bluuebunny/crossref_metadata_2025 huggingface dataset:
Como se dividem as cidades? A invenção dos assentamentos informais: notas e conclusões iniciais sobre uma agenda de pesquisa
Authors: Balbim Renato Nunes
Published: February 2024

A pesquisa "Como se Dividem as Cidades? A invenção dos assentamentos informais" investiga a evolução e o contexto geopolítico da terminologia "assentamentos informais", substituindo o termo "slums", frequentemente utilizado para descrever assentamentos urbanos precários. O estudo examina o uso dessa terminologia a nível global e nacional, com foco no Brasil, e explora políticas relacionadas a ela. Além disso, utiliza técnicas culturométricas e bibliométricas para analisar a produção acadêmica sobre assentamentos informais, destacando o crescimento significativo de publicações desde os anos 1990. A pesquisa propõe cinco dimensões da informalidade e examina como o conceito de cidade dividida é reproduzido por agências e organismos internacionais, enfatizando a relação entre informalidade e poder.
Agricultura familiar na América Latina e no Caribe: definições, tecnologia e políticas públicas
Authors: Castro César Nunes de , Pereira Caroline Nascimento
Published: February 2024

A agricultura familiar desempenha um papel fundamental na produção agropecuária, na segurança alimentar e na geração de renda em países da América Latina, embora sua realidade seja diversa tanto entre os países quanto dentro deles. Esta publicação tem como objetivo realizar uma análise comparativa abrangente da agricultura familiar na região, abordando diversos aspectos, desde a identificação dos conceitos até a caracterização do segmento, sua contribuição para a segurança alimentar, padrão tecnológico adotado, mecanismos de financiamento, assistência técnica e extensão rural, e os principais desafios enfrentados. A metodologia da pesquisa inclui revisão bibliográfica e análise de dados coletados, utilizando estatística descritiva e análise espacializada. Os autores planejam divulgar os resultados por meio de um livro, dividido em nove capítulos, que contextualizam o estudo, abordam o conceito de agricultura familiar, apresentam sua caracterização e discutem sua relação com a segurança alimentar.
Politicised Time in Environmental Regulatory Procedure: The Struggles Against the Thabametsi Coal Plant in South Africa
Authors: Deng Yaowen
Published: February 2024

This study revisits the enduring question of temporality in environmental politics, drawing on prognostic politics literature to identify temporality as the practice of making and enacting time claims within institutions at various scales. The research highlights the intersection of time, environmental governance and politicisation within the procedural aspects of environmental impact assessments (EIA) during infrastructure development. The case of South Africa’s Thabametsi coal plant (2014–2017) is examined to understand how disputes over the duration of the Thabametsi EIA shaped interpretations and responses to potential environmental impacts. This case highlights a distinct politicisation of time marked by the strategic deployment of scale. While developers and regulators leveraged national-level legislation to expedite the EIA for uninterrupted project development, environmental activists, influenced by post-apartheid legal norms, enforced a more comprehensive and slow-paced EIA. By scaling down their legal arguments and focusing on project-specific regulations, the activists managed to induce significant delays in the coal plant’s realisation.

This article was published open access under a CC BY licence:
https://creativecommons.org/licences/by/4.0
.
Notes from the Icehouse
Authors: Mseba Admire
Published: February 2024

This article was published open access under a CC BY-NC-ND 4.0 licence:
https://creativecommons.org/licenses/by-nc-nd/4.0/
.
On the Interpretation of XSPEC Abundances and Emission Measures
Authors: Leahy D. A. , Foster A. , Seitenzahl I.
Published: February 2024

The purpose of this work is to describe the assumptions built into the X-ray spectrum fitting software XSPEC for the calculation of element abundances and emission measure of a plasma and to describe the effects when those assumptions are not accurate. The ratio of electron density to hydrogen density in XSPEC is fixed at a constant. The correct ratio can be calculated from the ionization states of the elements. We show the constant value used in XSPEC is valid to within ≃3.5% for a solar-abundance plasma. For a plasma that deviates from solar abundance, e.g., hydrogen-poor or heavy-element-rich plasmas such as those found in the ejecta of supernova remnants, this ratio can be smaller by factors of 0.1–0.001. The hydrogen emission measure, defined by integral of electron density times hydrogen density over plasma volume, is derived from the norm in XSPEC, but one needs to include the hydrogen abundance factor. For other elements, the emission measures are the XSPEC values multiplied by the element abundance factors. Using the correct electron-to-hydrogen ratio and emission measures, we show the correct electron density is smaller by the square root of the correct electron density ratio divided by the XSPEC value. Element densities and total masses (for given distance and volume) are larger by the abundance factors divided by the above square root. Because hydrogen-poor plasmas occur in the ejecta of Type Ia supernova remnants, previously estimated element masses from X-ray spectra are likely to be significantly underestimated.
A Large Jet Narrow-line Seyfert 1 Galaxy: Observations from Parsec to 100 kpc Scales
Authors: Chen Sina , Kharb Preeti , Sasikumar Silpa , Nandi Sumana , Berton Marco , Järvelä Emilia , Laor Ari , Behar Ehud , Foschini Luigi , Vietri Amelia , Gu Minfeng , La Mura Giovanni , Crepaldi Luca , Zhou Minhua
Published: February 2024

We present new 1.5–8.5 GHz Very Long Baseline Array (VLBA) observations and 0.32–1.26 GHz Giant Meterwave Radio Telescope (GMRT) observations of J0354−1340, which is the only known radio-quiet (RQ) or radio-intermediate (RI) narrow-line Seyfert 1 galaxy with a 100 kpc, two-sided radio jet. A parsec-scale, one-sided jet in the southeastern direction from the core emission is found in the VLBA observations, while the kiloparsec-scale jet observed with the Karl G. Jansky Very Large Array (VLA) and GMRT is in the south–north direction. Core spectra on parsec and kiloparsec scales are presented in combination with archival VLA Sky Survey observations at 3.0 GHz and VLA C-configuration observations at 5.5 GHz. The parsec-scale emission dominates the kiloparsec-scale emission above ∼5 GHz, and the spectrum is inverted due to synchrotron self-absorption. This indicates a compact synchrotron source with a size of ∼0.04 pc, which is associated with either the jet base or the corona. A subkiloparsec-scale jet, which is unresolved on scales of ∼3″, probably dominates the emission below ∼5 GHz. Future radio observations can explore the jet structure between the parsec and 100 kpc scales, the origin of their direction mismatch, and the parsec-scale jet proper motion. It remains to be explored how common such large-scale jets are in RQ or RI active galactic nuclei.
Probing the Anisotropy and Non-Gaussianity in the Redshift Space through the Conditional Moments of the First Derivative
Authors: Kanafi M. H. Jalali , Movahed S. M. S.
Published: February 2024

Focusing on the redshift space observations with plane-parallel approximation and relying on the rotational dependency of the general definition of excursion sets, we introduce the so-called conditional moments of the first derivative (cmd) measures for the smoothed matter density field in three dimensions. We derive the perturbative expansion of cmd for the real space and redshift space where peculiar velocity disturbs the galaxies’ observed locations. Our criteria can successfully recognize the contribution of linear Kaiser and Finger-of-God effects. Our results demonstrate that the cmd measure has significant sensitivity for pristine constraining the redshift space distortion parameter β = f/b and interestingly, the associated normalized quantity in the Gaussian linear Kaiser limit has only β dependency. Implementation of the synthetic anisotropic Gaussian field approves the consistency between the theoretical and numerical results. Including the first-order contribution of non-Gaussianity perturbatively in the cmd criterion implies that the N-body simulations for the Quijote suite in the redshift space have been mildly skewed with a higher value for the threshold greater than zero. The non-Gaussianity for the perpendicular direction to the line of sight in the redshift space for smoothing scales R ≳ 20 Mpc h
−1 is almost the same as in the real space. In contrast, the non-Gaussianity along the line-of-sight direction in the redshift space is magnified. The Fisher forecasts indicate a significant enhancement in constraining the cosmological parameters Ω
m
, σ
8, and n

s
when using cmd + cr jointly.
Earth as an Exoplanet. III. Using Empirical Thermal Emission Spectra as an Input for Atmospheric Retrieval of an Earth-twin Exoplanet
Authors: Mettler Jean-Noël , Konrad Björn S. , Quanz Sascha P. , Helled Ravit
Published: February 2024

In this study, we treat Earth as an exoplanet and investigate our home planet by means of a potential future mid-infrared space mission called the Large Interferometer For Exoplanets (LIFE). We combine thermal spectra from an empirical data set of disk-integrated Earth observations with a noise model for LIFE to create mock observations. We apply a state-of-the-art atmospheric retrieval framework to characterize the planet, assess the potential for detecting the known bioindicators, and investigate the impact of viewing geometry and seasonality on the characterization. Our key findings reveal that we are observing a temperate habitable planet with significant abundances of CO2, H2O, O3, and CH4. Seasonal variations in the surface and equilibrium temperature, as well as in the Bond albedo, are detectable. Furthermore, the viewing geometry and the spatially and temporally unresolved nature of our observations only have a minor impact on the characterization. Additionally, Earth’s variable abundance profiles and patchy cloud coverage can bias retrieval results for the atmospheric structure and trace-gas abundances. Lastly, the limited extent of Earth’s seasonal variations in biosignature abundances makes the direct detection of its biosphere through atmospheric seasonality unlikely. Our results suggest that LIFE could correctly identify Earth as a planet where life could thrive, with detectable levels of bioindicators, a temperate climate, and surface conditions allowing liquid surface water. Even if atmospheric seasonality is not easily observed, our study demonstrates that next generation space missions can assess whether nearby temperate terrestrial exoplanets are habitable or even inhabited.
Measuring the Virial Factor in SDSS DR7 Active Galactic Nuclei with Redshifted Hβ and Hα Broad Emission Lines
Authors: Liu H. T. , Feng Hai-Cheng , Li Sha-Sha , Bai J. M. , Li H. Z.
Published: February 2024

Under the hypothesis of gravitational redshift induced by the central supermassive black hole and based on line widths and shifts of redward-shifted Hβ and Hα broad emission lines for more than 8000 Sloan Digital Sky Survey DR7 active galactic nuclei (AGNs), we measure the virial factor in determining supermassive black hole masses. The virial factor had been believed to be independent of accretion radiation pressure on gas clouds in broad-line regions (BLRs) and only dependent on the inclination effects of BLRs. The virial factor measured spans a very large range. For the vast majority of AGNs (>96%) in our samples, the virial factor is larger than the f = 1 usually used in the literature. The f-correction makes the percent of high-accreting AGNs decrease by about 100 times. There are positive correlations of f with the dimensionless accretion rate and Eddington ratio. The redward shifts of Hβ and Hα are mainly of gravitational origin, confirmed by a negative correlation between the redward shift and the dimensionless radius of the BLR. Our results show that radiation pressure force is a significant contributor to the measured virial factor, containing the inclination effects of the BLR. The usually used values of f should be corrected for high-accreting AGNs, especially high-redshift quasars. The f-correction increases their masses by 1–2 orders of magnitude, which will make it more challenging to explain the formation and growth of supermassive black holes at high redshifts.
EIGER IV. The Cool 104 K Circumgalactic Environment of High-redshift Galaxies Reveals Remarkably Efficient Intergalactic Medium Enrichment
Authors: Bordoloi Rongmon , Simcoe Robert A. , Matthee Jorryt , Kashino Daichi , Mackenzie Ruari , Lilly Simon J. , Eilers Anna-Christina , Liu Bin , DePalma David , Yue Minghao , P. Naidu Rohan
Published: February 2024

We report new observations of the cool diffuse gas around 29, 2.3 < z < 6.3 galaxies using deep JWST/NIRCam slitless grism spectroscopy around the sight line to the quasar J0100+2802. The galaxies span a stellar mass range of

7.1
≤

log

M

∗

/

M

⊙

≤
10.7

, and star formation rates (SFRs) of

−
0.1
<
log

SFR/M
⊙ yr−1 < 2.3. We find galaxies for seven Mg ii absorption systems within 300 kpc of the quasar sight line. The Mg ii radial absorption profile falls off sharply with radius, with most of the absorption extending out to 2–3 R
200 of the host galaxies. Six out of seven Mg ii absorption systems are detected around galaxies with

log

M

∗

/

M

⊙

>

9. The Mg ii absorption kinematics are shifted from the systemic redshifts of host galaxies with a median absolute velocity ≈ 135 km s−1 and standard deviation ≈ 85 km s−1. The high kinematic offset and large radial separation (R > 1.3 R
200), suggest that five out of the seven Mg ii absorption systems are not gravitationally bound to their host galaxy. In contrast, most of the cool circumgalactic medium at z < 1 is gravitationally bound. The high incidence of unbound Mg ii gas in this work suggests that toward the end of reionization, galaxy halos are in a state of remarkable disequilibrium, and are highly efficient in enriching the intergalactic medium. The two strongest Mg ii absorption systems are detected at z ∼ 4.22 and 4.5, the former associated with a merging galaxy system and the latter associated with three kinematically close galaxies. Both of these galaxies reside in local galaxy overdensities, indicating the presence of cool Mg ii absorption in two “protogroups” at z > 4.
The Hunt for Perpendicular Magnetic Field Measurements in Plasma
Authors: Jensen Elizabeth A. , Rahmani Yaser , Simpson Jamesina J.
Published: February 2024

The one consistent technique for remotely estimating the magnetic field in plasma has been Faraday rotation. It is only sensitive to the portion of the vector parallel to the propagation path. We show how to remotely detect the portion of the vector that is perpendicular using a modified measurement. Isolating this electromagnetic propagation wave mode to measure the magnetic field enables us to (i) study more about the magnetic field vector in plasma, (ii) reduce error in total electron content measurements, and (iii) discover new magnetic field information from archived data sets. The Appleton–Hartree equation is used to verify a new approach to calculating the phase change to an electromagnetic wave propagating through a plasma at frequencies larger than the gyrofrequency, the cyclotron frequency, and the upper hybrid frequency. Focusing on the perpendicular propagation modes, the simplified equation for the integrated path effect from a perpendicular magnetic field is calculated. The direction of the perpendicular component is unknown, because the magnetic field is squared. Isolating the magnetic term in the equation with dual frequency waves is shown. We also show how to eliminate the magnetic field contribution to total electron content measurements with a similar approach. In combination with Faraday rotation, the degeneracy of the magnetic field vector direction is reduced to a cone configuration.
The AO327 Drift Survey Catalog and Data Release of Pulsar Detections
Authors: Deneva J. S. , McLaughlin M. , Olszanski T. E. E. , Lewis E. F. , Pang D. , Freire P. C. C. , Bagchi M. , Stovall K.
Published: February 2024

The AO327 drift survey for radio pulsars and transients used the Arecibo telescope from 2010 until its collapse in 2020. AO327 collected ∼3100 hr of data at 327 MHz with a time resolution of 82 μs and a frequency resolution of 24 kHz. While the main motivation for such surveys is the discovery of new pulsars and new, even unforeseen, types of radio transients, they also serendipitously collect a wealth of data on known pulsars. We present an electronic catalog of data and data products of 206 pulsars whose periodic emission was detected by AO327 and are listed in the Australia Telescope National Facility catalog of all published pulsars. The AO327 data products include dedispersed time series at full time resolution, average (“folded”) pulse profiles, Gaussian pulse profile templates, and an absolute phase reference that allows phase aligning the AO327 pulse profiles in a physically meaningful manner with profiles from data taken with other instruments. We also provide machine-readable tables with uncalibrated flux measurements at 327 MHz and pulse widths at 50% and 10% of the pulse peak determined from the fitted Gaussian profile templates. The AO327 catalog data set can be used in applications like population analysis of radio pulsars, pulse profile evolution studies in time and frequency, cone and core emission of the pulsar beam, scintillation, pulse intensity distributions, and others. It also constitutes a ready-made resource for teaching signal-processing and pulsar astronomy techniques.
A Study of Broad Emission Line and Doppler Factor Estimation for Fermi Blazars
Authors: Chen Guohai , Zheng Zepeng , Zeng Xiangtao , Zhang Lixia , Xiao Hubing , Liu Xiang , Cui Lang , Fan Junhui
Published: February 2024

In this work, we obtained a sample of 979 Fermi blazars with broad emission lines, including 701 objects collected from published works and 278 objects developed in this work. For the 278 objects, we made a crossmatch from three catalogs, the Fermi Large Area Telescope Fourth Source Catalog (4FGL), the Sloan Digital Sky Survey, and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and calculated the broad-line region (BLR) luminosity. Then, we estimated the Doppler factor and studied the correlations between the BLR luminosities and the γ-ray luminosities, the synchrotron peak frequency (ν

p
), and Doppler factor (δ) for the whole sample. Our analyses and discussions came to the following main conclusions: For the 278 blazars, their BLR luminosity (log L
BLR) ranges from 40.44 to 45.45 erg s−1, with a mean value of 43.39 erg s−1. The Doppler factor ranges from δ = 0.45 to δ = 88.52, with a mean value of 12.99 for the 979 Fermi blazars, which is consistent with the results in the literature. Both the BLR luminosity and the Doppler factor exhibit positive correlations with the γ-ray luminosity. The BLR luminosity is anticorrelated with synchrotron peak frequency, implying a Compton cooling. A line of

log

L
BLR

=
1.58
log

ν
p

−
19.46

separating BL Lacertae objects and flat-spectrum radio quasars was obtained in the diagram of

log

L

BLR

against

log

ν
p

using a machine-learning method. Based on the analysis of the equivalent width and the Doppler factors, we proposed five changing-look blazar candidates.
Trends in the Clinical Presentation of Uveal Melanoma During the COVID-19 Pandemic
Authors: Adams Olufemi E. , Tanke Laurel B. , Mundae Rusdeep , Sodhi Guneet S. , Yu Michael D. , Yonekawa Yoshihiro , Dalvin Lauren A. , Tang Peter H.
Published: February 2024

Background and Objective:

The objective was to evaluate factors associated with clinical presentation of uveal melanoma (UM) during the initial two years of the coronavirus disease 2019 pandemic.

Patients and Methods:

This was a multi-site, retrospective cohort study of patients treated for uveal melanoma during the first (early) and second (late) year of the pandemic compared with the year prior (control).

Results:

A total of 48, 67, and 75 patients were in the control, early, and late cohorts, respectively. The early cohort had a higher frequency of large tumors (control: 29.2%, early: 40.3%, late: 29.3%;
P
< 0.001) at presentation. Both the early and late cohorts had higher rates of enucleation (control: 8.33%, early: 20.9%, late: 18.67%;
P
≤ 0.0338) compared to the control cohort.

Conclusions:

While there was an increase in large tumors along with a rise in enucleation during the first year of the pandemic, enucleation rates remained elevated even while tumor sizes normalized.

[
Ophthalmic Surg Lasers Imaging Retina
2024;55:278–284.]
Innovations in extractable compounds from date seeds: Farms to future
Authors: Alkatheri Asma Hussain , Alkatheeri Mahra Saleh , Cheng Wan-Hee , Thomas Warren , Lai Kok-Song , Lim Swee-Hua Erin
Published: February 2024

Since ancient times, date fruit has been used as a staple food because of its high nutritional value and caloric content. With the development of food science and the application of modern instrumentation, we now know that date seeds contain large amounts of dietary fiber, phenols, polyphenols, amino acids, fatty acids, and many vitamins and minerals. Due to the presence of these functional food ingredients, date seeds are used in various applications, including foods such as bread, hot beverages, cosmetics such as hair and skin products, and as feed for culturing aquatic animals. Date seeds have been used in clinical applications, making use of their antioxidant, anti-inflammatory, anti-cancer, anti-diabetic, and antimicrobial properties. There is now growing awareness of the value of date seeds, which were considered a waste product. In this review, we focused on explaining the major biochemical constituents of date seeds and developing these constituents for various applications. We also highlight the expected developments in date seed use for the future.
An improved composite particle swarm optimization algorithm for solving constrained optimization problems and its engineering applications
Authors: Sun Ying , Gao Yuelin
Published: February 2024

In the last few decades, the particle swarm optimization (PSO) algorithm has been demonstrated to be an effective approach for solving real-world optimization problems. To improve the effectiveness of the PSO algorithm in finding the global best solution for constrained optimization problems, we proposed an improved composite particle swarm optimization algorithm (ICPSO). Based on the optimization principles of the PSO algorithm, in the ICPSO algorithm, we constructed an evolutionary update mechanism for the personal best position population. This mechanism incorporated composite concepts, specifically the integration of the $ \varepsilon $-constraint, differential evolution (DE) strategy, and feasibility rule. This approach could effectively balance the objective function and constraints, and could improve the ability of local exploitation and global exploration. Experiments on the CEC2006 and CEC2017 benchmark functions and real-world constraint optimization problems from the CEC2020 dataset showed that the ICPSO algorithm could effectively solve complex constrained optimization problems.
Enhancing Artistic Learning Through Gamification
Authors: Durán Alejandro Galindo , Fuentes Raquel Sánchez
Published: February 2024

This research collects the results of the gamified didactic proposal of a visit to the archaeological museum of Almería based on the teaching methodology of gamification. The study was carried out with students of the Master's degree in teacher training with the aim of enhancing artistic learning and promoting a museum visit experience completely different from the traditional ones. The proposed methodology focused on the use of gamification elements such as points, achievements, rewards, status, among others, with the aim of increasing the motivation of students and thus developing their artistic potential. During the visit, different challenges were posed such as drawing different points and works of the museum allowing them to explore and discover different historical periods as well as solve different enigmas through their own drawings. The results obtained from the experience showed a high level of satisfaction and motivation, highlighting the significant increase in their creativity and artistic development after the visit.
Escape Room for Organisation Design
Authors: Navarro-del Aguila Irene , de Burgos-Jiménez Jeronimo
Published: February 2024

The main objective of this chapter is to illustrate a current example of a practical experience of gamification by studying a case of application of an escape room to the subject of organisation design, in university studies, specifically the 2nd year of the degree in business administration and management. It will highlight the use of an innovative tool for teaching and learning through an escape room applied to the subject of internationalisation of companies. It will be shown how it is possible to practice gamification within the area of business organisation. With this objective, an escape room will be presented, called “International Development of Nude Project.” This game has been designed so that participants know how to apply the knowledge, skills, and attitudes that enable the understanding of new theories of selection of the most appropriate and effective structure and form for an organisation, taking into account its internal characteristics and the elements of the general and specific environment.
Use of AI-Based Drones in Smart Cities
Authors: Shah Imdad Ali , Jhanjhi Noor Zaman , Brohi Sarfraz Nawaz
Published: February 2024

Autonomous drones, known as AI drones, have been working without human intervention. It is doing something like navigation, avoiding obstacles, and taking picture recognition without explicit human direction, thanks to AI technology. It's an advantage of AI-based drones that they are capable of flying without human intervention. This can be used for missions such as monitoring searches and rescue operations in remote areas where human lives are at risk. Because of their sophisticated cameras and detectors, AI-based drones are able to collect and analyze large amounts of data in real-time. With this data, comprehensive maps may be made, locations of interest can be found, and the situational awareness of human operators can be improved. These days, the concept of a “smart city” intrigues everyone. Advanced technologies such as AI, blockchain, the IoT, drones, and many more are integrated.
Digital Textbook and Educational Outcomes
Authors: Moundy Kamal , Chafiq Nadia , Talbi Mohammed , Bouiri Oussama
Published: February 2024

Educational technology has great potential to confront the challenges encountered in the educational system and place itself at the core of the teaching-learning process. The aim of this study is to use the digital textbook to enhance student learning within an active pedagogy and to strengthen the development of students' academic results. The experiments were carried out in two secondary schools belonging to the Casablanca regional academy in the Kingdom of Morocco. The research samples consisted of 362 students. A methodology describes the process of developing a digital textbook, from scripting to design and use with students. The results showed that developing the digital textbook according to a design and scripting model enabled the authors to design a textbook that could be used by students, with remarkable results. The use of digital textbooks enabled students to improve their educational outcome.
Enhancing Women's Participation in Environmental Leadership
Authors: Al Daraai Salim Bakhit , Al Rahbi Noor
Published: February 2024

This chapter explores the barriers women experience regarding environmental leadership and potential solutions and prospects for boosting female participation. Women continue to be restricted to lower-status occupations, mainly in administrative fields, despite recent efforts to improve gender representation. Multiple reasons contribute to this inequality, including discriminatory practices, inadequate access to resources and opportunities, and societal expectations around gender roles. Efforts to remedy women's underrepresentation in leadership roles should employ various tactics. These can include enacting gender-diverse policies and practices, providing mentorship and support to women seeking progress, and creating opportunities for leadership development. Organisations prioritising diversity and inclusion can foster an inclusive climate that encourages women to take on roles in environmental leadership.
Transfer Learning for Computer Vision
Authors: Khan Qadeem
Published: February 2024

Computer vision has benefited from deep learning, making it possible to create complex systems. Computer vision has seen radical changes using deep learning techniques, specifically transfer learning for computer vision. It enables computers to understand and interpret visual data, such as images and videos, with great precision. Transfer learning in particular, is a deep learning technique that has transformed several areas of computer vision, including face recognition, semantic segmentation, object detection, and image categorization. This powerful technology is essential in applications such as autonomous vehicles, healthcare, surveillance, and more, since it has improved our capacity to identify, locate, and classify objects in images as well as comprehend complex visual scenes. In computer vision, transfer learning is a method that allows us to use previously taught models to tackle new problems. Benefits include shortened training times and efficient feature extraction. This chapter provides a brief help for implementation of transfer learning for computer vision.
Real-Time Pose Recognition for Billiard Players Using Deep Learning
Authors: Chen Zhikang , Yan Wei Qi
Published: February 2024

In this book chapter, the authors propose a method for player pose recognition in billiards matches by combining keypoint extraction and an optimized transformer. Given that those human pose analysis methods usually require high labour costs, the authors explore deep learning methods to achieve real-time, high-precision pose recognition. Firstly, they utilize human key point detection technology to extract the key points of players from real-time videos and generate key points. Then, the key point data is input into the transformer model for pose analysis and recognition. In addition, the authors design a human skeletal alignment method for comparison with standard poses. The experimental results show that the method performs well in recognizing players' poses in billiards matches and provides real-time and timely feedback on players' pose information. This research project provides a new and efficient tool for training billiard players and opens up new possibilities for applying deep learning in sports analytics. In addition, one of these contributions is the creation of a dataset for pose recognition.
Mental Health in Messages
Authors: Dwivedi Dwijendra Nath , Mahanty Ghanashyama
Published: February 2024

In an era dominated by digital communication, textual data offers a treasure of insights into human behaviour and emotions. In today's digitally-driven world, the vast expanse of textual data generated from online interactions serves as a profound indicator of human emotions and behavioural nuances. This research delves deep into the realm of textual sentiment analysis to uncover patterns indicative of mental health states. Through a robust examination of synthetic textual datasets, the study employs advanced techniques to achieve the same. These methods include sentiment analysis, topic modelling, pattern recognition, and emotion detection. By interpreting these digital footprints, this study underscores the potential of textual analysis as a tool not just for understanding, but also for predicting and addressing mental health challenges in digital communication mediums. The findings reveal that digital textual signs can be effective indicators of mental health conditions.
Interventions to Enhance Creativity in the University Context
Authors: Velez Alexander , Alonso Rebeca Kerstin , Martínez-Monteagudo María Carmen
Published: February 2024

The development of creativity in the area of economics and business administration and management at the university level and searches for possible programs or interventions have increased exponentially in recent years. However, no reviews analyzing interventions have been published. The objective of this review was to analyze systematically the development of creativity through the different intervention programs carried out at the university level in the area of economics and business administration and management. A systematic review of PubMed, Web of Sciences, and Scopus was performed according to the PRISMA guidelines. Of the 375 studies initially identified, 15 were fully reviewed, and all interventions were extracted and analyzed. It has been shown that the development of creativity in relation to economics and business administration and management can be promoted in different contexts, and interventions can vary, making it a perfect field for creating and innovating.
Student Attitude and Its Relationship to Study Plan
Authors: Castellanos Magle Sanchez
Published: February 2024

The objective of the present research was to propose a model to describe the relationship between the variables, attitude toward study, and study plan in students in the first semester of higher education based on a simple linear regression analysis. The study approach was quantitative, nonexperimental, and correlational. The sample consisted of 170 students from a Colombian university. The instrument comprised 16 items and covered two dimensions. The data analysis was based on the application of simple linear regression using IBM SPSS software. The most relevant results were the possibility of specifying the relationships between the variables, building the model, and identifying variability of the attitudes with the study planning, constituting a valuable input that should be shared among students for their academic success.
Students´ Perceptions of Using Story Maps in Geography Teaching and Learning
Authors: Ribeiro Vitor P.
Published: February 2024

Geography is the science of space. Students must understand geographic patterns, relationships, and context over the Earth to acquire a spatial perspective and geographical knowledge and skills. Geotechnologies play an important role in reaching those geographic contents and promote spatial thinking. Mapping tools have an unprecedent growth due to the internet development. Teachers can use the potential of geographic information systems (GIS), 2D interactive maps, and 3D virtual globes to teach geography and promote interdisciplinarity. This chapter envisages students' perceptions on using web mapping tools in the process of teaching and learning. Results were obtained by a survey implemented to 30 students of initial teachers training class. Students had to implement a story map during the semester for practical assessment. Students revealed that they had never used story maps before, despite their potential for teaching and learning process and recent developments.
Profile of Academic Use of Smartphones by Postgraduate Students in Manabí, Ecuador
Authors: López-Padrón Alexander , Roig-Vila Rosabel , Rico-Gómez María L.
Published: February 2024

The digital transformation of graduate education in universities faces the challenge of adopting emerging technologies for ubiquitous learning. Therefore, the aim of this chapter was to characterise the profile of academic smartphone use perceived by postgraduate students in the field of education at the Technical University of Manabí (Ecuador). A quantitative methodological approach was adopted for the development of a descriptive research with a non-experimental cross-sectional research design, applying the “Questionnaire Smartphone and University. Student's Vision” to 207 students. As fundamental conclusions, a growing trend towards the academic use of smartphones by postgraduate students in the field of education was corroborated, highlighting their perception of the potential for communication with other students and the teacher, as well as the ubiquitous access to information that this device possesses.
Advances in Literary and (Neuro)Linguistics Skills That Can Contribute to Healing
Authors: Martines Vicent
Published: February 2024

This chapter analyses the influence of bibliotherapy on the perceptions of readers (children, young people, and [older] adults) with special needs on their form of social interaction. By reading and writing, and by explaining to others what they read and write, by talking about plots, by expressing opinions and emotions, feelings and thoughts are articulated, and expressive (linguistic), relational, cognitive, and neurological abilities are improved. From linguistics (theoretical, applied, and cognitive), literary studies, translation/multilingual environments, and pedagogy (literacy, didactics of language, and literature), methodological approaches and interventions that can be useful and effective in bibliotherapy to activate neurocognitive abilities are provided. Furthermore, bibliotherapy is presented as a coherent option for improving the management of situations of confinement, physical, real, voluntary, imposed, or perceived loneliness.
Potential of Digitalization for the Utilization of Artificial Intelligence Models for Uplifting Traditional Marketing Methods
Authors: Dadas Anandrao Bhanudas
Published: February 2024

This chapter intends to inform about the artificial intelligence intervention for enhancing the marketing of products as India is climbing new heights through the “Digital India” movement. Technologies lessen the market gaps globally. There are numerous domains where the digital arm can prove to be efficient. Online shopping and online educational facilities already proved to be sustained during the COVID-19 pandemic. The chapter discusses one of the segments of society among many segments that suffered during the pandemic: women's self-help groups. As a traditional means, women's self-help groups used to sell their products using exhibitions, but the pandemic and frequent lockdowns hampered the marketing strategy of such self-help groups. Digitalization can reach the smallest need, and research can provide need-based directions for application development. This chapter discusses how artificial intelligence can give wings to such women's self-help groups for marketing and market predictions.
Brand Building in the Metaverse
Authors: Anand Arpan , Jindal Priya
Published: February 2024

The metaverse is a shared, virtual space where people can meet and interact with each other. It is a digital world that is built on top of the existing Internet. The Metaverse is still in its early stages of development, but it has the potential to revolutionize the way we communicate, work, and even live. A Metaverse is a place where people can assume any identity they desire. People can create a completely new identity for themselves, or they can use their real name and look just like they do in the real world. Metaverse can be used for a wide range of business applications, including building brands, managing supply chain management, loyalty programs, and developing new online marketplaces. In the meantime, we all have to adjust to living in a world that is gradually becoming more virtual. To understand how the metaverse will change us, it is necessary for us to first comprehend our origins and how they will direct the development of the immersive internet. The metaverse is a space that is created by the combination of virtual reality and augmented reality.
Metaverse Platforms and Entrepreneurs' Emotional Intelligence and Co-Creation Towards Quality Delivery in the Service Industry
Authors: Murugan Marirajan , Prabadevi M. N.
Published: February 2024

The industrial revolution is facilitated by metaverse platforms, which encompass and integrates artificial intelligence (AI), machine learning methodologies (ML), augmented and virtual reality (AVR), industrial internet of things (IIoT), digital business transformation, and cloud computing services in the oil and gas service industries. The researchers conducted a literature analysis, analyzing case studies and concept studies from original equipment manufacturers (OEMs) and oil and gas operational service businesses. This research investigates the correlation between metaverse platforms, emotional intelligence, co-creation, and autonomous systems in relation to project quality and delivery throughout the Industrial Revolution. Scientists undertook an empirical investigation to comprehend the effects of metaverse platforms and entrepreneurs' emotional intelligence in the oil and gas industry during the Industrial Revolution.
Unravelling the Veil
Authors: Komalasari Rita
Published: February 2024

Functional somatic disorders (FSD) are invisible disabilities that require careful investigation due to their unclear biological origins. This chapter investigates the connection between adult FSD symptoms and insecure attachment using a meticulous literature study and data analysis of peer-reviewed studies. Despite challenges, the comprehensive approach revealed intricate patterns in FSD, shedding light on the complex interplay between psychological factors and invisible disabilities. Despite the meticulous analysis, establishing a definitive association between insecure attachment and FSD symptom severity proved elusive. The chapter advocates for future research, emphasizing the need for clarity in terminology, improved measurement techniques, and studies designed to elucidate causal relationships and mechanisms of change. This chapter advocates for heightened awareness and empathy, fostering a future where understanding illuminates the path for individuals navigating the complexities of FSD.
Psychological Impacts, Prevention Strategies, and Intervention Approaches Across Age Groups
Authors: Kushwah Jitendra Singh , Gupta Manju , Shrivastava Saurabh , Saxena Neeta , Saini Ranjeeta , Boopathi Sampath
Published: February 2024

Cyberbullying is a widespread issue that affects people of all ages, causing anxiety, depression, academic decline, social withdrawal, self-esteem issues, substance abuse, and even suicidal tendencies in children. Adults also face significant psychological impacts, affecting professional lives, mental health, and interpersonal relationships. To combat this issue, effective prevention strategies include education on digital citizenship, fostering empathy, and promoting responsible online behavior. Parents, educators, and policymakers play a crucial role in creating safe online spaces. Intervention approaches should be multifaceted and adaptable across age brackets, offering psychological support, counseling services, and helplines.
Exploring the Intersection of Nonprofit and Healthcare Management Leadership
Authors: Nguyen Colton
Published: February 2024

This literature review aims to explore the intricate intersection of nonprofit and healthcare leadership. The current landscape of healthcare disparities poses a question of what challenges for both nonprofit and healthcare leaders are being perpetuated by a lack of organizational preparedness for diversity. Additionally, it explores how nonprofit leaders can benefit from collaborative teams. This literature review delves into the critical question of how leaders in these sectors can provide effective solutions for systemic inequities. Through the analysis of the current body of existing literature, this chapter emphasizes the often-overlooked gender-diverse community. Using a comprehensive analysis, this chapter outlines strategies for nonprofits and healthcare leaders to serve gender-diverse and marginalized communities better. The proposed solutions emphasize the need for lean management and transformative leadership to address burnout, emotional labor, and low engagement among stakeholders.
How Platforms Inadvertently Facilitate Fraud and Cybercrime
Authors: Espinoza Michelle Denise
Published: February 2024

Startup founders do not intentionally create cybercrime havens any more than hoteliers intentionally create drug hotels. Low entry barriers are a prerequisite for platform companies to reach critical mass. These low entry barriers sometimes have unintended consequences. This qualitative multiple-case study examines how platform companies inadvertently facilitate cybercrime. This research contributes to the literature by exploring the understudied problem of how platforms enable cybercrime and contributes to the public discourse on the challenges faced by the global community in combating cybercrime. Addressing the issue is vital for the continued growth of the digital economy and to protect individuals and organizations from the ever-evolving threat landscape. Shedding light on this phenomenon is a step towards developing effective mitigation strategies.
Tackling Depression Detection With Deep Learning
Authors: Krishna N. Bala , Vikas Reddy Reddy Sai , Likhith M. , Priya N. Lasya
Published: February 2024

Traditionally, PHQ scores and patient interviews were used to diagnose depression; however, the accuracy of these measures is quite low. In this work, a hybrid model that primarily integrates textual and audio aspects of patient answers is proposed. Using the DAIC-WoZ database, behavioral traits of depressed patients are studied. The proposed method is comprised of three parts: a textual ConvNets model that is trained solely on textual features; an audio CNN model that is trained solely on audio features; and a hybrid model that combines textual and audio features and uses LSTM algorithms. The suggested study also makes use of the Bi-LSTM model, an enhanced variant of the LSTM model. The findings indicate that deep learning is a more effective method for detecting depression, with textual CNN models having 92% of accuracy and audio CNN models having 98% of accuracy. Textual CNN loss is 0.2 while audio CNN loss is 0.1. These findings demonstrate the efficacy of audio CNN as a depression detection model. When compared to the textual ConvNets model, it performs better.
Implementation of Machine Learning for Smart Wearables in the Healthcare Sector
Authors: Anandaram Harishchander , Gupta Deepa , Priyadarsini Ch. Indira , Christopher Benita
Published: February 2024

Artificial intelligence (AI) and the internet of things (IoT) are two of the world's most rapidly expanding technologies. More and more people are settling in urban areas, and the notion of a “smart city” centres on improved access to high-quality medical services. An exhaustive knowledge of the different brilliant city structures is vital for carrying out IoT and man-made intelligence for remote health monitoring (RHM) frameworks. The advancements, devices, frameworks, models, plans, use cases, and software programmes that comprise the backbone of these frameworks are all essential components. Clinical decision support systems and other variants of healthcare delivery also make use of ML techniques for creating analytic representations. After each component has been thoroughly examined, clinical decision support systems provide personalized recommendations for therapy, lifestyle changes, and care plans to patients. Medical care applications benefit from wearable innovation's ability to monitor and analyse data from the user's activities, temperature, heart rate, blood sugar, etc.