Rapid Herbivore-Induced Changes in Mountain Birch Phenolics and Nutritive Compounds and Their Effects on Performance of the Major Defoliator, Epirrita autumnata

Insect damage changes plant physiology and chemistry, and such changes may influence the performance of herbivores. We introduced larvae of the autumnal moth (Epirrita autumnataBorkh.) on individual branches of its main host plant, mountain birch (Betula pubescens ssp. czerepanovii (Orlova) Hämet-Ahti) to examine rapid-induced plant responses, which may affect subsequent larval development. We measured systemic responses to herbivory by analyzing chemistry, photosynthesis, and leaf growth, as well as effects on larval growth and feeding, in undamaged branches of damaged and control trees. Larvae reared on leaves from intact branches of the herbivore-damaged trees grew faster than those reared on leaves of control trees, indicating systemic-induced susceptibility. Herbivore damage did not lead to systemic changes in levels of primary nutrients or phenolic compounds. The analyses of photosynthetic activity and individual hydrolyzable tannins revealed a reversal of leaf physiology-herbivore defense patterns. On control trees, consumption by E. autumnata larvae was positively correlated with photosynthetic activity; on damaged trees, this correlation was reversed, with consumption being negatively correlated with photosynthetic activity. A similar pattern was found in the relationship between monogalloylglucose, the most abundant hydrolyzable tannin of mountain birch, and leaf consumption. Among the control trees, consumption was positively correlated with concentrations of monogalloylglucose, whereas among herbivore-damaged trees, this correlation was reversed and became negative. Our results suggest that herbivore performance is related to both concentrations of phenolic compounds and photosynthetic activity in leaves. This linkage between herbivore performance, leaf chemistry, and physiology was sensitive to induced plant responses caused by slight herbivore damage.     

Interactive Effects of Genotype, Environment, and Ontogeny on Resistance of Cucumber (Cucumis sativus) to the Generalist Herbivore, Spodoptera exigua

Host-plant genotype, environment, and ontogeny all play a role in determining plant resistance to herbivory, yet little is known about the nature of the interactions among these factors. We investigated resistance of cucumber plants Cucumis sativus to the generalist herbivore Spodoptera exigua in a manipulative experiment involving three factors. In particular, we tested the effects of bitter (cucurbitacins present) vs. sweet (cucurbitacins absent) plants (genotype), with or without previous herbivory (environment), and cotyledons vs. true leaves (ontogeny). Contrary to our expectations, S. exigua growth was 54% higher on bitter plants than on sweet plants; growth was 63% higher, however, on undamaged plants compared to damaged plants, and 59% higher on true leaves compared to cotyledons. Moreover, all two-way interaction terms between genotype, environment, and ontogeny were significant. For example, S. exigua performance was higher on bitter than on sweet plants; however, this effect was strongly influenced by whether the tissue consumed was a cotyledon or true leaf and also whether it had been previously damaged. An examination of leaf nutritional chemistry revealed that some of our results could be explained by genotypic, environmental, and ontogenic differences in foliar nitrogen content. In contrast, the cucurbitacin content of plants did not appear to affect caterpillar growth. Our results provide evidence for the importance of interactions between genotype, environment, and ontogeny in determining herbivory and illustrate the value of manipulative experiments in revealing the complexities of these interactions.     

A new grouping genetic algorithm approach to the multiple traveling salesperson problem

The multiple traveling salesperson problem (MTSP) is an extension of the well known traveling salesperson problem (TSP). Given m > 1 salespersons and n > m cities to visit, the MTSP seeks a partition of cities into m groups as well as an ordering among cities in each group so that each group of cities is visited by exactly one salesperson in their specified order in such a way that each city is visited exactly once and sum of total distance traveled by all the salespersons is minimized. Apart from the objective of minimizing the total distance traveled by all the salespersons, we have also considered an alternate objective of minimizing the maximum distance traveled by any one salesperson, which is related with balancing the workload among salespersons. In this paper, we have proposed a new grouping genetic algorithm based approach for the MTSP and compared our results with other approaches available in the literature. Our approach outperformed the other approaches on both the objectives.     

FakeBERT: Fake news detection in social media with a BERT-based deep learning approach

In the modern era of computing, the news ecosystem has transformed from old traditional print media to social media outlets. Social media platforms allow us to consume news much faster, with less restricted editing results in the spread of fake news at an incredible pace and scale. In recent researches, many useful methods for fake news detection employ sequential neural networks to encode news content and social context-level information where the text sequence was analyzed in a unidirectional way. Therefore, a bidirectional training approach is a priority for modelling the relevant information of fake news that is capable of improving the classification performance with the ability to capture semantic and long-distance dependencies in sentences. In this paper, we propose a BERT-based (Bidirectional Encoder Representations from Transformers) deep learning approach (FakeBERT) by combining different parallel blocks of the single-layer deep Convolutional Neural Network (CNN) having different kernel sizes and filters with the BERT. Such a combination is useful to handle ambiguity, which is the greatest challenge to natural language understanding. Classification results demonstrate that our proposed model (FakeBERT) outperforms the existing models with an accuracy of 98.90%.

     

WiFiRe: rural area broadband access using the WiFi PHY and a multisector TDD MAC

The needs of Indian rural telecom, and the economics of currently available broadband access technologies, motivate a new system for rural broadband access, which we call WiFiRe (WiFi rural extension). The system leverages the widely available, and highly cost-reduced, WiFi chipsets. We, however, retain only the PHY from these chipsets and propose a single-channel, multisector, TDD MAC using directional antennas. The proposed WiFiRe MAC is similar to the WiMAX MAC in several respects. In this article we motivate our approach, describe the system architecture and the MAC, analyse the spatial reuse, and then, using a simple scheduler, provide an assessment of the voice and data capacity of a WiFiRe system     

Structure–property relationship studies in amine functionalized multiwall carbon nanotubes filled polypropylene composite fiber

Amine functionalized multiwalled carbon nanotubes (a‐MWNT) based polypropylene (PP) composite fibers were prepared in the presence of polypropylene‐g‐maleic anhydride (PP‐g‐MA) by melt‐mixing followed by melt‐spinning with subsequent post‐drawing of the as‐spun fibers of varying draw ratio (DR). In order to enhance the interfacial interaction, a‐MWNT were utilized in combination with PP‐g‐MA during melt‐mixing. Fourier transform infrared spectroscopic analysis revealed the formation of imide bonds between MA functionality of PP‐g‐MA and amine functional group of a‐MWNT. Higher tensile properties of PP/a‐MWNT/PP‐g‐MA composite fibers were registered with varying DR of the as‐spun fiber. Orientation factors of a‐MWNT and PP chains along the fiber axis were correlated with the higher tensile modulus and tensile strength of PP/a‐MWNT/PP‐g‐MA composite fiber of varying DR. Crystallization studies indicated the role of hetero‐nucleating action of a‐MWNT in PP/a‐MWNT/PP‐g‐MA composite fiber. POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers     

Identification of influential vertices in complex networks: A hitting time-based approach

Unravelling the dynamics of network vertices is pivotal, and traditional centrality measures have limitations in adapting to structural changes, directed and weighted networks, and temporal analyses. This paper introduces a ground breaking approach - hitting time-based centrality. Utilizing network matrix notations and a random walk model on a connected network , we establish a Markov chain to quantify the hitting time, hitting distance, and hitting centrality, providing a nuanced measure prioritizing central vertices. Through extensive experiments using Kendall's tau coefficient, the paper evaluates the method's correlation with actual influence in the Susceptible-Infectious (SI) model, showcasing superior performance across diverse network sizes and structures. The hitting centrality method exhibits sensitivity to connectivity dynamics, effective incorporation of temporal dynamics, and robust handling of weighted and directed networks. Positive Kendall's tau coefficients underline the method's proficiency in prioritizing influential vertices by correlating hitting centrality values with actual infection ability. The demonstrated robustness to structural changes enhances its utility for dynamic network analysis. In conclusion, our hitting time-based centrality approach emerges as a promising method, mitigating the shortcomings of traditional measures. By integrating information propagation speed, accommodating network dynamics, and enabling time-dependent analyses, it offers a comprehensive tool for evaluating vertex importance and influence in complex networks.     

Component Inventory Costs in an Assembly Problem with Uncertain Supplier Lead-Times

We present a generic study of inventory costs in a factory stockroom that supplies component parts to an assembly line. Specifically, we are concerned with the increase in component inventories due to uncertainty in supplier lead-times, and the fact that several different components must be present before assembly can begin. It is assumed that the suppliers of the various components are independent, that the suppliers' operations are in statistical equilibrium, and that the same amount of each type of component is demanded by the assembly line each time a new assembly cycle is scheduled to begin. We use, as a measure of inventory cost, the expected time for which an order of components must be held in the stockroom from the time it is delivered until the time it is consumed by the assembly line. Our work reveals the effects of supplier lead-time variability, the number of different types of components, and their desired service levels, on the inventory cost. In addition, under the assumptions that inventory holding costs and the cost of delaying assembly are linear in time, we study optimal ordering policies and present an interesting characterization that is independent of the supplier lead-time distributions.