The research is devoted to the acute problem of cinema influence on the young audience. With the continuous development of mass media, cinema is still one of the most popular leisure activities, remaining an influential tool on the picture of the world, values, stereotypes, the behavior of viewers, etc. The paper studies the effects of the cinema on young viewers in relation to their ideas about the elderly. Using a psychosemantic technique that includes 25 scales designed specifically to identify the content of representation of older people, respondents evaluated their various characteristics before and after watching the film. It should be noted that after watching a film about the elderly, the respondents changed their representations of motivational and regulatory, cognitive and emotional characteristics of the older people. However, the changes were not similar in different groups of young people: students seemed to have more negative representation, graduate students’ assessment, on the contrary, changed for a better one. The discovered opposite effects of the cinema influence can be explained by a number of reasons starting from age, personal experience of the respondents, the formation of ideas to the special features of the film itself. In this regard, the contribution of individual factors to the efficiency of the cinema impact and the prediction of its specific effects requires further study.

We live in the information age and, ironically, meeting the core function of journalism – i.e., to provide people access to unbiased information – has never been more difficult. This paper explores deep journalism, our data-driven Artificial Intelligence (AI) based journalism approach to study how the LinkedIn media could be useful for journalism. Specifically, we apply our deep journalism approach to LinkedIn to automatically extract and analyse big data to provide the public with information about labour markets, people’s skills and education, and businesses and industries from multi-generational perspectives. The Great Resignation and Quiet Quitting phenomena coupled with rapidly changing generational attitudes are bringing unprecedented and uncertain changes to labour markets and our economies and societies, and hence the need for journalistic investigations into these topics is highly significant. We combine big data and machine learning to create a whole machine learning pipeline and a software tool for journalism that allows discovering parameters for age dynamics in labour markets using LinkedIn data. We collect a total of 57,000 posts from LinkedIn and use it to discover 15 parameters by Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-parameters, namely Generations-Specific Issues, Skills & Qualifications, Employment Sectors, Consumer Industries, and Employment Issues. The journalism approach used in this paper can automatically discover and make objective, cross-sectional, and multi-perspective information available to all. It can bring rigour to journalism by making it easy to generate information using machine learning and can make tools and information available so that anyone can uncover information about matters of public importance. This work is novel since none of the earlier works have reported such an approach and tool and leveraged it to use LinkedIn media for journalism and to discover multigenerational perspectives (parameters) for age dynamics in labour markets. The approach could be extended with additional AI tools and other media.

This pilot study explores the potential of using a citizen science approach for sourcing volunteered geographic information via social media to research wildlife tourism interactions with endangered Borneo Pygmy Elephants on the lower Kinabatangan River in Sabah, Malaysia. Such information is critical if the lower Kinabatangan region is to achieve the United Nations Sustainable Development Goals through a sustainable tourism industry based around viewing the pygmy elephants. Guests and guides from the Sukau Rainforest Lodge were encouraged to become close-range remote sensors by sharing geotagged photographs of pygmy elephant sightings on Flickr. A ten week on-ground trail generated 247 photographs shared by 17 individual contributors with approximately two-thirds (65%) of photographs being georeferenced for the time and location of the elephant sighting. Plotting those sighting to explore the vegetation matrix (i.e. remnant forest or oil palm plantation) showed almost three-quarter (73%) of the sightings occurred within 1 km of an oil palm plantation. Of greater concern is that one in two sightings (50%) along the river occurred within the 500 m of an oil palm planation, which is inside the riparian buffer that the Sabah Government recommended for conservation of the elephants in their Lower Kinabatangan range. This study therefore demonstrates proof of concept for this research method and its further application at the nexus of wildlife conservation and sustainable ecotourism research.

Vaccines decrease morbidity and mortality. Nevertheless, their benefits depend on public response. During COVID-19, vaccine hesitancy and refusal were rampant, threatening public health. A thorough understand-ing of opponents' arguments is required to address the diffusion of unreliable information on social media and prevent vaccine hesitancy from developing into vaccine refusal. Accordingly, the article examines vac-cine opponents' justifications on social media. Textual content analysis of reader comments on three health-related Israeli Facebook pages was conducted. Data collection encompassed the Israeli COVID-19 vaccination period from October 2020 to May 2022. The comments were analyzed according to the health beliefs model (HBM). We found that vaccine opponents were characterized by low perceptions of the severity of the disease combined with high perceptions of the damages of the vaccine; low perceived benefits of vac-cine compliance; vaccine hesitancy and fear along with public distrust as barriers to change; and call for ac-tion to resist the vaccine and spread related anti-establishment views on the web. As vaccination hesitancy was found to develop into public distrust in the state systems and escalate into conspiracy beliefs and an-ti-vaccination activism, its early detection may prevent future vaccine resistance.

For its enthusiasts, the blockchain is an archivist's dream come true: an immutable historical record that is publicly accessible and immune from censorship. Proposals like Juried Protocol Galleries could enable bots to compute the provenance of digital artworks and their appearance in exhibitions and publications. Distributed file systems like IPFS claim to store creative works in a redundant, networked fashion outside the control of any single cloud provider. Projects designed to work with blockchains like Filecoin and Arweave propose a dedicated cryptocurrency as financial incentive to support the cost of governing and sustaining this "permaweb." As dreamy as this picture sounds, many of these promises depend on technologies that have yet to be sufficiently developed or adopted. Rather than forecast the future, we can separate the hype from the reality in the present day by examining a real-life example, namely the 2021 auction of Andy Warhol's digital art with NFTs. This essay will focus less on blockchain's general promise as a preservation medium and more on the particular case of the digital Warhols, which both in form and spirit would seem a perfect application of NFTs to preserve historically important works of digital art. Which promises of the crypto-dream of permanent access to digital heritage ring true for this case study, and which are overblown?

A numerical study for the effect of crest width, breaking parameter and trunk permeability on hydrodynamics and flow behavior in the vicinity of rubble-mound, permeable, zero-freeboard breakwaters (ZFBs) is presented. The modified two dimensional Navier-Stokes equations for two-phase flows in porous media with a Smagorinsky model for the subgrid scale stresses were solved numerically. An immersed-boundary/level-set method was used. The numerical model was validated for the cases of wave propagation over a submerged impermeable trapezoidal bar and over a low-crested permeable breakwater. Five cases of breakwaters were examined, and the main results are: (a) The size of the crest width, B, does not notably affect the wave reflection, vorticity and currents in the seaward region of ZFBs, while wave transmission, currents in the leeward side, and mean overtopping discharge, all decrease with increasing B. A non-monotonic behavior of the wave setup is also observed. (b) As the breaking parameter decreases, wave reflection, transmission, currents, mean overtopping discharge, and wave setup decrease. This observation is also verified by relevant empirical formulas. (c) As the ZFB trunk permeability decreases, an increase of the wave reflection, currents, wave setup, and a decrease of wave transmission and mean overtopping discharge is observed.

Objective: Diabetes is associated with increased cardiovascular and cerebrovascular disease-related mortality. We investigated the association between carotid intima-media thickness (CIMT) with clusterin (CLU), amylin, secreted frizzled-related protein-4 (SFRP-4), total and active glucagon-like peptide-1 (GLP-1) levels, and dipeptidyl peptidase-4 (DPP-4) in type 2 diabetes mellitus (T2DM) individuals with or without coronary artery disease (CAD). Methods: This study consisted of four groups in Medicine Hospital between April- October, 2017: Control group (mean ages: 50.3 ± 10.7 years, 20 females and 15 males), diabetic group (DM) (mean ages: 53.9 ± 11.1, 14 females and 23 males), CAD group (mean ages: 62.6 ± 11.8, 17 females and 17 males) and CAD+ DM group: (mean ages: 62.6 ± 11.8 years, 18 females and 18 males). Results: Both CAD and CAD+DM groups have higher CIMT levels than controls. CAD+DM group have also significantly higher CIMT levels than DM group. Left external carotid artery (ECA) was only found different in DM group from controls. When compared with controls, DM, CAD groups have low DPP-4 and GLP-1_total concentration. Control group have significantly lower SFRP-4 levels than DM, CAD and CAD+DM (p<0.001) groups. Serum GLP-1_total levels were found to be significantly low in CAD+DM group when compared to control group. Conclusion: DPP-4 and SFRP-4 levels are predictive marker for atherosclerosis in diabetes, correlates well with HOMA-IR particularly in diabetes. CIMT has the potential to be a clinically useful predictor of vascular risk in diabetic patients with CAD. Large cohorts and at-risk populations are needed to confirm the predictive value of these findings.

Maintaining a healthy cyber society is a big challenge due to the users’ freedom of expression and behaving. It can be solved by monitoring and analyzing the users’ behavior and taking proper actions towards them. This research aims to present a platform that monitors the public content on Twitter by extracting tweet data. After maintaining the data, the users’ interactions are analyzed using Graph Analysis methods. Then the users’ behavioral patterns are analyzed by applying Metadata Analysis, in which the timeline of each profile is obtained; also, the time-series behavioral features of users are investigated. Then in the Abnormal Behavior Detection Filtering component, the interesting profiles are selected for further examinations. Finally, in the Contextual Analysis component, the contents will be analyzed using natural language processing techniques; A binary text classification model (SVM + TF-IDF with 88.89% accuracy) for detecting if the tweet is related to crime or not. Then, a sentiment analysis method is applied to the crime-related tweets to perform aspect-based sentiment analysis (DistilBERT + FFNN with 80% accuracy); because sharing positive opinions about a crime-related topic can threaten society. This platform aims to provide the end-user (Police) suggestions to control hate speech or terrorist propaganda.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.

: This study explores the perceptions of Chinese learners in Spain regarding the use of social networks for informal Spanish language learning. The objective is to identify the challenges and benefits of using social networks to address the real needs of students in learning Spanish. A qualitative phenomenological approach was adopted, focusing on participants’ perceptions before and after using social networks. Eight Chinese students were selected for the study. The study was conducted in Valencia and Barcelona, Spain, from 1 September 2023 to 20 March 2024, and three commonly used social media networks were compared. The results indicate positive perceptions towards social media as a tool for learning Spanish, highlighting its usefulness in improving language skills and enhancing cultural awareness. Additionally, Xiaohongshu and Bilibili emerged as the most popular platforms for Spanish language learning among Chinese students. This study concludes that social media effectively meets the authentic needs of Chinese students learning Spanish in Spain, enhancing both language skills and cultural adaptation. This multifaceted approach reflects the complexity of learning Spanish in the digital age, combining personal passion, professional aspirations, and cultural adaptation needs.

Antimicrobial peptides provide a powerful toolkit for combating multidrug resistance. Combatting eukaryotic pathogens is complicated by the fact, the intracellular drug targets in the eukaryotic pathogen are frequently homologs of cellular structures of vital importance in the host organism. The entomopathogenic bacteria, (symbionts of entomopathogenic nematode species), release a series of non-ribosomal templated antimicrobial peptides, some may be potential drug candidates. The ability of an entomopathogenic nematode /entomopathogenic bacterium symbiotic complex to survive in a given polyxenic milieu is a coevolutionary product, explaining that those gene complexes which are responsible for the biosynthesis of different non-ribosomal templated antimicrobial protective peptides (including those which are potently capable to inactivate the protist mammalian -pathogen Leishmania and the gallinaceous bird pathogen Histomonas) are co-regulated. Our approach is based on comparative antimicrobial bioassays of the culture media of the wild-type and regulatory mutant strains. We concluded that Xenorhabdus budapestensis and X. szentirmaii are excellent sources of non-ribosomal templated antimicrobial peptides, that are efficient antagonists of the mentioned pathogens. Data on selective cytotoxicity of different cell-free culture media encourages us to forecast that the recently discovered “easy-PACId” research strategy is suitable for constructing EPB strains producing and releasing single, harmless, non-ribosomal templated antimicrobial peptides with considerable drug, (probiotic) -candidate potential.

Whether the different NR-AMPs could ever be utilized as drugs not only against prokaryotic (bacteria) pathogens but eukaryotic (fungal pathogens, and parasitic protists) depends on the side effects. To get experimental experience about the option of applying EPB-produced antimicrobials to pathogens, and parasites of veterinary significance, we present here the results of an in vitro, and an accompanying in vivo study on chicken. In the in vitro study, we tested the cytotoxic potential of the cell-free conditioned culture media (CFCM) of three entomopathogenic bacterium species, - X. budapestensis, DSM16342 (EMA); X. szentirmaii DSM16338 (EMC); Photorhabdus luminescens ssp. akhurstii TT01 - on chicken tissue culture cells, namely, on the Leghorn Male Hepatoma (LMH), [92] cells, (a permanent confluent hepato-carcinoma cell line). Each CFCM proved rather cytotoxic in this test. In the in vivo study, we fed freshly hatched male broiler chickens for 42 days with XENOFOOD [39] which contained autoclaved cultures of EMA, and EMC). These bacteria were grown on standard chicken (starter and grower) [HM3] [u4] feed, and the whole culture was used as a “food supplement”. [HM5]. It had been known that these EPB species cannot grow that is, not viable) atbody temperature (above 33 C).