Exact Optimal Sample Allocation for Establishments having More Than Ten Employees in Qatar

The primary aim of this study is to select a stratified random sampling with three different techniques which is optimal allocation, proportional allocation and the new method is exact optimal allocation which is a great method with more advantage than other methods. In addition, we use two different stratification method which is: optimal rule of stratification and stratification based on establishment activity. In each two stratification we apply the three methods, and the total sample size is chosen by optimal allocation technique and set for both other techniques, so that we can make a comparison among there variance. The result we get is as following stratification by optimal rule of stratification give smaller variance in all three technique than stratification based on establishment activity. Among the three method we use, the powerful method is exact sampling allocation because it gives smaller variance than the other methods, followed by optimal allocation (Neyman) and the largest variance we get from proportional allocation in both method of stratification. In exact optimal allocation with predetermining variance, we get smaller number of sample size for stratification by establishment activity but with very large variance, otherwise with optimal rule of stratification with predetermining variance we get a large number of sample size with smaller variance

Effect of different salinity concentration on kidney of benni, Barbus sharpeyi

For this study, 144 healthy Barbus sharpeyi with an average weight of 350 ± 2.36 grams and length 25 ± 1.25 cm in five groups were studied. The first group as control located in municipal dechlorination water and the next four groups respectively were kept in salinity 4ppt, 8ppt, 12ppt and 16ppt in the same condition. On days 1 , 3 , 7 , 14 , 21 and 28 sample of kidney with maximum thickness of 0.5 cm prepare and were placed in bouin's solution.Then the standard method of parafin sections were done and 5- 6 micrometer thick of tissue sections prepared and stained with H&E methods. Results showed the gradual transfer of fish to water with high salinity caused obvious changes as increase the number and diameter of the glomeruli especially in high salinity but the severity was reduced at the end of the period (p<0.05). Also highest diameter and thickness of the collecting tubules were reported in fresh water at 28 days (p<0.05). These findings suggest that fish Barbus sharpeyi was friendly with salinity and ability to set vital to different salinity

Drought stress mitigation using supplemental irrigation in rainfed chickpea (Cicer arietinum L.) varieties in Kermanshah, Iran

An experiment was carried out in 2007 to investigate the effects of different irrigation regimes, and chickpea cultivars on chickpea production in the Agricultural Research Station, College of Agriculture, Islamic Azad University, Kermanshah Branch, Iran. The experimental design was split-plot with three replications. Supplemental irrigation at three levels, that is, control treatment (without irrigation) (I0), one time irrigation at 50% flowering stage (I1) and one time irrigation at pod-filling stage(I2), was allocated to main plots and the varieties ILC-482 (V1), Hashem (V2) and Arman (V3) were allotted to sub plots. A significant difference was observed between irrigation treatments in terms of grain yield, plantheight, number of axillary branches, distance to the first pod from soil surface, number of grain per plant, number of pod per plant, biological yield, harvest index and 100-grain weight. Such differences were also observed between testing varieties in terms of all traits rather than 100-grain weight. Grain yield was significantly higher for Arman than that of Hashem which was significantly higher than that of ILC-482. Of course, there was no significant difference between Hashem and ILC-482 in terms of grain yield. Arman had the highest values of the number of grain per plant and the highest pod per plant pertained to Arman and Hashem, respectively. High rate of grain yield in irrigation treatment at podfillingstage was associated with yield components, especially with the number of pod per plant and 100-grain weight. Grain yield was positively correlated with number of pod per plant (r = 0.654**), number of grain per plant (r = 0.902**) and 100-grain weight (r = 0.707**). This research showed that podfilling is the most sensitive stage to drought stress, and under water limitation conditions, we can considerably increase grain yield at this stage by one time irrigation, especially for Arman cultivar

Infection rate of the Shiroud River fishes with Clinostomum complanatum

Due to the variety of fishes and fisheries resources the Shiroud River is considered as one of the most valuable rivers in the west of Mazandaran Province. Therefore the infection rate of the fishes in the river with parasites was examined in Aquatic Disease laboratory of Mazandaran Fisheries Research Center. Among the observed parasitic infections, we will refer to Clinostomum complanatum, which may cause laryngo-pharyngitis in human. The examined fishes were Cobitis taenia, Capoeta capoeta,Neogobius fluviatilis, Carassius auratus, Albumoides bipunctatus, Chalcalburnus chalcoides, Barbus barbus plebejus, Leuciscus cephalus, Alburnus alburnus. Among the mentioned fishes Capoeta capoeta had the highest rate of infection with Clinostomum complanatum. In the research, Alburnoides bipunctatus and Cobitis taenia were introduced as the new hosts of this parasite

Dietary administration of vitamin C and Lactobacillus rhamnosus in combination enhanced the growth and innate immune response of the rainbow trout, Oncorhynchus mykiss

The effects of dietary vitamin C and Lactobacillus rhamnosus on immunity and growth performance were investigated in Oncorhynchus mykiss. For this purpose, 480 rainbow trout (68±5g) were obtained from a local farm and acclimated to laboratory conditions for 10 days and then divided into four groups in three replicates. During 30 days, juvenile rainbow trout were fed diets supplemented with vitamin C (1g/kg) and L. rhamnosus (at 5 × 107 CFU/g) or a control diet. Biometry was done at day -30 and blood samples were taken by caudal vein after fish anesthesia with clove powder at day 0, 15, 30 and 45. Serum lysozyme activity, alternative complement activity and total plasma immunoglobulin level were assayed as innate immune response of rainbow trout. Results showed fish fed with vitamin c and L. rhamnosus (group 3) statistically could improve fish growth performance. Also lysozyme activity and alternative complement activity of serum significantly were higher in group three than other groups, but total plasma level of immunoglobulin only was higher than all groups at day 30. In conclusion dietary administration of vitamin C and L. rhamnosus in rainbow trout diet could enhance the growth and innate immune response, but these properties need further studies on the field applications

Promjena indikatora kvalitete električne energije trošila predstavljanjem adaptivne metode za upravljanje DVR-om zasnovane na Hebbovom algoritmu učenja

Having electricity with high quality is one of the more important aims in electrical systems. Disturbances in distribution systems can change voltage waveform. There are some methods to prepare high power quality for sensitive loads. In this research we use “Dynamic Voltage Restorer” to compensate the harmful effects of disturbances on voltage. Since power systems fundamentally have complicated dynamic behavior, especially during faults, “Hebb” learning self-tuning controller, which is a powerful adaptive controller, has been used. In order to improve the performance of this controller from point of view of power quality’s indices, such as flash and sensitive load voltage THD, a new structure is proposed for this controller with fuzzification method. Simulation results indicate better operation of the system for the case of proposed controller. Voltage sag and harmonics in faulty conditions are both improved by the proposed controller. According to simulation results, it works better than both classical PI controller and conventional Hebb learning controller.Jedan od važnijih ciljeva elektroenergetskog sustava visoka je kvaliteta električne energije. Poremećaji u distribucijskom sustavu mogu neželjeno izmijeniti valni oblik napona. Postoji nekoliko metoda kako osigurati visoku kvalitetu energije za osjetljiva trošila. U istraživanju koristimo "dinamičku obnovu napona" za kompenziranje štetnih efekata poremećaja u naponu. Kako energetski sustavi u osnovi imaju složeno dinamičko ponašanje, posebno tijekom kvarova, korišten je vrlo moćan adaptivni regulator: "Hebbov" samopodešavajući regulator sa sposobnošću učenja. Da bi se unaprijedilo vladanje spomenutog regulatora s aspekta indikatora kvalitete energije kao što su parcijalna izbijanja i THD osjetljivog trošila, predložena je nova struktura regulatora s uključenim metodama neizrazite logike. Simulacijski rezultati pokazuju bolji rad sustava uz korištenje predloženog regulatora. Regulator smanjuje propade napona i poboljšava harmonični sastav sustava u kvarnim uvjetima. Rezultati simulacija također pokazuju bolje ponašanje u odnosu na uobičajeni PI regulator te konvencionalni Hebbov regulator s učenjem

Electrochemiluminescence on digital microfluidics for microRNA analysis

Electrochemiluminescence (ECL) is a sensitive analytical technique with great promise for biological applications, especially when combined with microfluidics. Here, we report the first integration of ECL with digital microfluidics (DMF). ECL detectors were fabricated into the ITO-coated top plates of DMF devices, allowing for the generation of light from electrically excited luminophores in sample droplets. The new system was characterized by making electrochemical and ECL measurements of soluble mixtures of tris(phenanthroline)ruthenium(II) and tripropylamine (TPA) solutions. The system was then validated by application to an oligonucleotide hybridization assay, using magnetic particles bearing 21-mer, deoxyribose analogues of the complement to microRNA-143 (miRNA-143). The system detects single nucleotide mismatches with high specificity, and has a limit of detection of 1.5 femtomoles. The system is capable of detecting miRNA-143 in cancer cell lysates, allowing for the discrimination between the MCF-7 (less aggressive) and MDA-MB-231 (more aggressive) cell lines. We propose that DMF-ECL represents a valuable new tool in the microfluidics toolbox for a wide variety of applications

Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning

Background and Objective:Image processing is one of the most important issues in the field of artificial intelligence, which is used in various industrial, medical, military, and security systems. One of the most important applications of image processing is the extraction of different types of classification in the field of medical sciences. By using powerful algorithms in this field, intelligent systems can be invented that automatically understand and interpret the medical characteristics of individuals without the need to the physician supervision can discover useful information to help experts make good judgments. When the necessary parameters for the diagnosis of the disease increase, the diagnosis and prognosis of the disease becomes very difficult even for an expert, which is why computer diagnostic tools have been used in recent decades to help the physicians. This has led to a reduction in possible errors due to fatigue or inexperience of the specialist, and to provide the required medical data to the physician in less time and with more detail and accuracy. The purpose of this study is to improve the classification of new methods using a multi-layered model to address retinal diseases diagnosis. Methods: This paper presents a multi-layer dictionary learning method for classification tasks.  Our multi-layer framework uses a label consistent in K-SVD algorithm to learn a discriminative dictionary for sparse coding in order to learn better features in retinal optical coherence tomography images. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discrimination in sparse codes during dictionary learning process. In fact, it relies on a succession of sparse coding and pooling steps in order to find an effective representation of data for classification. Moreover, we apply Duke dataset for validating our algorithm: Duke spectral domain OCT (SD-OCT) dataset, consisting of volumetric scans acquired from 45 subjects 15 normal subjects, 15 AMD patients, and 15 DME patients. Findings: Our classifier leads to a correct classification rate of 95.85% and 100.00% for normal and abnormal (DME and AMD). Experimental results demonstrate that our algorithm outperforms compared to many recent proposed supervised dictionary learning and sparse representation techniques. Conlusion: The results of this study were to provide an automatic system for the diagnosis of some retinal abnormalities in a way that it could do data analysis with high accuracy in comparison to other modern methods to diagnosis delicate patterns of OCT, separate images of normal and patient the normal and in two age-related macular degeneration diseases (AMD), and diabetic macular degeneration (DME), and help the physician to diagnose retinal pathology with great care. As a suggestion for professionals and future research, by generalizing this method to the more classes, we can cover the entire retinal myopia and use it as a potentially effective tool in computerized diagnosis and screening for retinal disease or in the wider eye area.   ===================================================================================== COPYRIGHTS  ©2019 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Biosynthesis of Silver Nanoparticles from Desmodium triflorum: A Novel Approach Towards Weed Utilization

A single-step environmental friendly approach is employed to synthesize silver nanoparticles. The biomolecules found in plants induce the reduction of Ag+ ions from silver nitrate to silver nanoparticles (AgNPs). UV-visible spectrum of the aqueous medium containing silver ions demonstrated a peak at 425 nm corresponding to the plasmon absorbance of silver nanoparticles. Transmission electron microscopy (TEM) showed the formation of well-dispersed silver nanoparticles in the range of 5–20 nm. X-ray diffraction (XRD) spectrum of the AgNPs exhibited 2θ values corresponding to the silver nanocrystal. The process of reduction is extracellular and fast which may lead to the development of easy biosynthesis of silver nanoparticles. Plants during glycolysis produce a large amount of H+ ions along with NAD which acts as a strong redoxing agent; this seems to be responsible for the formation of AgNPs. Water-soluble antioxidative agents like ascorbic acids further seem to be responsible for the reduction of AgNPs. These AgNPs produced show good antimicrobial activity against common pathogens

Forests and rangelands’ wildfire risk zoning using GIS and AHP techniques

Wildfire in forests and rangelands, apart from its initiating causes, is considered as an ecological disaster. Zoning natural areas according to their susceptibility to fire helps to put off operations and reduces catastrophic losses caused through a wise management plan. In this study, the zoning map of wildfire risk in forest and rangeland areas has been produced using GIS, Analytical Hierarchical Processing (AHP) and remote sensing techniques. The study area is about 196000 ha of Ilam Township, located in western Iran. The influencing factors in wildfire occurrence include current land use/cover, roads and rivers, as well as physiographic, climatic and anthropogenic themes. The locations of the wildfires have been registered by using a GPS from 2007 to 2009, to map wildfire occurring pattern in the study area. Then, using AHP techniques the influencing factors in occurrence and extension of the fires were compared in pairs and weighed. According to the weight calculated for each factor and its corresponding classes, the weighed maps of the factors were produced and employed to produce the final map of wildfire risk zoning. Finally, the zoning map of wildfire risk was produced including five classes of the risk from high to very low. Comparing the map of the wildfire risk potential to the actual fires that happened, it was found that 50 and 40 percents of the fires initiate form the areas, marked as high risk and risky zones on the map, respectively. The results indicate a high compliance of the map of wildfire risk zoning and the location of the fires in the study area. As so it predicts more than 90 percent of occurring forest and rangelands wildfires and would be helpful data for arranging a better wildfire fighting annual plan in national and regional forests and rangeland management headquarters. The model could turn to a more sophisticated one by adding extra influencing factors like, wind speed and its directions. The present model is a static one and to solve such a problem it should be promoted to a dynamic model