The using of gibberellic acid hormone on cotton mature embryo resulted by crossing between wild and commercial species on artificial medium

The wild species of cotton have important role in cotton breeding due to their favorable traits, which include pest and disease resistance, drought tolerance, fiber quality and male cytoplasmic sterility. Transferring these favorable genes from wild species to commercial cultivars of cotton by the traditional methods or classical plant breeding procedure will be very difficult and impossible. This is due to the following: Confronting disordering in flower structure, the problems involved in cotton flower pollens germination in stigma level and destruction of embryo and endosperm in different stages of evolution. The first sign of these problems is the falling of ovary. Therefore, the first and important barrier in crossing between diploid and tetraploid cotton species is the inability of hybrid seeds to produce. Solving of these problems can be the first step in hybridizations programs. The artificial control of fertilization by the gibberellic acid (GA3) after crossing and hybrid embryo culture in the media will increase probability of hybrid plants production. In this study, three species named Sahel (tetraploid), Hashemabad (diploid) and Kashmar (diploid) were used. The parental species were planted on six plots and crosses were made between them. It must be noticed that we used Sahel species as paternal and the two diploid species as maternal species. As the study continues, two investigations were separately done on hybrids. Firstly, it consisted of using different amount of Gibberellic acid after pollination for the maintenance of bolls and secondly, 45 days embryos of all the crosses combined were cultured on liquid and solid M.S media. The results show that when hormone was not used, the amount of bolls that fell was 100%, but when Gibberellic acid was applied at 100ppm concentration, there was considerable differentiation in maintenance of bolls. The Hashemabad cultivar created bolls more than Kashmar but the percentage of seeds inside the bolls was so lower than Kashmar cultivar. In comparison between parents used and their hybrids, the latter's response was better. Also among the different media culture, it is seen that the growth of mature embryo in the liquid media was better than solid.Key word: Cotton, diploid species, tetraploid species, hybrid, media culture

Facility Attractiveness and Social Vulnerability Impacts on Spatial Accessibility to Opioid Treatment Programs in South Carolina

Opioid dependence and opioid-related mortality have been increasing in recent years in the United States. Available and accessible treatments may result in a reduction of opioid-related mortality. This work describes the geographic variation of spatial accessibility to opioid treatment programs (OTPs) and identifies areas with poor access to care in South Carolina. The study develops a new index of access that builds on the two-step floating catchment area (2SFCA) method, and has three dimensions: a facility attractiveness index, defined by services rendered incorporated into the Huff Model; a facility catchment area, defined as a function of facility attractiveness to account for variable catchment size; and a Social Vulnerability Index (SVI) to account for nonspatial factors that mitigate or compound the impacts of spatial access to care. Results of the study indicate a significant variation in access to OTPs statewide. Spatial access to OTPs is low across the entire state except for in a limited number of metropolitan areas. The majority of the population with low access (85%) live in areas with a moderate-to-high levels of social vulnerability. This research provides more realistic estimates of access to care and aims to assist policymakers in better targeting disadvantaged areas for OTP program expansion and resource allocation

A reliability-based approach for influence maximization using the evidence theory

The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks for example. In this paper, we propose an influence measure that combines many influence indicators. Besides, we consider the reliability of each influence indicator and we present a distance-based process that allows to estimate the reliability of each indicator. The proposed measure is defined under the framework of the theory of belief functions. Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network. Finally, we present a set of experiments on a dataset collected from Twitter. These experiments show the performance of the proposed solution in detecting social influencers with good quality.Comment: 14 pages, 8 figures, DaWak 2017 conferenc

Analysis of Social Media Discussions on (#)Diet by Blue, Red, and Swing States in the U.S

The relationship between political affiliations and diet-related discussions on social media has not been studied on a population level. This study used a cost- and -time effective framework to leverage, aggregate, and analyze data from social media. This paper enhances our understanding of diet-related discussions with respect to political orientations in U.S. states. This mixed methods study used computational methods to collect tweets containing “diet” or “#diet” shared in a year, identified tweets posted by U.S. Twitter users, disclosed topics of tweets, and compared democratic, republican, and swing states based on the weight of topics. A qualitative method was employed to code topics. We found 32 unique topics extracted from more than 800,000 tweets, including a wide range of themes, such as diet types and chronic conditions. Based on the comparative analysis of the topic weights, our results revealed a significant difference between democratic, republican, and swing states. The largest difference was detected between swing and democratic states, and the smallest difference was identified between swing and republican states. Our study provides initial insight on the association of potential political leanings with health (e.g., dietary behaviors). Our results show diet discussions differ depending on the political orientation of the state in which Twitter users reside. Understanding the correlation of dietary preferences based on political orientation can help develop targeted and effective health promotion, communication, and policymaking strategies

Developing a dynamic digital twin at a building level: Using Cambridge campus as case study

A Digital Twin (DT) refers to a digital replica of physical assets, processes and systems. DTs integrate artificial intelligence, machine learning and data analytics to create dynamic digital models that are able to learn and update the status of the physical counterpart from multiple sources. A DT, if equipped with appropriate algorithms will represent and predict future condition and performance of their physical counterparts. Current developments related to DTs are still at an early stage with respect to buildings and other infrastructure assets. Most of these developments focus on the architectural and engineering/construction point of view. Less attention has been paid to the operation & maintenance (O&M) phase, where the value potential is immense. A systematic and clear architecture verified with practical use cases for constructing a DT is the foremost step for effective operation and maintenance of assets. This paper presents a system architecture for developing dynamic DTs in building levels for integrating heterogeneous data sources, support intelligent data query, and provide smarter decision-making processes. This will further bridge the gaps between human relationships with buildings/regions via a more intelligent, visual and sustainable channels. This architecture is brought to life through the development of a dynamic DT demonstrator of the West Cambridge site of the University of Cambridge. Specifically, this demonstrator integrates an as-is multi-layered IFC Building Information Model (BIM), building management system data, space management data, real-time Internet of Things (IoT)-based sensor data, asset registry data, and an asset tagging platform. The demonstrator also includes two applications: (1) improving asset maintenance and asset tracking using Augmented Reality (AR); and (2) equipment failure prediction. The long-term goals of this demonstrator are also discussed in this paper

Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new "Integrated Epilepsy Classification"?

Over the last few decades the ILAE classifications for seizures and epilepsies (ILAE-EC) have been updated repeatedly to reflect the substantial progress that has been made in diagnosis and understanding of the etiology of epilepsies and seizures and to correct some of the shortcomings of the terminology used by the original taxonomy from the 1980s. However, these proposals have not been universally accepted or used in routine clinical practice. During the same period, a separate classification known as the "Four-dimensional epilepsy classification" (4D-EC) was developed which includes a seizure classification based exclusively on ictal symptomatology, which has been tested and adapted over the years. The extensive arguments for and against these two classification systems made in the past have mainly focused on the shortcomings of each system, presuming that they are incompatible. As a further more detailed discussion of the differences seemed relatively unproductive, we here review and assess the concordance between these two approaches that has evolved over time, to consider whether a classification incorporating the best aspects of the two approaches is feasible. To facilitate further discussion in this direction we outline a concrete proposal showing how such a compromise could be accomplished, the "Integrated Epilepsy Classification". This consists of five categories derived to different degrees from both of the classification systems: 1) a "Headline" summarizing localization and etiology for the less specialized users, 2) "Seizure type(s)", 3) "Epilepsy type" (focal, generalized or unknown allowing to add the epilepsy syndrome if available), 4) "Etiology", and 5) "Comorbidities & patient preferences"

Latent provisions for building information modeling (BIM) contracts: a social network analysis approach

The effective adoption and use of Building Information Modeling (BIM) require appropriate contract design to fairly allocate the contracting parties’ rights and responsibilities. Several standards for BIM protocols and contracts have been developed for the industry. However, the awareness and the use of these are rather limited, leading to unclear provisions in BIM contracts. Therefore, the research aims to identify the influential legal aspects that serve as the latent contract provisions in BIM contracts. A questionnaire survey was conducted to survey experts and active BIM users in construction projects. The data were analyzed using social network analysis (SNA) by assuming interdependent relationships among various the legal aspects in BIM contacts. The key legal aspects associated with BIM contracts pertain to the roles and responsibilities of the project participants. The results also reveal that data security is the center of all latent legal aspects in the contracts. The study provides significant new insights into clarifying the required contract provisions in BIM contracts

Dynamic temporary blood facility location-allocation during and post-disaster periods

The key objective of this study is to develop a tool (hybridization or integration of different techniques) for locating the temporary blood banks during and post-disaster conditions that could serve the hospitals with minimum response time. We have used temporary blood centers, which must be located in such a way that it is able to serve the demand of hospitals in nearby region within a shorter duration. We are locating the temporary blood centres for which we are minimizing the maximum distance with hospitals. We have used Tabu search heuristic method to calculate the optimal number of temporary blood centres considering cost components. In addition, we employ Bayesian belief network to prioritize the factors for locating the temporary blood facilities. Workability of our model and methodology is illustrated using a case study including blood centres and hospitals surrounding Jamshedpur city. Our results shows that at-least 6 temporary blood facilities are required to satisfy the demand of blood during and post-disaster periods in Jamshedpur. The results also show that that past disaster conditions, response time and convenience for access are the most important factors for locating the temporary blood facilities during and post-disaster periods

Facility Attractiveness and Social Vulnerability Impacts on Spatial Accessibility to Opioid Treatment Programs in South Carolina

Opioid dependence and opioid-related mortality have been increasing in recent years in the United States. Available and accessible treatments may result in a reduction of opioid-related mortality. This work describes the geographic variation of spatial accessibility to opioid treatment programs (OTPs) and identifies areas with poor access to care in South Carolina. The study develops a new index of access that builds on the two-step floating catchment area (2SFCA) method, and has three dimensions: a facility attractiveness index, defined by services rendered incorporated into the Huff Model; a facility catchment area, defined as a function of facility attractiveness to account for variable catchment size; and a Social Vulnerability Index (SVI) to account for nonspatial factors that mitigate or compound the impacts of spatial access to care. Results of the study indicate a significant variation in access to OTPs statewide. Spatial access to OTPs is low across the entire state except for in a limited number of metropolitan areas. The majority of the population with low access (85%) live in areas with a moderate-to-high levels of social vulnerability. This research provides more realistic estimates of access to care and aims to assist policymakers in better targeting disadvantaged areas for OTP program expansion and resource allocation