Occurrence of parasites in selected fish species in Gandoman Lagoon, Iran

This study was carried out to investigate occurrence of parasite in selected cyprinid fish species in Gandoman Lagoon, in the vicinity of Gandoman City, Chaharmahal & Bakhtyari Province. A total of 90 fish specimens including Cyprinus carpio, Carassius auratus gibelio, Capoeta aculeata , C.damascina, Chondrostoma regium and Alburnus alburnus from Gandoman were examined during spring and summer 2007. Ten species of parasites were found, including Ichthyophthirius multifiliis, Trichodina sp. (Cilliophora), Myxobolus musayevi, Myxobolus sp. (Myxozoa), Dactylogyrus extensus, D.lenkorani (Monogenea), Diplostomum spathaceum, Tylodelphys clavata (Digenea). Argulus foliaceus and Lernea cyprinacea (Crustaceans). 77.7% of fishes were infected to parasites and 22.3 % did not show any infection. Chondrostoma regium and Alburnus alburnus are reported as new hosts for D. extensus

First record of Rhinocola aceris (L. 1758) (Hemiptera: Aphalaridae ) in Iran

During a faunistic survey of the jumping plant-lice in the Mazandaran province of Iran in the summer 2022, Rhinocola aceris (L. 1758) was collected on Acer sp. (Sapindales, Sapindaceae), which is newly recorded from Iran. This is also the first record of the genus Rhinocola Förster for the country

EFFECTIVE FACTORS IN THE QUALITY OF LIFE IN PATIENTS WITH TYPE 2 DIABETES IN CHAHARMAHAL & BAKHTEYARI PROVINCE

Abstract: Background and objectives: Quality of life can be considered as a marker of the quality of health care and is a part of the patient's treatment plan. Its measurement in type 2 diabetic patients provides useful information to health authorities Material and Methods: This study is a descriptive-analytic cross–sectional study that has attempted to measure the quality of life in diabetic patients in Chaharmahal & Bakhteyari Province. The number of patients was 254 and they were selected randomly in two stages. Data were collected

Improved COA with Chaotic Initialization and Intelligent Migration for Data Clustering

A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages such as fast convergence rate, intelligent operators and simultaneous local and global search which are the motivations behind choosing this algorithm. In the Extended Cuckoo Algorithm, we have enhanced the operators in the classical version of the Cuckoo algorithm. The proposed operator of production of the initial population is based on a Chaos trail whereas in the classical version, it is based on randomized trail. Moreover, allocating the number of eggs to each cuckoo in the revised algorithm is done based on its fitness. Another improvement is in cuckoos’ migration which is performed with different deviation degrees. The proposed method is evaluated on several standard data sets at UCI database and its performance is compared with those of Black Hole (BH), Big Bang Big Crunch (BBBC), Cuckoo Search Algorithm (CSA), traditional Cuckoo Optimization Algorithm (COA) and K-means algorithm. The results obtained are compared in terms of purity degree, coefficient of variance, convergence rate and time complexity. The simulation results show that the proposed algorithm is capable of yielding the optimized solution with higher purity degree, faster convergence rate and stability in comparison to the other compared algorithms

Wing geometry in the populations of Diaphorina citri (Hemiptera: Liviidae) in Iran and USA: an evidence for incongruence of molecular and morphometric data

Asian citrus psyllid (ACP), Diaphorina citri Kuwayama, is one of the most important citrus pests in the world.In addition to direct feeding damages, it also transmits the greening-disease pathogen. In order to improve understanding of geographic populations of ACP related to the mtCOI Haplotype-1, geometric morphometric was used to compare variations between populations of ACP in Iran and USA (Florida). The ACP populations were collected from the Iranian cities of Jiroft and Chabahar and Florida (USA) in 2014. 150 pecimens from five ACP populations (30 adult females per population) were randomly selected and analysed using ANOVA and MANOVA.The results indicate that wing-shape (Wilk.s lambda = 0.0910, F = 5.89, P < 0.0001) and wing-size (F = 61.41, df =4, P <.0001) were different between Iranian and USA populations. This study also showed incongruence betweenmorphometric and molecular data in the studied populations of D. citri from Iran and USA. The observed differences are probably due to genetic rather than environmental factors because of 1) significant multivariate differences in shape even after removing size variation and 2) significant correlation between geographic and morphometric distance matrices

Evaluation of the effects of different concentrations of neutral anolyte on fungal infected eggs in rainbow trout (Oncorhynchus mykiss) in comparison with green malachite

The objective of this study was to determine the effect of different concentrations of anolyte on saprolegniasis in comparison with green malachite in rainbow trout hatcheries, in the northern part of Iran, Tonekabon. Nearly 5000 green eggs of Oncorhynchus mykiss (equivalent to 300 g) were obtained from a private farm in the north of Iran. The study was designed in 5 treatments, 0.25, 0.5, 30 and 100 ppm of neutral anolyte and 2 ppm of green malachite and two controls including positive control, meaning that the green eggs were purposely infected with saprolegnia but without any disinfectant, and negative control, which was implied to as the untreated group, all in triplicate. There was no significant difference (α>0.05) in hatchability percent between 2 ppm of green malachite and the group treated with 0.25 ppm of neutral anolyte, contrary to other anolyte concentrations. It is concluded that constant use of 0.25 ppm of neutral electrolyzed oxidized water (NEOW) is a more effective anti-fungal solution with the least side effects in comparison with 2 ppm of green malachite

Current data and modeling bottlenecks for predicting crop yields in the United Kingdom

Identifying and implementing management actions that can mitigate the impacts of climate change on domestically grown crops is crucial to maintaining future food security for the United Kingdom (UK). Crop models serve as critical tools for assessing the potential impacts of climate change and making decisions regarding crop management. However, there is often a gap between yields predicted by current modeling methods and observed yields. This has been linked to a sparsity of models that investigate crop yield beyond field scale or that include data on crop management or crop protection factors. It remains unclear whether the lack of available data imposes these limitations or if the currently available data presents untapped opportunities to extend models to better capture the complex ecosystem of factors affecting crop yield. In this paper, we synthesize available data on plant physiology, management, and protection practices for agricultural crops in the UK, as well as associated data on climate and soil conditions. We then compare the available data to the variables used to predict crop yield using current modeling methods. We find there is a lack of openly accessible crop management and crop plant physiology data, particularly for crops other than wheat, which could limit improvements in current crop models. Conversely, data that was found to be available at large scales on climate and soil conditions could be used to explore upscaling of current approaches beyond the field level, and available data on crop protection factors could be integrated into existing models to better account for how disease, insect pest and weed pressures may impact crop yield under different climate scenarios. We conclude that while a lack of available data on crop management, protection, physiology, at scales other than field level, and for species other than wheat currently hampers advancement of modeling methods for UK crops, future investment into data collection and management across a broader range of factors affecting crops, at larger scales and for a broader range of crop species could improve predictions of crop plant development and yield