Application of Quantum Natural Language Processing for Language Translation

In this paper, we develop compositional vector-based semantics of positive transitive sentences using quantum natural language processing (Q-NLP) to compare the parametrized quantum circuits of two synonymous simple sentences in English and Persian. We propose a protocol based on quantum long short-term memory (Q-LSTM) for Q-NLP to perform various tasks in general but specifically for translating a sentence from English to Persian. Then, we generalize our method to use quantum circuits of sentences as an input for the Q-LSTM cell. This enables us to translate sentences in different languages. Our work paves the way toward representing quantum neural machine translation, which may demonstrate quadratic speedup and converge faster or reaches a better accuracy over classical methods

An Optimizing Method for Performance and Resource Utilization in Quantum Machine Learning Circuits

Quantum computing is a new and advanced topic that refers to calculations based on the principles of quantum mechanics. Itmakes certain kinds of problems be solved easier compared to classical computers. This advantage of quantum computingcan be used to implement many existing problems in different fields incredibly effectively. One important field that quantumcomputing has shown great results in machine learning. Until now, many different quantum algorithms have been presented toperform different machine learning approaches. In some special cases, the execution time of these quantum algorithms will bereduced exponentially compared to the classical ones. But at the same time, with increasing data volume and computationtime, taking care of systems to prevent unwanted interactions with the environment can be a daunting task and since thesealgorithms work on machine learning problems, which usually includes big data, their implementation is very costly in terms ofquantum resources. Here, in this paper, we have proposed an approach to reduce the cost of quantum circuits and to optimizequantum machine learning circuits in particular. To reduce the number of resources used, in this paper an approach includingdifferent optimization algorithms is considered. Our approach is used to optimize quantum machine learning algorithms forbig data. In this case, the optimized circuits run quantum machine learning algorithms in less time than the original onesand by preserving the original functionality. Our approach improves the number of quantum gates by 10.7% and 14.9% indifferent circuits and the number of time steps is reduced by three and 15 units, respectively. This is the amount of reduction forone iteration of a given sub-circuit U in the main circuit. For cases where this sub-circuit is repeated more times in the maincircuit, the optimization rate is increased. Therefore, by applying the proposed method to circuits with big data, both cost andperformance are improved

A systematic review on the impact of empowerment in improving self-care behaviors and some other factors in diabetic patients

Introduction: Traditional education seems to be sufficient in meeting the needs related to knowledge of patients, However, by recognizing the impact of psychosocial issues and the environment on patients 'behavior, educational techniques were used to change patients' behavior. And the education approach to diabetic patients has changed, as well as the theory and research on diabetes was introduced. And the focus of the capacity building approach to adapt treatment to self-efficacy and empowerment was changed. Empowerment is a collaborative approach to diabetes care and patient education. This systematic review was conducted with the aim of empowerment in improving self-care behaviors in diabetic patients. Materials and Methods: In order to achieve the aim of the study and to improve the accuracy of the study and its comprehensive understanding, this review study was conducted based on the Broome method. This method is carried out in three steps: searching for texts, evaluating data and analyzing data. So, in the search phase, postretrospective study texts are examined in four stages in terms of inclusion criteria. After obtaining the conditions for entry into the study, the content of the study is evaluated and at the end of the analysis of the data. Results: In this study, 12 articles were reviewed that showed that the empowerment approach of diabetic patients improves self-efficacy and self-care scores and reduces hemoglobin A1C, Improvement of general self-care behaviors, reduction of mean glycosylated hemoglobin and improvement of quality of life, blood glucose control, and so on. Conclusion: In researches done on the empowerment approach of diabetic patients, the importance of empowerment approach is confirmed by increasing control and self-care and improving some other factors in diabetic patients. Therefore, considering the importance of the concept of empowerment as an effective approach to supporting patients with diabetes, it is necessary to consider this approach in furtherresearch

Effect of pre- and postharvest salicylic acid treatment on quality characteristics of tomato during cold storage

Nowadays, there is a considerable tendency to replace dangerous chemicals with natural compounds, compatible with plant, human, and nature. This study was aimed to assess the effect of salicylic acid on quality and storage life of tomato (Lycopersicon esculentum cv. Baraka). The salicylic acid application was including plant foliar application three weeks before harvest at concentration 4 mM, followed by the postharvest dipping fruits in salicylic acid at different concentrations (1, 2, 4 mM), then storing at 10°C for 40 days to investigate quantitative and qualitative characteristics. The chilling injury symptoms, electrolyte leakage, decay and a* (redness) value significantly decreased and activity ascorbate peroxidase increased. Ascorbic acid content, total soluble solid, titratable acidity, firmness, and L* (lightness) retained by salicylic acid treatments. The salicylic acid application had no significant influence on weight loss and b*. Application of salicylic acid in all concentrations, especially a combination of treatments preharvest to concentrations 4 mM as well as postharvest 4 mM, had the highest influence on qualitative and quantitative characteristics and increased the postharvest life of the tomato fruit

Regulation of 3β-Hydroxysteroid Dehydrogenase/∆5-∆4 Isomerase: A Review

This review focuses on the expression and regulation of 3β-hydroxysteroi ddehydrogenase/Δ5-Δ4 isomerase (3β-HSD), with emphasis on the porcine version. 3β-HSD is often associated with steroidogenesis, but its function in the metabolism of both steroids and xenobiotics is more obscure. Based on currently available literature covering humans,rodents and pigs, this review provides an overview of the present knowledge concerning the regulatory mechanisms for 3β-HSD at all omic levels. The HSD isoenzymes are essential in steroid hormone metabolism, both in the synthesis and degradation of steroids. They display tissue-specific expression and factors influencing their activity, which therefore indicates their tissue-specific responses. 3β-HSD is involved in the synthesis of a number of natural steroid hormones, including progesterone and testosterone, and the hepatic degradation of the pheromone androstenone. In general, a number of signaling and regulatory pathways have been demonstrated to influence 3β-HSD transcription and activity, e.g., JAK-STAT, LH/hCG, ERα, AR, SF-1 and PPARα. The expression and enzymic activity of 3β-HSD are also influenced by external factors, such as dietary composition. Much of the research conducted on porcine 3β-HSD is motivated by its importance for the occurrence of the boar taint phenomenon that results from high concentrations of steroids such as androstenone. This topic is also examined in this review