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

Fly fauna of livestock’ s of Marvdasht County of Fars Province in the South of Iran

Flies damage the livestock industry in many ways, including damages, physical disturbances, the transmissions of pathogens and the emergence of problems for livestock like Myiasis. In this research, the fauna of flies of Marvdasht County was investigating, which is one of the central counties of Fars province in southern Iran. In this study, a total of 20 species of flies from 6 families and 15 genera have been identified and reported. The species collected are as follows: Muscidae: Musca domestica Linnaeus, 1758, Musca autumnalis* De Geer, 1776, Stomoxys calci-trans** Linnaeus, 1758, Haematobia irritans** Linnaeus, 1758 Fanniidae: Fannia canicularis* Linnaeus, 1761 Calliphoridae: Calliphora vomitoria* Linnaeus, 1758, Chrysomya albiceps* Wiedemann, 1819, Lu-cilia caesar* Linnaeus, 1758, Lucilia sericata* Meigen, 1826, Lucilia cuprina* Wiedemann, 1830 Sarcophagidae: Sarcophaga africa* Wiedemann, 1824, Sarcophaga aegyptica* Salem, 1935, Wohl-fahrtia magnifica** Schiner, 1862 Syrphidae: Eristalis tenax* Linnaeus, 1758, Syritta pipiens* Linnaeus, 1758, Eupeodes nuba* Wiedemann, 1830, Syrphus vitripennis** Meigen, 1822, Scaeva albomaculata* Macquart, 1842 Species identified with * for the first time in the county and the species marked with ** are reported for the first time from the Fars province

Efficacy of the EC 1.28% formulation of Neem, Azadirachta indica, on two-spotted spider mite, Tetranychus urticae (Acari: Tetranychidae), in laboratory and field conditions

The acaricidal activity of new formulation of Neem EC 1.28% was compared with Neem Azal® (EC 1%) and spirodiclofen against the two-spotted spider mite, Tetranychus urticae Koch, under both laboratory and field conditions. The method of leaf dipping was used for bioassay experiments. The common bean leaves were dipped into different concentrations of treatments before exposing them to the adult mites from the same age. The mortality for mites was recorded after 24 hours. The experiment was conducted under 25 ± 2ºC, RH 60 ± 5 %, and 16: 8 (L: D) h photoperiod conditions. LC50 and related parameters were calculated, using POLO-PC software. The field studies were conducted in randomized complete block design with five treatments of 1 ml/l, 2 ml/l and 3 ml/l of EC 1.28% formulation, 0.5 ml/l spirodiclofen and 1 ml/l of Neem Azal®. Plain water was used for the control group. The LC50 values for Neem Azal®, spirodiclofen and Neem EC 1.28% formulation were 52.04 mg/l, 37.55 mg/l and 21.06 mg/l, respectively. The results showed that mites were more susceptible to the new EC 1.28% formulation. In the field, spirodiclofen was found to be the most effective compound after 3 and 7 days of treatment causing 89.3 ± 1.7% and 77.8 ± 2.3% mortality, while Neem Azal® was less effective with 64.40 ± 4.04% and 68.7 ± 2.9% mortality on mites. The new EC 1.28% formulation was used at the rate of 3 ml/l, which caused 82.8 ± 2.4% and 70.2 ± 3.9% mortality, without significant difference with spirodiclofen treatment

A new detector for the beam energy measurement in proton therapy: a feasibility study

Fast procedures for the beam quality assessment and for the monitoring of beam energy modulations during the irradiation are among the most urgent improvements in particle therapy. Indeed, the online measurement of the particle beam energy could allow assessing the range of penetration during treatments, encouraging the development of new dose delivery techniques for moving targets. Towards this end, the proof of concept of a new device, able to measure in a few seconds the energy of clinical proton beams (from 60 to 230 MeV) from the Time of Flight (ToF) of protons, is presented. The prototype consists of two Ultra Fast Silicon Detector (UFSD) pads, featuring an active thickness of 80 um and a sensitive area of 3 x 3 mm2, aligned along the beam direction in a telescope configuration, connected to a broadband amplifier and readout by a digitizer. Measurements were performed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy), at five different clinical beam energies and four distances between the sensors (from 7 to 97 cm) for each energy. In order to derive the beam energy from the measured average ToF, several systematic effects were considered, Monte Carlo simulations were developed to validate the method and a global fit approach was adopted to calibrate the system. The results were benchmarked against the energy values obtained from the water equivalent depths provided by CNAO. Deviations of few hundreds of keV have been achieved for all considered proton beam energies for both 67 and 97 cm distances between the sensors and few seconds of irradiation were necessary to collect the required statistics. These preliminary results indicate that a telescope of UFSDs could achieve in a few seconds the accuracy required for the clinical application and therefore encourage further investigations towards the improvement and the optimization of the present prototype

Thin low-gain avalanche detectors for particle therapy applications

none18The University of Torino (UniTO) and the National Institute for Nuclear Physics (INFN-TO) are investigating the use of Ultra Fast Silicon Detectors (UFSD) for beam monitoring in radiobiological experiments with therapeutic proton beams. The single particle identification approach of solid state detectors aims at increasing the sensitivity and reducing the response time of the conventional monitoring devices, based on gas detectors. Two prototype systems are being developed to count the number of beam particles and to measure the beam energy with time-of-flight (ToF) techniques. The clinically driven precision (< 1%) in the number of particles delivered and the uncertainty < 1 mm in the depth of penetration (range) in radiobiological experiments (up to 108 protons/s fluxes) are the goals to be pursued. The future translation into clinics would allow the implementation of faster and more accurate treatment modalities, nowadays prevented by the limits of state-of-the-art beam monitors. The experimental results performed with clinical proton beams at CNAO (Centro Nazionale di Adroterapia Oncologica, Pavia) and CPT (Centro di Protonterapia, Trento) showed a counting inefficiency <2% up to 100 MHz/cm2, and a deviation of few hundreds of keV of measured beam energies with respect to nominal ones. The progresses of the project are reported.noneVignati, A.; Donetti, M.; Fausti, F.; Ferrero, M.; Giordanengo, S.; Hammad Ali, O.; Mart Villarreal, O.A.; Mas Milian, F.; Mazza, G.; Monaco, V.; Sacchi, R.; Shakarami, Z.; Sola, V.; Staiano, A.; Tommasino, F.; Verroi, E.; Wheadon, R.; Cirio, R.Vignati, A.; Donetti, M.; Fausti, F.; Ferrero, M.; Giordanengo, S.; Hammad Ali, O.; Mart Villarreal, O. A.; Mas Milian, F.; Mazza, G.; Monaco, V.; Sacchi, R.; Shakarami, Z.; Sola, V.; Staiano, A.; Tommasino, F.; Verroi, E.; Wheadon, R.; Cirio, R

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