bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Materialism on Student’s Lifestyle: A Case Study of a Rural-based University in Limpopo Province, South Africa
Authors: Mabina Karabo Suzan , Mukwevho Marubini Harry
Published: October 2024

Many students use their obsession with material possessions as a means of expressing their confidence and sense of self-worth. Therefore, the study looked at how materialism affected students’ lives and academic achievement at a rural South African university in the province of Limpopo. To explore materialism’s effects on students’ lifestyles and academic performance a qualitative approach was adopted. The impact of materialism on students’ lives and education was examined using an exploratory research design. The fourth-year male and female students were selected using a non-probability purposive sampling technique. Semi-structured in-person interviews were conducted to gather comprehensive data on the educational and lifestyle background of the students. The thematic analysis method was employed in the study to identify trends, and their lifestyles influencing the acquisition of numerous material possessions, leading to severe psychological and financial problems attributed to strained interpersonal relationships, low self-esteem, financial debt, and poor academic performance. Students are largely influenced by peer pressure, parental lifestyle, personality, culture, poverty and social media to spend a lot of money frivolously. Preoccupation with acquiring material goods leaves a trail of unpayable debts, mental illness and strained relationships. The study serves as an awareness creation campaign for various stakeholders such as tertiary institutions, parents, guardians, scholarships and bursary funders to intervene regarding materialistic attitudes.

Keywords: Funds, Lifestyle, Life Satisfaction, Materialism, Socio-economic Factors, Student.
La inviolabilidad de embajadas y consulados: a propósito del contencioso entre México vs. Ecuador ante la CIJ
Authors: Collantes Gonz´ález Jorge Luis
Published: October 2024

El 5 de abril de 2024, fuerzas de seguridad ecuatorianas ingresaron a la Embajada de México en Quito sin autorización, para detener al exvicepresidente de Ecuador, Jorge Glas, quien había recibido asilo en dicha embajada. Este incidente llevó a México y Ecuador a presentar el caso ante la Corte Internacional de Justicia (CIJ), realzando así la importancia de la Convención de Viena sobre las Relaciones Diplomáticas de 1961 (CVRD). La CIJ ha subrayado así la inviolabilidad de las embajadas y diplomáticos como un principio fundamental a respetar por la comunidad internacional. Por ello, al analizar el caso México-Ecuador, se plantean cuestiones sobre la inviolabilidad física y el uso indebido de tecnología, así como sobre el asilo otorgado para evadir responsabilidad penal. De esta forma, se subraya la necesidad de respetar la inviolabilidad de las misiones diplomáticas, y buscar soluciones pacíficas y legales en conflictos internacionales, reafirmando la importancia de los principios consagrados en la CVRD y el derecho internacional público.
Stripe 82X Data Release 3: Multiwavelength Catalog with New Spectroscopic Redshifts and Black Hole Masses
Authors: LaMassa Stephanie , Peca Alessandro , Urry C. Megan , Glikman Eilat , Ananna Tonima Tasnim , Auge Connor , Civano Francesca , Ghosh Aritra , Kirkpatrick Allison , Koss Michael J. , Powell Meredith , Salvato Mara , Trakhtenbrot Benny
Published: October 2024

We present the third catalog release of the wide-area (31.3 deg2) Stripe 82 X-ray survey. This catalog combines previously published X-ray source properties with multiwavelength counterparts and photometric redshifts, presents 343 new spectroscopic redshifts, and provides black hole masses for 1297 Type 1 active galactic nuclei (AGN). With spectroscopic redshifts for 3457 out of 6181 Stripe 82X sources, the survey has a spectroscopic completeness of 56%. This completeness rises to 90% when considering the contiguous portions of the Stripe 82X survey with homogeneous X-ray coverage at an optical magnitude limit of r < 22. Within that portion of the survey, 23% of AGN can be considered obscured by being either a Type 2 AGN, reddened (R − K > 4, Vega), or X-ray obscured with a column density of N
H > 1022 cm−2. Unlike other surveys, there is only an 18% overlap between Type 2 and X-ray obscured AGN. We calculated black hole masses for Type 1 AGN that have Sloan Digital Sky Survey spectra using virial mass estimators calibrated on the Hβ, Mg ii, Hα, and C iv emission lines. We find wide scatter in these black hole mass estimates, indicating that statistical analyses should use black hole masses calculated from the same formula to minimize bias. We find that the AGN with the highest X-ray luminosities are accreting at the highest Eddington ratios, consistent with the picture that most black hole mass accretion happens in the phase when the AGN is luminous (L
2−10keV > 1045 erg s−1).
A Model for Eruptive Mass Loss in Massive Stars
Authors: Cheng Shelley J. , Goldberg Jared A. , Cantiello Matteo , Bauer Evan B. , Renzo Mathieu , Conroy Charlie
Published: October 2024

Eruptive mass loss in massive stars is known to occur, but the mechanism(s) are not yet well understood. One proposed physical explanation appeals to opacity-driven super-Eddington luminosities in stellar envelopes. Here, we present a 1D model for eruptive mass loss and implement this model in the MESA stellar evolution code. The model identifies regions in the star where the energy associated with a local super-Eddington luminosity exceeds the binding energy of the overlaying envelope. The material above such regions is ejected from the star. Stars with initial masses of 10−100 M
⊙ at solar and SMC metallicities are evolved through core helium burning, with and without this new eruptive mass-loss scheme. We find that eruptive mass loss of up to ∼10−2
M
⊙yr−1 can be driven by this mechanism, and occurs in a vertical band on the H-R diagram between

3.5
≲
log
(

T

eff

/

K
)
≲
4.0

. This predicted eruptive mass loss prevents stars of initial masses ≳20 M
⊙ from evolving to become red supergiants (RSGs), with the stars instead ending their lives as blue supergiants, and offers a possible explanation for the observed lack of RSGs in that mass regime.
Constraining the Origin of the Nanohertz Gravitational-wave Background by Pulsar Timing Array Observations of Both the Background and Individual Supermassive Binary Black Holes
Authors: Chen Yunfeng , Yu Qingjuan , Lu Youjun
Published: October 2024

The gravitational waves (GWs) from supermassive binary black holes (BBHs) have long been sought by pulsar timing array (PTA) experiments, in the forms of both a stochastic GW background (GWB) and individual sources. Evidence for a GWB was reported recently by several PTAs with origins to be determined. Here we use a BBH population synthesis model to investigate the detection probability of individual BBHs by the Chinese PTA (CPTA) and the constraint on the GWB origin that may be obtained by PTA observations of both GWB and individual BBHs. If the detected GWB signal is entirely due to BBHs, a significantly positive redshift evolution (∝ (1 + z)2.07) of the mass scaling relation between supermassive black holes and their host galaxies is required. In this case, we find that the detection probability of individual BBHs is ∼85% or 64% if using a period of 3.4 yr of CPTA observation data, with an expectation of ∼1.9 or 1.0 BBHs detectable with a signal-to-noise ratio ≥3 or 5, and it is expected to increase to >95% if the observation period is extended to 5 yr or longer. Even if the contribution from BBHs to the GWB power signal is as small as ∼10%, a positive detection of individual BBHs can still be expected within an observation period of ∼10 yr. A nondetection of individual BBHs within several years from now jointly with the detected GWB signal can put a strong constraint on the upper limit of the BBH contribution to the GWB signal and help identify/falsify a cosmological origin.
Next-generation Accretion Disk Reflection Model: High-density Plasma Effects
Authors: Ding Yuanze , Garcıa Javier A. , Kallman Timothy R. , Mendoza Claudio , Bautista Manuel , Harrison Fiona A. , Tomsick John A. , Dong Jameson
Published: October 2024

Luminous accretion disks around black holes are expected to have densities of ∼1015−1022 cm−3, which are high enough that plasma physics effects become important. Many of these effects have been traditionally neglected in the calculation of atomic parameters, and therefore in photoionization models and ultimately also in X-ray reflection models. In this paper, we describe updates to the atomic rates used by the xstar code, which is in turn part of the xillver disk reflection model. We discuss the effect of adding necessary high-density corrections into the xillver code. Specifically, we find that the change of recombination rates plays an important role, dominating the differences between model versions. With synthetic spectra, we show that, even in a highly ionized state, high-density slabs can produce strong iron (∼6.5–9 keV) and oxygen (∼0.6–0.8 keV) resonance features. The significant iron emission could address the problem of the supersolar iron abundances found in some sources.
EIGER. VI. The Correlation Function, Host Halo Mass, and Duty Cycle of Luminous Quasars at z ≳ 6
Authors: Eilers Anna-Christina , Mackenzie Ruari , Pizzati Elia , Matthee Jorryt , Hennawi Joseph F. , Zhang Haowen , Bordoloi Rongmon , Kashino Daichi , Lilly Simon J. , Naidu Rohan P. , Simcoe Robert A. , Yue Minghao , Frenk Carlos S. , Helly John C. , Schaller Matthieu , Schaye Joop
Published: October 2024

We expect luminous (M
1450 ≲ −26.5) high-redshift quasars to trace the highest-density peaks in the early Universe. Here, we present observations of four z ≳ 6 quasar fields using JWST/NIRCam in the imaging and wide-field slitless spectroscopy mode and report a wide range in the number of detected [O iii]-emitting galaxies in the quasars’ environments, ranging between a density enhancement of δ ≈ 65 within a 2 cMpc radius—one of the largest protoclusters during the Epoch of Reionization discovered to date—to a density contrast consistent with zero, indicating the presence of a UV-luminous quasar in a region comparable to the average density of the Universe. By measuring the two-point cross-correlation function of quasars and their surrounding galaxies, as well as the galaxy autocorrelation function, we infer a correlation length of quasars at 〈z〉 = 6.25 of

r

0

QQ

=

22.0

−
2.9

+
3.0

cMpc

h

−
1

, while we obtain a correlation length of the [O iii]-emitting galaxies of

r

0

GG

=
4.1

±
0.3

cMpc

h

−
1

. By comparing the correlation functions to dark-matter-only simulations we estimate the minimum mass of the quasars’ host dark matter halos to be

log

10

(

M

halo
,
min

/

M

⊙

)
=

12.43

−
0.15

+
0.13

(and

log

10

(

M

halo
,
min

[
OIII
]

/

M

⊙

)

=

10.56

−
0.03

+
0.05

for the [O iii] emitters), indicating that (a) luminous quasars do not necessarily reside within the most overdense regions in the early Universe, and that (b) the UV-luminous duty cycle of quasar activity at these redshifts is f
duty ≪ 1. Such short quasar activity timescales challenge our understanding of early supermassive black hole growth and provide evidence for highly dust-obscured growth phases or episodic, radiatively inefficient accretion rates.
Simulated Solar-wind-induced Space Weathering of Olivine Powders: Spectral Alterations in the Ultraviolet, Visible, and Near-infrared
Authors: Jaramillo-Correa Camilo , Pearson Neil C. , Domingue Deborah , Savin Daniel W. , Clark Roger N. , Vilas Faith , Hendrix Amanda R.
Published: October 2024

Bombardment by solar wind ions is one of the main drivers of space weathering on airless bodies. Here, we simulate the solar-wind-driven spectral alteration of loosely packed olivine powders by irradiation with 1.2 keV helium ions (He+). We measured the reflectance spectra of the olivine powder in the ultraviolet–visible–near-infrared (UV–Vis–NIR) wavelength range (0.2–2 μm) as a function of ion fluence. In the Vis–NIR range, we observed spectral darkening, absorption band shallowing, and spectral reddening, in agreement with lunar-style space weathering and previous laboratory studies. In the UV–Vis, spectral darkening was also observed. However, a spectral bluing took place at wavelengths below 400 nm. As the simulated space weathering progressed, the spectral slopes shifted from steep-UV/shallow-NIR slopes to shallow-UV/steep-NIR slopes. Moreover, the change in the UV slope was almost 10 times larger than in the NIR, supporting the hypothesis that the UV spectral slope could be an earlier indicator of space weathering.
Detectability Simulations of a Near-infrared Surface Biosignature on Proxima Centauri b with Future Space Observatories
Authors: Metz Connor O. , Kiang Nancy Y. , Villanueva Geronimo L. , Parenteau M. N. , Kofman Vincent
Published: October 2024

Telescope missions are currently being designed that will make direct imaging of habitable exoplanets possible in the near future, and studies are needed to quantify the detectability of biosignature features in the planet’s reflectance spectrum. We simulated the detectability of a near-infrared-absorbing surface biosignature feature with simulated observations of the nearby exoplanet Proxima Centauri b. We modeled a biosignature spectral feature with a reflectance spectrum based on an anoxygenic photosynthetic bacterial species that has strong absorption at 1 μm, which could make it well suited for life on an M-dwarf-hosted planet. We modeled the distribution of this organism across the planet’s surface based on climate states from a 3D general circulation model (GCM) that were Archean- and Proterozoic-like exo-Earth analogs. We included the GCM states' prognostically simulated water clouds and added organic haze into the Archean-like atmospheres. We simulated observations of these Proxima Centauri b scenarios with the LUVOIR-A and B telescope concepts, with LUVOIR-B serving as a proxy to the planned Habitable Worlds Observatory. We calculated the integration times necessary to detect the biosignature and found that it would be detectable on Proxima Centauri b if the organism is moderately abundant (greater than a 1%–4% global surface area coverage), as long as the atmosphere is transmitting in the wavelength range under consideration. Small amounts of methane, clouds, and haze do not greatly impede detectability. We found preliminary evidence that such a biosignature would be detectable on exoplanets within 15 pc, but further investigations are needed to corroborate this.
Evaluating the Use of Unoccupied Aircraft Systems (UASs) for Planetary Exploration in Mars Analog Terrain
Authors: Carr Brett B. , Varnam Matthew , Hadland Nathan , Shah Jahnavi , Voigt Joana R. C. , Gwizd Samantha , Stack Kathryn M. , Calef Fred , Francis Raymond , Basu Udit , Björnsson Baldur , Chen Colin X. , Dong Elisa , Moersch Jeffrey E. , Phillips Michael , Springer Joshua , Neish Catherine D. , Hamilton Christopher W.
Published: October 2024

Planetary analog mission simulations are essential for testing science operations strategies and technologies. They also teach us how to use terrestrial analogs to inform studies of extraterrestrial environments. Unoccupied aircraft systems (UASs) have great potential for planetary surface exploration as demonstrated by the Mars 2020 Ingenuity helicopter and the in-development Dragonfly mission to Saturn’s moon Titan. Although applications of UAS technology for planetary exploration remain largely unexplored, simulated missions in planetary analog terrains can inform operational best practices. As part of the Rover–Aerial Vehicle Exploration Network project, we simulated a 12 sol UAS mission on Mars in the Holuhraun region of Iceland. The UAS had airborne imaging capability, as well as imaging, sampling, and geochemical analysis capabilities while landed. The mission evaluated the use of these instruments and developed operational strategies for using UASs to explore a planetary surface. Oblique airborne images were essential for mission planning and were used to scout large areas to identify both potential landing sites and targets for focused investigations. The airborne and landed data collected by the UAS allowed for detailed observations and interpretations not possible with analog orbital data sets, resulting in an improved scientific return for the simulated UAS mission compared to a premission analysis of only the analog orbital data. As a planetary exploration vehicle, a UAS is most advantageous for exploring large areas (many square kilometers) and is particularly useful when the terrain may be impassable to ground-based traverses (e.g., by rovers or humans).
Lisibilité et audibilité : le mainstream comme musique accessible
Authors: Mercier-Bellevue Thomas
Published: October 2024

Pour séduire le grand public, la musique mainstream doit être accessible sans effort, comme universellement audible. Cet article soutient toutefois que comme toute appréciation musicale, l’écoute du mainstream relève d’une activité de compréhension qui implique la saisie d’un sens. Après avoir montré que les paroles des chansons mainstream utilisent les stéréotypes pour favoriser leur propre lisibilité, nous nous appuyons sur les travaux de Leonard Meyer pour penser un sens proprement musical. Nous forgeons le concept d’hyperaudibilité pour décrire les procédés par lesquels le mainstream informe l’expérience d’écoute de manière à rendre le sens musical immédiatement disponible.
Crenobalneotherapy in modern Greece, assets and perspectives
Authors: Thymi Ioanna , Kosadinos Emmanuel , Shpak-Deschamps Natalia
Published: October 2024

L’utilisation thérapeutique moderne des sources thermales implique à l’échelle mondiale une gamme diversifiée de dispositifs médicaux et de bien-être. Dans le contexte du thermalisme grec, il existe des perspectives prometteuses pour exploiter ces ressources naturelles. Les efforts de collaboration avec des experts internationaux peuvent aider la Grèce à se placer en première ligne du tourisme thermal et de bien-être. L’intégration de recherches fondées sur des preuves et d’apports médicaux dans l’offre de services liés au thermalisme peut améliorer la crédibilité et l’efficacité de ces traitements. De surcroit, la promotion de la Grèce en tant que destination pour un bien-être holistique, renforcée par les bienfaits thérapeutiques de ses sources thermales, peut attirer un public plus large de visiteurs avertis sur les questions de santé. En s’alignant sur les tendances mondiales et en mettant l’accent sur la qualité et l’innovation, le thermalisme grec peut se positionner comme un leader dans le paysage mondial du thermalisme et du bien-être, sans cesse en évolution.
Global well-posedness of 2D incompressible Navier–Stokes–Darcy flow in a type of generalized time-dependent porosity media
Authors: Tan Linlin , Cheng Bianru
Published: October 2024

This study investigates the global well-posedness of a coupled Navier–Stokes–Darcy model incorporating the Beavers–Joseph–Saffman–Jones interface boundary condition in two-dimensional Euclidean space. We establish the existence of global strong solutions for the system in both linear and nonlinear cases where porosity depends on pressure. When dealing with the time-dependent porous media, the primary challenge in obtaining closed prior estimates arises from the presence of complex, sharp interfaces. To address this issue, we employ the classical Trace Theorem. Such space-time variable coupled systems are crucial for understanding underground fluid flow.
The binary codes generated from quadrics in projective spaces
Authors: Ma Lijun , Liu Shuxia , Tian Zihong
Published: October 2024

Quadrics are important in finite geometry and can be used to construct binary codes. In this paper, we first define an incidence matrix $ M $ based on points and non-degenerate quadrics in the classical projective space PG$ (n-1, q) $, where $ q $ is a prime power. As a consequence, we establish a binary code $ C(M) $ with the generator matrix $ M $ and determine the dimension of $ C(M) $ when $ q $ and $ n $ are both odd. In particular, we study the minimum distances of $ C(M) $ and $ C^{\perp}(M) $ in PG$ (2, q) $ and give their upper bounds.
Bivariate exponentiated generalized inverted exponential distribution with applications on dependent competing risks data
Authors: Sarhan Ammar M. , Gomaa Rabab S. , Magar Alia M. , Alsadat Najwan
Published: October 2024

This paper introduces a novel bivariate distribution derived from the univariate exponentiated generalized inverted exponential (EGIE) distribution, which we term the bivariate exponentiated generalized inverted exponential (BEGIE) distribution. The newly proposed distribution belongs to the Marshall-Olkin class. Several statistical attributes of the BEGIE distribution are explored. The utility of this distribution is examined through applications on both bivariate data and dependent competing risks data. Estimation processes for the model's parameters, using maximum likelihood and Bayesian methods, are outlined for scenarios involving both bivariate and dependent competing risks data. Due to the absence of closed-form solutions for these estimators, numerical optimization techniques are employed. Furthermore, the proposed distribution is illustrated and evaluated through the analysis of three real datasets: two involving bivariate data, and the other involving dependent competing risks data.
Leaving the walls of mental health institutions
Authors: Marquis Nicolas
Published: October 2024

This article offers first of all an analysis of the representation of the person suffering from mental disability or mental disorders which is found in the call for deinstitutionalisation aired by the Committee on the Rights of Persons with Disabilities (United Nations). It then shows how this anthropology, which is at the same time demanding and perfectly in sync with the ideals of a society in which personal autonomy is the right and the duty of each individual, is practically negotiated on the field of a mental health residential facility which provides support for its patients when they leave the institution at the end of their stay. The paper takes as empirical object a central feature of this process, the “partner-meetings” and the conversations taking place between the patient and other actors. The paper shows that, far from the abstraction of juridical texts, the care providers’ perception of the patient as a partner is a fragile process. The partnership is always conditioned, for the care providers, by an absence of worries about the persons’ (in)abilities to look after themselves, and by a demonstration of the latter’s desire for and capacities for autonomy. In these negotiations, the patient in mental healthcare is always potentially, but never completely, the partner in the process of leaving the institution.
Phia Ménard et Claire Massonnet : un binôme artiste – administratrice entre travail et intersubjectivité
Authors: Boivineau Pauline , Langeard Chloé
Published: October 2024

Les métiers relevant de la catégorie des cadres des arts de la scène – les administrateur·rices – restent jusqu’ici peu explorés et par conséquent invisibilisés. De fait, les compagnies comme les directions de lieux labellisés concentrent leur notoriété sur la figure de l’artiste. Si les directeur·rices artistiques définissent les orientations esthétiques de leurs compagnies / structures, les administrateur·rices les inscrivent dans l’économie du spectacle vivant et apparaissent en ce sens comme des piliers de l’organisation. En plaçant la focale sur un tel binôme porteur de la compagnie, il s’agit de repenser la manière dont s’opèrent la division du travail et les rapports de pouvoir autour d’une œuvre en prenant en considération son économie. Dans ce cadre, la collaboration au long cours de Phia Ménard avec Claire Massonnet, administratrice puis codirectrice de la compagnie Non Nova, apparaît comme exemplaire. Il s’agira d’en comprendre la genèse et les ressorts permettant le déploiement fructueux de la compagnie.
« Des choses du tout contraires à leurs sentiments »
Authors: Le Mauff Julien
Published: October 2024

En repartant d’une phrase issue des Mémoires de Richelieu faisant jouer sentiments du prince et raison d’État, il est proposé de retracer l’histoire du lien entre l’exception souveraine et la manière de concevoir les émotions politiques et princières, depuis la fin du Moyen Âge jusqu’au xviie siècle français. Ainsi, par un retour aux états et rapports sensibles qui fondent la politique, et en suivant l’affirmation progressive de la raison d’État et du divorce entre politique et « conscience », peut être mis en évidence le caractère affectif de l’État baroque, constitué comme sujet émotionnel et souverain.
Adapting school physical activity and health surveys for children with disabilities
Authors: Ng Kwok , Asunta Piritta , Kärnä Eija , Rintala Pauli
Published: October 2024

The physical activity (PA) and health behaviours among pupils in special education classes and schools (SECS) is largely understudied. The purpose of this study is to report the process of converting PA and health surveys that can be comparable to the general population. A series of studies were taken. 1. Usability of the survey in SECS, 2. Pilot study data collection, 3. Further testing with a simple version, 4. National data collection among pupils in SECS. Items from the Washington Group Child Functioning Module (CFM) were continuously developed. Data collected at each stage were used to guide the development of each sequential study. Feasibility of conducting data collection were based on time spent and ease of understanding the survey items. Visual analogue scales and simplified items were added. Almost half of the pupils (n=396/889) completed the simplified version and did so within a class period. Teachers reported positively about the administration of surveys. In national representative surveys, it is important to have clear instructions for administering surveys. Pupils in SECS may need assistance to understand the questions in the surveys and more testing is needed to investigate the effects it has on survey completion.
Fake News in History Education
Authors: Moreno-Vera Juan Ramón , Ailincai Aurora , Heckert Fynn , Sabiote-González María
Published: October 2024

The research presented here consists of a toolkit of ten activities to learn history through the use of primary historical sources. The activities allow the students to evaluate the reliability of the sources, foster critical thinking and, lastly, linking the topic proposed with current news and events in the actual days. All the activities suggested follow the method of Civic Online Reasoning (COR) by the Stanford Digital Inquiry Group divided into three differente steps: Contextualization of sources, Analysis of content and corroboration (lateral reading). In this case, the toolkit adds one more step to link the historical topic to nowadays relevant social problems.
Developing Digital Competencies in the Social Science Classroom Through Storymaps and Digital Narratives
Authors: Palomero-Ylardia Irene Magdalena , Mellado-Moreno Pedro C. , Bernal-Bravo César
Published: October 2024

The publication focuses on geolocated digital narratives related to the school curriculum of Social Sciences and their practical application by future teachers of Primary and Secondary Education. In the academic year 2023-2024, as part of an educational innovation project, it has been proposed to carry out an activity with university students to develop digital skills and learn the corresponding curriculum content, using ArcGIS StoryMaps. The activity proposal is presented, and its implementation is analyzed, also providing reflections from university teachers who have implemented it in university classrooms and students' opinions, aiming to consider potential future changes and improvements in the development of the innovation project.
Perceptions of Faculty on Research Productivity
Authors: Onyefulu Cynthia
Published: October 2024

This study investigated lecturers' perceptions of research productivity, factors impacting research productivity, and how to develop lecturers' competencies through teamwork, mentorship, and collaboration to improve research productivity. Five research questions guided the study and were answered using an online questionnaire and document review. The sample size was 31 lecturers from a single university in Jamaica. The results revealed that the rate of research productivity among lecturers has been increasing over the years. The results showed that across the 17 years examined, conference abstracts, presentations, and proceedings were the highest. Peer-reviewed journal papers follow this, with books and book chapters being the least. Lecturers' perceptions of conducting research and publications were reported under motivation, assistance, and mandatory.
Sculpting Educational Excellence
Authors: Thomas Remi John , Sawant Madhuri
Published: October 2024

This paper presents a comprehensive seven-stage conceptual framework for branding in higher education institutions, based on a study conducted in Maharashtra, India. It addresses research gaps in understanding the challenges faced by institutions in this diverse and dynamic setting. Drawing on personal experience, literature review, and marketing theories, the framework guides institutions in brand development and sustainability. The study emphasizes stages such as defining vision and purpose, creating a distinct brand identity, positioning the brand, enhancing awareness and performance, conducting brand audits, and sustaining brand equity. It offers valuable insights for institutions aiming to strengthen their brand presence in the competitive academic landscape.
Ethical Considerations in AI Development for Cloud Computing and Data-Driven Software Solutions
Authors: Gadani Naimil Navnit , Bhattacharya Pronaya
Published: October 2024

As Artificial Intelligence (AI) becomes increasingly integrated into cloud computing and data-driven software solutions, the ethical implications of its development and deployment gain paramount importance. This chapter delves into the complex ethical landscape surrounding AI technologies within these domains. It explores key ethical considerations such as privacy, bias, transparency, accountability, and the potential for misuse of AI-driven systems. The chapter also examines the challenges of ensuring data security and the ethical use of large datasets, emphasizing the need for robust frameworks that balance innovation with responsible AI practices. By analyzing case studies and current regulations, this chapter provides actionable insights and guidelines for developers, researchers, and policymakers to foster ethical AI development in cloud computing and data-driven environments. The aim is to contribute to a sustainable and equitable technological future where AI serves humanity responsibly and justly.
Ethical AI and Decision-Making in Management Leadership
Authors: Manda Vijaya Kittu , Christy Veena , Jitta Mallikharjuna Rao
Published: October 2024

Integrating Ethical Principles into the development and deployment processes becomes essential for management leaders as AI rapidly transforms workplaces. Ethical AI and Decision-Making ensure the alignment of AI applications with human values and societal goals. Fairness, transparency, accountability, privacy, societal impact, and human values are critical ethical principles that guide AI systems. Ethical decision-making models and methodologies offer structured frameworks for balancing competing ethical considerations. AI Ethics Boards provide governance and risk management. Interdisciplinary collaboration, Stakeholder engagement, and Inclusive processes bring diverse perspectives. Risk assessment, Governance Frameworks and mitigation strategies address potential harms and promote Responsible AI practices. By implementing ethical decision-making practices, promoting transparency and accountability, and engaging in responsible AI governance, organizations and leaders can benefit from AI while minimizing ethical risks and maximizing societal benefits.
Balancing Innovation With Responsibility
Authors: Singh Archana , Lakhera Girish , Ojha Megha , Mishra Amar kumar , Nain Arvind
Published: October 2024

The study examined 66 publications through a systematic review employing data mining, and bibliometric techniques. The results show a consistent increase in AI-related e-learning research, especially in the last few years, with major contributions from China, India, and the United States. Thematic analysis using t-SNE uncovers three prominent clusters: (1) the application of AI technologies in E-learning, (2) the utilization of algorithms to recognize, identify, and predict learner behaviors, and (3) the implementation of adaptive and personalized learning through AI. This information can direct the development of strategic methods to deal with obstacles and take advantage of AI-related opportunities in e-learning. In the end, the research aims to provide guidance on tactics that can further AI's development in e-learning.
A Comparative Analysis of Reported Earnings and Information Quality
Authors: Rajan Lalit , Shenoy Sneha
Published: October 2024

This research examines the differences between US GAAP and international financial reporting standards (IFRS) in terms of the quality of reported earnings for US companies listed on both US and European stock exchanges between 2020 and 2023. Regression analysis and descriptive statistics are used in quantitative analysis to assess transparency, relevance, consistency, and reliability of earnings under both standards. Results point to slightly greater consistency over time for US GAAP and higher transparency and accrual quality on average for IFRS. Information quality outcomes are influenced by institutional and cultural factors; IFRS is more flexible in this regard. Promoting uniform disclosures, recognizing the advantages of both standards, and addressing discrepancies in financial reporting are among the recommendations. For stakeholders navigating global financial reporting standards, this study provides insights.
Exploring the Dynamics of DL in WF
Authors: M. G. Pavithra , S. Visnu Dharsini , Sudarsan S. , J. Durga Prasath
Published: October 2024

Recent breakthroughs in AI-powered weather forecasting show impressive accuracy, rivaling traditional methods. However, there remains uncertainty regarding whether these deep-learning models capture atmospheric dynamics or rely solely on pattern matching to minimize forecast errors. Integrating quantum computing particularly quantum networking techniques offers a promising avenue for efficiently handling large and intricate datasets. The authors present a novel forecasting approach that leverages neural networks to generate forecasts across various locations and future timeframes simultaneously. This approach stands out from traditional post-processing methods which rely on specific distributional constraints. Employing quantum computation expedites the processing of vast weather datasets thereby improving the accuracy of predictions. By examining its fundamental architecture, the authors clarify how decisions within each design element align with underlying structural assumptions, providing insights into the mechanisms influencing model performance.
Forging Connections Between AI and Quantum Computing in Decentralized Networks
Authors: Khachariya Haresh D. , Isaac R. Augustian , Sasikala R. , Gokilavani M.
Published: October 2024

The mutually beneficial interaction that exists between artificial intelligence (AI) and quantum computing inside decentralized networks is presented in this research study. This study studies the possibility that artificial intelligence algorithms could improve the distribution of entanglement in quantum networks. Entanglement distribution is an essential component for ensuring secure communication and computation in the quantum domain. Several artificial intelligence (AI) approaches, including machine learning and optimization algorithms, are utilized in this study to offer novel strategies for optimizing entanglement distribution procedures. These strategies will ultimately result in quantum communication protocols that are more efficient and trustworthy. Through the overcoming of existing hurdles and the unlocking of new possibilities for quantum information processing and communication, the combination of artificial intelligence and quantum computing has the potential to revolutionize decentralized networks for the better.
Securing Quantum Web Utilizing Quantum Networks for Enhanced Website Security Assessments
Authors: Penta Chand Kowsik , Mustafa Ataul , Vutukuri Lakshmi Prasanna , Mehta Aashish , P. V. V. S. Srinivas , V. V. S. Sasank
Published: October 2024

The emergence of quantum networks promises revolutionary advancements in communication and computing. However, alongside these opportunities lie potential security vulnerabilities. This research project investigates the integration of quantum networks within website security assessments. The authors propose a novel framework that leverages the unique properties of quantum entanglement and superposition to enhance vulnerability detection and mitigation strategies. The project explores how quantum algorithms can be utilized to identify and exploit previously undetectable weaknesses in website security protocols. Furthermore, it investigates the potential of quantum cryptography for establishing secure communication channels within the website security assessment process. By evaluating the feasibility and limitations of this approach, the project aims to contribute to a more secure future for websites operating in a quantum-enabled internet landscape.
Innovative Visual Cipher
Authors: Singh Nishant Bhaskar , Kumar V. , Ajitha P.
Published: October 2024

Cloud computing's central role in contemporary data storage and sharing escalates the challenge of safeguarding sensitive information. This chapter introduces a groundbreaking approach to file encryption within cloud environments, capitalizing on the concept of noise images and their application in quantum networks and AI. Departing from conventional methods, this approach embeds visual noise patterns into the encryption process, markedly fortifying data security. The study commences with a comprehensive examination of the limitations inherent in traditional encryption techniques within cloud settings, elucidating vulnerabilities like data leakage and unauthorized access. To counteract these vulnerabilities, a pioneering encryption algorithm is presented, seamlessly integrating noise images derived from sophisticated mathematical models. These noise images function as dynamic and unpredictable encryption keys, substantially augmenting the security posture of cloud-stored data.
Interactive Hand Gesture Recognition With Audio Response
Authors: Jeyanthi P. , I. Abdul Ajees , Kumar Abel Priya , P. Vikash Ajin , Revathy S. , L. Mary Gladence
Published: October 2024

This research introduces a comprehensive sign language recognition system designed to address challenges faced by individuals seeking to learn sign language, particularly those with limited access to interactive and varied learning resources. Leveraging machine learning and computer vision technologies, the system integrates advanced hand landmark detection, dataset creation, model training using a random forest classifier and real-time inference. The core technology, powered by Media Pipe Hands, enables real-time capture and processing of hand landmarks for accurate sign language interpretation. This concept differs from classical network technology based on photon or electron transmission. Underlying principles of quantum theory and several aspects of quantum behavior make quantum networking possible. Here are some important quantum principles are incorporated in this project. The project underscores the potential to positively impact the lives of individuals with hearing impairments and contributes to the broader field of accessible communication systems.
Optimizing Project Management With Quantum Networked AI
Authors: Geete Prashant , Almahairah Mohammad Salameh , Raj Vijilius Helena , Laxminarayanamma K. , Nijhawan Ginni , Dhanraj Joshuva Arockia
Published: October 2024

When it comes to managing complex and large-scale systems, traditional design operation methodologies typically suffer from limitations in computational capacity and data processing skill. Combining the immense processing power of quantum computing with the sophisticated logical capabilities of artificial intelligence yields a groundbreaking result in quantum networked artificial intelligence. This community's ability to support real-time data analysis, prophetic modeling, and improved decision-making perfects the efficacy, delicacy, and inflexibility of design processes. This research looks at the potential strategic advantages and performance gains from applying a quantum of networked artificial intelligence at different phases of the design process. Planning, prosecution, monitoring, and completion are some of these phases. In this study, the authors compare typical design operation tools with systems that have been capacity-boosted, highlighting significant improvements in resource allocation.
AI and Quantum Networks for Efficient Supply Chain Management
Authors: Sheeba T. , Verma Rajshree , Sahoo Niranjan , Ayyavaraiah Monelli , Kalyan Nalla Bala , Sharma Pradeep
Published: October 2024

The combination of artificial intelligence (AI) with quantum networks has the potential to bring about a revolutionary change in the operation of force chains, bringing with it undiscovered advantages and the ability to foresee future events. The purpose of this investigation is to investigate the synergistic benefits that artificial intelligence and quantum networks can bring to the optimization of force chain operations. Examples of difficulties that are addressed include demand soothsaying, force operation, and logistics. The purpose of this research is to establish a robust framework that improves real-time decision-making and minimizes functional expenses. This will be accomplished by utilizing the machine literacy algorithms of artificial intelligence and the superior processing capacity of quantum computing. In order to highlight the real operations and benefits of this integration, the study takes a look at case stories from colorful diligence. In addition to this, it provides a balanced perspective on the implications of the technology by discussing the subtle difficulties.
Smart Infrastructure Development Using Quantum Networked AI
Authors: R. M. Jagadish , Mohammed Kahtan A. , Aravinda K. , Ajitha G. , Gupta Manish , Dhanraj Joshuva Arockia
Published: October 2024

The emergence of quantum networked AI has revolutionised city planning, resource management, and social functioning, thereby establishing an unprecedented turning point in numerous domains. Quantum computing and AI-driven networks offer unparalleled processing capabilities, which facilitate real-time data analysis, decision-making, and optimisation. This research implies that the integration of artificial intelligence and quantum computation has the potential to facilitate the creation of intelligent infrastructure systems that are more environmentally friendly, secure, and efficient. Intelligent transportation systems, smart infrastructure, dynamic urban landscapes, and enhanced communication networks are among the most notable applications. Quantum networked AI has the potential to substantially impact infrastructure development in a variety of sectors, including energy management, traffic flow, public safety, and environmental monitoring.
Machine Learning and Molecular Simulation
Authors: Jendoubi Ibtissem , Hendaoui Hamza , Essefi Elhoucine
Published: October 2024

Understanding complex quantum systems with many interacting particles is a major physical challenge. Classical methods struggle due to the exponential increase in complexity as the number of particles increases. This study explores two promising approaches: present an overview of the state-of-the-art research related to molecular dynamics and machine learning. The first approach studies diabaticity using a neural network, which offers richer dynamic properties than atoms. By studying the hybrid calcium system, CaH2, the authors present PESs adiabatic and diabatic of the ground state and the first excited state. As scoop results presented for the first time, detailed analysis identified new approaches to molecular dynamics beyond the Born-Oppenheimer approximation. The second approach tackles the problem from a computational perspective. Machine learning algorithms, particularly interpretable methods such as neural networks (NN) with influence functions, have been explored. This combination aims to achieve efficient solutions while retaining interpretability.
Challenges in the Application of Indicators for Assessment of Effectiveness as a Result of the Digitalisation of Processes in Control Institutions
Authors: Nedyalkova Plamena
Published: October 2024

The assessment of the effectiveness as a result of digitalisation of processes in control institutions is a complex methodological process that requires a combination of knowledge and skills of the persons engaged with it. The complexity also stems from the specifics of the organisation tested and analysed because each institution is an independent body and the digitalisation of processes undergoes different stages and digital transformations influence the respective institution in a different way. This study suggests ЕDPEO as a new indicator for studying the effectiveness resulting from digitalisation of processes in control institutions. The systematic literature review and the analysis of the data from control institutions during the period from 2015 to 2022 resulted in this new and innovative indicator.
Glaucoma knowledge and attitudes among diagnosed participants at a Vhembe clinic, South Africa
Authors: Mathiba Masilo C. , Landela Lerato K. , Metsing Thokozile I.
Published: October 2024

Background: Glaucoma remains a major public health concern worldwide. Most patients are dropping out of care, oblivious to the symptomless nature of glaucoma disease.Aim: This study aimed to investigate glaucoma knowledge and attitudes among those diagnosed with the condition in the Limpopo province (South Africa).Setting: The study was conducted at Elim Hospital in the Vhembe District of the Limpopo province, South Africa.Methods: The design of this study was cross-sectional and quantitative in approach. Those diagnosed with glaucoma and receiving eye care treatment at a district hospital in Limpopo province were purposively selected to participate in the study. Quantitative data on knowledge and attitudes towards glaucoma was collected and analysed using a self-administered questionnaire.Results: Eighty-nine purposively selected glaucoma patients, with an average age of 61.20 ± 14.77 years, participated in the study. Participants had an average knowledge score of 43 ± 20.87, with over 50% demonstrating an understanding of the importance of follow-up care, that treatment can slow the condition, and that the condition can progress rapidly if left untreated. The socio-demographic factors found to be statistically significant in relation to glaucoma knowledge were education and the duration of the condition, with p-values of 0.000 and 0.002, respectively. Concerns regarding the condition were expressed by the majority of participants, totalling 82% (n = 73).Conclusion: Awareness programmes need to be implemented to spread knowledge about the nature of glaucoma and the importance of adherence to treatment among those with low levels of education and newly diagnosed patients.Contribution: Awareness and knowledge regarding glaucoma can assist patients in treatment adherence, alleviation of the disease burden and concerns related to the eventuality of becoming blind.