Search

Background Nigeria is one of three countries projected to have the largest absolute increase in the size of its urban population and this could intensify malaria transmission in cities. Accelerated urban population growth is outpacing the availability of affordable housing and basic services and resulting in living conditions that foster vector breeding and heterogeneous malaria transmission. Understanding community determinants of malaria transmission in urban areas informs the targeting of interventions to populations at greatest risk. Methods In this study, we analyzed cluster-level data from the Demographic and Health Surveys (DHS) and the Malaria Indicator Survey (MIS) as well as geospatial covariates to describe malaria burden and its determinants in areas administratively defined as urban in Nigeria. Univariate and multivariable models were respectively used to identify potential intervention prioritization thresholds and likely casual impact of individual variables. Results Overall, we found low malaria test positivity across urban areas. We observed declines in test positivity rate over time and identified the percentage of individuals with post-primary education, the percentage of individuals in the rich wealth quintiles, the percentage of individuals living in improved housing in 2015, all age population density, median age, the percentage of children under the age of five that sought medical treatment for fever, total precipitation, and enhanced vegetation index as key community predictors of malaria transmission intensity. Conclusions The unrepresentativeness of the DHS and MIS in urban settings at the state and geopolitical zonal level, regional differences in malaria seasonality across Nigeria, and information detection bias were among likely factors that limited our ability to compare malaria burden across geographic space and ultimately drove model uncertainty. Nevertheless, study findings provide a starting point for informing decisions on intervention prioritization within urban spaces and underscore the need for improved regionally focused surveillance systems in Nigeria.

Fish farming in Senegal encounters many difficulties, especially during the first life stages, which are more demanding for food and more sensitive to variations in the physicochemical parameters. Most of the species of aquaculture interest have offspring whose size at birth is very small, thus requiring a particular rich food adapted to the size of the mouth (e.g. live preys which are very rich in nutritive reserves). The objective of this study was to set up a production system of live prey, daphnia for the feeding of fish fry. It consisted of culturing microalgae that were used to fed daphnia reared to fed the fry of the African catfish, Clarias gariepinus. The temperature and dissolved oxygen content in the culture and rearing media were monitored throughout the experiment. The results on species identification showed that the cultured microalgae and reared daphnia species are Microcystis sp and Daphnia magna, respectively. Analyses of algal biomass and daphnia abundance show an increase in these parameters with time. Temperature variations do not affect algal biomass, daphnia abundance and fry growth. On the other hand, a decrease in dissolved oxygen content below a certain threshold (6mg/l) leads to a decrease in algal biomass and daphnia abundance. Among the three feeding rates 1.5g, 3g, 4.5g (the equivalent of 0.5L, 1L, and 1.5L of microalgae, respectively) that were used to feed daphnia, the feeding rate of 3g of biomass corresponding to 1L is more adequate as it gave the best production. The comparison of the effects of the types of feed shows that live daphnia give better growths of C. gariepinus fry than the artificial feed, which may be due to their adequate size and nutrient richness. Thus, this study contributes to the establishment of live prey production systems to boost local aquaculture development and demonstrates the importance of daphnia for the feeding of early fish life stages.

For small groups fighting in multi-actor civil wars, joining a larger coalition is often a way to survive. Yet, it is not only rebel or pro-government non-state armed groups that form alliances; in many cases, jihadists have been surprisingly successful in building winning coalitions in civil wars. This is puzzling because jihadists attract fierce international opposition and are therefore very risky teams to join. Jihadists are also typically excluded from the political process, which means that they are unlikely to enjoy the spoils of a peace agreement. Why then would any local groups choose to join jihadist coalitions, rather than other rebel or pro-government coalitions in a conflict theatre? In this paper, we argue that ideology fails to explain this choice; rather, we contend that competition among rebel and pro-government coalitions inevitably produces winners and losers. Under these conditions, jihadists serve as an attractive spoiler coalition, drawing support from groups that see no chance of benefitting from an existing or future peace agreement. By offering these ‘losers’ a wider network and reference group, jihadists can expand their coalition base and territorial reach. By courting support from marginalized groups across ethnic and tribal lines, jihadists can create a winning coalition out of a diverse mix of losers.

Nigeria is one of three countries projected to have the largest absolute increase in the size of its urban population and this could intensify malaria transmission in cities. Accelerated urban population growth is out-pacing the availability of affordable housing and basic services and resulting in living conditions that foster vector breeding and heterogeneous malaria transmission. Understanding community determinants of malaria transmission in urban areas informs the targeting of interventions to populations at greatest risk. In this study, we analyzed cluster-level data from the Demographic and Health Surveys (DHS) and the Malaria Indicator Survey (MIS) as well as geospatial covariates to describe malaria burden and its determinants in areas administratively defined as urban in Nigeria. Overall, we found low malaria test positivity across urban areas,. We observed declines in test positivity rate over time and identified the percentage of individuals with post-primary education, the percentage of individuals in the rich wealth quintiles, the percentage of individuals living in improved housing in 2015, all age population density, median age, the percentage of children under the age of five that sought medical treatment for fever, total precipitation and enhanced vegetation index as key community predictors of malaria transmission intensity. The unrepresentativeness of the DHS and MIS in urban settings at the state and geopolitical zonal level, regional differences in malaria seasonality across Nigeria, and information detection bias were among likely factors that limited our ability to compare malaria burden across geographic space and ultimately drove model uncertainty. Nevertheless, study findings provide a starting point for informing decisions on intervention prioritization within urban spaces and underscore the need for improved regionally-focused surveillance systems in Nigeria.

Sclerocarya birrea (A. Rich.) Hochst. est un fruitier oléagineux d’Afrique. Les fortes mortalités après plantation sont dues à l’affectation inappropriée des plants dans les zones écologiques. La caractérisation phénotypique des plantules a pour objectif de déterminer dès le jeune âge des caractères d’adaptation aux conditions écologiques. L’étude porte sur 494 plantules originaires des populations de You, Yarci, Gonsé et Diapangou-Peulh au Burkina Faso. Celles-ci appartiennent à quatre localités circonscrites dans trois zones climatiques. Les résultats montrent que la levée groupée assure la présence de générations chevauchantes à l’intérieur des populations. L’analyse de variance qui fait apparaître des différences intra- et inter-population sur la majorité des variables traduit la diversité phénotypique des plantules. L’analyse en composantes principales montre des caractéristiques spécifiques à chaque population. Le dendrogramme de la classification ascendante hiérarchisée permet d’identifier trois groupes : G1 : Gonsé (55,88 %), Yarci (23,52 %) et You (20,58 %) ; G2 : You (46,15 %), Yarci (42,30 %), Diapangou-Peulh (7,69 %) et Gonsé (3,84 %) ; G3 : Diapangou-Peulh (90 %), Yarci (5 %) et You (5 %). Ces trois groupes traduisent le rapprochement phénotypique entre individus. Ces résultats mettent en évidence l’existence des gains génétiques pour la sélection individuelle et populationnelle. Ils montrent également que ces populations ne sont pas menacées d’impasse évolutive à court terme. L’étude des héritabilités indique que les caractères les plus héritables sont la hauteur de la tige (28,31 %), la longueur de la racine principale (44,30 %), le nombre de racines secondaires (81,89 %), le poids frais des racines (73,47 %) et le poids sec des racines (28,86 %). L’architecture du système racinaire traduit la capacité d’adaptation de Sclerocarya birrea à différents types de sols. Compte tenu de ces résultats, la sélection sur les caractères adaptatifs au jeune âge peut être envisagée.

Some tree improvement programs in Africa use nursery tests to investigate genetic and geographic variation in growth, but do they lead to the same conclusions as field tests? We investigated this question using provenance/progeny tests (12 provenances, 108 families) of Balanites aegyptiaca from semi-arid Niger. The nursery test included treatments for time (12–16 months) and watering regime (reduced and normal). Family variation was significant for shoot diameter (Sdia), height (Sht), dry weight (Swt) and root dry weight (Rwt) in the nursery, and for tree height at 1 and 2 years (Fht-1, Fht-2) but not at 13.5 years (Fht-13.5) in the field. Provenance variation was significant only for root/shoot weight ratio (RSwt) in the nursery. Family mean Fht-1 and Fht-2 were positively correlated with all nursery growth variables except RSwt. Provenance mean Fht-2 was positively correlated with Sht, while provenance mean Fht-13.5 was negatively correlated with Swt and positively correlated with RSwt. Family mean survival at 13.5 years was positively correlated with Swt, Sdia, Fht-1 and Fht-2. Family mean Rwt, RSwt and Fht-2 increased from the more humid western to the drier eastern locations. Most correlations with nursery growth variables were stronger at 16 than at 12 months and in the normal compared with the reduced watering regime. Results suggest that Swt and Sdia may be useful for predicting family survival in the field, and Rwt and RSwt may be useful for investigating geographic variation in growth in the field. We recommend conducting both nursery and long-term field tests.

The current traditional database management mechanisms and analytics architectures are not generally suitable for addressing the intrinsic characteristics of diversity, heterogeneity, large-scale, dynamic and large amount of data generated by the Internet of Things (IoT) networks and various IoT applications needs. Then, it is challenging to provide efficient IoT data storage and query processing mechanisms for meeting the requirements of applications. This paper identifies the most relevant characteristics and mechanisms of IoT data management and categorizes them. Moreover, a new four layers fog-based architecture using the distributed approach is proposed for providing a secure storage infrastructure and efficient real-time IoT data discovering with better latency. Finally, this work shows advances on IoT data management mechanisms, highlights their advantages and limits, and discusses the challenging open research issues that need to be focused for providing guidelines for new contributions.

The evolution of surveillance technologies allows a reduction in human interaction with the process, since most of the monitoring functions performed by an individual can be replaced by detection and recognition techniques in real-time. This paper proposes the development of a surveillance system, which uses these techniques to identify individuals present within the field of view of camera. A combination of the Histogram of Oriented Gradient and Support Vector Machine techniques is applied for face detection, while a Residual Network is used during the stage of recognizing individuals. This shows the possibility of implementing this set of techniques, even in hardware with processing limitations.

With the progress of new technologies, certain areas such as health have seen their functioning modes to be changed to accommodate the trend of the actual world. Then, new concepts have emerged such as telemedicine, e-health, or the Internet of Medical Things (IoMT). These innovations quickly spread around the world to turn the tide. But nevertheless, some West African countries, such as Senegal, are still trying to get to grips in the perfect use of these tools by trying to provide solutions that address real societal problems. This paper proposes an IoMT application for diagnosis and help of diabetics, DiabLoop. The application measures blood glucose levels at reconfigurable time intervals to detect potential diabetes or monitor the progress of existing diabetes. An algorithm-based intelligent part is built-in that allows the system to use a knowledge base to make decisions automatically to help or send an urgent notification to a registered physician, guardian and/or to a parent. The implementation and case studies for validation show that the application facilitates the daily life of diabetics, which is an innovation in the field of health in West Africa.

Global industry is undergoing major transformations with the genesis of a new paradigm known as the Internet of Things (IoT) with its underlying technologies. Many company leaders are investing more effort and money in transforming their services to capitalize on the benefits provided by the IoT. Thereby, the decision makers in public waste management do not want to be outdone, and it is challenging to provide an efficient and real-time waste management system. This paper proposes a solution (hardware, software, and communications) that aims to optimize waste management and include a citizen in the process. The system follows an IoT-based approach where the discarded waste from the smart bin is continuously monitored by sensors that inform the filling level of each compartment, in real-time. These data are stored and processed in an IoT middleware providing information for collection with optimized routes and generating important statistical data for monitoring the waste collection accurately in terms of resource management and the provided services for the community. Citizens can easily access information about the public waste bins through the Web or a mobile application. The creation of the real prototype of the smart container, the development of the waste management application and a real-scale experiment use case for evaluation, demonstration, and validation show that the proposed system can efficiently change the way people deal with their garbage and optimize economic and material resources.

BackgroundThis study explores the impact of using different criteria to identify nonfatal hospitalisations with self-harm injuries using 2017–2018 Wisconsin discharge data.MethodsUsing International Classification of Diseases, 10th Revision, Clinical Modification codes, we classified records by three mutually exclusive selection criteria: subset A--principal diagnosis of injury, and any code for self-harm, initial encounter only; subset B--non-injury principal diagnosis, and any code for self-harm, initial encounter only; subset C--any principal diagnosis, and any code for self-harm, subsequent and sequelae encounters only. These categories were used to conduct two separate logistic regression models. Model 1 analysed the impact of surveillance limited to a principal diagnosis of injury, initial self-harm encounter (subset B compared with A). Model 2 analysed the impact if limited to initial encounters for self-harm, regardless of principal diagnosis (subset C compared with (A+B)). Both patient-level and visit-level analyses were conducted.ResultsFor both patient-level models, subsets that included additional records based on an expansion of selection criteria were significantly more likely to include children (model 1: OR 2.8, model 2: OR 2.9; compared with those 25–54 years), those with mental health disorders (model 1: OR 6.5, model 2: OR 4.3) and rural residents (model 1: OR 1.2, model 2: OR 1.4). Drug-related disorder and means of self-harm were significantly different among subsets for both models. Visit-level analyses revealed similar results.DiscussionExpanding case selection criteria would better capture the scale of hospitalisation for nonfatal self-harm. Using restrictive selection criteria may result in biased understanding of the affected populations, potentially impacting the development of policy and prevention programmes.

In this letter, the performance of a diffractive gradient index lens antenna, constructed by using dielectric subwavelength structuration and manufactured by three-dimensional printing, is compared to the ones of conventional lens antennas in a small footprint configuration. It discusses the advantages and drawbacks of each configuration and compares the simulated and measured gain performances. It shows that structured lens antenna can achieve gain superior to conventional approaches, combined with a 1 dB bandwidth of 10.9%, thanks to the engineering of artificial gradient index. All these benefits are coming with a significant decrease in the antenna weight for the same footprint.

Internet of Things (IoT) is a network paradigm in which physical, digital, and virtual objects are equipped with identification, detection, networking, and processing functions to communicate with each other and with other devices and services on the Internet in order to perform the users’ required tasks. Many IoT applications are provided to bring comfort and facilitate the human life. In addition, the application of IoT technologies in the automotive industry has given rise to the concept of Industrial Internet of Things (IIoT) which facilitated using of Cyber Physic Systems, in which machines and humans interact. Due to the diversity, heterogeneity, and large volume of data generated by these entities, the use of traditional database management systems is not suitable in general. In the design of IoT data management systems, many distinctive principles should be considered. These different principles allowed the proposal of several approaches for IoT data management. Some middleware or architecture-oriented solutions facilitate the integration of generated data. Other available solutions provide efficient storage and indexing structured and unstructured data as well as the support to the NoSQL language. Thus, this paper identifies the most relevant concepts of data management in IoT, surveys the current solutions proposed for IoT data management, discusses the most promising solutions, and identifies relevant open research issues on the topic providing guidelines for further contributions.

Objective: Using the Wisconsin Enhanced Opioid Surveillance System, the present study evaluates the heroin hospitalization risk among the opioid recipients using the Prescription Drug Monitoring Data (PDMP) with following specific objectives: 1. Evaluate the risk of heroin overdose hospitalization following the prescription of opioid. 2. Assess the time elapsed between last prescribed opioid and first heroin overdose hospitalization. 3. Identify the main predictors of heroin overdose hospitalization among prescribed opioid users. Introduction: Nationally and in Wisconsin, heroin is the leading cause of opioid related death and hospitalization. Opioids are commonly prescribed for pain. Every day, over 1,000 people are treated in emergency departments for misusing prescription opioids 1 . In 2015, more than 15,000 people died from overdoses involving prescription opioids 1 . Approximately, three out of four heroin users report having abused prescription opioids prior to using heroin 2 . In Wisconsin from 2010 to 2014 the number of deaths involving any opioid increased by 51% and for heroin increased by 192%. Through the federal government funding and support Wisconsin has established a statewide tool to help combat the ongoing prescription drug abuse epidemic by providing valuable information about controlled substance prescriptions that are dispensed in the state. PDMP is continue to be among the most promising state-level interventions to improve opioid prescribing, inform clinical practice, and protect patients at risk. Methods: This was a Retrospective cohort study of PDMP patients who were prescribed an opioid and were subsequently hospitalized for heroin overdose between 2013 and 2015. Our analysis used a combination of univariate and survival data analysis to estimate the risk of heroin overdose hospitalization from the time of the last prescribed opioid to the first day of hospitalization. The outcome was defined as Heroin Hospitalization with any code of 965.01 (ICD9 2013 first quarter to third quarter of 2015), T40.1X1A, T40.1X4A (ICD10 fourth quarter of 2015). The exposure was defined as Prescription of Opioid limited to DEA class I, II, III, & IV. Our analysis used a combination of univariate and survival data analysis to estimate the risk of heroin hospitalization from the time of the last prescribed opioid to first day of hospitalization due to heroin overdose. Cox Regression Hazard modeling was used to analyze survival time data and to identify the main predictors of heroin hospitalization. Data were analyzed using the SAS 9.2 and the study was initiated with the Data Governance Board Approval. Results: From 2013 to 2015, a total of 1,397,493 unique patients that were hospitalized linked to 1,448,224 patients reported in the PDMP who received controlled substance. Among those 699,014 (48%) had at least one hospitalization event and out of those 396 (6%) had at least one hospitalization episode due to heroin. Annual ED visit rates due to heroin overdose have doubled from 179 in 2013 to 396 in 2015. On average, people who stopped receiving prescription drugs were at a 72% increased risk of being hospitalized for heroin overdose within five months with Log-Rank Test significance (p=0.01). Males, 90 morphine milligram equivalent recipients, and kidney disease morbidity were 3.63, 2.99, and 5.64 times higher risk to have heroin overdose hospitalization, respectively. Conclusions: Patients with a history of stopping prescription drugs within the previous five months are at higher risk for subsequent hospitalization for heroin overdose. Factors such as alcohol use, age,gender, and tapering of prescription influence the risk of heroin hospitalization. It may be prudent to transition patients to alternative treatments before they become addicted to the prescribed drugs.

Objective: 1. Develop an understanding of the benefits and challenges of analyzing free text fields on a population level. 2. Observe how a complex surveillance definition can be created from free text fields. 3. Observe how an ambulance data system can be used to describe the opioid epidemic. Introduction: In 2016, twelve states received Center for Disease Control and Prevention (CDC) Enhanced State Opioid Overdose Surveillance grants. The purpose of the grant is to explore enhanced data sources to track nonfatal opioid overdoses. One data source is ambulance runs. Wisconsin collects ambulance run information within the Wisconsin Ambulance Runs Data System (WARDS). Around 84% of all Wisconsin administrative services report into this electronic system. This is a timely, robust data system that has not been used previously to examine drug overdoses and presents an analytical challenge as it contains many free text fields. Methods: Wisconsin’s ambulance data system is robust, well-populated, and includes the majority of Emergency Medical Services (EMS) within the state. The analytic challenge with this data is that most of the reported fields are free text, which can be difficult to analyze on a population level. Wisconsin created a case definition using SAS regular expressions to take advantage of the free text fields. A combination of fields (chief complaint, secondary complaint, medications given, and the EMS narrative) were used to determine if the ambulance run was due to an opioid overdose. It was necessary to create a definition that used a diverse combination of phrases as free text fields are prone to spelling errors and there are many phrases used to identify opioid overdoses. It was also necessary to create a definition for unwanted phrases that signal a false positive, for example, “withdrawal”. Results: Wisconsin’s opioid definition uses regular expressions to search for the words “heroin”, “opioid”, “narcan”, or “methadone” (including various spellings). The overdose definition searches for words and phrases like “drug abuse”, “drug use”, “poisoning”, “drug ingestion”, and “overdose”. The medication administered fields are examined for “narcan”. In Wisconsin, the medication is listed every time it is used, so it is possible to determine the number of times Narcan was administered to a single person as well as how many ambulance runs used at least one dose of Narcan. False positives are identified with words and phrases like “withdrawal”, “detox”, and if Narcan was given but there is no indication that the ambulance run was due to drugs. From January 2016 – June 2017, Wisconsin had over 917,000 ambulance runs for people aged 11 years and older. We excluded non-emergency ambulance runs, like medical transports, and so our final denominator was 627,536 runs (32% of all runs were classified as non-emergencies). Suspected opioid overdoses were determined to be 1% of emergency ambulance runs. Narcan was administered in a total of 5,900 runs and the false positive flag picked up 10,399 runs that may not have been due to suspected opioid overdoses. Applying all of these components together, it was determined that in Wisconsin from January 2016 – June 2017, there were 4,041 emergency ambulance runs due to suspected, unintentional opioid overdoses for people 11 years and older (rate of 6 per 1,000 people). Conclusions: The use of regular expressions enables Wisconsin to extend analyses to data systems that contain robust information within free text fields. Within Wisconsin, this has been utilized to enhance opioid overdose surveillance with the use of a rapid data system previously not examined. Ambulance run information is a valuable resource to Wisconsin with the opioid epidemic. By creating case definitions with free text fields, we can quantify ambulance runs on a population level and create linkable analytic data sets to provide a more complete picture of the health of Wisconsin.

Despite suicide prevention efforts, there remains a high burden of self-inflicted injuries in Wisconsin.Compare methods of suicide and nonfatal self-inflicted injury by sex in Wisconsin over a 12-year period.Suicide and nonfatal self-inflicted injury rates in Wisconsin between 2002 and 2014 were compared by sex and method using data from the Wisconsin Interactive Statistics on Health. Percentages of total suicides by method of injury for each sex were calculated.Firearms and poisoning were the most common methods of suicide and nonfatal selfinflicted injuries, respectively. Rates of both suicide and nonfatal self-inflicted injuries differed significantly by sex and method.Suicide prevention strategies in Wisconsin must account for the variability of method of self-inflicted injury between sexes.

This study examined effects of climatic conditions on patterns of flowering and fruiting of tamarind (Tamarindus indica L.). Data were recorded over a period of 26 months in two contrasting climatic zones. The monitoring revealed that irrespective of climatic zones, flowering starts by the end of the dry season when hygrometry begins to rise and lasts two to three months. Fruiting begins around the peak of the rainy season and reaches the ripening stage six to eight months later during the dry season. Flowering and fruiting abilities weakly varied with climatic conditions. Flowering durations and active phases seemed to be significantly longer (p < 0.001) under wetter climatic conditions (Sudan-Guinea zone) while fruiting parameters showed the opposite trend. Flowering length was found to be weakly correlated to climatic conditions while the latter variable was positively correlated to fruiting length. A negative correlation was observed between fruiting length and trees diameter; suggesting that the younger the tree, the longer the fruiting phase. These results provide insights into the patterns of phenological events of tamarind that could help in managing its populations and anticipating its flowering and fruiting shifting response to climate changes. Thorough research should however focus on modeling the combined effect of climate, soil, land use regimes and age of trees on the inter-annual variation of flowering and fruiting patterns and productivity. Key words: Indigenous fruit trees, phenology, climate, Benin, West Africa.

Background Neural tube defects (NTDs) are very common and severe birth defects that are caused by failure of neural tube closure and that have a complex aetiology. Anencephaly and spina bifida are severe NTDs that affect reproductive fitness and suggest a role for de novo mutations (DNMs) in their aetiology. Methods We used whole-exome sequencing in 43 sporadic cases affected with myelomeningocele or anencephaly and their unaffected parents to identify DNMs in their exomes. Results We identified 42 coding DNMs in 25 cases, of which 6 were loss of function (LoF) showing a higher rate of LoF DNM in our cohort compared with control cohorts. Notably, we identified two protein-truncating DNMs in two independent cases in SHROOM3 , previously associated with NTDs only in animal models. We have demonstrated a significant enrichment of LoF DNMs in this gene in NTDs compared with the gene specific DNM rate and to the DNM rate estimated from control cohorts. We also identified one nonsense DNM in PAX3 and two potentially causative missense DNMs in GRHL3 and PTPRS . Conclusions Our study demonstrates an important role of LoF DNMs in the development of NTDs and strongly implicates SHROOM3 in its aetiology.

Wireless body area networks (WBANs) have received a lot of attention from both academia and industry due to the increasing need of ubiquitous computing for eHealth applications, the continuous advances in miniaturization of electronic devices, and the ultra-low-power wireless technologies. In these networks, various sensors are attached either on clothes, on human body or even implanted under the skin for real-time health monitoring of patients in order to improve their independent daily lives. The energy constraints of sensors, the vital and large amount of data collected by WBAN nodes require powerful and secure storage, and a query processing mechanism that takes into account both real-time and energy constraints. This paper addresses these challenges and proposes a new architecture that combines a cloud-based WBANs with statistical modeling techniques in order to provide a secure storage infrastructure and optimize the real-time user query processing in terms of energy minimization and query latency. Such statistical model provides good approximate answers to queries with a given probabilistic confidence. Furthermore, the combination of the model with the cloud-based WBAN allows performing a query processing algorithm that uses the error tolerance and the probabilistic confidence interval as query execution criterions. The performance analysis and the experiments based on both real and synthetic data sets demonstrate that the new architecture and its underlying proposed algorithm optimize the real-time query processing to achieve minimal energy consumption and query latency, and provide secure and powerful storage infrastructure.

Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana) and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change). We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs), climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as 'highly threatened' due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted regeneration in the central part where the current threat level is high due to overexploitation. In the same way, population-specific recommendations can be derived from the individual and combined threat maps of the other 15 food tree species. The approach can be easily transferred to other countries and can be used to analyze general and species specific threats at finer and more local as well as at broader (continental) scales in order to plan more selective and efficient conservation actions in time. The concept can be applied anywhere as long as appropriate spatial data are available as well as knowledgeable experts.

This paper presents a scalar model based on a modified Huygens-Fresnel principle to compute the electromagnetic field transformation operated by a dielectric component structured at sub-wavelength scale. The presented model is tested on a structured lens under a point source illumination in the 33 to 50 GHz band. Far field transformations and bandwidth are computed and compared to CST time solver results. The model allows for precise results and time savings by a factor of 400.

Objective Wisconsin is leading the way in novel approaches monitoring health outcomes for opioid-related adverse events. This panel will share innovative public health informatics methods that harness various data sources (e.g., Prescription Drug Monitoring Data (PDMP), death, birth and hospitalization data) for population health surveillance. Discussion will include topics on detection of drug abuse and diversion, identifying potential neonatal abstinence syndrome cases, surveillance of substance-related hospitalizations and overdose deaths, and modeling opioid-related mortality risk factors. Figure 1. Health Outcomes Opioids Surveillance System Diagram Figure 2. Ratios of MME and Length of Prescription for Select Groups (2013-2015) Map 1. Filled Opioids Over 90MME, Southeast Region Local Heaht Departments, Wisconsin, 2015.

Item does not contain fulltext Developmental and epileptic encephalopathy (DEE) is a group of conditions characterized by the co-occurrence of epilepsy and intellectual disability (ID), typically with developmental plateauing or regression associated with frequent epileptiform activity. The cause of DEE remains unknown in the majority of cases. We performed whole-genome sequencing (WGS) in 197 individuals with unexplained DEE and pharmaco-resistant seizures and in their unaffected parents. We focused our attention on de novo mutations (DNMs) and identified candidate genes containing such variants. We sought to identify additional subjects with DNMs in these genes by performing targeted sequencing in another series of individuals with DEE and by mining various sequencing datasets. We also performed meta-analyses to document enrichment of DNMs in candidate genes by leveraging our WGS dataset with those of several DEE and ID series. By combining these strategies, we were able to provide a causal link between DEE and the following genes: NTRK2, GABRB2, CLTC, DHDDS, NUS1, RAB11A, GABBR2, and SNAP25. Overall, we established a molecular diagnosis in 63/197 (32%) individuals in our WGS series. The main cause of DEE in these individuals was de novo point mutations (53/63 solved cases), followed by inherited mutations (6/63 solved cases) and de novo CNVs (4/63 solved cases). De novo missense variants explained a larger proportion of individuals in our series than in other series that were primarily ascertained because of ID. Moreover, these DNMs were more frequently recurrent than those identified in ID series. These observations indicate that the genetic landscape of DEE might be different from that of ID without epilepsy.

Espece d’interet economique, le karite a un âge a la premiere mise a fruit compris entre 12 et 20 ans. Ceci rallonge son schema de selection. Pour lever cette contrainte il faut effectuer des tests precoces des l’âge de la pepiniere. La presente etude porte sur cinq ethno-varietes de karite identifiees au Burkina Faso. Les ethno-varietes sont des noms attribues par les paysans a differentes variantes de fruits du karite. L’objectif de l’etude est d’identifier des caracteres juveniles pertinents comme indice de selection precoce. L’etude porte sur 100 plantules de 5 ethno-varietes. Au total 16 variables biometriques ont ete mesurees au niveau des parties aeriennes et souterraines. Les analyses statistiques revelent des differences significatives entre les ethno-varietes au niveau du nombre de rameau ( P=0,04 ), du poids sec des feuilles ( P=0,02 ), de la largeur de la feuille ( P=0,03 ), la longueur du pivot ( P=0,0001 ), du poids frais des racines ( P=0,005 ) et du poids sec des racines ( P=0,014 ). De plus un compromis d’investissement des ressources est observe entre les parties aeriennes et souterraines ainsi qu’entre les racines principales et secondaires. Il ressort de cette etude que les caracteres discriminants au jeune âge constituent des indicateurs pour une selection precoce des ethno-varietes. © 2019 International Formulae Group. All rights reserved Mots cles: Vitellaria paradoxa , ethno-variete, Selection precoce English Title: Variability of morphological characters of seedlings of five ethnovarieties of shea ( Vitellaria paradoxa C. F. Gaertn, Sapotaceae) in Burkina Faso English Abstract A species of economic interest, shea has an age at first fruit set between 12 and 20 years. This extends his selection scheme. To overcome this constraint, early tests must be performed at nursery age. This study focuses on five ethno-varieties of shea identified in Burkina Faso. Ethno-varieties are names attributed by farmers to different varieties of shea fruits. The objective of the study is to identify relevant juvenile traits as an early selection index. The study covers 100 seedlings of 5 ethno-varieties. A total of 16 biometric variables were measured in the aerial and underground parts. Statistical analyzes reveal significant differences between ethno-varieties in shoot number ( P = 0.04 ), leaf dry weight ( P = 0.02 ), leaf width ( P = 0, 03 ), pivot length ( P = 0.0001 ), fresh root weight ( P = 0.005 ) and root dry weight ( P = 0.014 ). In addition, a compromise of investment of resources is observed between the aerial and underground parts as well as between the main and secondary roots. This study shows that early discriminant traits are indicators for early selection of ethno-varieties. © 2019 International Formulae Group. All rights reserved Keywords: Vitellaria paradoxa , ethnovariety, early selection

Background Neural tube defects (NTD) are among the most common defects affecting 1:1000 births. They are caused by a failure of neural tube closure during development. Their clinical presentation is diverse and dependent on the site and severity of the original defect on the embryonic axis. The etiology of NTD is multifactorial involving environmental factors and genetic variants that remain largely unknown. Methods We have conducted a whole exome sequencing (WES) study in five new NTD families and pooled the results with WES data from three NTD families and 43 trios that were previously investigated by our group. We analyzed the data using biased candidate gene and unbiased gene burden approaches. Results We identified four novel loss‐of‐function variants in three genes, MTHFR,DLC1, and ITGB1, previously associated with NTD. Notably, DLC1 carried two protein truncating variants in two independent cases. We also demonstrated an enrichment of variants in MYO1E involved in cytoskeletal remodeling. This enrichment reached borderline significance in a replication cohort supporting the association of this new candidate gene to NTD. Conclusion These data provide some key insights into the pathogenic mechanisms of human NTD and demonstrate the power of next‐generation sequencing in deciphering the genetics of this complex trait.

Introduction . Notre etude a porte sur l’identification des insectes nuisibles des fruits de jujubiers indiens introduits au Burkina Faso. Notre objectif a ete de faire l’inventaire de ces insectes ravageurs infeodes a ces nouveaux cultivars de jujubiers et de tester diverses techniques pour leur piegeage. Apres identification des insectes dont la plante hote est le jujubier, nous avons determine ceux qui accomplissent leur cycle de reproduction sur les jujubes. Materiel et methodes . Nous avons utilise des appâts alimentaires avec des pieges de fabrication industrielle renfermant du torula et du terpinyl acetate et teste l’efficacite de complexes [pieges artisanaux / attractifs naturels] par rapport aux pieges a torula. Ensuite, nous avons mis en incubation des fruits attaques afin d’identifier les insectes qui en emergeraient. La fluctuation des populations de Tephritidae a ete suivie a partir de releves hebdomadaires dans les pieges a torula. Simultanement l’evolution de la production fruitiere a ete etudiee. Resultats . L’inventaire effectue en verger de jujubiers indiens a revele la presence de plusieurs familles appartenant a l’ordre des dipteres parmi lesquelles figurent dix especes de mouches de fruits reparties dans quatre genres (Bactrocera , Dacus , Ceratitis et Carpomya ) ; une noctuelle de l’ordre des lepidopteres (genre Agrotis ) a egalement ete identifiee. Les especes les plus representees dans les collectes effectuees par pieges ont ete Carpomya incompleta (44,86 %), Bactrocera invadens (21,58 %) et Bactrocera cucurbitae (18,49 %). Le taux d’emergence apres incubation des jujubes attaques a ete de 50 %. Deux especes seulement ont emerge de ces fruits : C. incompleta (84 %) et Agrostis sp. (16 %). Parmi les appâts alimentaires naturels testes, seul le melange [biere locale + banane] a permis de pieger des Tephritidae (Bactrocera invadens ) et la noctuelle Agrotis sp. Cependant, deux autres appâts naturels (fruits en putrefaction et lait concentre) ont permis de capturer Agrotis sp. Discussion et conclusion . Nos resultats ont mis en evidence les deux ravageurs potentiels des jujubiers indiens au Burkina Faso. Des etudes complementaires sur l’identification de l’espece d’Agrotis , et sur la biologie, l’ecologie et le comportement des ravageurs incrimines seront necessaires pour la definition de methodes de lutte en plantations de jujubiers au Burkina.

In the recent past, search in sensor systems focused on node hardware constraints and very limited energy resources. But nowadays, that new applications need data processing with temporal constraints in their tasks; then one of the new challenges faced by wireless sensor networks (WSNs) is handling real-time storage and querying the data they process. Two main approaches to storage and querying data are generally considered warehousing and distributed. The warehousing approach stores data in a central database and then queries may be performed to it. In a distributed approach, sensor devices are considered as local databases and data are managed locally. The data collected by sensors must represent the current state of the environment; for this reason they are subject to logic and time constraints. Then, this paper identifies the main specifications of real-time data management and presents the available real-time data management solutions for WSNs, in order to discuss them and identify some open issues and provide guidelines for further contributions.