Cleaning Efficiency of Root Canal after Irrigation with New Irrigation Technique: A Scanning Electron Microscopic Study

Introduction: The aim of this study was to evaluate the ability of pressurized water irrigation technique (AquaPick Device) as an intra-canal irrigation technique and compare it with sonic irrigation device (Endoactivator) for their ability to remove smear layer from canals. Methods and Materials: Total number of 80 single rooted teeth (premolars) were prepared, divided into eight main groups, Group 1: Aquapick with apically vented needle/18 mm depth, Group 2: Aquapick with apically vented needle/15 mm depth, Group 3: Endoactivator device/18 mm depth, Group 4: Endoactivator device/15 mm depth, Group5: Aquapick with 2 side vented needle/18 mm depth, Group 6: Aquapick with 2 side vented needle/15 mm depth and two control groups. Then all samples were tested by SEM in 3, 6 and 9-mm distances from the apical foramen. The data were statistically analyzed using Kruskal Wallis and Mann-Whitney U tests. Results: There was a high significant difference among the tested groups with the best removal of smear layer by the use of pressurized water irrigation device with apical vented needle especially at the 3 mm area. Conclusion: Pressurized water irrigation technique could be used as intra-canal irrigation technique with good results.Keywords: AquaPick Device; Endoactivator; Smear Layer Removal; Pressurized Wate

Evaluation of Canal Transportation after Using Different Types Rotary Glide Path Files

Introduction: Canal transportation is a common problem caused by rotary instruments. The purpose of the present study was to evaluate root canal transportation after using WaveOne Gold Glider, ProGlider, Path File and K-file. Methods and materials: Forty resin blocks with L-shaped canals were divided into four groups (n=10). Group 1; canals were prepared with WaveOne Gold Glider, group 2; ProGlider, group 3; Path Files and group 4; #10, #15, and #20 stainless steel manual K-Files. Pre- and post-instrumentation photographic images were superimposed and resin removed from the inner and outer surfaces of the root canal was calculated through 3 points at 3, 6 and 9 mm from the end of canal which represented canal transportation. All data were analyzed by one way ANOVA test. The level of significance was set at 0.05. Results: Statistical analysis by one-way ANOVA test revealed that there was no significant differences (P>0.05) between the tested files in canal transportation in apical, middle and coronal third. The last amount of canal transportation happened at the apical third in WaveOne Gold Glider group. Conclusions: This in vitro study showed that using WaveOne Gold Glider files lead to less canal transportation especially in the apical third area with less significant differences with ProGlider, PathFiles and K-File.Keywords: Canal Transportation; Glide Path File; Resin Block; WaveOne Gold Glide

Some Qur’anic Discourse Strategies in the Realization and Use of Terror vs.Horror: A Pragmalinguistic Study with Reference to the Translation Impacts

تبحث هذه الورقة البحثية في الاستراتيجيات اللغوية والسياقية المرتبطة بفهم واستخدام التعبيرين المتضادين "الإرهاب" و"الإرعاب" فيما يتعلق بمعانيهما المعجمية والإيحائية في خطاب القرآن المجيد والحديث الشريف. ولهذا الغرض، تم اختيار عدد من الآيات القرآنية  وبعض الأحاديث التي تحتوي على المصطلحين, وتم تحليل هذه العينات في ضوء الإطار النظري لمنهج سياقي- لغوي أستخدم كمنظور تحليلي لهذه الدراسة يستند في معظمه على نظرية عالم اللغة السياقي جيففير شيرين (1999), نظرية التكيف اللغوي (LAT). ومن خلال هذا المنهج,  تم وضع فرضية تنص على أن فهم واستخدام هذين المصطلحين في الخطاب الديني في القرآن والحديث يرتبط سياقيا باستراتيجيات لغوية وسياقية عديدة كامنة ذات دلالات معجمية وإيحائية مختلفة تتبلور من خلال التأثيرات والانطباعات الإدراكية الايجابية منها والسلبية على المتلقين للخطاب.وفي هذا السياق, يحاجي البحث بأن هذا الخطاب الديني يرتكز على عملية التكيف، القائمة على اتخاذ الاختيار والتفاوض الديناميكي الحيوي والتكيف اللغوي للمتغيرات الفيزيائية والاجتماعية والذهنية المتعلقة بسياق الموقف. ومن خلال هذا المنظور، يمكن تفسير وفهم هذا الخطاب من خلال استنباط وتكوين  المعنى  المستمد من نقاط التركيز الأربعة وهي: السياق والبناء الهيكلي والديناميكية والأهمية. وكشفت نتائج التحليل أن هذين المصطلحان يستخدمان بهدف  تحقيق استراتيجيات سياقية وأيديولوجية ترتكز في نوعها ومدلولاتها الخطابية على المعاني المعجمية والإيحائية المتضادة لهذين المصطلحين.لقد توصل البث إلى نتيجة مفادها أن هذين المصطلحين  يفهمان ويستخدمان بفعالية  وبقصد على أنهما  تعبيرين متضادين  في معانيهما اللفظية والإيحائية, وعلى أساس هذا الفهم والإدراك  يتم استخدامهما لغرض الوصول الى استراتيجيات سياقية محددة تجعل من النص الديني أداة وظيفية تضعها اللغة بيد المتحدثين والمتلقين لغرض تحقيق غاياتهم التواصلية بشكل أكثر ملائمة. وأخيرا, يأمل الباحثان بأن نتائج البحث فيما يتعلق بالمصطلحين اللغويين المتضادين "الإرهاب" و "الإرعاب" يمكن أن تكون ذو تأثير على قضايا ومجالات الترجمة, وخصوصا في العالم العربي.This paper investigates the communicative pragmatic strategies associated with the realization and use of the linguistic dichotomy"Terror" vs."Horror", with regard to their denotative and connotative meanings in the Glorious Quran (and Hadith) discourse. To that end, a number of Qur’anic verses and Hadith utterances containing the two terms have been chosen and analyzed within the theoretical framework of a pragmalinguistic approach as a perspective, mostly based on Jef Verschueren’s (1999) Linguistic Adaptation Theory (LAT).On the light of this model, it is argued here that the realization and use of these two terms in the religious discourse of Quran and Hadith indicate various underlying linguistic and pragmatic strategies with different denotations and connotations revealed from the positive and negative conceptualized impacts on interpreters. It is also argued that in the relevant  discourse, the adaptation process, based on choice making, dynamic negotiation, and linguistic adaptation to physical, social and cognitive variables of the context of situation, is used. From this perspective, such a discourse is interpreted with reference to the meaning generation derived from the focal points of context, structure, dynamics and salience. The results of the analysis reveal that these two terms are used for various different pragmatic (and ideological) strategies based on their contrasting denotations and connotations. The paper reaches a conclusion that these two linguistic expressions are dynamically and intentionally realized as two antonymous expressions with reference to their denotations and connotations, and used for certain  pragmatic strategies that make the religious discourse function as a tool provided by language for the utterers and interpreters to satisfy their communicative needs most appropriately. The results and conclusions, raised here, might be of significant effects, or impacts, on translation matters; particularly, in the Arabic world, insofar as the linguistic dichotomy "Terror" vs. "Horror" is concerned

Power savings analysis of clipping and filtering method in OFDM systems

The clipping and filtering method is analyzed in terms of power savings. The analysis takes account of the gain in the amplifier efficiency due to peak-to-average-power-ratio (PAPR) reduction. Assuming a linear amplifier and a typical digital signal processor, the power savings is shown to be in the order of Watts

On the spectral efficiency for selection combiner diversity (SCD) over slow fading

In this paper we derive closed-form expressions for the single-user capacity of selection combining diversity (SCD) system, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. The complex channel estimate and the actual channel are modelled as jointly Gaussian random variables with a correlation that depends on the estimation quality. Two adaptive transmission schemes are analyzed: 1) optimal power and rate adaptation; and 2) constant power with optimal rate adaptation. Our numerical results show the effect of Gaussian channel estimation error on the achievable spectral efficiency

Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks

لضمان الإستجابة للخطأ والإدارة الموزعة، يتم استخدام البروتوكولات الموزعة كأحد المفاهيم المعمارية الرئيسية التي تتضمنها شبكة الإنترنت. ومع ذلك، يمكن التغلب على عدم الكفاءة وعدم الاستقرار والقصور بمساعدة بنية الشبكات الجديدة التي تسمى الشبكات المعرفة بالبرمجيات SDN. الخاصية الرئيسية لهذه المعمارية هي فصل مستوى التحكم عن مستوى البيانات. إن تقليل التصادم سيؤدي إلى تحسين سرعة الإستجابة وزيادة البيانات المرسلة بصورة صحيحة، لهذا السبب يجب أن يكون هناك توزيع متجانس للحمل المروري عبر مسارات الشبكة المختلفة. تقدم هذه الورقة البحثية أداة توجيه ذكية SFSA لتوجيه تدفق البيانات بناءاً على ظروف الشبكة الحالية. لتحسين الإنتاجية وتقليل زمن الوصول، فإن الخوارزمية المقترحة SFSA تقوم بتوزيع حركة مرور البيانات داخل الشبكة على مسارات مناسبة ، بالإضافة إلى الإشراف على الإرتباطات التشعبية وحمل مسارات نقل البيانات. تم استخدام سيناريو خوارزمية توجيه شجرة الامتداد الدنياMST وأخرى مع خوارزمية التوجيه المعروفة بفتح أقصر مسار أولاً OSPF لتقييم جودة الخوارمية المقترحة SFSA . على سبيل المقارنة ، بالنسبة لخوارزميات التوجيه المذكروة آنفاً ، فقد حققت استراتيجيةSFSA المقترحة انخفاضاً بنسبة 2٪ في معدل ضياع حزم البيانات PDR ، وبنسبة تتراوح بين 15-45٪ في سرعة إستلام البيانات من المصدر إلى الالوجهة النهائية لحزمة البيانات وكذلك انخفاض بنسبة 23 ٪ في زمن رحلة ذهاب وعودة RTT . تم استخدام محاكي Mininet ووحدة التحكم POX لإجراء المحاكاة. ميزة أخرى من SFSA على MST و OSPF هي أن وقت التنفيذ والاسترداد لا يحمل تقلبات. يتقوم أداة التوجيه الذكية المقترحة في هذه الورقة البحثية من فتح أفقاً جديداً لنشر أدوات ذكية جديدة في شبكة SDN تعزز قابلية برمجة الشبكات وإدارتها .To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management

Dynamic neural network architecture inspired by the immune algorithm to predict preterm deliveries in pregnant women

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants is most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. There is a strong body of evidence emerging that suggests the analysis of uterine electrical signals, from the abdominal surface (Electrohysterography – EHG), could provide a viable way of diagnosing true labour and even predict preterm deliveries. This paper explores this idea further and presents a new dynamic self-organized network immune algorithm that classifies term and preterm records, using an open dataset containing 300 records (38 preterm and 262 term). Using the dataset, oversampling and cross validation techniques are evaluated against other similar studies. The proposed approach shows an improvement on existing studies with 89% sensitivity, 91% specificity, 90% positive predicted value, 90% negative predicted value, and an overall accuracy of 90%

Enhancement efficiency of polymer solar cells by incorporating metal oxide nanoparticles

Gold nanoparticles (AuNPs) deposited at the interface of the hole-collecting buffer layer [poly(3,4ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS)] and regiore-gular poly (3-hexylthiophene) :[6,6]-phenylC61-butyricacidmethylester(rr-P3HT):(PCBM) active layer were found to significantly increase solar cell performance. The photo-physical properties of these devices incorporated with AuNPs with different space distributions in the interface of PEDOT:PSS buffer layer and P3HT:PCBM active layer are investigated. We find that, the optical property is improved as the AuNPs are large enough to penetrate into the active layer and the performance of Photovoltaic solar cells (PSCs) with large AuNPs can benefit from the improved hole collection efficiency. The efficiency enhancement for the device with a PEDOT:PSS: AuNPs film is more significant than for the device with PEDOT:PSS film. Keywords: PEDOT:PSS, Buffer layer, P3HT:PCBM, Gold oxide nanoparticle

Prediction of Flood Severity Level Via Processing IoT Sensor Data Using Data Science Approach

The ‘riverine flooding’ is deemed a catastrophic phenomenon caused by extreme climate changes and other ecological factors (e.g., amount of sunlight), which are difficult to predict and monitor. However, the use of internet of things (IoT), various types of sensing including social sensing, 5G wireless communication and big data analysis have devised advanced tools for early prediction and management of distrust events. To this end, this paper amalgamates machine learning models and data analytics approaches along-with IoT sensor data to investigate attribute importance for the prediction of risk levels in flood. The paper presents three river levels: normal, medium and high-risk river levels for machine learning models. Performance is evaluated with varying configurations and evaluations setup including training and testing of support vector machine and random forest using principal components analysis-based dimension reduced dataset. In addition, we investigated the use of synthetic minority over-sampling technique to balance the class representations within dataset. As expected, the results indicated that a “balanced” representation of data samples achieved high accuracy (nearly 93%) when benchmarked with “imbalanced” data samples using random forest classifier 10-folds cross-validation