Real Implications Research Articles

The Geneticization of Education and Its Bioethical Implications.

The day has arrived that genetic tests for educational outcomes are available to the public. Today parents and students alike can send off a sample of blood or saliva and receive a 'genetic report' for a range of characteristics relevant to education, including intelligence, math ability, reading ability, and educational attainment. DTC availability is compounded by a growing "precision education" initiative, which proposes the application of DNA tests in schools to tailor educational curricula to children's genomic profiles. Here I argue that these happenings are a strong signal of the geneticization of education; the process by which educational abilities and outcomes come to be examined, understood, explained, and treated as primarily genetic characteristics. I clarify what it means to geneticize education, highlight the nature and limitations of the underlying science, explore both real and potential downstream bioethical implications, and make proposals for mitigating negative impacts.

The Urgency of Social Media “Diet” for Generation Z

Social media and generation Z (Gen Z) are like two sides of a coin that cannot be separated. Various positive and negative impacts have arisen as a result of internet addiction among Gen Z. Thus, this research was conducted to obtain a suitable formulation for Gen Z, both in consuming information and using social media. Hopefully, this research contributes to decreasing the negative impacts from the consumption of information and use of social media. The research was conducted through a qualitative approach. Data was collected through Focus Group Discussions (FGD) through Zoom meetings and literature studies. The research findings provide a social media diet model that includes three aspects: Self-Awareness, Action, and Evaluation (SAAE). The first chart of Self-Awareness includes action, motivation, and self-knowledge. The Action aspect contains five dimensions: choosing social media that suits your needs, limiting and selecting the type of information consumed, setting a daily schedule, consuming more offline content, and doing productive activities. The Evaluation highlights the concern on obedience and consistency. Researchers believe that this model can create awareness among social media users about the importance of social media diet information and provide real implications in the application of social media diet models. The social media diet prospectively works for Gen Z and other generations. Keywords: Generation Z, information diet, social media, social media diet models, urgency.

How I as a Fundraiser Would Use Twenty Million Dollars for Anti-Trafficking Work

Representations of human trafficking in film and media have widely missed the mark by misinforming the public and funders and harming those with lived experience. This has real implications for the anti-trafficking movement, including a lack of sufficient financial support for victim services and the failure to implement long-term systemic change. To change this, this article argues that we must invest in narrative change around human trafficking, under the leadership of those with lived experience. If done well, this could potentially bring additional funding for services by reaching the wider public, and even move the needle on trafficking prevention.

Kajian Teologis Transformasi Batiniah melalui Lensa Teologi Paulus: Dampak Praktis bagi Umat Kristen

This research aims to explore the concept of inner transformation in Paul's theology and analyze its practical impact on the daily lives of Christians. This study focuses on key verses in Paul's letters that describe the process of transformation of the heart and mind through faith in Christ. Through this approach, this research will also identify the real and concrete implications of Paul's theology in shaping the behavior and practical lives of Christians.

Heat transfer innovation of engine oil conveying SWCNTs-MWCNTs-TiO2 nanoparticles embedded in a porous stretching cylinder

The influence of boundary layer flow of heat transfer analysis on hybrid nanofluid across an extended cylinder is the main focus of the current research. In addition, the impressions of magnetohydrodynamic, porous medium and thermal radiation are part of this investigation. Arrogate similarity variables are employed to transform the governing modelled partial differential equations into a couple of highly nonlinear ordinary differential equations. A numerical approach based on the BVP Midrich scheme in MAPLE solver is employed for solution of the set of resulting ordinary differential equations and obtained results are compared with existing literature. The effect of active important physical parameters like Magnetic Field, Porosity parameter, Eckert number, Prandtl number and thermal radiation parameters on dimensionless velocity and energy fields are employed via graphs and tables. The velocity profile decreased by about 65% when the magnetic field parameter values increases from 0.5 to 1.5. On the other hand increased by 70% on energy profile. The energy profile enhanced by about 62% when the Radiation parameter values increases from 1.0 < Rd < 3.0. The current model may be applicable in real life practical implications of employing Engine oil-SWCNTs-MWCNTs-TiO2 nanofluids on cylinders encompass enhanced heat transfer efficiency, and extended component lifespan, energy savings, and environmental benefits. This kind of theoretical analysis may be used in daily life applications, such as engineering and automobile industries.

Personality Rights and Real Person Fictions: Do The Real Person Get a Say?

In this rapidly evolving world individuals have found various ways to express themselves and share that part of them with the world. In this modern age anyone with smart device and an internet connect can become a celebrity and with the same items anyone can create fictional works that are based on those and other celebrities. These creations are generally referred to as Real Person Fictions (RPFs). RPFs can bem short stories, poems, artworks and even full length novels. These works help creators practice their craft, bond with a community and break the bounds of reality but what happens if this right of the author to express themselves starts interfering with the real person’s right to publicity and privacy? Celebrities have expressed the implication of harmful portrayals in these RPFs which have had real life implications. The growing trend of commercializing RPFs on a big scale adds an incentive to look into this issueand address it as a bud. The concept of personality right is well established in India however the lack of codification of the same has led to contradictory judgments and blurred lines of boundaries. In this regard this article attempts to address the issue of personalityright or the right to publicity when it comes to real person fictions. This paper is divided in three parts. The first part deals with definition of real person fictions and how it differs from the existing classifications of fictional creations. The second part analyzes the efficiency of existing Indian laws when it comes to governing RPFs and the implication of the same. The third chapter provides informed suggestions for an enactment to govern personality right in India.

Highly efficient novel heterojunction catalyst in the elimination of antibiotics under the photo-Fenton-like process

The antibiotic residues in aquatic environments pose severe environmental concerns due to their ability to mediate antibiotic resistance genes through the microbes. The prime concern is the efficient and sustainable treatment of these residual antibiotics from waterbodies. The study aims to derive a novel bimetallic heterogeneous nano-catalyst, Ag0/Fe0/OSBC, by simple impregnation method in a greener process that involves natural phytochemicals of Artocarpus heterophyllus Lam leaves. The phytochemicals readily synthesize in in-situ Fe and Ag nanoparticles. Various advanced analytical tools reasonably characterize the synthesized materials. The study evaluates insights into heterojunction catalyst efficiency in degrading the sulfamethoxazole (SMX) and amoxicillin (AMX) under the advanced oxidation process. The photo-Fenton-like process assesses the elimination efficacy of the catalyst under dark, LED-VIS, and UV-A light conditions. The optimized batch operation parameters include solution pH 3.0, hydrogen peroxide dosage 0.10 mL/L (SMX); 0.25 mL/L (AMX), catalyst dosage 250.0 mg/L (SMX); 150.0 mg/L (AMX), and pollutant concentration of 2.0 mg/L. The parametric investigations offer insights into the degradation process's mechanisms and, the removal efficacy achieves 82.6 % and 92.8 %, respectively, for SMX and AMX. The process of mineralization using UV-A light achieves 68.0 % and 70.4 % for SMX and AMX, respectively. Minimal corrosion of Fe from the catalyst shows the catalyst's enhanced applicability and stability. The repeated cycles enabled a sustainable catalytic process, and real implications showed a higher selectivity of the process.

Analyzing the Role of Influencers in Digital Marketing Strategy: A Case Study in the Online Fashion Industry

In the contemporary landscape of digital marketing, the role of influencers has become increasingly prominent, particularly within the online fashion industry. Understanding the impact of influencer collaborations on digital marketing strategy is essential for brands seeking to effectively engage with consumers in the digital sphere. This research is important because it provides a deep understanding of the role of influencers in digital marketing strategies within the online fashion industry, which is currently one of the most dynamic and competitive industries digitally. By analyzing factors such as influencer authenticity and credibility, the impact of engaging content, and strategies to enhance brand visibility and consumer engagement through influencer collaborations, this research offers invaluable insights for brands and marketing practitioners in optimizing their strategies. This study aims to analyze the role of influencers in digital marketing strategy within the online fashion industry, with a focus on their effectiveness in enhancing brand visibility and driving consumer engagement. The research explores the influence of authenticity and credibility of influencers, the impact of engaging content creation, and the strategies for building brand visibility and consumer engagement through influencer collaborations. The research methodology employed in this study involves a comprehensive review of existing literature on influencer marketing in the context of the online fashion industry. The analysis utilizes NVivo as a tool for data analysis, allowing for the systematic categorization and interpretation of key themes and findings from the literature. The analysis reveals that influencers play a significant role in shaping brand perception, driving consumer behavior, and amplifying brand reach within the online fashion industry. Authenticity and credibility emerge as crucial factors influencing consumer trust and brand loyalty. Engaging content creation by influencers proves instrumental in fostering meaningful interactions and driving consumer engagement. Strategic collaborations with influencers aligned with brand values and audience demographics are identified as effective approaches for building brand visibility and fostering consumer engagement in the digital landscape. The real implications of this research include the ability to steer more effective digital marketing practices, enhance interactions with consumers, and ultimately, improve business performance such as increased sales and the development of a loyal customer base.

Artificial Neural Network and Numerical Simulation for Magneto Hydrodynamics Hybrid Nanofluid Flow Towards a Stretching Cylinder

The present study focuses on influence of boundary layer flow of heat transfer analysis on hybrid nanofluid through a stretching cylinder. Moreover, the impressions of porous medium, heat generation/absorption are discussed. Further, the stimulus of non-linear thermal radiation and MHD are part of this investigation. For motivation, the Artificial Neural Networks also deliberated. Arrogate similarity variables are employed to transform the governing modelled PDEs into a couple of highly nonlinear ODEs. A numerical approach based on the shooting approach with MATLAB bvp5c built in function is employed for solution of the set of resulting ODEs and acquired outcomes are compared with existing literature, obtained results an exceptional agreement. Artificial nerve cells or node locations form a network of nerves, a contemporary name for a chain composed of human brain cells. The impact of physical parameters like Magnetic Field, Eckert number, Porosity, Prandtl number, Heat generation, thermal radiation, parameters on dimensionless velocity and energy fields are discussed through graphs and tables. The velocity profile decreased by about 42% when the magnetic field parameter values increases from 0.5 to 1.5. On the other hand increased by 78% on energy profile. The energy profile improved by about 97% when the Eckert number values increases from 1.0 &lt; Ec &lt; 3.0. The current model may be applicable in real life practical implications of employing Water–Cu/Ag/Al2O3 nanofluids on cylinders encompass enhanced heat transfer efficiency, and extended component lifespan, energy savings, and environmental benefits. This kind of theoretical analysis may be used in daily life applications, such as industrial and biomedical industries.

Asking students how to best teach statistics virtually: results of focus group discussions

ABSTRACT Objective The unique circumstances of COVID-19 have raised questions of best practices for how to teach statistics virtually. The present study evaluated which characteristics of statistics learning activities in the virtual environment increase undergraduate psychology students’ (a) engagement, (b) satisfaction, and (c) knowledge of statistics. Method Semi-structured focus groups (N = 13 participants, aged 21–58, 64.3% female, 28.6% male, 7.1% gender fluid) were conducted. The focus group conversations were transcribed and analysed using reflexive thematic analysis. Results The findings indicate three main themes: catering to/supporting external students, why learning statistics online does not work, and how to make teaching and learning statistics online work. Social norms that prioritise time efficiency over engagement and interaction mean that the immediacy of learning and engaging with an instructor is often lost virtually. Suggestions for how to improve teaching and learning statistics online centred on readily accessible content, statistical software access, a teaching delivery that is methodical and flexible, immediacy of instructor response, and prioritising student-student and student-instructor connection. Conclusion These findings illustrate key challenges specific to teaching and learning statistics virtually, with real implications for how to better design and implement related curriculum.

Implementation of Tax Incentives on Issuers' Financial Ratios: Reduction and Reaction

This study aims to analyze whether the implementation of reduction (deduction) of tax incentives has or does not have a reaction (influence) on the financial ratio (ROE) of shares of IDX issuers LQ45 Index during the COVID-19 outbreak in 2022. The study employs a hypothesis testing approach with classical assumption tests and simple regression analysis, focusing on secondary data from the LQ45 index during the 2022 Covid-19 outbreak. It examined a population of 45, using 36 samples that met specific criteria. A simple linear analysis model was used to investigate the impact, if any, of tax incentive reductions on the financial ratio (ROE) of the issuers' stocks. This study, which uses simple regression analysis, reveals that the implementation of tax incentive reductions made by the Indonesian government does not react (influence) on the financial ratio (ROE) of IDX-listed stocks in the LQ45 Index during the COVID-19 outbreak in 2022. The study suggests that the Indonesian government's tax incentive reductions may not impact the financial ratios (ROE) of companies listed on the IDX, particularly in the LQ45 Index during the Covid-19 outbreak in 2022. This lack of impact is attributed to companies not utilizing these incentives, possibly due to insufficient awareness of their benefits and challenging criteria set by the government for obtaining these incentives. Despite common beliefs that tax incentives can influence financial performance, this study indicates they might not significantly affect the financial ratios of these companies. The real implications is research indicates that the Indonesian government's reduction of tax incentives did not elicit a response in the financial ratio (ROE) of shares issued by LQ45 Index companies on the Indonesia Stock Exchange during the Covid-19 outbreak in 2022. This suggests that the implementation of tax incentive cuts by the Indonesian government had no impact on the financial ratio (ROE) of LQ45 issuer shares during the Covid-19 outbreak in 2022, based on a sample size of 36.

Examining the Real Implications of the Purchasing Power Parity

This study focuses on the purchasing power between the dollar and the yuan and its usefulness in forecasting changes in exchange rates in the long run. In particular, PPP theory helps to clarify the inclination of countries with high inflation to incur a depreciation of their exchange rates. The theoretical part highlights the deviations from theory, its causes and its interconnections with other theories that analyse the relationship between exchange rates and other macroeconomic variables. Then, the validity of the theory for the USD / JPY exchange rate is examined from 1980 to 2013. The test found proof in support of the theory at 1% confidence level. Substantial emphasis is given on the effects of the asset price bubble in Japan during 1986 - 1992 and the US economic crisis of 2008 and more specifically on the behaviour of the parity during such a period of increased uncertainty. Received: 25 December 2023 / Accepted: 25 February 2024 / Published: 23 April 2024

Secure and Trustworthy Artificial Intelligence-extended Reality (AI-XR) for Metaverses

Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalized experiences to socialize, work, and play in self-sustaining and hyper-spatio-temporal virtual world(s). The advancements in different technologies such as augmented reality, virtual reality, extended reality (XR), artificial intelligence (AI), and 5G/6G communication will be the key enablers behind the realization of AI-XR metaverse applications. While AI itself has many potential applications in the aforementioned technologies (e.g., avatar generation, network optimization), ensuring the security of AI in critical applications like AI-XR metaverse applications is profoundly crucial to avoid undesirable actions that could undermine users’ privacy and safety, consequently putting their lives in danger. To this end, we attempt to analyze the security, privacy, and trustworthiness aspects associated with the use of various AI techniques in AI-XR metaverse applications. Specifically, we discuss numerous such challenges and present a taxonomy of potential solutions that could be leveraged to develop secure, private, robust, and trustworthy AI-XR applications. To highlight the real implications of AI-associated adversarial threats, we designed a metaverse-specific case study and analyzed it through the adversarial lens. Finally, we elaborate upon various open issues that require further research interest from the community.

Genotyping of Leptospira spp. in wild rats leads to first time detection of L. kirshneri serovar Mozdok in Serbia.

This study aimed to investigate the prevalence and molecular characterization of Leptospira species in Belgrade, Serbia, an area where this disease is underexplored. Specifically, the study sought to employ molecular and multilocus sequence typing analyses to fill the gap in understanding the diversity and distribution of Leptospira species within the region. A comprehensive molecular analysis was conducted on kidney samples obtained from Norway rats (Rattus norvegicus) in the urban environment. The study utilized molecular diagnostic techniques including real-time PCR targeting the lipL32 gene and performing sequence-based typing schemes utilizing adk, icdA, lipL32, lipL41, rrs2, and secY genes. These methodologies were applied to ascertain the presence and characterize different Leptospira species and serovars, respectively. The findings revealed the presence of two Leptospira species and three separate serovars in the Belgrade area. This study identified the presence of L. kirschneri serovar Mozdok in Serbia for the first time, a significant discovery previously undocumented in the region. This pioneering investigation sheds light on the molecular diversity and prevalence of Leptospira species in Serbia. The study underscores the importance of employing molecular typing methods to gain insights into the epidemiology and characterization of Leptospira species. These findings significantly contribute to both local and global perspectives on leptospirosis epidemiology, providing vital insights for the development of effective control strategies and interventions. In our recent study, we explored the presence and performed molecular typing of the Leptospira species, the bacteria responsible for leptospirosis, in wild rats in Serbia. This was the first time such a study was conducted in the region. Leptospirosis is a serious disease that affects both animals and humans, often transmitted through contact with water contaminated by infected animals. Our focus was on understanding which types of Leptospira were present in these animals. Excitingly, we discovered a particular strain of Leptospira, known as L. kirshneri serovar Mozdok, for the first time in Serbia. This finding is significant because it sheds light on the presence and spread of different Leptospira serovars in Serbia. It also raises awareness about the potential health risks associated with this serovar, which was previously unknown in the area. Our work fits into a broader context of disease surveillance and public health. By identifying the types of Leptospira present in a specific region, we can better understand the risks to public health and take steps to prevent and control the spread of leptospirosis. This discovery is not just important for scientists studying infectious diseases; it has real implications for public health officials, veterinarians, and anyone concerned with preventing and treating leptospirosis. Our findings highlight the need for ongoing monitoring of Leptospira in wildlife and synanthropic fauna, to protect both animal and human health.

Labour market dynamics in the era of technological advancements: The system-wide impacts of labour augmenting technological change

The employment impact of future technological change is much debated. Some commentators predict devastating job losses, while others are more sanguine, claiming that technological change raises living standards without reducing total employment. Our analysis a use a combination of partial equilibrium and dynamic computable general equilibrium (CGE) analysis with neo-Keynesian characteristics. These models are employed to assess the implications of skill-biased labour-augmenting technological change. They are calibrated on recent German Social Accounting Matrix data and parameterised using the best available empirical results from developed economies. The numerical CGE multi-sectoral model simulates the system-wide impacts of pervasive technical change affecting all sectors of the economy. The model allows investigation of alternative scenarios based around a common economic structure and set of parameter values. The results suggest that labour-augmenting technological change typically stimulates GDP growth and long-run total employment. However, there are negative short- and medium-run employment and real wage implications which might require government policy intervention. The simulations indicate that for open developed economies, improving the efficiency of skilled workers, as opposed to unskilled workers, is the most beneficial. This improvement has positive long-run impacts that are spread across both skill classifications. On the other hand, increasing the efficiency of the unskilled produces negative impacts on skilled employment and real wages. Additionally, the openness of the economy to migration and trade are important in determining the scale of these system-wide effects.

Climate finance across sub-Saharan Africa: Decision trees and network flows

The structure of climate finance flows from donors (multilateral sources) to recipients (sub-Saharan African countries) was studied. This is the first study to provide a comprehensive network structure of the climate finance flows into Africa, based on the global public climate finance governance system. Network theory and decision tree techniques were employed. The results obtained generally fit the multilateral funding units (MFUs) into two categories: central funding units (CFUs), which simultaneously attend to the climate-related projects of many African countries, and the boundary funding units (BFUs), which cater to only a few countries at once. An isolated region with no BFUs was identified. African countries within this group could be more exposed to climate financial risk as they rely on only the CFUs. In general, with the exception of mitigation REDD (reducing emissions from deforestation and forest degradation) climate finance, a disproportionate distribution of climate themes, with particular reference to adaptation finance, was observed across sub-Saharan Africa. This has real implications for equitable resource allocation of climate funds. The need for African-bred region-wide MFUs is recommended.

Increasing Farmers' Income in the Agricultural Sector in Central Java

In the agricultural sector of Central Java, this study examines the relationship between supply chain effectiveness, government policies, infrastructure development, and farmers' income. This study investigates the current status of infrastructure accessibility, government regulations, supply chain dynamics, and income sources through quantitative analyses involving 250 farmers. To verify and examine the correlation between the variables, structural equation modelling with partial least squares, or SEM-PLS, was used. Variations in the level of supply chain efficiency, farmers' attitudes towards government policies, infrastructure quality, and income distribution are shown by descriptive statistics. All proposed hypotheses were supported by the structural model, and the measurement model showed excellent levels of validity and reliability. The results of this study highlight the importance of infrastructure, sensible public policies, and efficient supply chains in increasing farmers' income. There is a discussion of practical consequences and suggestions for stakeholders and policymakers, with a focus on the need for focused action to improve the socio-economic conditions of farmers in Central Java. Although the statistical relationship between these variables is strong, farmers and the government are highly interdependent, so the real implications for the government to improve farmers in Central Java include regulation and distribution similar to other big cities.

Digitally mediated psychotherapy: Intimacy, distance, and connection in virtual therapeutic spaces

ABSTRACT This paper is a commentary on the articles in this Technology, AI Bots and Psychology Special Issue. The Special Issue presents a range of conceptual, practice-based and empirical reflections on digitally mediated therapy. This includes looking back to a significant shift in digital engagement due to the COVID-19 pandemic, along with anticipations regarding the landscape of future therapeutic practices mediated by digital technologies. I will discuss key themes resonating across the Special Issue, along with attending to some of the nuance and diversity of the potential and real implications of a greater integration of digital technologies in current and future therapeutic practice.

What are tenants demanding the most? A machine learning approach for the prediction of time on market

PurposeThis is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.Design/methodology/approachThe random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.FindingsResults show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.Practical implicationsThe findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.Originality/valueAlthough machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.

Non-GAAP Reporting and Investment

ABSTRACT The wide-spread reporting of non-GAAP earnings suggests efficiency gains from doing so. By estimating a dynamic investment model, we examine the real implications of investors using both GAAP and non-GAAP earnings to value firms. When investors use the firm’s GAAP earnings only, the firm’s manager—who cares about current stock prices—underinvests, and his investment is sensitive to transitory earnings. Non-GAAP earnings can improve investment efficiency by adjusting for these transitory earnings, but can also hide inefficient investment by introducing opportunistic bias. Although non-GAAP earnings induce overinvestment, they dominate GAAP-only reporting. Counterfactual analysis reveals supplementing GAAP earnings with biased non-GAAP earnings increases firm value by 3.4 percent relative to GAAP-only reporting. Precluding bias reduces overinvestment and further increases firm value by 1 percent. Data Availability: Data are available from the sources cited in the text. JEL Classifications: E22; G31; G34; M40.