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تعداد مقالات یافته شده: 1536
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1 شیوع، همبستگی‌های اجتماعی-جمعیتی و دانشگاهی اختلال وسواسی جبری در دانشجویان دانشکده علوم پزشکی کاربردی دانشگاه ام القرا
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 21
مقدمه: مطالعاتی که شیوع وسواس جبری را در منطقه عربستان سعودی نشان می‌دهد بسیار اندک است و بیشتر در نمونه جمعیتی دانشجویان پزشکی و پیراپزشکی وجود دارد. هدف از این مطالعه برآورد شیوع علائم وسواس اجباری در یک نمونه جامعه دانشجویان علوم پزشکی کاربردی بود. علاوه بر این، ارتباط بین علائم وسواسی جبری و متغیرهای اجتماعی-جمعیتی و چندین جنبه از زندگی دانشگاهی بررسی شد.
روشها: در این مطالعه مقطعی 404 دانشجوی دانشگاه متعلق به چهار بخش به کار گرفته شدند. ابزارهایی که در این مطالعه استفاده شد، شامل معیارهای ارزیابی وسواس جبری (OCI - R) ، DSM - IV برای تشخیص مقیاس درجه بندی شدت OCD و Y - BOCS بود. نتیجه اصلی اختلال وسواس جبری احتمالی است (امتیاز OCI - R> 21). دانشجویان با نمره بیشتر از 21 بیشتر از نظر وجود اختلال وسواس جبری با استفاده از معیارهای DSM - IV و Y - BOCS ارزیابی شدند.
یافته ها: شیوع OCS با ابزار غربالگری OCI-R 20% بود [95% CI(19.902-20.098)]. شیوع واقعی OCD تأیید شده 5.06٪ بود [95% CI(4.39-6.12)]. وجود OCD احتمالی در دانشجویان گروه آزمایشگاه پزشکی بسیار زیاد بود [002/0 = p و95% CI(31.3-3.33) [. ارتباط مهمی بین حضور OCS و عدم رضایت از انتخاب دوره [001/0 = p ، 95٪ CI (1.38 - 3.92)] ، احساس طرد شدن [0.004 = p ، 95٪ CI (1.39 - 5.88]) و علائم افسردگی [0001/0 = p و CI (8/1 - 89/1)] وجود داشت. نمونه ما به زنان در سن دانشگاه محدود بود، بنابراین تفسیر شیوع قابل تعمیم نیست.
نتیجه گیری: وجود چنین اختلالی احتمالاً بر عملکرد تحصیلی ، کیفیت زندگی و روابط بین فردی تأثیر می گذارد ، شناسایی و درمان در زمان مناسب به بهبود عملکرد تحصیلی و کیفیت زندگی کمک می کند.
کلمات کلیدی: وسواس جبری | علائم وسواسی جبری | دانشجویان پزشکی و پیراپزشکی | اختلال روانی
مقاله ترجمه شده
2 افزایش هوشمندی به منظور بهره وری ، زیست پذیری و پایداری
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 11
این کتاب به دنبال توسعه چارچوبی برای بررسی تجربیات شهرهای هوشمند در حوزه های قضایی مختلف در سراسر آسیا اقیانوسیه ، قاره آمریکا ، اروپا و انگلستان ، خاورمیانه و آفریقا است. این چارچوب ، که در فصل 2 شرح داده شده ، برای درک محرک ها ، هنرمندان و نتایج سیاست ها و همچنین سیستم عامل های فناوری است که پایه و اساس نوآوری هایی است که باعث افزایش بهره وری ، پایداری و زیست پذیری شده اند. در حالی که مقیاس ابتکارات شهرهای هوشمند در زمینه های مختلف جغرافیایی متفاوت است ، این مسئله که چگونه مردم به سوی نوآوری روی بیاورند و چگونه آن را در کل شهر قابل استفاده کرد؛ اهمیت به سزایی دارد. این کتاب عوامل اصلی عملکردهای فعلی شهرهای هوشمند را در چندین مکان مشخص بیان می کند. همچنین به شرح عوامل اصلی و نقش های آنها - دولت ها ، صنایع خصوصی ، شرکت های فناوری اطلاعات و ارتباطات (ICT) ، شهروندان و کاربران نهایی در هر زمینه می پردازد. شناسایی محرکها ، هنرمندان و نتایج کلیدی به صورت سازمان یافته، بینش مهمی در سایر حوزه های قضایی در مورد چگونگی بازنگری یا تدوین بهتر سیاستها و برنامه¬های فعلی و آینده¬ی جنبش¬های نوآوری در زمینه فناوری و اجتماعی فراهم می کند.
مقاله ترجمه شده
3 Identification and differentiation of commercial and military explosives via high performance liquid chromatography – high resolution mass spectrometry (HPLC-HRMS), X-ray diffractometry (XRD) and X-ray fluorescence spectroscopy (XRF): Towards a forensic substance database on explosives
شناسایی و تمایز مواد منفجره تجاری و نظامی از طریق کروماتوگرافی مایع با کارایی بالا - طیف سنجی جرمی با وضوح بالا (HPLC-HRMS) ، پراش سنجی اشعه ایکس (XRD) و طیف سنجی فلورسانس اشعه ایکس (XRF): به سمت پایگاه داده مواد پزشکی قانونی در مورد مواد منفجره-2020
The identification of confiscated commercial and military explosives is a crucial step not only in the uncovering of distribution pathways, but it also aids investigating officers in criminal casework. Even though commercial and military explosives mainly rely on a small number of high-energy compounds, a great variety of additives and synthesis by-products can be found that can differ depending on the brand, manufacturer and application. This makes the identification of commercial and military explosives based on their overall composition a promising approach that can be used to establish a pan-European Forensic Substance Database on Explosives. In this work, three analytical techniques were employed to analyze 36 samples of commercial and military explosives from Germany and Switzerland. An HPLC-HRMS method was developed, using 27 analytes of interest that encompass high-energy compounds, synthesis by-products and additives. HPLCHRMS and XRD were used to gather and confirm molecular information on each sample and XRF analyses were carried out to gain insight on the elemental composition. Combining the results from all three techniques, 41 different additives could be identified as being diagnostic analytes and all samples showed a unique analytical fingerprint, which allows for a differentiation of the samples. Therefore, this work presents a set of methods that can be used as a foundation for the creation and population of a database on explosives that enables the assigning of specific formulations to certain brands, manufacturers and countries of origin.
Keywords: HPLC-HRMS | Powder XRD | XRF | Explosives | Commercial explosives | Military explosives
مقاله انگلیسی
4 A symbolic computational approach to finding solutions and conservation laws for (3 + 1)-dimensional modified BBM models
یک روش محاسباتی نمادین برای یافتن راه حل ها و قوانین حفاظت از مدل های BBM اصلاح شده بعدی (3 + 1)-2020
In this work three recently introduced (3 + 1)-dimensional nonlinear modified Benjamin-Bona-Mahony equations are studied from the modern group-theoretical analysis standpoint. The (3 + 1)-dimensional nonlinear differential equations are considered to be more realistic equations compared to the (1 + 1) and (2 + 1)-dimensional equations. Here we construct soliton and Jacobi elliptic function solutions of these three underlying equations and compute their conservation laws by employing Noether’s approach. The obtained solutions are presented graphically.  2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria.
KEYWORDS : (3 + 1)-dimensional modified | BBM equations | Jacobi elliptic function solutions | Noether symmetries | Conservation laws
مقاله انگلیسی
5 Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty
تجزیه و تحلیل جایگزین قدرت تطبیقی مبتنی بر یادگیری تقویتی برای مدیریت انرژی سیستم های ذخیره سازی انرژی ترکیبی مستقل با توجه به عدم اطمینان-2020
Hybrid energy storage systems (HESS) involve synergies between multiple energy storage technologies with complementary operating features aimed at enhancing the reliability of intermittent renewable energy sources (RES). Nevertheless, coordinating HESS through optimized energy management strategies (EMS) introduces complexity. The latter has been previously addressed by the authors through a systems-level graphical EMS via Power Pinch Analysis (PoPA). Although of proven efficiency, accounting for uncertainty with PoPA has been an issue, due to the assumption of a perfect day ahead (DA) generation and load profiles forecast. This paper proposes three adaptive PoPA-based EMS, aimed at negating load demand and RES stochastic variability. Each method has its own merits such as; reduced computational complexity and improved accuracy depending on the probability density function of uncertainty. The first and simplest adaptive scheme is based on a receding horizon model predictive control framework. The second employs a Kalman filter, whereas the third is based on a machine learning algorithm. The three methods are assessed on a real isolated HESS microgrid built in Greece. In validating the proposed methods against the DA PoPA, the proposed methods all performed better with regards to violation of the energy storage operating constraints and plummeting carbon emission footprint.
Keywords: Hybrid energy storage systems | Energy management strategies | Model predictive control | Kalman filter | Reinforcement learning
مقاله انگلیسی
6 Implementation of a standardized voiding management protocol to reduce unnecessary re-catheterization - A quality improvement project
اجرای یک پروتکل استاندارد مدیریت تخلیه برای کاهش دوباره کاتتریزاسیون غیر ضروری - یک پروژه بهبود کیفیت-2020
Objective. To design and implement a standardized postoperative voiding management protocol that accurately identifies patients with urinary retention and reduces unnecessary re-catheterization. Methods. A postoperative voiding management protocol was designed and implemented in patients undergoing major, inpatient, non-radical abdominal surgery with a gynecologic oncologist. No patients had epidural catheters. The implemented quality improvement (QI) protocol included: 1) Foley removal at six hours postoperatively; 2) universal bladder scan after the first void; and 3) limiting re-catheterization to patientswith bladder scan volumes N150 ml. A total of 96 patients post-protocol implementation were compared to 52 patients preprotocol. Along with baseline demographic data and timing of catheter removal,we recorded the presence or absence of urinary retention and/or unnecessary re-catheterization and postoperative urinary tract infection rates. Fishers exact test and students t-tests were performed for comparisons. Results. The overall rate of postoperative urinary retention was 21.6% (32/148). The new voiding management protocol reduced the rate of unnecessary re-catheterization by 90% (13.5% vs 2.1%, p = 0.01), without overlooking true urinary retention (23.1% vs 20.8%, p = 0.83). Additionally, there was a significant increase in hospital-defined early discharge prior to 11:00 AM (4.0% vs 22.0%, p = 0.022). There was no difference in the postoperative urinary tract infection rate between the groups (p=1.00). Risk factors associatedwith urinary retention included older age (p b 0.01), use of medications with anticholinergic properties (p b 0.01), and preexisting urinary dysfunction (p b 0.01). Conclusions. Implementation of this new voiding management protocol reduced unnecessary recatheterization, captured and treated true urinary retention, and facilitated early hospital discharge
Keywords: Quality improvement | Bladder voiding | Urinary retention | Postoperative management | Gynecologic Oncology surgery | Urinary tract infection
مقاله انگلیسی
7 Flow and heat transfer past a permeable power-law deformable plate with orthogonal shear in a hybrid nanofluid
انتقال جریان و حرارت از یک صفحه قابل تغییر قدرت قانون با برشی متعامد در یک نانوسیال ترکیبی-2020
This study concerns the three-dimensional hybrid nanofluid flow and heat transfer due to a deformable (stretching/shrinking) plate with power-law velocity and orthogonal surface shear. The flow due to the shrinking sheet is maintained with the imposition of wall mass suction. The effect of adding Cu and Al2O3 nanoparticles are represented by a homogeneous mixture model with the modified thermophysical properties. Two types of thermophysical properties for hybrid nanofluids are discussed and compared in this interesting work. The three-dimensional model is then, reduced into a relevant set of ordinary differential equations using similarity transformation. The results are generated using the bvp4c solver and presented in the tables and graphs. Duality of solutions are observed in both stretching and shrinking regions, however, only the first solution is proved to be stable and realistic. Surprisingly, the heat transfer rate augments when the power law velocity is used. The hybrid nanofluid with an upsurge of copper volume fraction also reduces the rate of heat transfer.
KEYWORDS : Stretching/shrinking surface | Three dimensional | Hybrid nanofluid | Heat transfer | Dual solutions
مقاله انگلیسی
8 Rapid discrimination of Salvia miltiorrhiza according to their geographical regions by laser induced breakdown spectroscopy (LIBS) and particle swarm optimization-kernel extreme learning machine (PSO-KELM)
تبعیض سریع miltiorrhiza مریم گلی با توجه به مناطق جغرافیایی خود را با طیف سنجی شکست ناشی از لیزر (LIBS) و یادگیری ماشین افراطی بهینه سازی ازدحام ذرات (PSO-KELM)-2020
Laser-induced breakdown spectroscopy (LIBS) coupled with particle swarm optimization-kernel extreme learning machine (PSO-KELM) method was developed for classification and identification of six types Salvia miltiorrhiza samples in different regions. The spectral data of 15 Salvia miltiorrhiza samples were collected by LIBS spectrometer. An unsupervised classification model based on principal components analysis (PCA) was employed first for the classification of Salvia miltiorrhiza in different regions. The results showed that only Salvia miltiorrhiza samples from Gansu and Sichuan Province can be easily distinguished, and the samples in other regions present a bigger challenge in classification based on PCA. A supervised classification model based on KELM was then developed for the classification of Salvia miltiorrhiza, and two methods of random forest (RF) and PSO were used as the variable selection method to eliminate useless information and improve classification ability of the KELM model. The results showed that PSO-KELM model has a better classification result with a classification accuracy of 94.87%. Comparing the results with that obtained by particle swarm optimization-least squares support vector machines (PSO-LSSVM) and PSO-RF model, the PSO-KELM model possess the best classification performance. The overall results demonstrate that LIBS technique combined with PSO-KELM method would be a promising method for classification and identification of Salvia miltiorrhiza samples in different regions.
Keywords: Laser-induced breakdown spectroscopy | Particle swarm optimization | Kernel extreme learning machine | Salvia miltiorrhiza | Classification
مقاله انگلیسی
9 A real-time blended energy management strategy of plug-in hybrid electric vehicles considering driving conditions
یک استراتژی مدیریت انرژی ترکیبی از زمان واقعی خودروهای برقی پلاگین با توجه به شرایط رانندگی-2020
In this study, a blended energy management strategy considering influences of driving conditions is proposed to improve the fuel economy of plug-in hybrid electric vehicles. To attain it, dynamic programming is firstly applied to solve and quantify influences of different driving conditions and driving distances. Then, the driving condition is identified by the K-means clustering algorithm in real time with the help of Global Positioning System and Geographical Information System. A blended energy management strategy is proposed to achieve the real-time energy allocation of the powertrain with incorporation of the identified driving conditions and the extracted rules, which includes the engine starting scheme, gear shifting schedule and torque distribution strategy. Simulation results reveal that the proposed strategy can effectively adapt to different driving conditions with the dramatic improvement of fuel economy and the decrement of calculation intensity and highlight the feasibility of real-time implementation
Keywords: Plug-in hybrid electric vehicles | Energy management strategy | Global optimization | Driving condition | Equivalent driving distance coefficient
مقاله انگلیسی
10 Establishment and application of intelligent city building information model based on BP neural network model
ایجاد و کاربرد مدل اطلاعات هوشمند شهرسازی براساس مدل شبکه عصبی BP-2020
The construction of smart cities in our country has received extensive attention. Under the situation that smart cities are vigorously promoted nowadays, compared with traditional construction and operation and maintenance methods, building information model (BIM) technology is more suitable to serve as an important foundation for intelligent management in the whole process of construction projects. BIM is an abbreviation for building information model. BIM relies on a variety of digital technologies, which can be used to realize information modeling of urban buildings and infrastructure. The efficiency of information exchange in the process of intelligence construction ensures the integrity and accuracy of information data exchange and maintains the consistency of information data exchange. Data and information have objectivity, applicability, transferability, and sharing. Geographic data is a digital representation of various geographical features and phenomena and their relationships. BIM is a digital representation of physical and functional characteristics of a facility. It can It is used as a shared knowledge resource for facility information. It becomes a reliable basis for facility life-cycle decision-making. Input BP neural network, and then learn and train by BP neural network.
Keywords: BP neural network | Smart city | Building information model
مقاله انگلیسی
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