Study of fungal infection frequency in libraries affiliated with Shahrekord University of Medical Sciences in 2013

زمینه و هدف: کتب و اسناد آسیب دیده و آلوده از طریق میکروارگانیسم ها تهدیدی جدی برای سلامتی کاربران و کتابداران هستند. این مطالعه با هدف بررسی هوا، سطوح کتاب ها و قفسه های کتابخانه های دانشگاه علوم پزشکی شهرکرد از نظر حضور انواع قارچ ها انجام شده است. روش بررسی: در این مطالعه توصیفی تعداد 307 نمونه از قارچ های موجود از هوا و نیز سطوح مختلف کتابخانه شامل مخزن کتب فارسی و لاتین، سالن مطالعه، میز امانت و بخش مجلات نمونه برداری شد. کشت بر روی محیط کشت سابور و دکستروز آگار توسط سواب انجام و بعد از گذشت 10 روز، کلنی های رشد کرده، لام مستقیم تهیه شد و جنس قارچ ها مشخص گردیدند. یافته ها: توزیع فراوانی رشد قارچ ها در کتاب های لاتین بیشتر از کتاب های فارسی، قفسه ها و فضاها بود. فراوان ترین نوع قارچ در بخش های مختلف مورد بررسی، پنی سیلیوم بود. نتیجه گیری: با توجه به رشد بیشتر قارچ ها در کتب لاتین و حضور قارچ هایی از جمله پنی سیلیوم در این کتب، لزوم توجه بیش از پیش به این بخش لازم و ضروری می باشد

The effect of Entonox on severity of pain and mother hemodynamic and fetus apgar in natural vaginal delivery

زمینه و هدف: درد زایمان از جمله شدیدترین دردهایی است که توسط انسان تجربه می‌شود و ترس از این درد باعث انتخاب سزارین در مادران می‌گردد. یکی از روش‌های دارویی سالم و ارزان جهت تسکین درد زایمان گاز انتونکس است. این مطالعه با هدف بررسی اثرات انتونکس بر شدت درد و وضعیت همودینامیک مادر و آپگار جنین در زایمان طبیعی انجام شد. روش بررسی: در این مطالعه کارآزمایی بالینی 60 زن کاندید زایمان طبیعی مراجعه کننده به مرکز آموزشی درمانی هاجر شهرکرد که شرایط یکسان برای ورود به مطالعه داشتند، به طور در دسترس انتخاب و به صورت تصادفی به 2 گروه تقسیم شدند. پس از شروع فاز فعال زایمان انتونکس توسط ماسک در اختیار مادران گروه مداخله قرار ‌گرفت و مادران تا پایان مرحله دوم زایمان از این گاز استنشاق ‌کردند. میانگین شدت درد، وضعیت همودینامیک مادر در حین دریافت گاز و آپگار جنین پس از تولد ثبت ‌و با گروهی که انتونکس دریافت نکردند، مقایسه شد. داده‌ها با استفاده از آزمونt مستقل مورد تجزیه و تحلیل قرار گرفت. یافته‌ها: میانگین شدت درد درمرحله اول زایمان در گروه مداخله 7/2±98/3 و در گروه شاهد 8/3 60/5 بود (03/0=P) و در مرحله دوم زایمان به ترتیب 6/0±20/7 و 10 (04/0P=) بود. بین دو گروه تفاوت معنی‌داری در میزان فشار خون مادر، میانگین ضربان قلب جنین و نمره آپگار دقایق 1 و 5 جنین وجود نداشت. میانگین تعداد تنفس و ضربان قلب مادر در گروه مداخله بیشتر از گروه شاهد بود (05/0

Too Hot To Be True: Temperature Calibration for Higher Confidence in NN-assisted Side-channel Analysis

The past years have witnessed a considerable increase in research efforts put into neural network-assisted profiled side-channel analysis (SCA). Studies have also identified challenges, e.g., closing the gap between metrics for machine learning (ML) classification and side-channel attack evaluation. In fact, in the context of NN-assisted SCA, the NN’s output distribution forms the basis for successful key recovery. In this respect, related work has covered various aspects of integrating neural networks (NNs) into SCA, including applying a diverse set of NN models, model selection and training, hyperparameter tuning, etc. Nevertheless, one well-known fact has been overlooked in the SCA-related literature, namely NNs’ tendency to become “over-confident,” i.e., suffering from an overly high probability of correctness when predicting the correct class (secret key in the sense of SCA). Temperature scaling is among the powerful and effective techniques that have been devised as a remedy for this. Regarding the principles of deep learning, it is known that temperature scaling does not affect the NN’s accuracy; however, its impact on metrics for secret key recovery, mainly guessing entropy, is worth investigating. This paper reintroduces temperature scaling into SCA and demonstrates that key recovery can become more effective through that. Interestingly, temperature scaling can be easily integrated into SCA, and no re-tuning of the network is needed. In doing so, temperature can be seen as a metric to assess the NN’s performance before launching the attack. In this regard, the impact of hyperparameter tuning, network variance, and capacity have been studied. This leads to recommendations on how network miscalibration and overconfidence can be prevented

The Effects of Age, Gender, Teaching Experience, Teaching Context, and Academic Degree on Iranian English Teachers’ Classroom Management Behaviors

Research has shown that classroom management plays a critical role in facilitating effective learning, making it a permanent concern for teachers as well as researchers. In the related literature, one area which needs further consideration is to explore the effect of different personal and contextual factors on the way teachers choose to manage their classrooms. Therefore, the present study aimed at exploring the effects of age, gender, teaching experience, teaching context, and academic degree on Iranian English teachers’ classroom management behaviors. To achieve this, a researcher-made questionnaire based on four classroom management questionnaires was developed. The questionnaire was distributed among 152 EFL teachers teaching in different settings in Iran. To analyze the obtained data, Point-Biserial correlation followed by an independent samples t-test, and one-way ANOVA were used. The results revealed that men and women were quite different with regard to the classroom management behaviors they showed. However, age, teaching context, teaching experience, and academic degree did not significantly affect teachers’ classroom management behaviors. Possible explanations of the results in light of the previous literature are further discussed

THE IMPACT OF STABILITY RANGE EXERCISES ON GAIT PARAMETER AND QUALITY OF LIFE AMONG ACTIVE ELDER WOMEN

The purpose of this research is to discuss the impacts of stability range exercises on certain gait parameters and quality of life among active elder women. The population of this research includes 100 women aged between 61 and 88 years who inhabit in the nursing home of Kahrizak, Karaj. Among the population, 40 individuals matched our research criterions and consequently, these 40 were selected as the sample group. The subjects’ age range was 61-88 years, also their height range was 139.5-160cms and their weight range was 48-88 kilograms. The subjects of the experimental group were administered 24 sessions of reformation exercises. In addition, the control group performed morning exercises, under the supervision of the facility’s coach. The collected statistical data were subjected to further analyses through the independent-t and independent-t tests as well as the Kolmogorov-Smirnoff test for confirming the normality of data distributions at the confidence level of P= 0.05. Results indicated that stability range exercises are capable of increasing the lengths of both the left and right paces significantly. The variables of life quality, pace speed, pace frequency, stance time and swing time were significantly increased among the subjects of experimental group, however compared to the control group; this increase was not statistically significant.  Article visualizations

Time is money, friend! Timing Side-channel Attack against Garbled Circuit Constructions

With the advent of secure function evaluation (SFE), distrustful parties can jointly compute on their private inputs without disclosing anything besides the results. Yao’s garbled circuit protocol has become an integral part of secure computation thanks to considerable efforts made to make it feasible, practical, and more efficient. These efforts have resulted in multiple optimizations on this primitive to enhance its performance by orders of magnitude over the last years. The advancement in protocols has also led to the development of general-purpose compilers and tools made available to academia and industry. For decades, the security of protocols offered in those tools has been assured with regard to sound proofs and the promise that during the computation, no information on parties’ input would be leaking. In a parallel effort, however, side-channel analysis (SCA) has gained momentum in connection with the real-world implementation of cryptographic primitives. Timing side-channel attacks have proven themselves effective in retrieving secrets from implementations, even through remote access to them. Nevertheless, the vulnerability of garbled circuit frameworks to timing attacks has, surprisingly, never been discussed in the literature. This paper introduces Goblin, the first timing attack against commonly employed garbled circuit frameworks. Goblin is a machine learning-assisted, non-profiling, single-trace timing SCA, which successfully recovers the garbler’s input during the computation under different scenarios, including various GC frameworks, benchmark functions, and the number of garbler’s input bits. Furthermore, we discuss Gob- lin’s success factors and countermeasures against that. In doing so, Goblin hopefully paves the way for further research in this matter