homicide. Therefore, several investigative techniques are in common practice, such as DNA profiling and fingerprint analysis etc. However, it is not known how an ‘Intelligence-Led Policing Model’ (ILPM) can be applied in cold case homicide investigations and literature is currently lacking that would enable us to shed light on this issue. The aim of the research is to develop a robust understanding on how an ILPM can help to solve old and cold case homicides

Identifying gender-responsive approaches in rural advisory services that contribute to the institutionalisation of gender in Pakistan

Purpose: Unequal reach and access to information is an issue that affects women involved in agricultural activities around the world. Recent initiatives to address gender unequal access to agricultural information have been clumsy, overlooking participatory approaches that focus on transformative change. This study uses Pakistani rural advisory services to compare farmers' and extension workers’ perceptions of access to agricultural information, to identify culturally acceptable gender-responsive schemes. Design/methodology/approach: One-hundred and eleven extension workers in Pakistan’s public rural advisory services were interviewed and crosstabulated with farmers’ answers in previous studies. Findings: Male extension workers are aware that women access less information less often; however they might not be aware of its importance in the gender inequality debate. Lead farmers could offer a potentially transformative knowledge pathway because of its blend of formal and informal interactions – both systems favoured by female smallholders. An exclusively female-led lead farmer approach could be developed and trialled in specific areas of the province. Practical implications: Targeted initiatives focusing on improving awareness and importance of gender inequalities in information access as well as specific extension system development centred on lead female farmers and extension agents are important in institutionalising gender and creating transformative change. Theoretical implications: Linking these activities to in-depth social network and agricultural innovation system analyses would provide further evidence of the importance of focused gender activities and their impact on food security. Originality/value: This paper highlights the importance of analysing individual perceptions to understand the types of initiatives that could be considered for a wider institutionalisation of gender in RAS