Utilization of petroleum hydrocarbons by Pseudomonas sp. and transformed E. coli

Our previous studies showed that the biodegradation of petroleum oil by a i>pseudomonas isolated from a petroleum-contaminated soil was instable. In this work, t is shown that when the isolates are immobilized on Perlite, they are more stable for oil egradation. Although the isolate did not have any chemotaxis to octadecane, dodecane and ctane but utilize octadecane and dodecane better than octane and it did not utilized exane, benzene, kerosene, pentane, heptane or thiophenol. The generation time for degradation of petroleum oil, dodecane and octadecane was 20, 22, and 25 h respectively. This phenotype was not transformed to Pseudomonas by conjugation even with lysozyme treatment, however the petroleum oil and octadecane utilization were transformed to E. coli by lysozyme treatment. The transformed E. coli lost the ability to use octadecane after three subcultures on nutrient broth and 34 generations.African Journal of Biotechnology Vol. 4 (2), pp. 172-176, 200

Effectiveness of Solution-Focused Brief Therapy (SFBT) on Reducing Symptoms of Depression in Women

زمینه و هدف: درمان کوتاه مدت راه حل محور یکی از انواع درمان‌های متداول در کاهش مشکلات روانشناختی از جمله افسردگی در بین درمانگران و مشاوران خانواده است. پژوهش حاضر با هدف بررسی اثر بخشی درمان کوتاه مدت راه حل محور بر کاهش نشانگان افسردگی زنان طراحی شد. روش بررسی: پژوهش حاضر از نوع نیمه تجربی و از روش پیش آزمون- پس آزمون و پیگیری با گروه کنترل بهره گرفته شده است. جامعه این پژوهش شامل کلیه زنانی بودند که با مشکل افسردگی به مرکز همیاران سلامت روان شهر بجنورد تحت نظارت سازمان بهزیستی خراسان شمالی در سال 1392 مراجعه نموده اند و بر اساس مصاحبه بالینی و تشخیصی، افسردگی در مورد آنها تشخیص داده شده بود. با استفاده از نمونه گیری در دسترس، 20 نفر از زنان بعنوان نمونه انتخاب شدند و با گمارش تصادفی در دو گروه آزمایش و کنترل قرار گرفتند. ابزار پژوهش پرسشنامه افسردگی بک (Beck) بود که توسط آزمودنی‌ها در مراحل پیش آزمون، پس آزمون و پیگیری تکمیل گردید. درمان کوتاه مدت راه حل محور در 6 جلسه 5/1 ساعته برای آزمودنی‌های گروه آزمایش برگزار شد اما برای گروه کنترل مداخله‌ای ارایه نگردید. داده‌ها با بهره‌گیری از نرم افزار SPSS و به روش تحلیل کوواریانس تک متغیره مورد تجزیه و تحلیل قرارگرفتند. یافته‌ها: نتایج کاهش معنادار نمرات افسردگی زنان گروه آزمایش را در مراحل پس آزمون و پیگیری نسبت به گروه کنترل نشان داد. یافته ها حاکی از آن بود که درمان کوتاه مدت راه حل محور باعث کاهش علایم افسردگی زنان گروه مداخله شده و نتایج در دوره پیگیری نیز از ثبات لازم برخوردار بوده است (001/0 >P). نتیجه گیری: درمان کوتاه مدت راه حل محور بر کاهش افسردگی موثر است. مشاوران و روان درمانگران می‌توانند از این رویکرد درمانی موثر و کارآمد جهت حل مشکلات روانشناختی مراجعان بهره ببرند

Seed treatments to overcome dormancy of waterlily tulip (Tulipa kaufmanniana Regel.)

Abstract Dormancy and germination requirements were investigated in seeds of Tulipa kaufmanniana Regel (Liliaceae). The present study was conducted to study the dormancy breaking treatment in Tulip seed. An experiment was conducted with four replications and three treatments including: 3 different stratification periods (0, 5 and 7 weeks), varying concentrations of GA 3 (0, 250 and 500ppm) and 4 levels of KNO 3 (0, 0.1, 0.2 and 0.3% v/v). Germination percentage and mean germination time were significantly enhanced by treating seeds with mentioned treatments compared with the untreated control seeds. It was concluded that stratification for 7 weeks was more effective treatment on studied traits than 5 weeks. Moreover, cold stratification was a better treatment on breaking seed dormancy of waterlily seeds than GA 3 and KNO 3 treatments. Applying 500ppm concentration of GA 3 and 0.1 of KNO 3 after stratification resulted in higher germination in waterlily dormant seeds

Diagnosing COVID-19 disease using an efficient CAD system

Todays, COVID-19 has caused much death and its spreading speed is increasing, regarding virus mutation. This outbreak warns diagnosing infected people is an important issue. So, in this research, a computer-aided diagnosis (CAD) system called COV-CAD is proposed for diagnosing COVID-19 disease. This COV-CAD system is created by a feature extractor, a classification method, and a content-based imaged retrieval (CBIR) system. The proposed feature extractor is created by using the modified AlexNet CNN. The first modification changes ReLU activation functions to LeakyReLU for increasing efficiency. The second change is converting a fully connected (FC) layer of AlexNet CNN with a new FC, which results in reducing learnable parameters and training time. Another FC layer with dimensions 1 × 64 is added at the end of the feature extractor as the feature vector. In the classification section, a new classification method is defined in which the majority voting technique is applied on outputs of CBIR, SVM, KNN, and Random Forest for final diagnosing. Furthermore, in retrieval section, the proposed method uses CBIR because of its ability to retrieve the most similar images to the image of a patient. Since this feature helps physicians to find the most similar cases, they could conduct further statistical evaluations on profiles of similar patients. The system has been evaluated by accuracy, sensitivity, specificity, F1-score, and mean average precision and its accuracy for CT and X-ray datasets is 93.20% and 99.38%, respectively. The results demonstrate that the proposed method is more efficient than other similar studies

Full Length Research Paper - Utilization of petroleum hydrocarbons by Pseudomonas sp. and transformed Escherichia coli

Our previous studies showed that the biodegradation of petroleum oil by a pseudomonas isolated from a petroleum-contaminated soil was instable. In this work, it is shown that when the isolates are immobilized on Perlite, they are more stable for oil degradation. Although the isolate did not have any chemotaxis to octadecane, dodecane and octane but utilize octadecane and dodecane better than octane and it did not utilized hexane, benzene, kerosene, pentane, heptane or thiophenol. The generation time for degradation of petroleum oil, dodecane and octadecane was 20, 22, and 25 h respectively. This phenotype was not transformed to Pseudomonas by conjugation even with lysozyme treatment, however the petroleum oil and octadecane utilization were transformed to Escherichia coli by lysozyme treatment. The transformed E. coli lost the ability to use octadecane after three subcultures on nutrient broth and 34 generations

A new method for image classification and image retrieval using convolutional neural networks

This article proposes a new method for image classification and image retrieval. The advantages of the proposed method are its high performance and requiring less memory compared to other methods. In order to extract image features, a Convolutional Neural Network (CNN), AlexNet, has been used. For image classification, we design a committee of four classifiers trained on graphics cards, narrowing the gap to human performance. For image retrieval, the similarity between extracted features from dataset images and features of the query image is calculated and the final results are visualized. Comprehensive experiments on Corel-1k, Corel-10k, Caltech-101 object and Scene-67 datasets have been investigated to find optimal parameters of the proposed method. The experiments demonstrate the high performance of the proposed method in comparison with the state-of-the-art in the field

Dosimetric characteristics of ¹⁰³ Pd (theragenices, model 200) brachytherapy source

Accurately determination of dosimetric parameters for low-energy ¹⁰³ Pd source is crucial to use by treatment planning systems. The dosimetric parameters such as the air kerma strength, Sk, dose rate constant, L, radial dose function, g(r) and anisotropy function, F(r, q) for the lowenergy ¹⁰³ Pd source were investigated. MCNPX (2.6.0) simulation code was used to calculate all dosimetry parameters. Full details of Theragenices-¹⁰³ Pd source model 200 (dimentiones, materials and energy spectrum) were implementd in MC simulations. The ¹⁰³ Pd source was centered in infinite water phantom and the radial dose function calculation the dose was scored in concentric rings with different thickness bonded by 88° and 92° conics. Due to symmetry of source geometry and in order to reducing of errors, the 0.5 mm thickness rings were bounded with two oblique cones (with interval angel of 1°) from 0° to 90° in order to calculate Anisotropy function. The air kerma strength, Sk and dose rate constant, L were found equal to 0.646 cGycm2h⁻¹mCi⁻¹ and 0.798 cGyh⁻¹U⁻¹, respectively. For radial dose function, g(r), using an equation as g(r) = a₀+a₁r+a₂r²+a₃r²lnr+ a₄/r², Where a₀=1.6440, a₁=-0.8338, a₂=0.1917, a₃=-0.0539, a₄=-0.0062 with R²=0.9995 have been yielded a better fitting than the fifth-order polynomial equation recommended by AAPM, TG-43U1. The calculated anisotropy values included the distances of clinical interest for this type of lowenergy photon source, up to 2 cm, and especially for smaller angles, q0.9935. The calculated results and extracted equations are in good agreement with the corresponding values reported by AAPM, TG-43U1 and can be used in Monte Carlo based treatment planning system

A fast and yet efficient YOLOv3 for blood cell detection

These days, blood cell detection in microscopic images plays a vital role in cognition, the health of a patient. Since disease detection based on manual checking of blood cells is mostly time-consuming and full of errors, analysis of blood cells using object detectors can be considered as an effective tool. Hence, in this study, an object detector has been proposed which is used for detecting blood objects such as white blood cells, red blood cells, and platelets. This detector is called FED (Fast and Efficient YOLOv3) and it is a One-Stage detector, which is similar to YOLOv3, performs detection in three scales. For the purpose of increasing efficiency and flexibility, the proposed object detector utilizes the EfficientNet Convolutional Neural Network as the backbone effectiveness. Furthermore, the Dilated Convolution is indeed applied in order to increase receptive view of the backbone. In addition, the Depthwise Separable Convolution method is utilized to minimize the detector's parametersand the Distance Intersection over Union is further used for bounding box regression. Besides, for increasing the performance, the Swish activation function is employed. The experiments are run on the BCCD dataset that the average precision of platelets, red blood cells, and white blood cells become 90.25%, 80.41%, and 98.92%, respectively. The results of experiments and comparisons demonstrate that the proposed FED detector is more efficient than other existing studies for blood cell detection

Calculation of organs doses and secondary cancer risk during mantle field radiotherapy for Hodgkin's Lymphoma

Occurrence of radiation-induced secondary cancer risk following mantle field radiotherapy for Hodgkin's lymphoma (HL) patients with long survival demands well-established radiotherapy strategy. Organs doses and resulted secondary cancer risk due to out-of field photons were calculated during mantle field radiotherapy for Hl patient. The male and female mathematical phantom of the Oak Ridge National Laboratory (ORNL) and validated 6MV photon beam of a Varian 2300 C/D were modeled by MCNPX 2.4.0 MC code. Using suitable lungs and thyroid shields for AP and PA fields, the organ specific absorbed doses, effective dose, and secondary cancer risk were calculated following to mantle field radiotherapy for HL. Among the out-of-field organs, the nose, eyes, head and neck's skins and sinuses have the higher received doses. The total effective doses and secondary cancer risk for a male and female were estimated to be 199, 234 mSv and 1.72, 1.87 respectively. During mantle field radiotherapy for Hodgkin's lymphoma, accurately estimations of organs dose near to the field's edge and suitable shielding of critical in-field organs are crucial factor to establish an optimal treatment plan

Novel FGbSA: fuzzy-Galaxy-based search algorithm for multi-objective reconfiguration of distribution systems

Reconfiguration according to different criteria is an important problem in distribution systems. This paper presents a new method for optimal multi-objective reconfiguration of distribution system based on the Galaxy-based Search Algorithm (GbSA). To avoid the convergence problem, the input and output data are normalized in the same range using fuzzy sets. The main objectives of the proposed algorithm have been considered as power loss reduction, voltage profile improvement and increase of the system load balancing. The proposed technique has been investigated using the IEEE 33-bus test system and a real distribution network i.e. Tai-Power 11.4-kV distribution system. The obtained results revealed the superiority of the proposed fuzzy-GbSA method in terms of accuracy compared to the GbSA and other intelligent search algorithms such as Genetic Algorithm (GA) or Particle Swarm Optimization (PSO). Furthermore, the proposed algorithm efficiently converged to the optimum solution compared to the other intelligent counterpart algorithms