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The main purpose of this paper is to analyze a tourist destination using sentiment analysis techniques with data from Twitter and Instagram to find the most representative entities (or places) and perceptions (or aspects) of the users.

The authors used 90,725 Instagram posts and 235,755 Twitter tweets to analyze tourism in Granada (Spain) to identify the important places and perceptions mentioned by travelers on both social media sites. The authors used several approaches for sentiment classification for English and Spanish texts, including deep learning models.

The best results in a test set were obtained using a bidirectional encoder representations from transformers (BERT) model for Spanish texts and Tweeteval for English texts, and these were subsequently used to analyze the data sets. It was then possible to identify the most important entities and aspects, and this, in turn, provided interesting insights for researchers, practitioners, travelers and tourism managers so that services could be improved and better marketing strategies formulated.

The authors propose a Spanish-Tourism-BERT model for performing sentiment classification together with a process to find places through hashtags and to reveal the important negative aspects of each place.

The study enables managers and practitioners to implement the Spanish-BERT model with our Spanish Tourism data set that the authors released for adoption in applications to find both positive and negative perceptions.

This study presents a novel approach on how to apply sentiment analysis in the tourism domain. First, the way to evaluate the different existing models and tools is presented; second, a model is trained using BERT (deep learning model); third, an approach of how to identify the acceptance of the places of a destination through hashtags is presented and, finally, the evaluation of why the users express positivity (negativity) through the identification of entities and aspects.

这项工作的主要目的是使用情感分析技术和来自 Twitter 和 Instagram 的数据来分析旅游目的地, 以便找到最具代表性的实体（或地点）和用户的感知（或方面）。

我们使用 90,725 个 Instagram 帖子和 235,755 个 Twitter 推文来分析格拉纳达（西班牙）的旅游业, 以确定旅行者在两个社交媒体网站上提到的重要地点和看法。我们使用了几种方法对英语和西班牙语文本进行情感分类, 包括深度学习模型。

测试集中的最佳结果是使用来自Transformers (BERT) 模型的双向编码器表示 (BERT) 用于西班牙语文本和Tweeteval 用于英语文本, 这些结果随后用于分析我们的数据集。然后可以确定最重要的实体和方面, 这反过来又为研究人员、从业人员、旅行者和旅游管理者提供了有趣的见解, 从而可以改进服务并制定更好的营销策略。

我们提出了一个用于执行情感分类的西班牙旅游 BERT 模型, 以及通过主题标签找到地点并揭示每个地点的重要负面方面的过程。

该研究使管理人员和从业人员能够使用我们发布的西班牙旅游数据集实施西班牙-BERT 模型, 以便在应用程序中采用该数据集, 以找到正面和负面的看法。

本研究提出了一种如何在旅游领域应用情感分析的新方法。首先, 介绍了评估不同现有模型和工具的方法; 其次, 使用 BERT（深度学习模型）训练模型; 第三, 提出了如何通过标签识别目的地地点的接受度的方法, 最后通过实体和方面的识别来评估用户表达积极性（消极性）的原因。

Referring to the theory of organizational empowerment, the purpose of this study is to examine the relationship of organizational support and perceived environment on quality of care and job satisfaction, with organizational commitment as a mediator for the first variable.

This study employed a cross-sectional research design and data was collected from seven private and public sector hospitals in Pakistan, involving 352 nurses on a voluntary basis through a self-administered survey.

The results showed that organizational commitment mediates the relationship between organizational support and job satisfaction with the quality of care. Moreover, the perceived environment has an impact on job satisfaction and quality of care.

Healthcare service quality seems strictly dependent on the perceived quality of care and job satisfaction among healthcare workers. Theoretical and practical implications for policymakers and HR management are discussed.

To assess the effectiveness of an integrated care program for post-acute care of stroke patients, the return home program (RHP program), deployed in Barcelona (North-East Spain) between 2016 and 2017 in a context of health and social care information systems integration.

The RHP program was built around an electronic record that integrated health and social care information (with an agreement for coordinated access by all stakeholders) and an operational re-design of the care pathways, which started upon hospital admission instead of discharge. The health outcomes and resource use of the RHP program participants were compared with a population-based matched control group built from central healthcare records of routine care data.

The study included 92 stroke patients attended within the RHP program and the patients' matched controls. Patients in the intervention group received domiciliary care service, home rehabilitation, and telecare significantly earlier than the matched controls. Within the first two years after the stroke episode, recipients of the RHP program were less frequently institutionalized in a long-term care facility (5 vs 15%). The use of primary care services, non-emergency transport, and telecare services were more frequent in the RHP group.

The authors' analysis shows that an integrated care program can effectively promote and accelerate delivery of key domiciliary care services, reducing institutionalization of stroke patients in the mid-term. The integration of health and social care information allows not only a better coordination among professionals (thus avoiding redundant assessments) but also to monitor health and resource use outcomes of care delivery.

In this work, a microstrip antenna array for wireless power transfer (WPT) application is reported. The proposed 4 × 4 antenna array operating at 16 GHz is designed using a flexible Kapton polyimide substrate for a far-field charging unit (FFCU).

The proposed antenna is designed using the transmission line model on a flexible Kapton polyimide substrate. The finite element method (FEM) is used to perform the full-wave electromagnetic analysis of the proposed design.

The antenna offers −10 dB bandwidth of 240 MHz with beam width and broadside gain found to be 29.4° and 16.38 dB, respectively. Also, a very low cross-polarization level of −34.23 dB is achieved with a radiation efficiency of 36.67%. The array is capable of scanning −15° to +15° in both the elevation and azimuth planes.

The radiation characteristics achieved suggest that the flexible substrate antenna is suitable for wireless charging purposes.

Despite the fact that there being a large literature on simulation, there is as yet no generic paradigm or architecture to develop a three-dimensional (3-D) simulator which depends on autonomous intelligent objects. This has motivated us to introduce a 3-D simulation system based on intelligent objects for Physics Experimentation. We formulated the system’s components as an object-orientation model. So, the entities in every experiment’s work cell are modeled by characterizing their properties and functions into classes and objects of the system hierarchy. Intelligent objects are realized by developing a knowledge base (KB) that captures a set of rules/algorithms that operate on 3-D objects. Rules fall into two categories: action and property rules. In the simulation layer, the student is allowed, by using the virtual system, to stroll throughout the Physics laboratory in light of a walking model. Student gets to a simulation region to do an experiment through the detection of mathematical collision. From software engineering perspective, the proposed system facilitates the Physics experiment through making the specification of its applicable parts more modular and reusable. Moreover, a major pedagogical objective is achieved by permitting the student tuning parameters, fixing component of a device then visualizing outputs. This provides student well interpretation by viewing how distinct parameters affect the outcomes of the experiment. With the objective of student performance measuring, we utilized an exploratory group relying upon pre- and post-testing. The application results demonstrate that the simulator contributes positively to student performance in regard to practical Physics.