. The concept of resilience has evolved considerably since Holling’s (1973) seminal paper. Different interpretations of what is meant by resilience, however, cause confusion. Resilience of a system needs to be considered in terms of the attributes that govern the system’s dynamics. Three related attributes of social– ecological systems (SESs) determine their future trajectories: resilience, adaptability, and transformability. Resilience (the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks) has four components—latitude, resistance, precariousness, and panarchy—most readily portrayed using the metaphor of a stability landscape. Adaptability is the capacity of actors in the system to influence resilience (in a SES, essentially to manage it). There are four general ways in which this can be done, corresponding to the four aspects of resilience. Transformability is the capacity to create a fundamentally new system when ecological, economic, or social structures make the existing system untenable. The implications of this interpretation of SES dynamics for sustainability science include changing the focus from seeking optimal states and the determinants of maximum sustainable yield (the MSY paradigm), to resilience analysis, adaptive resource management, and adaptive governance.
This study reviews 60 papers using a Likert scale and published between 2012 – 2021. Screening for literature review uses the PRISMA method. The data analysis technique was carried out through data extraction, then synthesized in a structured manner using the narrative method. To achieve credible research results at the stage of the data collection and data analysis process, a group discussion forum (FGD) was conducted. The findings show that only 10% of studies use a measurement scale with an even answer choice category (4, 6, 8, or 10 choices). In general, (90%) of research uses a measurement instrument that involves a Likert scale with odd response choices (5, 7, 9, or 11) and the most popular researchers use a Likert scale with a total response of 5 points. The use of a rating scale with an odd number of responses of more than five points (especially on a seven-point scale) is the most effective in terms of reliability and validity coefficients, but if the researcher wants to direct respondents to one side, then a scale with an even number of responses (six points) is possible. more suitable. The presence of response bias and central tendency bias can affect the validity and reliability of the use of the Likert scale instrument.
Social media data are being increasingly used in conservation science to study human–nature interactions. User‐generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user‐generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well‐being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk‐based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.
This paper aims to provide a broad overview regarding the relationship between major mental disorders and criminal thinking which further alludes to criminal behaviour. Current research proposes an especial correlation between Antisocial Personality Disorder (ASPD) and criminal tendencies, where ASPD will be utilized as an exemplar to offer intricate explanations of such relationships. As previous studies of similar angles tend to focus on subtle aspects within this web; zooming out allows for a comprehensive summary of current findings and suggested directions for further investigation. Symptoms of other mental disorders associated with the topic will not be omitted despite the primary focus on ASPD. Whilst it is important to note that the materialization of thinking into behaviour is undeniably complex, the analytic framework of epidemiology can be used to deduce potential causes for delinquencies and offences which in turn fuels according change within criminal justice systems. Many questions and controversies remain unresolved especially in relation how disorder should authorize special treatment. ‘Crime’ in this case refers to both mindset and action; psychiatric lens are likely to lend more insights to motives within the broader socio-cultural landscape. This paper will account for the social values whilst maintaining a precise scientific approach, sketching out a logical chain from causes to consequences of crime in relation to mental disorders and finally its implications from a legal and rehabilitative perspective.
This study aims to provide an assessment of the existing literature on the role of social media advertising in hospitality, tourism and travel (HTT) as well as an agenda for future research.,Covering a 15-year time span (2004–2019), this study is focused on journal papers archived in two academic databases in social sciences: Business Source Complete and Communication and Mass Media Complete. Each of the 192 papers collected was coded for 8 major variables: journal, year of publication, research topic, country studied, type of social media investigated, method, theoretical underpinning and key findings.,Three major topic areas are identified in this study: use of social media from consumer’s perspective, use of social media from organization’s perspective and effects of social media.,Although a few prior papers have provided a literature review of social media in tourism and hospitality, no review-based papers have ever examined social media as an advertising vehicle in the context of HTT. Most reviews to date have been limited to general social media studies, without much advancement of theory building in advertising research.,To the best of the authors’ knowledge, this paper represents the first theoretical review of academic research on social media advertising in HTT. The review concludes by suggesting a theoretical framework for studying social media advertising in HTT and offering an agenda for future research.
El término realidad virtual es entendido como un escenario tridimensional simulado por computadora, en el que es posible experimentar el entorno mediante el uso de algún dispositivo electrónico especial. En el campo de la publicidad y la mercadotecnia, la realidad virtual permite a los consumidores simular la experiencia de consumo, lo que facilita la evaluación del producto y puede eliminar la indecisión de compra. Sin embargo, su uso es menos conocido en empresas pequeñas. En este trabajo se prueba un anuncio de realidad virtual y un anuncio tradicional de una panadería de Comala, Colima, México, para medir el efecto en dos grupos de edad: de 18 a 25 años y mayor a 25 años. Los hallazgos muestran que la publicidad de realidad virtual tiene un efecto significativo sobre la publicidad tradicional en la permanencia en la mente de los consumidores jóvenes y en la intención de compartir.
Economic theory. Demography, Social sciences (General)
The digital transformation of enterprises is a significant catalyst for achieving cleaner production and directly affects a company’s carbon performance. This research elucidates the theoretical logic and potential impact mechanisms of digital transformation in reducing corporate carbon emissions. Second, using a panel data set of Chinese A-share listed companies from 2007 to 2020, this study quantitatively investigates the effect of corporate digital transformation on the carbon emissions intensity of businesses. The empirical results indicate that corporate digital transformation has a statistically significant negative effect on the carbon emissions intensity of Chinese firms. Several robustness tests have validated this conclusion. The heterogeneity analysis reveals that state-owned businesses, firms with high carbon intensity, and those with strong financing capacity would benefit more from digital transformation in achieving the goal of reducing carbon emissions. Furthermore, the impact of digital transformation on corporate carbon emission abatement is more prominent in industries with limited technological input and high energy consumption. At the regional level, digital transformation has a more significant impact on reducing carbon emissions in cities with stringent environmental regulation, advanced marketization, and resource-based economies. The transmission mechanism analysis confirms that improving corporate energy use efficiency, enhancing financial performance, and fostering green innovation are crucial transmission mechanisms through which digital transformation can help enterprises decrease their carbon emissions. These findings assist companies in comprehending the role of digital transformation in lowering carbon emissions and provide them with valuable insights.
The dual credit policy is currently the main starting point for China to achieve the green and sustainable development of the auto market. However, the policy’s impact on future market development remains unclear. It is necessary to consider the market capacity constraints and the market competition environment. By researching the impact of the dual credit policy on the micro-decision-making of automakers and the long-term evolution of the macro-auto market, the effect of the dual credit policy on the Chinese auto industry is obtained. This paper considers the market capacity constraint, combines the competitive relationship and game payment matrix between NEV makers and CFV makers, constructs a game model of the competition density between NEVs and CFVs, simulates the development and evolution of China’s auto market size, and analyzes the effect of the quantitative parameters of the dual credit policy on the auto market. The results show that: (1) the increase in NEV makers’ sale of credits will stimulate their production incentives, and the increase in conventional fuel vehicle (CFV) makers’ cost of purchasing credits will reduce their production incentives; (2) tightened fuel consumption standards for CFVs has an enhanced stimulating effect on the increase in the market share of NEVs, which can effectively reduce the market share of CFVs; (3) the price of credits facilitates the growth of the NEV market share, but credit prices that are too high do not stimulate the growth of the NEV market share to a significant degree; (4) the increase in the proportion of credits required for NEVs and the increase in the price of credits together help to reduce the market share of CFVs and increase the market share of NEVs.
In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which greatly complicates data management, and therefore the relevance of the analysis of artificial intelligence technologies increases. Training employees for industrial processes is a major challenge in any industry. Effective human resource management requires an accurate assessment and presentation of available competencies, as well as an effective mapping of the required competencies for specific positions. Competences enable the company to achieve high production and economic results. The aim of the study is to develop a structural model of a predictive expert system for managing data on the competencies of a modern manager by combining artificial and human intelligence, which can serve as a decision support tool for managers in real conditions to improve the efficiency of a particular enterprise. The study of the demand for managers and requirements for candidates in the Russian Federation and the Republic of Tatarstan was conducted on the data of the largest Russian Internet recruitment company HeadHunter. To develop a structural model of the proposed expert system, information from specialized scientific publications published in the Russian and foreign scientific literature of the Web of science and Scopus databases was used. The expert system will allow the manager to find the best options for using employees, predict the development of the enterprise as a whole and its individual divisions, which will significantly increase the key performance indicators of any company.
Objective: To investigate the feasibility and effectiveness of hydrogen in the treatment of retinitis pigmentosa (RP) patients through the drinking of hydrogen-rich water (HRW). Methods: RP patients clinically diagnosed in our hospital were selected and given HRW for drinking at 400–500 ml twice a day for four consecutive weeks. Changes in best corrected visual acuity (BCVA), intraocular pressure, the retinal thickness, and choroidal thickness, as well as the amplitude and peak time of visual electrophysiological examinations before and after HRW drinking were observed. Data were statistically analyzed. Results: In total, 24 eyes of 13 patients with RP (3 males and 10 females aged–27-65 years old, were enrolled in the study. The BCVA after HRW drinking was 0.34 ± 0.25, which was statistically improved compared with that before (P < 0.05). There were no significant differences in intraocular pressure, retinal lhickness, or choroidal thickness before and after HRW drinking (all P > 0.05). The amplitudes of the b-wave in Dark-adaptation 0.01 response, a and b waves in Dark-adaptation 3.0 response, the Dark-adaptation Ops total wave, a and b waves in Light-adaptation 3.0 response, and the Light-adaptation Flicker response of electroretinogram (ERG) were significantly higher than those before HRW drinking (all P < 0.05). The corresponding peak times iwere mproved to some extent compared to those before HRW consumption (all P < 0.05). Six patients with RP (11 eyes) had a BCVAm ore than 20/200. The amplitude and peak time of the P100 -ave from the 1°p attern visual evoked potentials (PVEP) were not significantly different from those before HRW drinking (P > 0.05), while the data from the 15′ PVEP were statistically different (P < 0.05). Seven patients with RP (13 eyes) had a BCVA less than. 20/200 No significant differences were found in the amplitude and peak time of the P2 wave from the 1.0 Hz flash visual evoked potentials (FVEP) and the amplitude from the 12 Hz FVEP compared with those before HRW drinking (all P > 0.05). Conclusion: Short-term HRW drinking slightly improved visual function in patients with primary RP, whereas no significant improvement was found in the thickness of the retina and choroid.
There is an urgent need to increase the social inclusion of postsecondary faculty with disabilities by reducing the need to adapt to ableist and sanist neoliberal standards. In this article, two social work faculty with disabilities argue that their social exclusion is inevitable under systemic neoliberal priorities of individualism, efficiency, and productivity. We engage in a systems analysis of how educational institutions, namely universities, engage in practices and processes of social exclusion of faculty with disabilities through neoliberal ideologies, policies, and practices. Using an autoethnographic case study method, guided by an intersectional and disability justice theoretical framing, the authors challenge the ahistorical and non‐relational tendencies of neoliberalism in its many forms. Using lived experience as data, the authors elucidate strategies to promote social inclusion aimed at universities and at the discipline of social work. In conclusion, the authors advocate for change at the structural level for the social work profession and for postsecondary institutions.
Tahany Saleh Aldayel, Mohamed M. Badran, Abdullah H. Alomrani
et al.
Aloe perryi (AP) has gained considerable interest as a medicinal herb in various biological applications due to its rich phytochemical composition. However, the therapeutic benefits of AP could be potentiated by utilizing nanotechnology. Moreover, cationic solid lipid nanoparticles (CSLNs) possess remarkable characteristics that can greatly enrich a variety of biological uses. An optimization approach was used to achieve high-quality CSLNs to maximize the therapeutic efficacy of AP. Therefore, a factorial design was used to investigate the influence of various variables on the attributes of CSLNs quality. In this study, the factors under investigation were compritol 888 ATO (C-888, X1), poloxamer 188 (PL188, X2), and chitosan (CS, X3), which served as independent variables. The parameters measured as dependent variables included particle size (Y1), zeta potential (Y2), and encapsulation efficiency EE (Y3). The relationship among these variables was determined by Analysis of Variance (ANOVA) and response surface plots. The results revealed that PL188 played a significant role in reducing the particle size of CSLNS (ranging from 207 to 261 nm with 1 % PL188 to 167–229 nm with 3 % PL188). Conversely, an increase in the concentration of CS led to a rise in the particle size. The magnitude of positive zeta potential values was dependent on the increased concentration of CS. Moreover, the higher amounts of C-888 and PL188 improved the EE% of the CSLNs from 42 % to 86 %. Furthermore, a concentration-dependent antioxidant effect of the optimized AP-CSLNs was observed. The antioxidant activity of the optimized AP-CSLNs at 100 μg/mL was 75 % compared to 62 % and 60 % for AP-SLNs and AP solution, respectively. A similar pattern of improvement was also observed with antimicrobial, and anticancer activities of the optimized AP-CSLNs. These findings demonstrated the potential of AP-CSLNs as a carrier system, enhancing the biological activities of AP, opening new possibilities in herbal medicines.
Microbes influence the surrounding environment and contribute to human health. Metagenomics can be used as a tool to explore the interactions between microbes. Metagenomic assemblies built using long read nanopore data depend on the read level accuracy. The read level accuracy of nanopore sequencing has made dramatic improvements over the past several years. However, we do not know if the increased read level accuracy allows for faster assemblers to make as accurate metagenomic assemblies as slower assemblers. Here, we present the results of a benchmarking study comparing three commonly used long read assemblers, Flye, Raven, and Redbean. We used a prepared DNA standard of seven bacteria as our input community. We prepared a sequencing library using a VolTRAX V2 and sequenced using a MinION mk1b. We basecalled with Guppy v5.0.7 using the super-accuracy model. We found that increasing read depth benefited each of the assemblers, and nearly complete community member chromosomes were assembled with as little as 10× read depth. Polishing assemblies using Medaka had a predictable improvement in quality. We found Flye to be the most robust across taxa and was the most effective assembler for recovering plasmids. Based on Flye’s consistency for chromosomes and increased effectiveness at assembling plasmids, we would recommend using Flye in future metagenomic studies.
The general factor of personality (GFP) represents the shared variance between personality traits that yield social adjustment and acts as a core personality disposition. In the present study, the existence of GFP in a sample of 249 Slovenian adolescents aged 15–19 years was investigated, and the relationship between GFP, the Dark Triad, and social intelligence was researched. The study used three self-report questionnaires to measure the Big Five, the Dark Triad, and three dimensions of social intelligence. It was found that, in adolescents, GFP exists (although in a somewhat different composition than in previous studies) and is negatively correlated with Machiavellianism and psychopathy and positively correlated with social skills and social awareness. GFP acts as a significant positive predictor of all social intelligence dimensions, and Machiavellianism acts as a significant positive predictor of social information processing and social skills. It can be concluded that GFP and, to a certain extent, perhaps some manipulative tendencies positively predict how an individual functions in society. With these findings, the study contributes to the understanding of the (hierarchical) structure of personality and its association with behavior in social interactions, which is one of the most important developmental tasks in adolescence.