Effect of linear and stepwise sodium and ultra filtration profiles on intradialytic hypotension and muscle cramps in renal disease patients

زمینه و هدف: افت فشارخون و کرامپ های عضلانی از عوارض شایع حین دیالیز است که علاوه بر نارضایتی بیماران، کفایت دیالیز را نیز پایین می آورد. یکی از روش هایی که اخیراً مطرح شده، استفاده از پروفایل های سدیم و اولترافیلتراسیون می باشد. هدف این مطالعه بررسی و مقایسه تاثیر پروفایل های خطی و پلکانی سدیم و اولترافیلتراسیون بر افت فشارخون و کرامپ های عضلانی حین همودیالیز بود. روش بررسی: در این مطالعه کارآزمایی بالینی 26 بیمار تحت همودیالیز مراجعه کننده به دو مرکز همودیالیز بیمارستان های حضرت علی اصغر(ع) و الزهرا(س) اصفهان که در طول یک ماه قبل از انجام پژوهش در بیش از 20 درصد جلسات دیالیز، دچار هیپوتانسیون حین دیالیز شده بودند، انتخاب شدند. در این پژوهش هر یک از بیماران به مدت سه جلسه با روش روتین (غلظت ثابت سدیم بر روی 138 میلی مول در لیتر)، 3 جلسه با روش پروفایل 1 سدیم و پروفایل 1 اولترافیلتراسیون (پروفایل خطی) و سه جلسه دیگر نیز با روش پروفایل 3 سدیم و پروفایل 3 اولترافیلتراسیون (پروفایل پلکانی) تحت دیالیز قرار گرفتند. جهت تجزیه و تحلیل داده ها از آمار توصیفی و استنباطی کای اسکوئر استفاده شد. یافته ها: میــانگین سنی بیماران 19±8/46 سال بود. نتایج مطالعه نشان داد که میزان بروز هیپوتانسیون و کرامپ های عضلانی در روش پروفایل خطی سدیم و پروفایل خطی اولترافیلتراسیون و روش پروفایل پلکانی سدیم و پروفایل پلکانی اولترافیلتراسیون در مقایسه با روش روتین (کنترل) بطور معنی داری کاهش یافت (05/0P). نتیجه گیری: بکارگیری پروفایل های سدیم و اولترافیلتراسیون روشی ساده و بدون هزینه است که با تنظیم غلظت سدیم و میزان برداشت اولترافیلتراسیون باعث ثبات وضعیت همودینامیک بیمار در طول دیالیز می شود. بنابراین به منظور جلوگیری از افت فشارخون و کرامپ های عضلانی در طول دیالیز، استفاده از پروفایل های سدیم و اولترافیلتراسیون (نوع خطی و پلکانی) نسبت به روش روتین پیشنهاد می گردد

Regularity of the free boundary for a parabolic cooperative system

In this paper we study the following parabolic system Delta u - partial derivative(t)u = vertical bar u vertical bar(q-1) u chi({vertical bar u vertical bar > 0}), = (u(1), ... , u(m)), with free boundary partial derivative{vertical bar u vertical bar > 0). For 0Peer reviewe

Leveraging data mining techniques to understand drivers of obesity

Abstract—Substantial research has been carried out to explain\ud the effects of economic variables on obesity, typically\ud considering only a few factors at a time, using parametric\ud linear regression models. Recent studies have made a significant\ud contribution by examining economic factors affecting body\ud weight using the Behavioral Risk Factor Surveillance System\ud data with 27 state-level variables for a period of 20 years (1990-\ud 2010). As elsewhere, the authors solely focus on individual\ud effects of potential drivers of obesity than critical interactions\ud among the drivers. We take some steps to extend the literature\ud and gain a deeper understanding of the drivers of obesity.\ud We employ state-of-the-art data mining techniques to uncover\ud critical interactions that may exist among drivers of obesity\ud in a data-driven manner. The state-of-the-art techniques reveal\ud several complex interactions among economic and behavioral\ud factors that contribute to the rise of obesity. Lower levels of\ud obesity, measured by a body mass index (BMI), belong to\ud female individuals who exercise outside work, enjoy higher\ud levels of education and drink less alcohol. The highest level of\ud obesity, in contrast, belongs to those who fail to exercise outside\ud work, smoke regularly, consume more alcohol and come from\ud lower income groups. These and other complementary results\ud suggest that it is the joint complex interactions among various\ud behavioral and economic factors that gives rise to obesity or\ud lowers it; it is not simply the presence or absence of individual\ud factor

Tangential Touch between the Free and the Fixed Boundary in a Semilinear Free Boundary Problem in Two Dimensions

The main result of this paper concerns the behavior of a free boundary arising from a minimization problem, close to the fixed boundary in two dimensions

Features in extractive supervised single-document summarization: case of Persian news

Text summarization has been one of the most challenging areas of research in NLP. Much effort has been made to overcome this challenge by using either abstractive or extractive methods. Extractive methods are preferable due to their simplicity compared with the more elaborate abstractive methods. In extractive supervised single document approaches, the system will not generate sentences. Instead, via supervised learning, it learns how to score sentences within the document based on some textual features and subsequently selects those with the highest rank. Therefore, the core objective is ranking, which enormously depends on the document structure and context. These dependencies have been unnoticed by many state-of-the-art solutions. In this work, document-related features such as topic and relative length are integrated into the vectors of every sentence to enhance the quality of summaries. Our experiment results show that the system takes contextual and structural patterns into account, which will increase the precision of the learned model. Consequently, our method will produce more comprehensive and concise summaries

Adoption of Digital Technology in Corporate R&D Context

Achieving tangible benefits from digitalization often requires changes in processes, culture and reward systems. This need is especially acute in research and development, yet the attitudes and skills of R&D staff may impede their use of automation. We examine the ongoing digitalization of R&D activities at Unilever. Using thematic analysis, we analyze in-depth interviews to uncover attitudes towards, and experiences with, digitalization of R&D using robots. We build on these findings and conduct sequence analysis to extract a number of within-interview sequential associations between themes. These associations have been mapped onto patterns aligned with four established models of digitalization and IT adoption: the Technology Acceptance Model, Resistance to Change, Task Technology Fit and Process Virtualization

Scaling Limits for Internal Aggregation Models with Multiple Sources

We study the scaling limits of three different aggregation models on Z^d: internal DLA, in which particles perform random walks until reaching an unoccupied site; the rotor-router model, in which particles perform deterministic analogues of random walks; and the divisible sandpile, in which each site distributes its excess mass equally among its neighbors. As the lattice spacing tends to zero, all three models are found to have the same scaling limit, which we describe as the solution to a certain PDE free boundary problem in R^d. In particular, internal DLA has a deterministic scaling limit. We find that the scaling limits are quadrature domains, which have arisen independently in many fields such as potential theory and fluid dynamics. Our results apply both to the case of multiple point sources and to the Diaconis-Fulton smash sum of domains.Comment: 74 pages, 4 figures, to appear in J. d'Analyse Math. Main changes in v2: added "least action principle" (Lemma 3.2); small corrections in section 4, and corrected the proof of Lemma 5.3 (Lemma 5.4 in the new version); expanded section 6.