An Improved Intrusion Weed Optimization Algorithm for Node Location in Wireless Sensor Networks

The distribution optimization of WSN nodes is one of the key issues in WSN research, and also is a research hotspot in the field of communication. Aiming at the distribution optimization of WSN nodes, the distribution optimization scheme of nodes based on improved invasive weed optimization algorithm(IIWO) is proposed. IIWO improves the update strategy of the initial position of weeds by using cubic mapping chaotic operator, and uses the Gauss mutation operator to increase the diversity of the population. The simulation results show that the algorithm proposed in this paper has a higher solution quality and faster convergence speed than IWO and CPSO. In distribution optimization example of WSN nodes, the optimal network coverage rate obtained by IIWO is respectively improved by 1.82% and 0.93% than the IWO and CPSO. Under the condition of obtaining the same network coverage rate, the number of nodes required by IIWO is fewer.

Ethnic Use, Phytochemistry, and Pharmacology of Cyperus rotundus

Cyperus rotundus (nut grass in English) is a perennial erect sedge plant and is distributed in over 90 countries of the world, where it has been mostly classified as a highly invasive weed. Despite this classification, the plant has been considered from traditional times to be medicinally important. The traditional uses of the plant in various countries include uses against various gastrointestinal tract disorders, skin diseases, leprosy, fever, and neurological disorders. Evaluation of the plant and especially its rhizomes in a scientific manner has revealed the presence of numerous phytochemicals and wide-ranging pharmacological activities, which include anti-microbial, gastrointestinal, wound healing, anti-diabetic, anti-cancer, anti-malarial, anti-obesity, hepatoprotective, and anti-pyretic activity. The scientific validation of a number of traditional uses strongly indicates that the plant may prove useful in the discovery of a number of lead compounds and novel drugs.

On the Utilization of an Ensemble of Meta-Heuristics for Simulating Energy Consumption in Buildings

Predicting energy consumption has been a substantial topic because of its ability to lessen energy wastage and establish an acceptable overall operational efficiency. Thus, this research aims at creating a meta-heuristic-based method for autonomous simulation of heating and cooling loads of buildings. The developed method is envisioned on two tiers, whereas the first tier encompasses the use of a set of meta-heuristic algorithms to amplify the exploration and exploitation of Elman neural network through both parametric and structural learning. In this regard, ten meta-heuristic were utilized, namely differential evolution, particle swarm optimization, invasive weed optimization, teaching-learning optimization, ant colony optimization, grey wolf optimization, grasshopper optimization, moth-flame optimization, antlion optimization, and arithmetic optimization. The second tier is designated for evaluating the meta-heuristic-based models through performance evaluation and statistical comparisons. Besides, an integrative ranking of the models is achieved using average ranking algorithm.

Improved Invasive Weed Optimization Algorithm for Global Maximum Power Point Tracking of PV Array Under Partial Shading Conditions

Photovoltaic (PV) array under partial shading conditions (PSCs) has several maximum power points (MPPs) on the power-voltage curve of the PV array. These points; have a unique global peak (GP) and the others are local peaks (LPs). This paper aims to study an improved version of a heuristic optimization technique namely, Invasive Weed Optimization (IWO) to track the global maximum power point (GMPP) of a PV array which is an important issue. The proposed improved IWO (IIWO) algorithm modifies IWO to speed up the convergence and make the system more efficient. In addition to study the effect of changing input parameters of IIWO on its performance. An overall statistical evaluation of IIWO, with standard IWO and Particle Swarm Optimization (PSO) is executed under different shading conditions. The simulation results show that IIWO has faster and better convergence as it can reach the GMPP in less time compared with other techniques.

Review of the Biology, Distribution, and Management of the Invasive Fireweed (Senecio madagascariensis Poir)

Whilst exotic invasive species are a major threat to natural and modified ecosystems around the world, management programs to reduce their impacts often fail due to a lack of information about their biology and how best to control them in various situations. This paper reviews the currently available information on the biology, distribution, and management options for the invasive weed Senecio madagascariensis Poir. (fireweed). In addition, we developed a model to predict the climatic suitability of this weed around the world based on the current climate. Senecio madagascariensis originates from southern Africa but it has been introduced to several other countries including Australia. Climatic suitability suggests that there are large areas around the world suitable for the weed’s growth where it is currently not present. The weed poses a major threat to livestock industries in these countries through its ability to reduce pasture production and poison animals. A range of control techniques have been used to try and manage S. madagascariensis. This paper highlights how a better understanding of the biology of S. madagascariensis can help determine the most effective treatments to impose and to further develop integrated management strategies. Besides using traditional approaches, the use of competitive pastures and more tolerant livestock (such as sheep and goats) are some of the other options recommended as part of an integrated approach. On-going research to identify host-specific biological control agents is also considered a priority.

Investigating the Phenotypic Plasticity of the Invasive Weed Trianthema portulacastrum L.

Phenotypic plasticity is frequently highlighted as a key factor in plant invasiveness, as it enables invasive species to adapt to diverse, complicated habitats. Trianthema portulacastrum is one of the most common aggressive species that threaten different crops around the world. Phenotypic plasticity in T. portulacastrum was investigated by comparing variation in germination, vegetative macromorphology, photosynthetic pigments, stomatal complexes, and seed micromorphological traits of 35 samples collected from 35 different localities. One-way cluster analysis and principal component analysis (PCA) were used to classify samples into homogeneous groups based on the measured traits. Pairwise statistical comparisons were conducted between the three resulting groups. The phenotypic plasticity index (PI) was calculated and compared among different groups of characters. Results showed that photosynthetic pigments and macromorphological characteristics had the highest PI, followed by seed micromorphology, and then stomatal complex traits, while germination parameters showed the lowest PI. We propose that soil moisture, salinity, and temperature are the most determinative and explanative variables of the variation between the three classified groups. We strongly believe that the phenotypic plasticity of T. portulacastrum will support species abundance and spread even under expected changes in climatic conditions, in contrast to the vulnerable traditional crops.

​Harmful Effect of the Invasive Weed Mikania micrantha with Special Reference to India: A Review

Mikania micrantha is an economically damaging invasive weed, which is widely naturalized in the tropical and subtropical regions of the world. This weed has reported yield losses in various cash crops and plantation crops in South East Asia including India. M. micrantha was found to change the soil microbial communities (bacteria, fungi and actinomycetes) as well as the soil chemical properties. It enhances a significant increase in aerobic bacteria but decreases in anaerobic bacteria due to which infested soil were free from other weeds. Similarly, in soil chemical characteristics significant increases in pH, total N and P were observed and a decrease in soil organic matter where M. micrantha is prevalent. It has allelopathic properties which affect neighbouring crops, weeds, insects and pathogens. This weed produces allelochemicals (phenolics, flavonoids, alkaloids and terpenes) that may be released by volatilization and decomposition of plant debris. It was also found that the aqueous leaf extract of invasive weed M. micrantha inhibited seed germination and seedling growth of various cereals, vegetables, and other plants. A similar result was found in test crops but there was no affected case found in the greenhouse experiment. This review will help the researchers and scientists in understanding the harmful effect of this invasive weed.

Multitrophic Interactions Between Arbuscular Mycorrhizal Fungi, Foliar Endophytic Fungi and Aphids

Almost all living plants can be simultaneously colonised by arbuscular mycorrhizal fungi in the roots and endophytes in the shoots, while also being attacked by insect herbivores. However, to date, no study has ever examined the multitrophic interactions between these two different fungal groups and insects on any species of forb. Here, we examined the effects of two commercial species mixtures of arbuscular mycorrhizal fungi (AMF) and two foliar endophytes (Colletotrichum acutatum and Cladosporium oxysporum) on the growth of an invasive weed, Impatiens glandulifera, and the aphids that attack it. AMF reduced plant biomass, which was most evident when C. oxysporum was inoculated. Mycorrhizal fungi had few effects on aphids, and these depended on the identity of the endophytes present. Meanwhile, endophytes tended to increase aphid numbers, but this depended on the identity of the AMF inoculum. Throughout, there were differences in the responses of the plant to the two mycorrhizal mixtures, demonstrating clear AMF specificity in this plant. These specific effects were also strongly affected by the endophytes, with a greater number of interactions found between the AMF and endophytes than between the endophytes themselves. In particular, AMF reduced infection levels by the endophytes, while some endophyte inoculations reduced mycorrhizal colonisation. We suggest that both AMF and endophytes could play an important part in future biological control programmes of weeds, but further multitrophic experiments are required to unravel the complexity of interactions between spatially separated parts of the plant microbiome.