scholarly journals Reduction in population size and not a shift in parasite community affect evolution of immune genes in island birds.

2021 ◽  
Author(s):  
Mathilde Barthe ◽  
Claire Doutrelant ◽  
Rita Covas ◽  
Martim Melo ◽  
Juan Carlos Illera ◽  
...  
Keyword(s):  
Population Size ◽  
Selection Pressure ◽  
Comparative Genomic ◽  
Immune Functions ◽  
Relaxed Selection ◽  
Immune Genes ◽  
Island Species ◽  
Public Data ◽  
Island Syndrome ◽  
The Impact

Shared ecological conditions encountered by species that colonize islands often lead to the evolution of convergent phenotypes, commonly referred to as "island syndrome". Reduced immune functions have been previously proposed to be part of the island syndrome, as a consequence of the reduced diversity of pathogens on island ecosystems. According to this hypothesis, immune genes are expected to exhibit genomic signatures of relaxed selection pressure in island species. In this study, we used comparative genomic methods to study immune genes in island species (N = 20) and their mainland relatives (N = 14). We gathered public data as well as generated new data on innate (Toll-Like Receptors, Beta Defensins) and acquired immune genes (Major Histocompatibility Complex classes I and II), but also on hundreds of genes annotated as involved in various immune functions. As a control, we used a set of 97 genes not involved in immune functions, to account for the lower effective population sizes in island species. We used synonymous and non-synonymous variations to estimate the selection pressure acting on immune genes. For the genes evolving under balancing selection, we used simulation to estimate the impact of population size variation. We found a significant effect of drift on immune genes of island species leading to a reduction in genetic diversity and efficacy of selection. However, the intensity of relaxed selection was not significantly different from control genes, except for MHC class II genes. These genes exhibit a significantly higher level of non-synonymous loss of polymorphism than expected assuming only drift and an evolution under frequency dependent selection, possibly due to a reduction of extracellular parasite communities on islands. Overall, our results showed that demographic effects lead to a decrease in the immune functions of island species, but the relaxed selection caused by a reduced parasite pressure may only occur in some immune genes categories.

scholarly journals An Analysis of Selection in Genetic Programming

2021 ◽  
Author(s):  
◽  
Huayang Xie
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Selection Pressure ◽  
Clustering Algorithm ◽  
Selection Process ◽  
Fitness Evaluation ◽  
Parent Selection ◽  
Size Limitation ◽  
Tournament Selection ◽  
The Impact

<p>This thesis presents an analysis of the selection process in tree-based Genetic Programming (GP), covering the optimisation of both parent and offspring selection, and provides a detailed understanding of selection and guidance on how to improve GP search effectively and efficiently. The first part of the thesis providesmodels and visualisations to analyse selection behaviour in standard tournament selection, clarifies several issues in standard tournament selection, and presents a novel solution to automatically and dynamically optimise parent selection pressure. The fitness evaluation cost of parent selection is then addressed and some cost-saving algorithms introduced. In addition, the feasibility of using good predecessor programs to increase parent selection efficiency is analysed. The second part of the thesis analyses the impact of offspring selection pressure on the overall GP search performance. The fitness evaluation cost of offspring selection is then addressed, with investigation of some heuristics to efficiently locate good offspring by constraining crossover point selection structurally through the analysis of the characteristics of good crossover events. The main outcomes of the thesis are three new algorithms and four observations: 1) a clustering tournament selection method is developed to automatically and dynamically tune parent selection pressure; 2) a passive evaluation algorithm is introduced for reducing parent fitness evaluation cost for standard tournament selection using small tournament sizes; 3) a heuristic population clustering algorithm is developed to reduce parent fitness evaluation cost while taking advantage of clustering tournament selection and avoiding the tournament size limitation; 4) population size has little impact on parent selection pressure thus the tournament size configuration is independent of population size; and different sampling replacement strategies have little impact on the selection behaviour in standard tournament selection; 5) premature convergence occurs more often when stochastic elements are removed from both parent and offspring selection processes; 6) good crossover events have a strong preference for whole program trees, and (less strongly) single-node or small subtrees that are at the bottom of parent program trees; 7) the ability of standard GP crossover to generate good offspring is far below what was expected.</p>

scholarly journals An Analysis of Selection in Genetic Programming

2021 ◽  
Author(s):  
◽  
Huayang Xie
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Selection Pressure ◽  
Clustering Algorithm ◽  
Selection Process ◽  
Fitness Evaluation ◽  
Parent Selection ◽  
Size Limitation ◽  
Tournament Selection ◽  
The Impact

<p>This thesis presents an analysis of the selection process in tree-based Genetic Programming (GP), covering the optimisation of both parent and offspring selection, and provides a detailed understanding of selection and guidance on how to improve GP search effectively and efficiently. The first part of the thesis providesmodels and visualisations to analyse selection behaviour in standard tournament selection, clarifies several issues in standard tournament selection, and presents a novel solution to automatically and dynamically optimise parent selection pressure. The fitness evaluation cost of parent selection is then addressed and some cost-saving algorithms introduced. In addition, the feasibility of using good predecessor programs to increase parent selection efficiency is analysed. The second part of the thesis analyses the impact of offspring selection pressure on the overall GP search performance. The fitness evaluation cost of offspring selection is then addressed, with investigation of some heuristics to efficiently locate good offspring by constraining crossover point selection structurally through the analysis of the characteristics of good crossover events. The main outcomes of the thesis are three new algorithms and four observations: 1) a clustering tournament selection method is developed to automatically and dynamically tune parent selection pressure; 2) a passive evaluation algorithm is introduced for reducing parent fitness evaluation cost for standard tournament selection using small tournament sizes; 3) a heuristic population clustering algorithm is developed to reduce parent fitness evaluation cost while taking advantage of clustering tournament selection and avoiding the tournament size limitation; 4) population size has little impact on parent selection pressure thus the tournament size configuration is independent of population size; and different sampling replacement strategies have little impact on the selection behaviour in standard tournament selection; 5) premature convergence occurs more often when stochastic elements are removed from both parent and offspring selection processes; 6) good crossover events have a strong preference for whole program trees, and (less strongly) single-node or small subtrees that are at the bottom of parent program trees; 7) the ability of standard GP crossover to generate good offspring is far below what was expected.</p>

scholarly journals Impact of Chronic Exposure to Sublethal Doses of Glyphosate on Honey Bee Immunity, Gut Microbiota and Infection by Pathogens

2021 ◽  
Vol 9 (4) ◽  
pp. 845
Author(s):  
Loreley Castelli ◽  
Sofía Balbuena ◽  
Belén Branchiccela ◽  
Pablo Zunino ◽  
Joanito Liberti ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Honey Bee ◽  
Chronic Exposure ◽  
Pollination Services ◽  
Deformed Wing Virus ◽  
Immune Genes ◽  
Bee Health ◽  
Honey Bee Health ◽  
Sublethal Doses ◽  
The Impact

Glyphosate is the most used pesticide around the world. Although different studies have evidenced its negative effect on honey bees, including detrimental impacts on behavior, cognitive, sensory and developmental abilities, its use continues to grow. Recent studies have shown that it also alters the composition of the honey bee gut microbiota. In this study we explored the impact of chronic exposure to sublethal doses of glyphosate on the honey bee gut microbiota and its effects on the immune response, infection by Nosema ceranae and Deformed wing virus (DWV) and honey bee survival. Glyphosate combined with N. ceranae infection altered the structure and composition of the honey bee gut microbiota, for example by decreasing the relative abundance of the core members Snodgrassella alvi and Lactobacillus apis. Glyphosate increased the expression of some immune genes, possibly representing a physiological response to mitigate its negative effects. However, this response was not sufficient to maintain honey bee health, as glyphosate promoted the replication of DWV and decreased the expression of vitellogenin, which were accompanied by a reduced life span. Infection by N. ceranae also alters honey bee immunity although no synergistic effect with glyphosate was observed. These results corroborate previous findings suggesting deleterious effects of widespread use of glyphosate on honey bee health, and they contribute to elucidate the physiological mechanisms underlying a global decline of pollination services.

scholarly journals Behavior of Traffic Congestion and Public Transport in Eight Large Cities in Latin America during the COVID-19 Pandemic

2021 ◽  
Vol 11 (10) ◽  
pp. 4703
Author(s):  
Renato Andara ◽  
Jesús Ortego-Osa ◽  
Melva Inés Gómez-Caicedo ◽  
Rodrigo Ramírez-Pisco ◽  
Luis Manuel Navas-Gracia ◽  
...  
Keyword(s):  
Latin American ◽  
Public Transport ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Urban Transport ◽  
Control Measures ◽  
Johns Hopkins Hospital ◽  
Large Cities ◽  
Public Data ◽  
The Impact

This comparative study analyzes the impact of the COVID-19 pandemic on motorized mobility in eight large cities of five Latin American countries. Public institutions and private organizations have made public data available for a better understanding of the contagion process of the pandemic, its impact, and the effectiveness of the implemented health control measures. In this research, data from the IDB Invest Dashboard were used for traffic congestion as well as data from the Moovit© public transport platform. For the daily cases of COVID-19 contagion, those published by Johns Hopkins Hospital University were used. The analysis period corresponds from 9 March to 30 September 2020, approximately seven months. For each city, a descriptive statistical analysis of the loss and subsequent recovery of motorized mobility was carried out, evaluated in terms of traffic congestion and urban transport through the corresponding regression models. The recovery of traffic congestion occurs earlier and faster than that of urban transport since the latter depends on the control measures imposed in each city. Public transportation does not appear to have been a determining factor in the spread of the pandemic in Latin American cities.

A Tale of Two Entities

2021 ◽  
Vol 2 (2) ◽  
pp. 1-21
Author(s):  
Hossam ElHussini ◽  
Chadi Assi ◽  
Bassam Moussa ◽  
Ribal Atallah ◽  
Ali Ghrayeb
Keyword(s):  
Power Flow ◽  
Power Grid ◽  
Communication Protocols ◽  
Charging Infrastructure ◽  
Electric Vehicle Charging ◽  
Public Data ◽  
Simulation Based ◽  
Charging Stations ◽  
The Impact ◽  
Ev Charging

With the growing market of Electric Vehicles (EV), the procurement of their charging infrastructure plays a crucial role in their adoption. Within the revolution of Internet of Things, the EV charging infrastructure is getting on board with the introduction of smart Electric Vehicle Charging Stations (EVCS), a myriad set of communication protocols, and different entities. We provide in this article an overview of this infrastructure detailing the participating entities and the communication protocols. Further, we contextualize the current deployment of EVCSs through the use of available public data. In the light of such a survey, we identify two key concerns, the lack of standardization and multiple points of failures, which renders the current deployment of EV charging infrastructure vulnerable to an array of different attacks. Moreover, we propose a novel attack scenario that exploits the unique characteristics of the EVCSs and their protocol (such as high power wattage and support for reverse power flow) to cause disturbances to the power grid. We investigate three different attack variations; sudden surge in power demand, sudden surge in power supply, and a switching attack. To support our claims, we showcase using a real-world example how an adversary can compromise an EVCS and create a traffic bottleneck by tampering with the charging schedules of EVs. Further, we perform a simulation-based study of the impact of our proposed attack variations on the WSCC 9 bus system. Our simulations show that an adversary can cause devastating effects on the power grid, which might result in blackout and cascading failure by comprising a small number of EVCSs.

scholarly journals Pest Status and Management of Corn Earworm (Lepidoptera: Noctuidae) in Field Corn in the United States

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Francis P F Reay-Jones
Keyword(s):  
United States ◽  
Selection Pressure ◽  
The United States ◽  
Corn Earworm ◽  
Bt Corn ◽  
Pest Status ◽  
Field Corn ◽  
Type Of Injury ◽  
The Impact ◽  
Economic Pest

Abstract The corn earworm, Helicoverpa zea (Boddie), is a common lepidopteran pest of corn (Zea mays L.) in the United States. This article provides an overview of the life history, ecology, plant injury, and management of H. zea in corn. Leaf injury by H. zea feeding can occur in vegetative stage corn, though this type of injury is rare. The most common type of injury is caused by larval feeding in ears. Because kernel injury is typically limited to the tip of the ear, H. zea is generally not considered an economic pest. The use of transgenic corn hybrids expressing insecticidal Cry proteins from Bacillus thuringiensis (Bt) Berliner can reduce injury from H. zea, though complete control is not achieved with most Bt traits. Resistance has been reported to several Bt toxins. Because H. zea is a major economic pest in cotton (Gossypium hirsutum L.) and because H. zea moths that developed on corn can migrate to cotton, selection pressure on H. zea in Bt corn has major implications for the pest status and injury to Bt cotton. Although the impact of H. zea on yield of field corn is generally negligible, the selection pressure exerted by Bt corn has led to management issues in cotton.

scholarly journals The Impact of Armed Conflict on the Epidemiological Situation of COVID-19 in Libya, Syria and Yemen

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed A. Daw
Keyword(s):  
Armed Conflict ◽  
Early Stage ◽  
Armed Conflicts ◽  
Cumulative Number ◽  
The Novel ◽  
Global Pandemic ◽  
Large Numbers ◽  
Public Data ◽  
Novel Coronavirus ◽  
The Impact

Background: Since the Arab uprising in 2011, Libya, Syria and Yemen have gone through major internal armed conflicts. This resulted in large numbers of deaths, injuries, and population displacements, with collapse of the healthcare systems. Furthermore, the situation was complicated by the emergence of COVID-19 as a global pandemic, which made the populations of these countries struggle under unusual conditions to deal with both the pandemic and the ongoing wars. This study aimed to determine the impact of the armed conflicts on the epidemiology of the novel coronavirus (SARS-CoV-2) within these war-torn countries and highlight the strategies needed to combat the spread of the pandemic and its consequences.Methods: Official and public data concerning the dynamics of the armed conflicts and the spread of SARS-COV-2 in Libya, Syria and Yemen were collected from all available sources, starting from the emergence of COVID-19 in each country until the end of December 2020. Datasets were analyzed by a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the conflict and the prevalence of COVID-19.Results: The data indicated that there was an increase in the intensity of the violence at an early stage from March to August 2020, when it approximately doubled in the three countries, particularly in Libya. During that period, few cases of COVID-19 were reported, ranging from 5 to 53 cases/day. From September to December 2020, a significant decline in the intensity of the armed conflicts was accompanied by steep upsurges in the rate of COVID-19 cases, which reached up to 500 cases/day. The accumulative cases vary from one country to another during the armed conflict. The highest cumulative number of cases were reported in Libya, Syria and Yemen.Conclusions: Our analysis demonstrates that the armed conflict provided an opportunity for SARS-CoV-2 to spread. The early weeks of the pandemic coincided with the most intense period of the armed conflicts, and few cases were officially reported. This indicates undercounting and hidden spread during the early stage of the pandemic. The pandemic then spread dramatically as the armed conflict declined, reaching its greatest spread by December 2020. Full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its consequences.

scholarly journals Collaborative Filtering Recommendation Algorithm Based on TF-IDF and User Characteristics

2021 ◽  
Vol 11 (20) ◽  
pp. 9554
Author(s):  
Jianjun Ni ◽  
Yu Cai ◽  
Guangyi Tang ◽  
Yingjuan Xie
Keyword(s):  
Collaborative Filtering ◽  
User Characteristics ◽  
Recommendation Algorithm ◽  
Data Set ◽  
Rating Data ◽  
User Similarity ◽  
Public Data ◽  
Weighted Algorithm ◽  
Collaborative Filtering Algorithm ◽  
The Impact

The recommendation algorithm is a very important and challenging issue for a personal recommender system. The collaborative filtering recommendation algorithm is one of the most popular and effective recommendation algorithms. However, the traditional collaborative filtering recommendation algorithm does not fully consider the impact of popular items and user characteristics on the recommendation results. To solve these problems, an improved collaborative filtering algorithm is proposed, which is based on the Term Frequency-Inverse Document Frequency (TF-IDF) method and user characteristics. In the proposed algorithm, an improved TF-IDF method is used to calculate the user similarity on the basis of rating data first. Secondly, the multi-dimensional characteristics information of users is used to calculate the user similarity by a fuzzy membership method. Then, the above two user similarities are fused based on an adaptive weighted algorithm. Finally, some experiments are conducted on the movie public data set, and the experimental results show that the proposed method has better performance than that of the state of the art.

The dietary arachidonic acid improved growth and immunity of honey bee (Apis mellifera ligustica)

2021 ◽  
pp. 1-10
Author(s):  
Jing Yu ◽  
Weixing Zhang ◽  
Xuepeng Chi ◽  
Wenfeng Chen ◽  
Zhenfang Li ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Arachidonic Acid ◽  
Apis Mellifera ◽  
The Body ◽  
Control Group ◽  
Immune Functions ◽  
Pufa Content ◽  
Apis Mellifera Ligustica ◽  
Immune Genes ◽  
Mrna Expression Levels

Abstract Honeybees cannot synthesize arachidonic acid (ARA) themselves, only obtain it from food. Most pollen is deficient or contains a small amount of ARA. The necessity of supplementary ARA in bees’ diet has not been studied. The objective of this study was to investigate the effects of dietary ARA levels on the growth and immunity of Apis mellifera ligustica. A total of 25 honeybee colonies were randomly assigned to five dietary groups which were fed basic diets supplemented with 0, 2, 4, 6, and 8% of ARA. The diet with 4% ARA improved the body weight of newly emerged worker bees compared with the control group. Supplement of ARA in honeybee diets changed the fatty acid composition of honeybee body. SFA and MUFA contents of bees’ body declined, and PUFA content rised in the ARA group. Compared with the control group, the supplement of ARA in honeybee diets increased the contents of ARA, C22:6n-3 (DHA) and C18:3n-6 in bees’ body significantly, but decreased the contents of C16:1 and C18:3n-3. The diet supplied with 4% ARA reduced the mortality rate of honeybee infected with Escherichia coli. The activity of immune enzymes (phenoloxidase, antitrypsin, and lysozyme) and the mRNA expression levels of immune genes (defensin-2, toll, myd88, and dorsal) were improved by ARA diets to varying degrees depending on the ARA levels, especially 4% ARA. These results suggested that dietary ARA could improve the growth, survival, and immune functions of honeybees. Supplement of ARA in bees’ diet would be valuable for the fitness of honeybees.

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