S. B. Singh

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum.

Development of temporal modeling for forecasting and prediction of the incidence of lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), using time-series (ARIMA) analysis

The most destructive enemy of the lychee, Litchi chinensis Sonn. (Sapindales: Sapindaceae), in India is a stink bug, Tessaratoma papillosa (Drury) (Hemiptera: Tessaratomidae). The population of T. papillosa on lychee trees varied from 1.43 ± 0.501 to 9.85 ± 3.924 insects per branch in this study. An increase in the temperature and a decrease in the relative humidity during summer months (April to July) favor the population buildup of T. papillosa. A forecasting model to predict T. papillosa incidences in lychee orchards was developed using the autoregressive integrated moving average (ARIMA) model of time-series analysis. The best-fit model for the T. papillosa incidence was ARIMA (1,1), where the P-value was significant at 0.01. The highest T. papillosa incidences were predicted for April in 2010, January in 2011, May in 2012, and February in 2013. A model based on time series offers longer-term forecasting. The forecasting model, ARIMA (1,1), developed in this study will predict T. papillosa incidences in advance, thus providing functional guidelines for effective planning of timely prevention and control measures.

First report of economic injury to tomato due to Zeugodacus tau (Diptera: Tephritidae): relative abundance and effects of cultivar and season on injury

Abstract Insect infestation can adversely affect tomato (Solanum lycopersicum L.; Solanaceae) development and yield. Fruit flies (Diptera: Tephritidae) are a serious pest of tomato, and are spreading to areas where they were not previously found. This study was undertaken to determine if tephritid fruit flies were present, which species were most abundant, how tomato cultivars responded, and what amount of damage occurred in the Eastern Himalayas of India during May 2014 and 2015. Mature and ripe fruit (n = 20) per cultivar were picked at random from 12 cultivars at weekly intervals to assess percentage of infestation, fly species composition, larval infestation, pupal mortality, adult emergence, and sex ratio during 2 seasons. Seasonal fluctuation of male adults of Zeugodacus tau (Walker) (Diptera: Tephritidae) in tomato was studied by installing 3 modified clear traps, made from plastic bottles, that were baited with 0.5 mL Cue-lure and the insecticide dichlorovos 76% EC (Nuvan®). Survey and subsequent identification confirmed the presence of Z. tau in tomato in the Himalayas of India. This is the first report of the insect in the province, and of population outbreaks resulting in serious damage to tomato in India. Among fruit fly species present on tomato, Z. tau was more abundant (71.4–96.4%) in all geographical regions of Mizoram, India, than were Bactrocera correcta (Bezzi), B. dorsalis (Hendel), and B. latifrons (Hendel), which ranged from 3.6 to 28.6%. The highest percentage of infestation was in Champhai (72.7 ± 6.7%) and Kolasib (80.7 ± 3.5%) and the lowest in Mamit (14.7 ± 4.8%) and Serchhip (19.3 ± 4.7%). Cultivar influenced pupal mortality and adult emergence of Z. tau. Seasonal fluctuation of Z. tau males on tomato varied; the greatest numbers were trapped during May and Dec. Occurrence of Z. tau at high population densities was associated with high levels of damage and could lead to high economic losses in tomato fruit production.

A New Hybrid MGBPSO-GSA Variant for Improving Function Optimization Solution in Search Space

In this article, a newly hybrid nature-inspired approach (MGBPSO-GSA) is developed with a combination of Mean Gbest Particle Swarm Optimization (MGBPSO) and Gravitational Search Algorithm (GSA). The basic inspiration is to integrate the ability of exploitation in MGBPSO with the ability of exploration in GSA to synthesize the strength of both approaches. As a result, the presented approach has the automatic balance capability between local and global searching abilities. The performance of the hybrid approach is tested on a variety of classical functions, ie, unimodal, multimodal, and fixed-dimension multimodal functions. Furthermore, Iris data set, Heart data set, and economic dispatch problems are used to compare the hybrid approach with several metaheuristics. Experimental statistical solutions prove empirically that the new hybrid approach outperforms significantly a number of metaheuristics in terms of solution stability, solution quality, capability of local and global optimum, and convergence speed.

Distribution and Biology of Mallada desjardinsi (Neuroptera: Chrysopidae) in India and Its Predatory Potential Against Aleurodicus dispersus (Hemiptera: Aleyrodidae)

Abstract In this study, we report the prevalence of Mallada desjardinsi (Navas) in seven geographical regions of India and provide the first report of its kind outlining the preying of all stages of the spiraling whitefly, Aleurodicus dispersus Russell, by M. desjardinsi. Sampling was conducted in seven regions of two provinces in India, Bengaluru (Karnataka) and Tiruppur (Tamil Nadu), which demonstrated that M. desjardinsi populations were most dense at the former and least at the later. To the best of our knowledge, this is the first report of its kind outlining observations regarding the biology and feeding potential of M. desjardinsi on A. dispersus under laboratory conditions. It was observed that the second nymphal stadium of A. dispersus was most preferred prey for M. desjardinsi and the least preferred was the A. dispersus adult. It was also seen that the third stadium of M. desjardinsi consumed more A. dispersus individuals than any other life stages. The longevity of female and the total developmental period of M. desjardinsi were computed as 27.6 ± 1.69 and 24.1 ± 0.99 d, respectively. The average total number of eggs laid by the M. desjardinsi female was 211.1 ± 6.35 eggs. M. desjardinsi was observed to be extremely efficient in terms of prey searching and predatory potential with respect to A. dispersus. The results of this study indicate strongly that M. desjardinsi has the potential to be used for the control of A. dispersus.

Solution of Bio-Medical Problem by Genetic Algorithm

In operation research and computer science, a genetic algorithm (GA) is a most powerful meta-heuristic approach, its inspired by the process of natural selection. This approach is usually applied to generate superior quality results to standard and real life functions. Several number of researcher has been solved most number of real applications related to different fields with the help of this technique. After Inspired of these researchers, has been also solved the Breast Cancer and Iris data set problems in this article using some recent metaheuristics of nature inspired. For verification, the solutions are compared with some of the most well-known evolutionary trainers: Particle Genetic Algorithm (GA), Swarm Optimization (PSO), Ant Colony Optimization (ACO), Differential Evolution (DE), Personal Best Position Particle Swarm Optimization (PBPPSO), Evolutionary Strategy (ES), Biogeographical Based Optimization (BBO) and Population based Incremental Learning (PBIL). The numerical and statistical solutions show that GA algorithm is able to provide very competitive solutions in terms of improved local optima avoidance. The solutions also reveal a high level of accuracy in classification.

Brief Communication: Dexpanthenol and Its Ophthalmic Uses

Sparshi Jain1*, Sweta Singh2 and Anjali Nagar3 1Department of Ophthalmology, Indra Gandhi Employees State Insurance Corporation, India 2Chandigarh Laser Eye Center, India 3IGESI Hospital, Jhilmil, New Delhi, India *Corresponding author: Sparshi Jain, Department of Ophthalmology, Indira Gandhi Employees State Insurance Corporation, Jhilmil, Delhi 110032, India, Tel: 919899867167; E-Mail: dr.sparshi@gmail.com

Temporal modeling for forecasting of the incidence of litchi stink bug using ARIMAX analysis

The litchi, Litchi chinensis Sonn. is an important sub-tropical evergreen fruit crop. Among various insect pests of litchi, stink bug, Tessaratoma papillosa (Drury) is a major one causing extensive damage in Mizoram. The forecasting model to predict stink bug incidence in litchi was developed by ARIMAX model of weekly casesand weather factors. In exploring different prediction models by fitting covariates to the time series data, model ×(mean maximum and minimum temperature, morning and evening relative humidity and rainfall) was found bestmodel for predicting the stink bug incidence; all covariates were found significant predictors except evening RH, which did not have any significant covariates as predictor of stink bug incidence.

Transient ischemic attack presenting in an elderly patient with transient ophthalmic manifestations

Transient ischemic attack (TIA) is a transient neurological deficit of cerebrovascular origin without infarction which may last only for a short period and can have varying presentations. We report a case of 58-year-old male with presenting features of sudden onset transient vertical diplopia and transient rotatory nystagmus which self-resolved within 12 h. Patient had no history of any systemic illness. On investigating, hematological investigations and neuroimaging could not explain these sudden and transient findings. A TIA could possibly explain these sudden and transient ocular findings in our patient. This case report aims to highlight the importance of TIA for ophthalmologists. We must not ignore these findings as these could be warning signs of an impending stroke which may or may not be detected on neuroimaging. Thus, early recognition, primary prevention strategies, and timely intervention are needed.