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The current research aims to know the prevalence of marital compatibility among married female students at Tishreen University, and know the differences in marital compatibility according to some variables (method of marriage, place of residence, pre sence of children). The research was applied to a sample of married students at Tishreen University, whose number was (100) students. To achieve this goal, the marital compatibility scale prepared by (Ammar, 2015) was used, which includes dimensions (intellectual, affectionalemotional, sexual, and social compatibility) distributed within (54) items. The researcher conducted the psychometric study of the scale to ensure its validity and reliability in relation to the current research sample is high, and there are no statistically significant differences in the marital compatibility of the research sample according to the variable of the place of residence and the presence of children. As for the variable of the method of marriage it was found that there were statistically significant differences in favor of marriage after a love story.
With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic has been declared one of the mo st important focus areas of the World Health Organization, with dangers ranging from promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic. Addressing the issue requires solving a number of challenging problems such as identifying messages containing claims, determining their check-worthiness and factuality, and their potential to do harm as well as the nature of that harm, to mention just a few. To address this gap, we release a large dataset of 16K manually annotated tweets for fine-grained disinformation analysis that (i) focuses on COVID-19, (ii) combines the perspectives and the interests of journalists, fact-checkers, social media platforms, policy makers, and society, and (iii) covers Arabic, Bulgarian, Dutch, and English. Finally, we show strong evaluation results using pretrained Transformers, thus confirming the practical utility of the dataset in monolingual vs. multilingual, and single task vs. multitask settings.
Automatic summarization aims to extract important information from large amounts of textual data in order to create a shorter version of the original texts while preserving its information. Training traditional extractive summarization models relies heavily on human-engineered labels such as sentence-level annotations of summary-worthiness. However, in many use cases, such human-engineered labels do not exist and manually annotating thousands of documents for the purpose of training models may not be feasible. On the other hand, indirect signals for summarization are often available, such as agent actions for customer service dialogues, headlines for news articles, diagnosis for Electronic Health Records, etc. In this paper, we develop a general framework that generates extractive summarization as a byproduct of supervised learning tasks for indirect signals via the help of attention mechanism. We test our models on customer service dialogues and experimental results demonstrated that our models can reliably select informative sentences and words for automatic summarization.
This study aimed to identify the psychological and social consequences of ‎contacting medical staff in the Palestinian Ministry of Health with ‎patients during the Corona pandemic, and also aimed to identify if there ‎are differences in the psycholog ical and social effects of contacting ‎medical staff in the Palestinian Ministry of Health with patients during ‎the Corona pandemic According to the variables of the study (gender, job ‎title, academic qualification, years of experience), and to achieve the goal ‎of the study, a questionnaire consisting of (26) items distributed into two ‎areas was developed, and it was distributed to (95) medical staff and its ‎validity and reliability were confirmed by A committee of specialized ‎arbitrators, and after the process of distributing and collecting the ‎questionnaires, they were coded and entered into the computer, and ‎statistically processed using the statistical package for the social sciences. ‎The study showed that the degree of psychological effects of contact with ‎medical staff in the Palestinian Ministry of Health with patients during ‎the Corona pandemic was great, so the degree of psychological effects of ‎contact of medical staff in the Palestinian Ministry of Health with ‎patients during the Corona pandemic, as it was found that there is no ‎There are statistically significant differences at the level of significance (α ‎‎= 0.05) in each of the psychological and social effects of contact of ‎medical staff in the Palestinian Ministry of Health with patients during ‎the Corona pandemic due to variables (gender, job title, academic ‎qualification, years of experience. Based on the results of this study, the ‎researcher recommended several recommendations, the most important ‎of which were: The necessity to allocate sufficient free time for medical ‎staff in the Ministry of Health.‎‏ ‏The need to increase the number of ‎medical personnel in the Ministry of Health.‎
Building tools to remove sensitive information such as personal names, addresses, and telephone numbers - so called Protected Health Information (PHI) - from clinical free text is an important task to make clinical texts available for research. These de-identification tools must be assessed regarding their quality in the form of the measurements precision and re- call. To assess such tools, gold standards - annotated clinical text - must be available. Such gold standards exist for larger languages. For Norwegian, how- ever, there are no such resources. Therefore, an already existing Norwegian synthetic clinical corpus, NorSynthClinical, has been extended with PHIs and annotated by two annotators, obtaining an inter-annotator agreement of 0.94 F1-measure. In total, the corpus has 409 annotated PHI instances and is called NorSynthClinical PHI. A de-identification hybrid tool (machine learning and rule-based meth- ods) for Norwegian was developed and trained with open available resources, and obtained an overall F1-measure of 0.73 and a recall of 0.62, when tested using NorSynthClinical PHI. NorSynthClinical PHI is made open and available at Github to be used by the research community.
This work describes the adaptation of a pretrained sequence-to-sequence model to the task of scientific claim verification in the biomedical domain. We propose a system called VerT5erini that exploits T5 for abstract retrieval, sentence selection, an d label prediction, which are three critical sub-tasks of claim verification. We evaluate our pipeline on SciFACT, a newly curated dataset that requires models to not just predict the veracity of claims but also provide relevant sentences from a corpus of scientific literature that support the prediction. Empirically, our system outperforms a strong baseline in each of the three sub-tasks. We further show VerT5erini's ability to generalize to two new datasets of COVID-19 claims using evidence from the CORD-19 corpus.
With mental health as a problem domain in NLP, the bulk of contemporary literature revolves around building better mental illness prediction models. The research focusing on the identification of discussion clusters in online mental health communitie s has been relatively limited. Moreover, as the underlying methodologies used in these studies mainly conform to the traditional machine learning models and statistical methods, the scope for introducing contextualized word representations for topic and theme extraction from online mental health communities remains open. Thus, in this research, we propose topic-infused deep contextualized representations, a novel data representation technique that uses autoencoders to combine deep contextual embeddings with topical information, generating robust representations for text clustering. Investigating the Reddit discourse on Post-Traumatic Stress Disorder (PTSD) and Complex Post-Traumatic Stress Disorder (C-PTSD), we elicit the thematic clusters representing the latent topics and themes discussed in the r/ptsd and r/CPTSD subreddits. Furthermore, we also present a qualitative analysis and characterization of each cluster, unraveling the prevalent discourse themes.
Freezing sperms and eggs is one of the contemporary jurisprudential Issues. Therefore knowing its rules in Islamic jurisprudence requires searching for similar cases in the resources of Islamic Jurisprudence and practicing analogy where, in origina l case, used as a criterion for the new one. This paper is an endeavor to find out the jurisprudential stand of the cases where human sperms and eggs are frozen, and to which level this is compatible with Islamic shari’ah and its rules, particularly if fertilization is used for the husband and his wife (legal marriage), and if the aim of this process is to help the husband and the wife to give birth at the time they wish to, or at the time of elevating the preventive reason which was at the time of freezing. This paper concluded that the ruling of freezing the sperms and eggs is based on the reason which lead to that process; as there are reasons for which the freezing becomes lawful and there are ones for which the freezing becomes forbidden. This maxim in addition to some particular boundaries and conditions would rule the issue of freezing.
The demand for health services is of great importance as it is linked to the social aspect, which is the health status of citizens in a country, and it is from this importance that our current study focusing on a very important problem related to the ability to estimate the total social demand for health services was chosen. The study was the reality of social demand On health services in the public sector in Lattakia Governorate is one of the most important objectives of the study, in addition to studying the reality of social demand for health services in the private sector in Lattakia Governorate, and working on proposing a model for estimating social demand for health services in the public and private sectors.An analytical descriptive approach has been used, and at the end of the study the study reached an important set of results related to the port of the model and the estimation of social demand for health services in pharmacies, clinics and laboratories based on a questionnaire distributed to families in Latakia, in addition to the opinion of specialists from doctors, pharmacists, laboratory owners, and specialists At the Doctors Syndicate, the Dental Association, and the Pharmacists Syndicate. The health insurance system applied to workers in the country also contributed to increasing the demand for medical treatment in private sector clinics, as well as increasing social demand for health services provided in public hospitals during the study period, and the current crisis and the war on Syria have increased the demand for health services in general in Lattakia Governorate.
الصلة بين ماهو نفسي وجسمي الأمراض السيكو-فسيولوجية مفهوم الضغط النفسي زملة الضغط العام وطاقة التكيف أحداث الحياة كمصدر للضغط نوع الإصابة المرضية تتحدد بنوع الضغط وشدته مصادر الضغوط معاشية الضغوط ومعالجتها
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