Academic information on Twitter: A user survey

Although counts of tweets citing academic papers are used as an informal indicator of interest, little is known about who tweets academic papers and who uses Twitter to find scholarly information. Without knowing this, it is difficult to draw useful conclusions from a publication being frequently tweeted. This study surveyed 1,912 users that have tweeted journal articles to ask about their scholarly-related Twitter uses. Almost half of the respondents (45%) did not work in academia, despite the sample probably being biased towards academics. Twitter was used most by people with a social science or humanities background. People tend to leverage social ties on Twitter to find information rather than searching for relevant tweets. Twitter is used in academia to acquire and share real-time information and to develop connections with others. Motivations for using Twitter vary by discipline, occupation, and employment sector, but not much by gender. These factors also influence the sharing of different types of academic information. This study provides evidence that Twitter plays a significant role in the discovery of scholarly information and cross-disciplinary knowledge spreading. Most importantly, the large numbers of non-academic users support the claims of those using tweet counts as evidence for the non-academic impacts of scholarly researc

Contrastive Analysis of Bilingual and Monolingual EFL Learners' Syntactic Errors in Translation

This study aimed at the analysis of syntactic errors in translation done by both bilingual and monolingual EFL learners. Research on the subject of the study implied that there might be differences between monolinguals and bilingual learners of foreign languages. The gaps of studies on differences between monolinguals and bilingual’s translations from Persian into English language presumed as research question of the study. Through a quantitative and experimental analysis, the researcher collected data from two universities of IAU of South Tehran (monolingual) and Jihad University of Kermanshah (bilingual) using students majoring in translation studies. The OPT test was applied to specify eligible students for the study and then a Persian literary text was offered to students to measure their syntactic errors as introduced by Keshavarz’s (1996) model of error analysis. From 100 participants 36 monolinguals and 24 bilinguals were eligible for the study whose translations were scored by the two raters. The results of the study indicated that there is a significant difference between the scores of monolingual and bilingual translators. In addition, the rate of literal errors and approximation was more than other errors that were reported as the result of language learning strategies and communicative strategies. However, new studies are suggested to investigate the types of errors made by monolinguals and bilinguals and graduate students with advanced level of language learning

SSHA: Video Violence Recognition and Localization Using a Semi-Supervised Hard Attention Model

Current human-based surveillance systems are prone to inadequate availability and reliability. Artificial intelligence-based solutions are compelling, considering their reliability and precision in the face of an increasing adaption of surveillance systems. Exceedingly efficient and precise machine learning models are required to effectively utilize the extensive volume of high-definition surveillance imagery. This study focuses on improving the accuracy of the methods and models used in automated surveillance systems to recognize and localize human violence in video footage. The proposed model uses an I3D backbone pretrained on the Kinetics dataset and has achieved state-of-the-art accuracy of 90.4% and 98.7% on RWF and Hockey datasets, respectively. The semi-supervised hard attention mechanism has enabled the proposed method to fully capture the available information in a high-resolution video by processing the necessary video regions in great detail.Comment: 11 pages, 4 figures, 4 equations, 3 tables, 1 algorith

The CYP17 MSP AI (T-34C) and CYP19A1 (Trp39Arg) variants in polycystic ovary syndrome: A case-control study

Background: Polycystic ovary syndrome (PCOS) is a common and chronic disorder of endocrine glands where genetic factors play a major role in the susceptibility to the disease. The cytochrome (CYP) 17 enzyme is essential for androgens biosynthesis. Also, the CYP19 enzyme converts the androgens to the aromatic estrogens.Objective: We aimed to investigate the association of CYP 17 MSP AI (T-34C) and CYP 19A1 (Trp39Arg) variants with the pathogenesis of PCOS in a population from Western Iran with Kurdish ethnic background.Materials and Methods: The present case-control study consisted of 50 patients with PCOS and 109 controls. The CYP17 T-34C and CYP19A1 (Trp39Arg) polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism. The serum lipid and lipoprotein profile were detected by the Bionic Diagnostic Kits. Estradiol, dehydroepiandrosterone (DHEA), and sex hormone-binding globulin (SHBG) levels were measured using the chemiluminescent method.Results: The serum levels of estradiol and SHBG in PCOS patients were lower than controls (p < 0.001 and p =0.06, respectively). However, the level of DHEA was higher (p= 0.01) in patients compared to controls. The higher frequency of CYP17 TC genotype in patients (30%) compared to controls (15.6%) was associated with 2.31-fold susceptibility to PCOS (p = 0.038). The frequency of CYP19 TC genotype was 6.4% in controls and10% in patients (p = 0.42).Conclusion: The present study suggests that CYP17 TC genotype could be associated with the risk of PCOS. Also, the study indicated the sex steroid hormones level alteration and the lower level of SHBG in PCOS patients compared to healthy individuals

The study of potassium ferrate application efficiency for advanced treatment of sewage

زمینه و هدف: طیف وسیعی از منعقد کننده‌ها، اکسیدان‌ها و گندزداها در تصفیه آب و فاضلاب استفاده می‌شوند. یون فرات به عنوان یک اکسیدان قوی بالاترین پتانسیل اکسیداسیون-احیاء را بین همه اکسیدان‌ها و گندزداها در تصفیه آب و فاضلاب داراست. یون فرات (شش ظرفیتی) در آب به یون هیدروکسید فریک احیا می‌شود و می‌تواند در یک فرآیند چند منظوره به عنوان منعقد کننده، اکسیدان و گندزدا مورد استفاده قرار گیرد. هدف از این مطالعه بررسی فرآیند تصفیه پیشرفته پساب فاضلاب شهری با استفاده از فرات پتاسیم بود. روش بررسی: در این مطالعه نیمه تجربی تصفیه پیشرفته فاضلاب شهری توسط فرات‌پتاسیم در مقیاس آزمایشگاهی روی پساب فاضلاب گندزدایی نشده با تعیین اثر متغیرهای pH و غلظت بر میزان حذف کدورت، ترکیبات ارگانی آب (COD) و فسفر مورد بررسی قرار گرفت. به منظور تعیین کارایی گندزدایی فرات پتاسیم نیز اثر سه متغیر زمان تماس، غلظت فرات و pH روی فرآیند گندزدایی با استفاده از شاخص (MPN (Most Probable Number مشخص شد. یافته‌ها: بهترین راندمان حذف ترکیبات ارگانی آب و کدورت با استفاده از فرات‌پتاسیم در شرایط بهینه (5=pH و غلظت mg/L10) به ترتیب 65 و 90 بود. pH و غلظت بهینه فرات ‌پتاسیم در حذف فسفر نیز 5=pH و غلظت mg/L 12 بود که موجب حذف 72 درصدی فسفر شد. بهترین شرایط کاربرد فرات پتاسیم به عنوان گندزدا در غلظت mg/L 4 و زمان تماس های 25 دقیقه و 6=pH بود. نتیجه گیری: فرات ‌پتاسیم به عنوان یک ماده شیمیایی مؤثر اکسید کننده، گندزدا و منعقد کننده می ‌تواند در تصفیه انواع پساب های شهری و صنعتی مورد استفاده قرار گیرد و با این کار دسترسی به چند هدف در یک فرآیند را میسر گرداند