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Objectives: To describe the clinical presentation, treatment and outcomes of cats diagnosed with thymic epithelial tumours and to determine prognostic factors for survival and recurrence. Materials and Methods: Clinical records of cats diagnosed with a thymic epithelial tumour between 1999 and 2021 at three referral institutions were retrospectively reviewed. Results: Sixty‐four cats were included. Paraneoplastic syndromes were present in nine cats and metastatic disease was seen in two cats, one at diagnosis and one at the time of recurrence. Median tumour diameter was 6 cm (range, 2 to 15) and a cystic appearance was described on imaging in 25 cats. Surgical excision was attempted in 54 cats with a perioperative mortality rate of 11%. Median survival time for cats surviving to hospital discharge was 897 days (range, 21 to 3322). The 1‐, 2‐ and 5‐year survival rates for surgically treated thymic epithelial tumour were 86%, 70% and 66%, respectively. Survival was longer for cats with Masaoka‐Koga stage I and II tumours compared to stages III and IV (1366 days versus 454 days; P=0.002). Masaoka‐Koga stage was the only significant prognostic factor detected on multi‐variable analysis, with stage III and IV tumours associated with increased risk of death (hazard ratio: 5.67, 95% confidence interval: 1.29 to 24.91, P=.021). Tumour recurrence occurred in 11 cats at a median of 564 days (range, 93 to 1095); no significant prognostic factors for recurrence were identified. Clinical Significance: Cats with thymic epithelial tumours had a good long‐term prognosis following surgery. Tumour recurrence can occur late in the disease course and ongoing monitoring should therefore be considered. Masaoka‐Koga stage may influence survival time and could be used to predict outcome. [ABSTRACT FROM AUTHOR]

The amount of data related to cyber threats and cyber attack incidents is rapidly increasing. The extracted information can provide security analysts with useful Cyber Threat Intelligence (CTI) to enhance their decision-making. However, because the data sources are heterogeneous, there is a lack of common representation of information, rendering the analysis of CTI complicated. With this work, we aim to review ongoing research on the use of semantic web tools such as ontologies and Knowledge Graphs (KGs) within the CTI domain. Ontologies and KGs can effectively represent information in a common and structured schema, enhancing interoperability among the Security Operation Centers (SOCs) and the stakeholders on the field of cybersecurity. When fused with Machine Learning (ML) and Deep Learning (DL) algorithms, the constructed ontologies and KGs can be augmented with new information and advanced inference capabilities, facilitating the discovery of previously unknown CTI. This systematic review highlights the advancements of this field over the past and ongoing decade and provides future research directions.

The aim of this study is to investigate how amplifiers are used in Twitter (now called “X”) during election campaigns. Specifically, the main purpose is to identify the role and engagement of Twitter amplifiers in the 2019 European elections, the visibility of political parties and leaders, and the way in which automated tools are used to manipulate public opinion by influencing voting decisions. The countries considered in the study are two economic powers of Western Europe, France and Germany, as well as two countries of the European South, which are affected by the economic and financial crisis, Greece and Italy. The countries from Southern Europe were included in the sample as they are often used by mass media as political campaign tools. This paper emphasizes the Twitter platform through which the data collection was implemented using the official API of the social networking tool, focusing on the 2019 European elections. We collected data on 88 party leaders and MEP candidates between 10 May and 30 May 2019, as well as on 44,651 accounts that retweeted them. We concluded using 237,813 election-related tweets and used network theory to analyze and visualize the data. The results demonstrate that all political parties use amplifiers to promote their tweets, and some use the same amplifiers between different countries.

The systematic coverage of the coronavirus pandemic by the Greek mass media began in February 2020, specifically, from the time the virus made its appearance in the most significant way in Italy. Until then, news about the virus had been sporadically visible depending mainly on news reports coming from the international media and press agencies. The assessment of the COVID-19 pandemic as an “infodemic” by the World Health Organization (WHO) made obvious the need to study media coverage and map its patterns, along with the unprecedented political and social response and the massive consequences on the global economy. Through a large content analysis, containing 7457 news items from 13 different media outlets, plus a comparative Twitter analysis of 36,317 tweets, we took the present situation as an opportunity to collect real-time data but also as a point of departure for addressing issues connected to journalistic practices and technological changes in the framework of COVID-19. According to our findings, the Greek media faced the crisis “with a view to the world”, emphasizing international coverage, giving priority to the authorities and scientists, and keeping (at least in their majority) hoaxes and conspiracy theories out of the agenda.

The present paper focuses on adaptive audio detection, segmentation and classification techniques in audio broadcasting content, dedicated mainly to voice data. The suggested framework addresses a real case scenario encountered in media services and especially radio streams, aiming to fulfill diverse (semi-) automated indexing/annotation and management necessities. In this context, aggregated radio content is collected, featuring small input datasets, which are utilized for adaptive classification experiments, without searching, at this point, for a generic pattern recognition solution. Hierarchical and hybrid taxonomies are proposed, firstly to discriminate voice data in radio streams and thereafter to detect single speaker voices, and when this is the case, the experiments proceed into a final layer of gender classification. It is worth mentioning that stand-alone and combined supervised and clustering techniques are tested along with multivariate window tuning, towards the extraction of meaningful results based on overall and partial performance rates. Furthermore, the current work via data augmentation mechanisms contributes to the formulation of a dynamic Generic Audio Classification Repository to be subjected, in the future, to adaptive multilabel experimentation with more sophisticated techniques, such as deep architectures.

Social media platforms have led to the creation of a vast amount of information produced by users and published publicly, facilitating participation in the public sphere, but also giving the opportunity for certain users to publish hateful content. This content mainly involves offensive/discriminative speech towards social groups or individuals (based on racial, religious, gender or other characteristics) and could possibly lead into subsequent hate actions/crimes due to persistent escalation. Content management and moderation in big data volumes can no longer be supported manually. In the current research, a web framework is presented and evaluated for the collection, analysis, and aggregation of multilingual textual content from various online sources. The framework is designed to address the needs of human users, journalists, academics, and the public to collect and analyze content from social media and the web in Spanish, Italian, Greek, and English, without prior training or a background in Computer Science. The backend functionality provides content collection and monitoring, semantic analysis including hate speech detection and sentiment analysis using machine learning models and rule-based algorithms, storing, querying, and retrieving such content along with the relevant metadata in a database. This functionality is assessed through a graphic user interface that is accessed using a web browser. An evaluation procedure was held through online questionnaires, including journalists and students, proving the feasibility of the use of the proposed framework by non-experts for the defined use-case scenarios.

Objective: The efficacy of renal sympathetic denervation (RDN) has been affirmed by a number of recent clinical studies, despite controversies in this field over the last five years. Therefore, it is of paramount importance that hypertension experts debate the merits of RDN by revealing and expressing their personal beliefs and perspectives regarding this procedure. Methods: A cross-sectional survey was conducted among Greek leaders of the Hypertension Excellence Centers with the use of a closed-type questionnaire specifically designed to elicit information and evaluate the respondent's views and perspectives about RDN efficacy, safety and ideal target patient population. Results: A total of 36 participants completed the survey. Based on the results, RDN was considered efficient (91.7%) and safe (94.5%), while the overwhelming majority of the participants felt confident in the long-term efficacy (88.9%) of the intervention and that it lacks reliable predictors of blood pressure response (94.5%). Patients with resistant (91.7%), ultra-resistant (94.4%), and uncontrolled hypertension (80.6%) were suggested as ideal candidates for RDN. Establishing a close co-operation between interventionalists and hypertension experts was considered essential to ensure the efficacy (97.2%) as well as the safety (97.3%) of the procedure. Conclusion: The vast majority of Greek hypertension experts surveyed were convinced of the efficacy and safety of RDN based on the preponderance of available scientific and clinical data. Identification of the ideal patient group remains controversial. Respondents generally agreed on the necessity of building close collaborative relationships between interventionalists and hypertension experts in order to improve RDN clinical outcome.

In this article, the quality of media studies education through effective teaching utilizing audiovisual media technologies and audiovisual content (audiovisual media communications) to budding journalists as adult learners (18 years and older) is researched, with results primarily intended for application in radio lessons at all educational levels and disciplines (including adult education). Nowadays, audiovisual media communications play an important role in the modern and visual-centric way of our life, while they require all of us to possess multiple-multimodal skills to have a successful professional practice and career, and especially those who study media studies, such as tomorrow’s new journalists. Data were collected after three interactive teachings with emphasis on educational effectiveness in technology-enhanced learning, through a specially designed written questionnaire with a qualitative and quantitative form (evaluation form), as case study experiments that applied qualitative action research with quasi-experiments. The results (a) confirmed (i) the theory of audiovisual media in education, as well as (ii) the genealogical characteristics and habits of budding journalists as highlighted in basic generational theory, something which appears to be in agreement with findings of previous studies and research; and (b) showed that (i) teaching methodology and educational techniques aimed primarily at adult learners in adult education kept the interest and attention of the budding journalists through the use of such specific educational communication tools as audiovisual media technologies, as well as (ii) sound/audio media, as audiovisual content may hold a significant part in a lecture.

Speech Emotion Recognition (SER) is an important part of Affective Computing and emotionally aware Human–Computer Interaction. Emotional expression may vary depending on the language, culture, and the speaker’s personality and vocal attributes. Speaker-adaptive systems can address this issue. In real-world applications, it is not feasible to obtain big datasets for deep learning model training from a specific speaker. This paper proposes a transfer learning approach for personalized SER based on convolutional neural networks. A CNN is trained in a multi-user dataset for generalization and then is fine-tuned for a small speaker-specific dataset. A VGGish model, pre-trained a large-scale dataset for audio event recognition is also evaluated for the task. This comparison highlights the significance of network capacity, dataset length, and domain-relativity for transfer learning. To enhance the applicability of this approach in real-world conditions, a web crowdsourcing application is implemented. An online platform is provided where contributors can follow a standard procedure to record and submit annotated utterances of emotional speech. The recordings are validated and added to the publicly available AESDD dataset of emotional speech. The platform can be used for the creation of personalized emotional speech datasets for speaker-adaptive SER, following the transfer learning strategies that have been evaluated.

Media authentication relies on the detection of inconsistencies that may indicate malicious editing in audio and video files. Traditionally, authentication processes are performed by forensics professionals using dedicated tools. There is rich research on the automation of this procedure, but the results do not yet guarantee the feasibility of providing automated tools. In the current approach, a computer-supported toolbox is presented, providing online functionality for assisting technically inexperienced users (journalists or the public) to investigate visually the consistency of audio streams. Several algorithms based on previous research have been incorporated on the backend of the proposed system, including a novel CNN model that performs a Signal-to-Reverberation-Ratio (SRR) estimation with a mean square error of 2.9%. The user can access the web application online through a web browser. After providing an audio/video file or a YouTube link, the application returns as output a set of interactive visualizations that can allow the user to investigate the authenticity of the file. The visualizations are generated based on the outcomes of Digital Signal Processing and Machine Learning models. The files are stored in a database, along with their analysis results and annotation. Following a crowdsourcing methodology, users are allowed to contribute by annotating files from the dataset concerning their authenticity. The evaluation version of the web application is publicly available online.

Audiovisual content is highly employed in modern education curricula. This study aimed to identify students’ perceptions regarding the use of video in the courses they attend. Quantitative research was conducted among students of journalism and communication studies. Four courses were used for this study that employ video-based and video-assisted teaching strategies for active learning. Students used videos in different educational settings for flipped learning, blended learning, and autonomous self-paced learning. Their perceptions were examined through an extended form of the Technology Acceptance Model, encompassing more parameters (such as self-efficacy, perceived enjoyment, satisfaction, attitude, and intention of use) to identify causal relationships. In addition, the roles of technical parameters, such as internet connection, audio quality, and video quality, along with the duration of a video, were explored. The findings reveal students’ positive attitudes towards videos, and all factors were significantly related to the intention of use. In addition, the technical aspects of the video did not constitute a problem in the educational process, most likely due to contemporary quality in internet connections and audiovisual productions along with playback equipment. The duration of the videos was also not presented as an issue as there are flexible ways to embed videos in the learning process. Overall, videos can be used in multiple active learning scenarios to enhance students’ motivation and engagement and provide a joyful, collaborative, and hospitable learning environment. Students are familiar with digital tools and technologies and seem to enjoy audiovisual material in the learning process.

Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in Greece, Italy, and Spain. In this direction, a web interface for the creation and the query of a multi-source database containing hate speech-related content is implemented and evaluated. The selected sources include Twitter, YouTube, and Facebook comments and posts, as well as comments and articles from a selected list of websites. The interface allows users to search in the existing database, scrape social media using keywords, annotate records through a dedicated platform and contribute new content to the database. Furthermore, the functionality for hate speech detection and sentiment analysis of texts is provided, making use of novel methods and machine learning models. The interface can be accessed online with a graphical user interface compatible with modern internet browsers. For the evaluation of the interface, a multifactor questionnaire was formulated, targeting to record the users’ opinions about the web interface and the corresponding functionality.

The current paper focuses on the investigation of spoken-language classification in audio broadcasting content. The approach reflects a real-word scenario, encountered in modern media/monitoring organizations, where semi-automated indexing/documentation is deployed, which could be facilitated by the proposed language detection preprocessing. Multilingual audio recordings of specific radio streams are formed into a small dataset, which is used for the adaptive classification experiments, without seeking—at this step—for a generic language recognition model. Specifically, hierarchical discrimination schemes are followed to separate voice signals before classifying the spoken languages. Supervised and unsupervised machine learning is utilized at various windowing configurations to test the validity of our hypothesis. Besides the analysis of the achieved recognition scores (partial and overall), late integration models are proposed for semi-automatically annotation of new audio recordings. Hence, data augmentation mechanisms are offered, aiming at gradually formulating a Generic Audio Language Classification Repository. This database constitutes a program-adaptive collection that, beside the self-indexing metadata mechanisms, could facilitate generic language classification models in the future, through state-of-art techniques like deep learning. This approach matches the investigatory inception of the project, which seeks for indicators that could be applied in a second step with a larger dataset and/or an already pre-trained model, with the purpose to deliver overall results.

Art and technology have always been very tightly intertwined, presenting strong influences on each other. On the other hand, technological evolution led to today’s digital media landscape, elaborating mediated communication tools, thus providing new creative means of expression (i.e., new-media art). Rich-media interaction can expedite the whole process into an augmented schooling experience though art cannot be easily enclosed in classical teaching procedures. The current work focuses on the deployment of a modern-art web-guide, aiming at enhancing traditional approaches with machine-assisted blended-learning. In this perspective, “machine” has a two-folded goal: to offer highly-interdisciplinary multimedia services for both in-class demonstration and self-training support, and to crowdsource users’ feedback, as to train artificial intelligence systems on painting movements semantics. The paper presents the implementation of the “Istoriart” website through the main phases of Analysis, Design, Development, and Evaluation, while also answering typical questions regarding its impact on the targeted audience. Hence, elaborating on this constructive case study, initial hypotheses on the multidisciplinary usefulness, and contribution of the new digital services are put into test and verified.

The internet and web technologies have radically changed the way that users interact with museum exhibits. The websites and their related services play an important role in accessibility and interaction with the multimedia content of museums. The aim of the current research is to present a heuristic evaluation of forty-seven medical and anatomy museum websites from usability experts, for the determination of the principal/key characteristics and issues towards the effective design of a museum website. For homogeneity and comparison purposes, the websites of museums with no support of English language were not included in the evaluation process. In the present paper, the methodology was structured with the assessment of the technologies and services of anatomy museum websites in mind. The results of the current statistical examination are subsequently analyzed and discussed.

During the last years, there has been a growing multidisciplinary interest in alternative educational approaches, such as serious games, aiming at enhancing thinking skills and media literacy. Likewise, the objective of this study is to present the design and the development of an educational web application for learning the necessary steps towards the detection of bogus content, according to the fact-checking procedures. The game presents news articles, which have to be characterized as fake or real by the players. During the effort to reach the correct decision, the players can use tools and practices for identifying relevant information regarding the clues, which frame a news story (title, date, creator, source, containing images). After presenting the progress of interface design and development, this paper reports the results of a randomized online field study (n = 111), which provides some preliminary evidence. Specifically, it is validated that the game can raise awareness, teach about authentication tools, and highlight the importance of patterns that include evidence regarding the authenticity of articles. Additionally, thorough discussion was conducted within a media class (n = 35) to receive useful feedback/evaluation about the offered utilities and their usability. The findings suggest that educational games may be a promising vehicle to inoculate the public against misinformation.

Journalism is in a state of perpetual change due to the implementation of technological tools on an everyday basis. In the contemporary news distribution environment, the boundaries between media are no longer distinct, therefore media/journalism educational institutions should adapt curricula according to the needs of each type of medium. The aim of this paper is to present the incorporated technologies in the radio journalism undergraduate course of the School of Journalism and Mass Communications at the Aristotle University of Thessaloniki and evaluate their necessity according to the students themselves. After the completion of the course, which involves the use of specialized technological tools in audio recording and editing, a survey employing quantitative method based on the technology acceptance model was conducted. The results indicate that the students, despite the difficulties that were encountered due to the initial lack of knowledge on the technology applied, evaluated very highly both their satisfaction with the produced outcome and the usefulness of the procedure. In fact, the major result is that perceived usefulness is a key factor that determines the utilization of specialized technology.

Objectives: In the general population aortic stiffening assessed by carotid femoral pulse wave velocity (cf-PWV) is associated with cognitive dysfunction (CO/DY). Data in chronic kidney disease (CKD) are limited. Our study tests the hypothesis that large artery stiffness and microvascular damage in CKD patients are related to brain microcirculation changes reflected by impaired cognitive function. Methods: Among 244 patients, finally 44 with CKD stage 1; 47 stage 2; 25 stage 3; 35 stage 4, with mean age 58.4 years (64.5% males), were enrolled in a cross-sectional study. Cognitive impairment measured by Mini Mental State Examination (MMSE), Clock – drawing test (Clock-test), and Instrumental Activity of Daily Living (IADL) was considered as primary outcome. We directly measured brachial, aortic, systolic blood pressure, pulse pressure, mean blood pressure and cf-PWV. Results: Our patients revealed a significant linear deterioration in all the domains of cognitive function according to CKD stages, assessed by MMSE, Clock-test and IADL. The risk of cognitive dysfunction increased significantly from CKD stage 3 to 4 (p

The platelet-activating factor acetylhydrolase activity associated with high density lipoprotein (HDL-PAF-AH) may substantially contribute to the antioxidant, anti-inflammatory, and overall antiatherogenic effects of HDL. Two enzymes associated with HDL express PAF-AH catalytic activity, PAF-AH itself and paraoxonase-1 (PON1). The relative contribution of these enzymes in the expression of PAF-AH activity on HDL remains to be established. We investigated whether the PON1 polymorphisms (M55L and Q192R) or the PAF-AH polymorphism V379A could affect the PAF-AH activity associated with HDL in both normolipidemic and dyslipidemic (type IIA and IIB) populations. We show for the first time that the PON1 M55L polymorphism significantly affects the HDL-PAF-AH activity in all studied groups, the PON1 L55L individuals having lower enzyme activity compared to those having 1 M and 2 M alleles. No differences in the HDL content concerning the major apolipoprotein and lipid constituents were observed between individuals carrying the PON1 L55L and those with the M55M polymorphism.Our results provide evidence that PON1 significantly contributes to the pool of HDL-PAF-AH activity in human plasma, and suggest that the low PAF-AH activity in HDL carrying the PON1 L alloenzyme may be an important factor contributing to the low efficiency of this HDL in protecting LDL against lipid peroxidation.

The aim of this study was to estimate the risk factors, the frequency of development and the methods of management of Acute Renal Failure (ARF) in patients who underwent surgical repair of abdominal aorta aneurysms, pro-grammed or urgently. Researchers studied 16 patients, 14 males and 2 females, with aneurysm of abdominal aorta. 8 had emergency repair, and 8 programmed. The shows that the abnormal preoperative renal function tests, the existence of shock intra-operative as well as the multiple blood transfusions constitute risk factors for the early postoperative development of ARF in patients who underwent surgical intervention for abdominal aorta aneurysm. The presence of ARF is much more frequent in those who had an emergency repair because of rupture and it contributes considerably in the bad forecast of these patients.

Hematological indices play a prognostic role in human osteosarcoma (OSA), but data are limited in dogs. The aim of this retrospective multicentric cohort study was to investigate the prognostic significance of pre-operative hematological/inflammatory indices in a cohort of client-owned dogs with appendicular OSA receiving standardized treatment. Cut-offs associated with progression-free survival (PFS) for pre-operative hematological values/ratios were established using the minimal p -value approach. Historical prognostic factors were also assessed. Statistical analyses were performed for the whole population and after the exclusion of sighthounds. Fifty-nine dogs were included (13 were sighthounds). Multivariable analysis revealed that a low neutrophil count (<4.37 × 10 9 /L, HR0.28, CI 95% 0.13-0.61, p = 0.001), a high red blood cell count (≥7.91, HR3.5, CI 95% 1.56-7.9, p = 0.002), and a proximal humerus location (HR3.0, CI 95% 1.48-6.1, p = 0.002) were associated with shorter PFS. In the sighthound-only population, only OSA location was significantly associated with PFS in univariable analysis. When sighthounds were excluded, a low neutrophil count, a low monocyte count, and a proximal humerus location were associated with shorter PFS, in multivariable analysis. Neutrophil count and possibly monocyte and red blood cell counts can be useful prognostic markers in canine OSA treated with amputation and adjuvant carboplatin. However, not all indices are appropriate in sighthounds.

Background: This study aimed to describe the management of cases of suspected and confirmed canine multicentric lymphoma (ML) in first opinion practice (FOP) and investigate whether socioeconomic factors are associated with initial management., Methods: Clinical narratives from electronic health records collected by the Small Animal Veterinary Surveillance Network (SAVSNET) were searched to identify dogs with peripheral lymphadenomegaly in which ML was the major differential. Cases were grouped as either ML confirmed (ML-C) or ML suspected but not confirmed (ML-S). Associations between initial management and socioeconomic factors were assessed via multivariable logistic regression., Results: Two hundred and sixty-four cases with ML-C and 410 with ML-S were identified. There was an increased probability that owners of ML-C cases resided in less deprived areas. Moreover, a diagnosis was made more commonly in insured dogs. Only insured pets were more likely to be treated with chemotherapy following diagnosis. The majority of dogs in both groups were treated with corticosteroids alone (ML-S, n = 256/410; ML-C, n = 123/264). A small minority were referred (n = 30/674)., Conclusion: Socioeconomic inequalities appear to be associated with the diagnosis and management of dogs with suspected or confirmed ML in FOP. Most dogs with suspected multicentric lymphoma (in the UK) are managed in FOP (n = 644/674). Consequently, expanding the knowledge base relevant to this setting offers an opportunity to improve the management of canine lymphoma., (© 2022 British Veterinary Association.)