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On most e-commerce websites, there are two crucial factors that customers rely on to assess product quality and dependability: customer reviews provided online and related ratings. Reviews offer feedback to customers about the product's merits, reasons for negative reviews, and feelings of satisfaction or dissatisfaction with the provided service. As for ratings, they express customer opinions about the product's quality as numerical values from one to five (one or two for the worst opinion, three for the neutral opinion, and four or five for the best opinion). Usually, the customer reviews may be inconsistent with their relevant ratings; the customer may write the worst review despite providing a four- or five-star rating or write the best review with only a one- or two-star rating. Due to this inconsistency, customers may need help to identify relevant information. Therefore, it is required to develop a model that can classify reviews as either positive or negative, depending on the polarity of thoughts, to demonstrate if there is an inconsistency between customer reviews and their actual ratings by comparing them with the ratings resulting from the model. This paper proposes an efficient deep learning (DL) model for classifying customer reviews and assessing whether there is inconsistency. The recommended model's performance and stability are examined on a large dataset of product reviews from Amazon e-commerce. The experimental findings showed that the proposed model dominates and significantly outperforms its peers regarding prediction accuracy and other performance measures. [ABSTRACT FROM AUTHOR]

This critical policy discourse analysis examines how No Excuses charter schools communicate their school goals and environments, and how they represent and portray their current and prospective students in online materials. We also aim to understand how the No Excuses paradigm has evolved and how, if at all, it is currently represented by these charter networks. We focus on whether and how the discourse in these materials may reflect deficit perspectives or contain language that shapes the construction of students and their families as policy targets, and thus create discourses that may ultimately be harmful to racially-minoritized students. [ABSTRACT FROM AUTHOR]

To improve the effect of web page information extraction, this paper proposes an improved information extraction method of mixed text density grids. Under various power constraints of the relay node itself, this paper proposes a design scheme of joint beamforming and artificial noise based on safety and rate maximisation. Furthermore, with the help of semidefinite relaxation techniques and first‐order approximations, it can be approximated as a semidefinite programming problem that is easy to solve. In addition, this paper uses an iterative algorithm based on a continuous convex approximation to process data to improve the accuracy of web page data extraction. The experimental results show that the information extraction method based on improved mixed text density webpages proposed in this paper has a good information extraction effect. [ABSTRACT FROM AUTHOR]

With the emerging era of E‐commerce and online shopping, people are also in a habit to receive default product recommendations on the web pages that they access. Google is already providing such suggestions. Till now recommendations were made only based on previous sentiments or feedback or ratings, but this research has improved the product recommendation method by including one more parameter for the same. This article represents two parameters for making predictions of product allocation to a new customer. These parameters are ratings given by the existing users for that particular product and the region to which the new customer belongs. Following these parameters, a prediction model and an algorithm, Improved_Collab_Similarity, have been implemented. The dataset has been developed where India as a country along with all its States has been considered for products which are popular for their creation based on regional and ancient skills of the people belonging to that area. Results for the mentioned prediction model have been discussed in this article where generally precision increases with the increase in a number of products but at some points, it does not increase when a smaller number of that product was purchased by the customers. [ABSTRACT FROM AUTHOR]

Background While the number of female plastic surgeons has continued to increase over time, plastic surgery has historically been a male-dominated profession with only 15% of practicing plastic surgeons being female. Microsurgery, as a subspecialty, has been long perceived as an even more male-centric career path. The objective of this study was to determine the representation of females in the subspecialty field of microsurgery and the impact of microsurgical fellowship training. Methods A review of all microsurgery fellowship programs participating in the microsurgery fellowship match from 2010 to 2019 were analyzed. Fellows were identified through fellowship Web site pages or direct contact with fellowship program coordinators and directors. The current type of practice and performance of microsurgery were also identified through a Web search and direct contact with fellowship program coordinators and directors. Results A total of 21 programs and 317 fellows over a 10-year period were analyzed. Over this 10-year period, there was a total of 100 (31.5%) female microsurgery fellows and 217 (68.5%) male microsurgery fellows. There was a small, statistically insignificant increase in the yearly percentage of female microsurgery fellows over this 10-year period with an average yearly increase of 2.7% (p = 0.60; 95% confidence interval: –6.9 to 13.2%). There were significantly fewer females who continued to practice microsurgery compared to males (75 [75.0%] vs. 186 [85.7%], p = 0.02). There was no significant difference in the current practice types (academic, private, and nonacademic hospital) between females and males (p = 0.29). Conclusion Women are underrepresented in the field of microsurgery to a similar extent as they are underrepresented in overall plastic surgery. While there is a small insignificant increase in the number of female microsurgery fellows every year, a significantly smaller proportion of females continue to practice microsurgery compared to males. [ABSTRACT FROM AUTHOR]

Background: This study assesses the quality and readability of Arabic online information about orthodontic pain. With the increasing reliance on the internet for health information, especially among Arabic speakers, it's critical to ensure the accuracy and comprehensiveness of available content. Our methodology involved a systematic search using the Arabic term for (Orthodontic Pain) in Google, Bing, and Yahoo. This search yielded 193,856 results, from which 74 websites were selected based on predefined criteria, excluding duplicates, scientific papers, and non-Arabic content. Materials and methods: For quality assessment, we used the DISCERN instrument, the Journal of the American Medical Association (JAMA) benchmarks, and the Health on the Net (HON) code. Readability was evaluated using the Simplified Measure of Gobbledygook (SMOG), Flesch Reading Ease Score (FRES), and Flesch-Kincaid Grade Level (FKGL) scores. Results: Results indicated that none of the websites received the HONcode seal. The DISCERN assessment showed median total scores of 14.96 (± 5.65), with low overall quality ratings. In JAMA benchmarks, currency was the most achieved aspect, observed in 45 websites (60.81%), but none met all four criteria simultaneously. Readability scores suggested that the content was generally understandable, with a median FKGL score of 6.98 and a median SMOG score of 3.98, indicating middle school-level readability. Conclusion: This study reveals a significant gap in the quality of Arabic online resources on orthodontic pain, highlighting the need for improved standards and reliability. Most websites failed to meet established quality criteria, underscoring the necessity for more accurate and trustworthy health information for Arabic-speaking patients. [ABSTRACT FROM AUTHOR]

Background: With the increasing popularity of the internet, a growing number of patients and their companions are actively seeking health-related information online. Objective: The aim of this study was to assess the quality and readability of online information about Alzheimer's disease (AD) in China. Methods: A total of 263 qualified AD-related web pages from different businesses, governments, and hospitals were obtained. The quality of the web pages was assessed using the DISCERN tool, and the readability of the web pages was assessed using a readability measurement website suitable for the Chinese language. The differences in readability and quality between different types of web pages were investigated, and the correlation between quality and readability was analyzed. Results: The mean overall DISCERN score was 40.93±7.5. The government group scored significantly higher than the commercial and hospital groups. The mean readability score was 12.74±1.27, and the commercial group had the lowest readability score. There was a positive correlation between DISCERN scores and readability scores. Conclusions: This study presents an evaluation of the quality and readability of health information pertaining to AD in China. The findings indicate that there is a need to enhance the quality and readability of web pages about AD in China. Recommendations for improvement are proposed in light of these findings. [ABSTRACT FROM AUTHOR]

iPhone operating system (iOS) devices utilize binary cookies as a data storage tool, encoding user-specific information within an often-neglected element of smartphone analysis. This binary format contains details such as cookie flags, expiration, and creation dates, domain, and value of the cookie. These data are invaluable for forensic investigations. This study presents a comprehensive methodology to decode and extract valuable data from these files, enhancing the ability to recover user activity information from iOS devices. This paper provides an in-depth forensic investigation into the structure and function of iOS binary cookie files. Our proposed forensic technique includes a combination of reverse engineering and custom-built Python scripts to decode the binary structure. The results of our research demonstrate that these cookie files can reveal an array of important digital traces, including user preferences, visited websites, and timestamps of online activities. It concludes that the forensic analysis of iOS binary cookie files can be a tool for forensic investigators and cybersecurity professionals. In the rapidly evolving domain of digital forensics, this research contributes to our understanding of less-explored data sources within iOS devices and their potential value in investigative contexts. [ABSTRACT FROM AUTHOR]

Background: Tremendous research efforts have been made in the Alzheimer's disease (AD) field to understand the disease etiology, progression and discover treatments for AD. Many mechanistic hypotheses, therapeutic targets and treatment strategies have been proposed in the last few decades. Reviewing previous work and staying current on this ever-growing body of AD publications is an essential yet difficult task for AD researchers. Methods: In this study, we designed and implemented a natural language processing (NLP) pipeline to extract gene-specific neurodegenerative disease (ND) -focused information from the PubMed database. The collected publication information was filtered and cleaned to construct AD-related gene-specific publication profiles. Six categories of AD-related information are extracted from the processed publication data: publication trend by year, dementia type occurrence, brain region occurrence, mouse model information, keywords occurrence, and co-occurring genes. A user-friendly web portal is then developed using Django framework to provide gene query functions and data visualizations for the generalized and summarized publication information. Results: By implementing the NLP pipeline, we extracted gene-specific ND-related publication information from the abstracts of the publications in the PubMed database. The results are summarized and visualized through an interactive web query portal. Multiple visualization windows display the ND publication trends, mouse models used, dementia types, involved brain regions, keywords to major AD-related biological processes, and co-occurring genes. Direct links to PubMed sites are provided for all recorded publications on the query result page of the web portal. Conclusion: The resulting portal is a valuable tool and data source for quick querying and displaying AD publications tailored to users' interested research areas and gene targets, which is especially convenient for users without informatic mining skills. Our study will not only keep AD field researchers updated with the progress of AD research, assist them in conducting preliminary examinations efficiently, but also offers additional support for hypothesis generation and validation which will contribute significantly to the communication, dissemination, and progress of AD research. [ABSTRACT FROM AUTHOR]

Women and underrepresented-in-medicine applicants value a climate for diversity when selecting graduate medical education training programs. Climate may not be accurately represented during virtual recruitment. Optimizing program websites may help overcome this barrier. We reviewed websites for adult infectious disease fellowships that participated in the 2022 National Resident Matching Program for emphasis on diversity, equity, and inclusion (DEI). Fewer than half expressed DEI language in their mission statement or had a dedicated DEI statement or webpage. Programs should consider emphasizing their commitment to DEI prominently on their websites, which may help recruit candidates from diverse backgrounds. [ABSTRACT FROM AUTHOR]

Sustaining grant funded digital humanities websites has become a major challenge in the field. Three American universities with digital humanities centers kept eight of nine websites funded by the United States National Endowment for the Humanities (1996–2003) online to 2022. Center personnel made website preservation a part of everyday operations without additional funds devoted to the task. Web software developed rapidly in this period, however and center staff members' efforts often did not succeed in providing necessary updates. Funded materials became increasingly obsolete. The extent of center personnel's efforts, compared with their results, suggests that their approach itself will in many cases prove unsustainable. In one case, a university shifted responsibility for a popular website to its library. The library completely rebuilt it, only to find that the resource had again become obsolete less than 10 years later. Reconstruction should therefore be understood as an ongoing process, and its cost and complexity suggest that many online resources will not benefit from it. A new approach converting websites to a static state can facilitate sustainability at lower cost, but it also requires resources for implementation. Two American funding agencies have recently made grants available for website preservation and reconstruction. Similar organizations in other parts of the world have not followed suit and should consider doing so. In the absence of a comprehensive effort to identify and evaluate legacy websites for preservation, the competitive process of securing grant awards can begin to determine which legacy websites will survive. [ABSTRACT FROM AUTHOR]

Factors, such as whether a website is designed to be user-oriented beyond its mere visual design, its effectiveness and efficiency, its usability, and the organisation of the information it offers, have come to the fore once again after the Covid-19 pandemic. It has been evident that the link structure in a website, better known as the website's information architecture, helps the practitioners with identifying factors that affect the usability of a website. In this sense, practitioners must ensure that the information architecture supports the usage intentions of a websites' visitors to better serve and motivate them. However, in many cases, different types of users navigate websites that contain immense amounts of information, so understanding their needs is also important for practitioners. In parallel, this article addresses the problem that different visitors of a large-scale website will need to navigate through dense information to find the information they are looking for, and the information architecture of the website must support different user tasks for the website to be widely adopted. Thus, unlike previous studies, this article combines the principles of information architecture and the technology acceptance model to investigate the effect of information architecture on visitor's usage intentions. The work also guides practitioners in developing architectural strategies to better enable visitors to fulfil their objectives in the least amount of time. [ABSTRACT FROM AUTHOR]

To assess the web accessibility and readability of patient-oriented educational websites for cataract surgery. Cross-sectional electronic survey. Websites with information dedicated to educating patients about cataract surgery. An incognito search for "cataract surgery" was performed using a popular search engine. The top 100 patient-oriented cataract surgery websites that came up were included and categorized as institutional, private practice, or medical organization according to authorship. Each site was assessed for readability using 4 standardized reading grade–level formulas. Accessibility was assessed through multilingual availability, accessibility menu availability, complementary educational video availability, and conformance and adherence to the Web Content Accessibility Guidelines (WCAG) 2.0. A standard t test and chi-square analysis were performed to assess the significance of differences with regard to readability and accessibility among the 3 authorship categories. The main outcome measures were the website's average reading grade level, number of accessibility violations, multilingual availability, accessibility menu availability, complementary educational video availability, accessibility conformance level, and violation of the perceivable, operable, understandable, and robust (POUR) principles according to the WCAG 2.0. A total of 32, 55, and 13 sites were affiliated with institutions, private practice, and other medical organizations, respectively. The overall mean reading grade was 11.8 ± 1.6, with higher reading levels observed in private practice websites compared with institutions and medical organizations combined (12.1 vs. 11.4; P = 0.03). Fewer private practice websites had multiple language options compared with institutional and medical organization websites combined (5.5% vs. 20.0%; P = 0.03). More private practice websites had accessibility menus than institutions and medical organizations combined (27.3% vs. 8.9%; P = 0.038). The overall mean number of WCAG 2.0 POUR principle violations was 17.1 ± 23.1 with no significant difference among groups. Eighty-five percent of websites violated the perceivable principle. Available patient-oriented online information for cataract surgery may not be comprehensible to the general public. Readability and accessibility aspects should be considered when designing these resources. The author(s) have no proprietary or commercial interest in any materials discussed in this article. [ABSTRACT FROM AUTHOR]

Phishing, a well-known cyberattack that cannot be completely eradicated from the Internet, has increased dramatically since the COVID-19 pandemic. Despite previous efforts to reduce this prevalent Internet threat, constantly changing attacks make phishing detection a difficult task. The lack of continuous learning support provided by existing solutions and the lack of a systematic knowledge acquisition process make its detection more difficult. SmartiPhish is introduced in this context as the first anti-phishing solution with integrated continuous learning support with an innovative knowledge acquisition process. SmartiPhish combines deep learning and reinforcement learning to have a successful phishing detection solution. The deep learning model predicts a phishing probability for a given web page based on the URL and HTML content, and the probability is then passed to a reinforcement learning environment to make a decision based on the popularity of the web page and prior knowledge of it. SmartiPhish has a detection accuracy of 96.40% and a detection time of 4.3 s. SmartiPhish performs well in an imbalanced environment, and zero-day attack detection is also interesting. Furthermore, SmartiPhish demonstrated a 5.65% performance improvement in just six weeks, in contrast to the existing anti-phishing tools' declining performance trend over time. [ABSTRACT FROM AUTHOR]

Hospitals use different technological tools to implement corporate communication initiatives and, in this way, improve their relationships with stakeholders (employees, patients, media companies) and build a reputed brand. However, they face different barriers: limited budgets for corporate communication, strict legal frameworks, and stakeholders’ new needs regarding information and emotional support. This paper aims to analyze how the 100 best hospitals in the United States manage smart technologies to promote their brand. To do that, we conducted a literature review about smart hospitals, branding, and corporate communication; and then we defined 34 quantitative indicators to evaluate how the hospitals previously mentioned managed their websites, online newsrooms, about us sections, and artificial intelligence department web sites for reputation purposes. Our results proved that most hospitals respected indicators related to the homepage (8.67/11) but not those referring to online newsrooms (4.44/11) or about us sections (2.66/6). Besides, only 23 hospitals had implemented a department specialized in artificial intelligence that collaborated with external organizations. We concluded that most American hospitals focused their reputation efforts on patients rather than other targets (media companies, employees, suppliers, shareholders); and that these organizations did not integrate enough artificial intelligence projects into their smart branding initiatives. [ABSTRACT FROM AUTHOR]

This article delves into local public diplomacy from the perspective of climate action. A cross-sectional analysis is made of the climate perspective in the international 2030 Sustainable Development Agenda, considering the social, political, and economic challenges implied by human alteration of the environment. The websites of local municipal corporations in Portugal are analysed to identify the information referring to Agenda 2030 and its convergence in climate action. To this end, a content analysis method was designed based on the relationship of the Agenda’s sustainable development goals (SDGs) with their associated climate change goals. Attention is paid primarily to the websites’ fixed sections, and secondarily to their informational content and external portals. The method is applied to the websites of seven of Portugal’s municipalities. Conclusions are drawn concerning whether or not they provide information on climate change so that the effort directed by these local governments towards climate action can be determined. A comparison is made with the international case. This tool contributes to localizing the SDGs and prioritizing environmentally important components. [ABSTRACT FROM AUTHOR]

The internet holds a significant role in all aspects of our lives, and its importance continues to grow each day. Therefore, the usability of the Internet holds great significance. Low data quality and disinformation severely impact the usability of the internet. Consequently, people face challenges in obtaining accurate and clear information. In the present day, websites predominantly feature image-based content like pictures and videos, as opposed to text-based content. The classification of such content holds immense importance for search engines. As a result, the classification of web pages stands as a crucial research area for scholars. This study focuses on the classification of image-based web pages. A deep learning-based approach is proposed to categorize web pages into four main groups: tourism, machinery, music, and sports. The suggested method yielded the most favourable outcomes when utilizing the Stochastic Gradient Descent (SGD) optimization method, achieving an accuracy of 0.9737, a recall of0.9474, an Fl score of 0.9474, and an Area Under the ROC Curve (AUC) value of 0.9649. Furthermore, the utilization of Deep Learning (DL) led to achieving the most advanced results in web page classification within the existing literature, particularly on the WebScreenshots dataset. [ABSTRACT FROM AUTHOR]

In the current landscape, product prices exhibit significant variations across diverse ecommerce platforms. Numerous price comparison websites have emerged to aid users in finding their desired products at the best prices. However, these systems face challenges such as irrelevant search results, outdated product prices, and accuracy issues. This study seeks to address these challenges by developing a user-friendly system. Our system comprises two components. JSoup is employed for data collection, while TF-IDF, SVD, and Cosine Similarity are integrated for product offerings. The proposed platform gathers data from reputable retailers, analyzes it to extract product information, and presents the findings to consumers. We evaluated the system's performance using real data obtained from various marketplaces. The results demonstrate that our system achieved an acceptable accuracy rate when compared to similar industrial solutions and relevant literature. Consequently, users are empowered to make more informed purchasing decisions, leveraging the capabilities provided by the proposed system. [ABSTRACT FROM AUTHOR]

This article presents a pilot study in agentive modeling, a mixed-methods approach for visualizing networked models of agency. The study assesses technical and public seismic risk visuals from the websites of key organizations concerned with seismic activity. Preliminary findings indicate the need for visuals that stage more complex networks in order to create greater opportunities for engagement and danger-reducing action. [ABSTRACT FROM AUTHOR]

Background: Previous studies have suggested that information offered by sellers of health-related direct-to-consumer genetic tests (DTC-GTs) is often incomplete, unbalanced, or too difficult to understand. The extent to which this is the case for sellers accessible to Dutch consumers has not previously been studied. Methods and Goals: The present study aimed to assess the completeness, balance, readability, and findability of informational content on a selection of websites from several health-related DTC-GT sellers accessible to Dutch consumers. An in-depth content analysis was performed based on a recently published checklist outlining key items for policy guidance regarding DTC-GT services. Results: The information provided by sellers did not equally cover all aspects relevant to health-related DTC-GT service provision. The provided information was slightly unbalanced, with benefits of health-related DTC-GT usage being overemphasized compared to its risks and limitations. The readability of the provided information was low, on average requiring college education for proper understanding. A findability analysis showed that information concerning all themes is overall relatively evenly distributed across analyzed sellers' websites. Conclusions: Information provision by assessed health-related DTC-GT sellers is suboptimal regarding completeness, balance, and readability. To better empower potential consumers to make an informed decision regarding health-related DTC-GT usage, we advocate industry-wide enhancement of information provision. [ABSTRACT FROM AUTHOR]

Geoscientific models have rapidly developed in recent decades as effective tools to understand the past, perceive the present, and predict the future. However, with the increasing number of models available, discovering suitable ones and applying them properly in problem‐solving situations has become more challenging. Existing materials describing geoscientific models (e.g., articles, manuals, handbooks, metadata documents, and web pages) are scattered and varied in structure and content. To help model users from different disciplinary backgrounds find, access, implement, and reuse models more conveniently, we propose an open knowledge framework for geoscientific models. The knowledge framework includes three levels: a resource level for indicating where to find a model, a connection level for indicating what materials are related to a model, and an application level for indicating how the model is applied. Through such a three‐level framework, model users can collaboratively provide descriptive information for a model, link different materials to a model (e.g., data, references, and tools), and contribute experiences regarding model application in practical cases (as reusable solutions). Thus, a web‐based community can be formed to facilitate the better use of geoscientific models. This article introduces the Open Geographic Modeling and Simulation System (OpenGMS) as the implementation of this open knowledge framework. Case studies are given to showcase the effectiveness and capability of the proposed framework. [ABSTRACT FROM AUTHOR]

An online survey (N = 561) tested perceptions of the personalization of online political news. A third-person effect emerged: respondents believed others would be more affected by political news personalization than themselves. Those who thought others would be more affected were also more likely to support restrictions on websites' use of audience data to personalize news. Narcissism was a significant moderator of the relationship between the third person differential and support for restrictions on data collection. [ABSTRACT FROM AUTHOR]

Given Wikipedia's breadth of coverage, social impact, and longevity as an impactful open knowledge resource, the encyclopedia has been the subject of considerable interdisciplinary research. Building on scholarship related to collaboration, authorship, ownership, and editing in Wikipedia, this study sought to better understand Wikipedians as writers, paying specific attention to their sense of ownership. While previous research has shown that editors engage in individualist editing practices at times, often ignoring community-mediated policy regarding ownership, findings from a mixed-method survey of 117 editors demonstrate the existence of both "individual" and "community" notions of ownership that often reinforce, or mutually inform, each other. This study adds clarity to these issues by demonstrating how feelings of individual ownership, voice, and pride in writing often occur in collaborative circumstances. This research ultimately extends our understanding of collaborative writing in what is one of the most well-known collaborative websites. Despite contemporary theoretical strides advocating for relinquishing ownership concepts in favor of distributed or ecological frameworks, the concept of ownership remains prevalent within digital writing communities, exemplified by Wikipedia. [ABSTRACT FROM AUTHOR]

How long indoor sex workers stay employed in collectives is a poorly understood aspect of sex worker agency in industrialized democracies. This study provides estimates of turnover, the rate at which workers leave employment, using a subsample of 76 collectives representing 3545 workers over a one-year period. All the collectives provided data on individual workers via external websites. The collectives were identified in a larger random sample of 783 advertisers from a popular Canadian classifieds site used by sex workers, all of whom provided URLs as part of their ad contact information. Monthly between October 2022 and October 2023, individual workers associated with the subsample of advertisers were identified from web pages maintained by these advertisers and scheduling data was collected where available. Worker turnover was estimated based on whether workers were visible one month to the next. Over the year, estimated turnover ranged from 12.0% to 16.0% (mean 14.2% SD 1.1%). Turnover was not affected by month or number of workers in the collectives. Mean 41.1% workers (SD 23.5%, N = 51 advertisers) were scheduled on any given day. Workers were visible for a mean 5.5 months (SD 4.5) with those visible for one month being the largest single group. Most sex workers in collectives are likely not permanent full time employees, and the extremely brief work histories of many suggest that failure in the industry may be common for this subpopulation. [ABSTRACT FROM AUTHOR]

In this digital era, there is a tremendous increase in the volume of data, which adds difficulties to the person who utilizes particular applications, such as websites, email, and news. Text summarization targets to reduce the complexity of obtaining statistics from the websites as it compresses the textual document to a short summary without affecting the relevant information. The crucial step in multi-document summarization is obtaining a relationship between the cross-sentence. However, the conventional methods fail to determine the inter-sentence relationship, especially in long documents. This research develops a graph-based neural network to attain an inter-sentence relationship. The significant step in the proposed multi-document text summarization model is forming the weighted graph embedding features. Furthermore, the weighted graph embedding features are utilized to evaluate the relationship between the document's words and sentences. Finally, the bidirectional long short-term memory (BiLSTM) classifier is utilized to summarize the multi-document text summarization. The experimental analysis uses the three standard datasets, the Daily Mail dataset, Document Understanding Conference (DUC) 2002, and Document Understanding Conference (DUC) 2004 dataset. The experimental outcome demonstrates that the proposed weighted graph embedding feature + BiLSTM model exceeds all the conventional methods with Precision, Recall, and F1 score of 0.5352, 0.6296, and 0.5429, respectively. [ABSTRACT FROM AUTHOR]

Website localization plays an important role in guiding firms on how to customize websites across countries in which they have a local presence. However, few studies on website localization have systematically examined this topic from a theoretically grounded perspective. Drawing upon the theoretically driven consumer-company identification perspective, we propose that three website localization strategies (web similarity strategy, web distinctiveness strategy, and web prestige strategy) have positive effects on local users' perceived website localization, which, in turn, is related to local users' website loyalty. We further investigate the effects of these website localization strategies in a cross- cultural setting, focusing on the individualism-collectivism dimension of culture. Based on our online experiments in both the United States and China, we find that these website localization strategies have significant impacts on consumers' perceived website localization, which is related to consumers' website loyalty. We also find that web distinctiveness and web prestige strategies are more effective for people from collectivistic societies than for those from individualistic societies, whereas web similarity strategies do not differ across societal types. These findings highlight the importance of website localization strategies for customizing websites for global e-commerce. [ABSTRACT FROM AUTHOR]

Background: Library websites are important for marketing library services and providing access to electronic resources. Objectives: To determine the extent and quality of medical college (school) library websites in Pakistan, according to predetermined criteria. Methods: A checklist of 40 items was developed from the literature on academic library website evaluation as well as observation of known best practice. The checklist was used on the 45 medical college websites that fitted initial inclusion criteria. Results: Of the possible 114 candidates for inclusion, 52 institution websites contained no information about the library, 17 only provided minimum details, leaving 45 medical college library websites that could be included. Library websites lack uniformity, and most of the important features as only three library websites contained more than 20 items from the checklist. The Agha Khan University Medical College, Karachi library website contained the highest (27) number of items. Discussion: The findings indicate the design of medical college library websites is generally inadequate in Pakistan. The websites are not performing a useful role in communicating with faculty and students. The findings point to inadequate website design skills among librarians or the lack of co‐operation with professional website designers. Conclusions: Marketing of library services and good customer relations demand improvements in the information architecture of medical college library websites as well as continued maintenance of the content to ensure that it is up to date. [ABSTRACT FROM AUTHOR]

Nowadays, web applications play central roles in information systems using the Internet. Then, client-side web programming using HTML, CSS, and JavaScript should be mastered first by novice students. Previously, we have presented the element fill-in-blank problem (EFP) for its self-study. An EFP instance requests to fill in the blank elements in the given source code by referring to the screenshots of the corresponding web page. The correctness of any answer is marked through string matching. However, these blanks were manually selected by considering the importance of elements and the uniqueness of their correct answers. In this paper, we propose a blank element selection algorithm to automatically generate a new EFP instance from a given source code for client-side web programming. We define the seven rules on blank element selections from the code, and implement the procedure in Python using the open source BeautifulSoup and regular expressions' ' For evaluations, we applied the algorithm to the 47 source codes used for manual generations and obtained the better EFP instances with more blanks. Besides, we verified the effectiveness by generating 10 new instances with the algorithm and assigning them to 40 students. In addition, we extended its application to three source codes for games and verified the effectiveness by assigning them to 20 students, to further validate the applicability of the algorithm in EFP instance generations. We also evaluated the relationships between the number of blanks, the number of lines in source codes, the submission times and answer rates of students to further assess the adaptability of the algorithm. These results allow us to measure the algorithm's versatility in generating a wide range of EFP instances and contributes to comprehensive understanding of instance difficulties and learning outcomes. [ABSTRACT FROM AUTHOR]

Web archives capture, retain, and present historical versions of web pages. Viewing web archives often amounts to a user visiting the Wayback Machine homepage, typing in a URL, then choosing a date and time significant of the capture. Other web archives also capture the web and use Memento as an interoperable point of querying their captures. Memento aggregators are web accessible software packages that allow clients to send requests for past web pages to a single endpoint source that then relays that request to a set of web archives. Though few deployed aggregator instances exist that exhibit this aggregation trait, they all, for the most part, align to a model of serving a request for a URI of an original resource (URI-R) to a client by first querying then aggregating the results of the responses from a collection of web archives. This single tier querying need not be the logical flow of an aggregator, so long as a user can still utilize the aggregator from a single URL. In this paper, we discuss theoretical aggregation models of web archives. We first describe the status quo as the conventional behavior exhibited by an aggregator. We then build on prior work to describe a multi-tiered, structured querying model that may be exhibited by an aggregator. We highlight some potential issues and high-level optimization to ensure efficient aggregation while also extending on the state-of-the-art of memento aggregation. Part of our contribution is the extension of an open-source, user-deployable Memento aggregator to exhibit the capability described in this paper. We also extend a browser extension that typically consults an aggregator to have the ability to aggregate itself rather than needing to consult an external service. A purely client-side, browser-based Memento aggregator is novel to this work. [ABSTRACT FROM AUTHOR]

This study explores the intermedia agenda-setting of the U.S. gun control movement in 2018, with a specific focus on the role of activism/advocacy media and ephemeral websites in shaping the movement discourse in news outlets. Structural topic modeling and cross-lagged correlation analyses of the Facebook URLs Share dataset show that activism/advocacy media played an important role in proposing unique agendas and aligning them with other news outlets. Meanwhile, ephemeral websites were prone to containing conspiratorial information, which could have been purposive to influence the movement. The study provides empirical insights into how various media actors interact to shape social movement discourses. [ABSTRACT FROM AUTHOR]

Doctoral education in Europe has changed significantly in the last two to three decades. This transformation, visible in the structuring dimensions of doctoral education, appears to indicate a move to a more instrumental approach. This paper aims to determine the prevalence of an instrumental concept of doctoral education in Portuguese universities. It draws on the findings of a 2020 study that focused on how these institutions are adhering to this concept. The study relied on the analysis of the information disclosed by the institutional websites of 118 doctoral programmes, selected to be representative of all the doctoral offer in the country. Findings suggest the existence of a hybrid concept of doctoral education among Portuguese universities, which is revealed by its association sometimes with a traditional concept, other times with an instrumental concept, or with a combination of both. Especially in these two last cases, the influence of academic capitalism and isomorphic pressures is evident. [ABSTRACT FROM AUTHOR]

An attempt was made to assess the quality of the International Data Centre (IDC) Reviewed Event Bulletin (REB) by comparing it with the Reviewed bulletin of the International Seismological Centre (ISC). To accomplish the task of comparison, the ISC Reviewed Bulletin events as downloaded from the ISC Web page for the month of October 2020 were used. The corresponding REB events as listed in the ISC bulletin were considered. During this period, a total of 3431 and 2652 (excluding 39 Infrasound events) events were considered for ISC and IDC bulletins, respectively. The comparison was performed using the information given in the header lines of the ISC bulletin from which matched and unmatched events could be extracted. The results showed that a total of 2315 events could be matched between the two bulletins. The percentage of matched events with relative location difference (D) < 1° was about 95.3% while the percentage of events with D ≥ 5o was about 0.35%. There were two potential events with IDC magnitude (mb) ≥ 4.0 and D ≥ 5°. The percentage of matched events with intersecting error ellipses was about 75.5%. Some results obtained from earlier studies which were produced by using similar approaches were also used in this study. In general, the results obtained in this study show that there was a slight difference when compared to the earlier comparison results. [ABSTRACT FROM AUTHOR]

Summary Shu is a visualization tool that integrates diverse data types into a metabolic map, with a focus on supporting multiple conditions and visualizing distributions. The goal is to provide a unified platform for handling the growing volume of multi-omics data, leveraging the metabolic maps developed by the metabolic modeling community. In addition, shu offers a streamlined python API, based on the Grammar of Graphics, for easy integration with data pipelines. Availability and implementation Freely available at https://github.com/biosustain/shu under MIT/Apache 2.0 license. Binaries are available in the release page of the repository and the web application is deployed at https://biosustain.github.io/shu. [ABSTRACT FROM AUTHOR]

The evolution of Internet technology has led to an increase in online users. This study focuses on the pivotal role of visual elements in web content conveyance and their impact on user browsing behavior. Therefore, the use of visual elements in web design based on big data has aroused widespread concern among web designers, they apply visual elements to their web design works to make the web more attractive. This study examines the composition and distribution characteristics of key visual elements identified through user behavior data in a big data environment and discusses the use of visual elements in web design in the era of network economy. In addition, this paper issued 200 questionnaires to investigate the degree of attention to visual elements in web pages for users of different occupations and different educational backgrounds. Our survey indicated that visual elements captured the attention of 41% of corporate employees, whereas a mere 1% of social welfare workers focused on web content; 36% of undergraduates pay attention to visual elements of web pages, but only 5% and 4% of postgraduates and doctoral degrees and above. Therefore, the visual elements of the designed web page need to conform to the user's cultural background and professional background. [ABSTRACT FROM AUTHOR]

Objectives: Due to the limitations of the Coronavirus disease pandemic, medical applicants have relied on remote means of information, such as a program's website, to decide where to apply. However, studies have shown that many residency and fellowship websites lack information. Vascular neurology fellowship websites have not yet been studied. This study evaluates the availability and accessibility of information on vascular neurology fellowship websites. Methods: From 2021 to 2022, a total of 109 U.S. vascular neurology fellowship programs from the Fellowship and Residency Electronic Interactive Database were investigated to determine whether they had websites. Each website was evaluated on the immediate availability of 34 different criteria, which were deemed important by past studies. These criteria were reviewed under four categories: program overview, application information, fellow life, and curriculum. The comprehensiveness of the information among these different categories were analyzed. Programs were grouped by geographic region and electronic residency application service (ERAS)-participation status and comparisons were made within these groups. Results: There were 107 programs with websites (98%). ERAS-participating programs fulfilled more criteria on average than non-participating programs (P = 0.004). All websites provided information on general descriptions of their programs, but information on board exam pass rates, fellow testimonials, history of the fellowship program, responsibility progression, family and social events, parking availability, and application deadline were provided by less than 25% of websites. Conclusion: This study found that there was a large lack of information on vascular neurology fellowship websites, which could be improved to attract more applicants. [ABSTRACT FROM AUTHOR]

We examined how four hunting organizations in Finland and in the UK (The Finnish Wildlife Agency, Finnish Hunters' Association, The British Association for Shooting and Conservation, and Countryside Alliance) describe wild animals on their web pages and what the moral implications of these descriptions are. How do these hunting organizations define animals, and how does this impact the moral regard given to these animals? Using discourse analysis together with philosophical analysis, our examination revealed that the descriptions focus mainly on physical attributes, leaving out the minds of animals. Therefore, hunting organizations take part in dementalization (underestimation or denial of minds) of nonhuman animals, which interlinks with mechanomorphism (the depiction of animals as biological machines). We argue that dementalization and mechanomorphism in the descriptions serve a strategic purpose, as they hinder the possibility of recognizing animal experiences and individuality and keep animal ethical questions out of view. Further, the organizations tend to approach the ethics of hunting through the perspective of human interests only, whilst the interests and inherent value of animals are sidelined. In sum, the way in which hunting organizations depict animals is prone to sidelining ethical issues concerning the killing of animals. [ABSTRACT FROM AUTHOR]

Radionuclide-based diagnostics and therapy require proper selection of production nuclear reaction based on knowledge of the production excitation functions and the achievable yields completed with data on the formation of possible impurities. In the present work the existing IAEA recommended cross section data database for production of therapeutic isotopes is extended to production of the 47Sc,47Ca(47Sc), 58mCo, 71As(71Ge), 71Ge, 77Br, 77Kr(77Br), 80mBr, 103Pd, 103Pd(103mRh), 103Ru(103mRh), 105Rh, 117mSn, 119Sb, 119mTe(119Sb), 134Ce, 135La, 149gTb, 161Tb, 165Er, 165Tm(165Er), 167Tm, 197mHg, 197gHg, 198gAu, and 230Pa(230U) radioisotopes. Nearly 60 nuclear reactions are presented and discussed. The new recommended cross-section data and their uncertainties for the production of these 21 radionuclides will be available on the Web page of the IAEA Nuclear Data Section at https://nds.iaea.org/radionuclides and also at the IAEA medical portal https://nds.iaea.org/medportal. [ABSTRACT FROM AUTHOR]

Context: Strandings are an important source of information for estimating marine mammal biodiversity, particularly in data-sparse ocean basins such as Oceania. Aims: Here, we report on knowledge acquired from 218 stranding events recorded in the waters of New Caledonia (1877–2022). Methods: We investigated spatio-temporal distribution, stable isotope signatures, trace element concentrations, biometry measurements, genetic diversity, and diet, for the four most commonly stranded taxa (dugongs, 35% of events; sperm whales, 19%; Delphinidae, 18%; pygmy and dwarf sperm whales, 14%). Key results: Beginning in 1991, reports of stranding events increased (183 events, 322 individuals, 20 species from seven families: Dugongidae, Physeteridae, Delphinidae, Kogiidae, Ziphiidae, Balaenopteridae, Otariidae), with hotspots identified on the west coast (Bourail, Ouano, Nouméa) and in Prony Bay. Causes of death were not determined in 84% of stranding events, but were identified in the majority of expert-led necropsies (24 of 29 individuals from 10 species). Yet, valuable information regarding the impact of anthropogenic activities was gathered for some species of concern, such as the endangered dugong (28% human-caused). Since 2016, training and outreach have been provided to rangers, veterinarians, and various public safety officers to support their engagement in the scientific monitoring of marine mammal strandings. A website (www.rescue.ird.nc) was developed to facilitate standardised data collection and storage, and to provide public access to stranding records. Conclusion: Although the number of individuals reported here remains modest, this study provides new information on poorly documented species in New Caledonia. Implications: Long-term monitoring of strandings can help design effective conservation measures. RESUME: Contexte: Les échouages constituent une source d'informations importante pour estimer la biodiversité des mammifères marins, en particulier dans les bassins océaniques pour lesquels les données sont rares, comme l'Océanie Objectif: Nous présentons ici les connaissances acquises à partir de 218 échouages enregistrés dans les eaux de Nouvelle-Calédonie (1877–2022). Méthodes: Nous avons étudié la distribution spatio-temporelle, les signatures isotopiques, les éléments traces, les mesures biométriques, la diversité génétique et le régime alimentaire des quatre taxons les plus fréquemment échoués (dugongs, 35% des échouages; cachalots, 19%; Delphinidae, 18% ; cachalots pygmées et nains, 14%). Principaux résultats: À partir de 1991, les signalements d'échouages ont augmenté (183 événements, 322 individus, 20 espèces de sept familles: Dugongidae, Physeteridae, Delphinidae, Kogiidae, Ziphiidae, Balaenopteridae, Otariidae), avec des points chauds identifiés sur la côte ouest de la Grande Terre (Bourail, Ouano, Nouméa) et dans la Baie de Prony. Les causes de décès n'ont pas été déterminées pour 84% des échouages, mais elles ont été identifiées dans la majorité des autopsies réalisées par des vétérinaires (24 des 29 individus de 10 espèces). Des informations précieuses concernant l'impact des activités anthropiques ont été recueillies pour certaines espèces préoccupantes, telles que le dugong, une espèce en voie de disparition (28% des échouages d'origine humaine). Depuis 2016, des formations et des activités de sensibilisation ont été dispensées aux gardes nature, aux vétérinaires et à divers agents publics pour soutenir leur engagement dans la surveillance scientifique des échouages de mammifères marins. Un site Web (www.rescue.ird.nc) a été développé pour faciliter la collecte et le stockage de données standardisées et pour fournir un accès public aux enregistrements d'échouages. Conclusion: Bien que le nombre d'individus signalés échoués ici reste modeste, cette étude apporte de nouvelles informations sur des espèces peu documentées en Nouvelle-Calédonie. Implications: La surveillance à long terme des échouages peut aider à concevoir des mesures de conservation efficaces. Map of strandings in New Caledonia; people gathered around a stranded whale; four commonly stranded species. Conservation of marine mammals in Oceania is limited by a lack of understanding of these relatively rare, yet emblematic species. Here, we report on significant biological and ecological data acquired from several decades of monitoring strandings in New Caledonia. This increased knowledge may help guide management measures locally and regionally. Photograph by Marine Mammal Stranding Center. This article belongs to the Collection Marine Mammals in the Pacific. [ABSTRACT FROM AUTHOR]

In this article, the website infrastructures of both pro science climate change and climate denier websites are examined. The focus is on the backstage of the website, defined as the use of widgets, ad trackers, beacons, and analytics and not the website content, or what might be described as the front stage. This research addresses questions about the presence and use of trackers within the commodification of user attention, the audience economy. The study concludes that organizations on both sides of the climate issue use similar strategies in monetizing their websites and tracking user behavior. Moreover, the infrastructure that is created among the platforms reflects the major role that big tech plays in developing an interconnected web of tracker technologies. While website transparency may remain an ideal, the study advocates for a responsible approach to website development, one that acknowledges the complexity of the issue within a stronger regulatory environment. [ABSTRACT FROM AUTHOR]