bluuebunny/crossref_metadata_2025 huggingface dataset:
From Halos to Galaxies. IX. Estimate of Halo Assembly History for SDSS Galaxy Groups
Authors: Lyu Cheqiu , Peng Yingjie , Jing Yipeng , Yang Xiaohu , Ho Luis C. , Renzini Alvio , Zhao Dingyi , Mannucci Filippo , Mo Houjun , Wang Kai , Wang Bitao , Xu Bingxiao , Dou Jing , Gallazzi Anna R. , Gu Qiusheng , Maiolino Roberto , Wang Enci , Yuan Feng
Published: August 2024

The properties of the galaxies are tightly connected to their host halo mass and halo assembly history. Accurate measurement of the halo assembly history in observation is challenging but crucial to the understanding of galaxy formation and evolution. The stellar-to-halo mass ratio (M
*/M
h) for the centrals has often been used to indicate the halo assembly time t
h,50 of the group, where t
h,50 is the lookback time at which a halo has assembled half of its present-day virial mass. Using mock data from the semi-analytic models, we find that M
*/M
h shows a significant scatter with t
h,50, with a strong systematic difference between the group with a star-forming central (blue group) and passive central (red group). To improve the accuracy, we develop machine learning models to estimate t
h,50 for galaxy groups using only observable quantities in the mocks. Since star formation quenching will decouple the co-growth of the dark matter and baryon, we train our models separately for blue and red groups. Our models have successfully recovered t
h,50, within an accuracy of ∼1.09 Gyr. With careful calibrations of individual observable quantities in the mocks with Sloan Digital Sky Survey (SDSS) observations, we apply the trained models to the SDSS Yang et al. groups and derive the t
h,50 for each group for the first time. The derived SDSS t
h,50 distributions are in good agreement with that in the mocks, in particular for blue groups. The derived halo assembly history, together with the halo mass, make an important step forward in studying the halo–galaxy connections in observation.
New Synoptic Observations of the Cosmic Optical Background with New Horizons
Authors: Postman Marc , Lauer Tod R. , Parker Joel W. , Spencer John R. , Weaver Harold A. , Shull J. Michael , Stern S. Alan , Brandt Pontus , Conard Steven J. , Gladstone G. Randall , Lisse Carey M. , Porter Simon B. , Singer Kelsi N. , Verbiscer Anne. J.
Published: August 2024

We obtained New Horizons LORRI images to measure the cosmic optical background (COB) intensity integrated over 0.4 μm ≲ λ ≲ 0.9 μm. The survey comprises 16 high-Galactic-latitude fields selected to minimize scattered diffuse Galactic light (DGL) from the Milky Way, as well as scattered light from bright stars. This work supersedes an earlier analysis based on observations of one of the present fields. Isolating the COB contribution to the raw total sky levels measured in the fields requires subtracting the remaining scattered light from bright stars and galaxies, intensity from faint stars within the fields fainter than the photometric detection limit, and the DGL foreground. DGL is estimated from 350 μm and 550 μm intensities measured by the Planck High Frequency Instrument, using a new self-calibrated indicator based on the 16 fields augmented with eight additional DGL calibration fields obtained as part of the survey. The survey yields a highly significant detection (6.8σ) of the COB at 11.16 ± 1.65 (1.47 sys, 0.75 ran) nW m−2 sr−1 at the LORRI pivot wavelength of 0.608 μm. The estimated integrated intensity from background galaxies, 8.17 ± 1.18 nW m−2 sr−1, can account for the great majority of this signal. The rest of the COB signal, 2.99 ± 2.03 (1.75 sys, 1.03 ran) nW m−2 sr−1, is formally classified as anomalous intensity but is not significantly different from zero. The simplest interpretation is that the COB is completely due to galaxies.
Investigating the Mass of the Black Hole and Possible Wind Outflow of the Accretion Disk in the Tidal Disruption Event AT2021ehb
Authors: Xiang Xin , Miller Jon M. , Zoghbi Abderahmen , Reynolds Mark T. , Bogensberger David , Dai Lixin , Draghis Paul A. , Drake Jeremy J. , Godet Olivier , Irwin Jimmy , Miller M. Coleman , Mockler Brenna , Saxton Richard , Webb Natalie
Published: August 2024

Tidal disruption events (TDEs) can potentially probe low-mass black holes (BHs) in host galaxies that might not adhere to bulge or stellar-dispersion relationships. At least initially, TDEs can also reveal super-Eddington accretion. X-ray spectroscopy can potentially constrain BH masses, and reveal ionized outflows associated with super-Eddington accretion. Our analysis of XMM-Newton X-ray observations of the TDE AT2021ehb, around 300 days post-disruption, reveals a soft spectrum and can be fit with a combination of multicolor disk blackbody and power-law components. Using two independent disk models with properties suited to TDEs, we estimate a BH mass at M ≃ 105.5
M
⊙, indicating AT2021ehb may expose the elusive low-mass end of the nuclear BH population. These models offer simple yet robust characterization; more complicated models are not required, but provide important context and caveats in the limit of moderately sensitive data. If disk reflection is included, the disk flux is lower and inferred BH masses are ∼0.35 dex higher. Simple wind formulations imply an extremely fast v
out = −0.2c outflow and obviate a disk continuum component. Assuming a unity filling factor, such a wind implies an instantaneous mass outflow rate of

M

̇

≃
5

M

⊙

yr

−
1

. Such a high rate suggests that the filling factor for the ultrafast outflow (UFO) must be extremely low, and/or the UFO phase is ephemeral. We discuss the strengths and limitations of our analysis and avenues for future observations of TDEs.
Velocity-resolved Ionization Mapping of Broad Line Region. I. Insights into Diverse Geometry and Kinematics
Authors: Li Sha-Sha , Feng Hai-Cheng , Liu H. T. , Bai J. M. , Ji Xiang , Pang Yu-Xuan , Cheng Cheng , Lu Kai-Xing , Wang Jian-Guo , Li Rui
Published: August 2024

Broad emission lines of active galactic nuclei (AGNs) originate from the broad-line region (BLR), consisting of dense gas clouds in orbit around an accreting supermassive black hole. Understanding the geometry and kinematics of this region is crucial for gaining insights into the physics and evolution of AGNs. Conventional velocity-resolved reverberation mapping may face challenges in disentangling the degeneracy between intricate motion and geometry of this region. To address this challenge, new key constraints are required. Here, we report the discovery of an asymmetric BLR using a novel technique: velocity-resolved ionization mapping, which can map the distance of emitting gas clouds by measuring Hydrogen line ratios at different velocities. By analyzing spectroscopic monitoring data, we find that the Balmer decrement is anticorrelated with the continuum and correlated with the lags across broad emission line velocities. Some line ratio profiles deviate from the expectations for a symmetrically virialized BLR, suggesting that the redshifted and blueshifted gas clouds may not be equidistant from the supermassive black hole (SMBH). This asymmetric geometry might represent a formation imprint, provide new perspectives on the evolution of AGNs, and influence SMBH mass measurements.
ϵ Sagittarii: An Extreme Rapid Rotator with a Decretion Disk
Authors: Bailey Jeremy , Lewis Fiona , Howarth Ian D. , Cotton Daniel V. , Marshall Jonathan P. , Kedziora-Chudczer Lucyna
Published: August 2024

We report high-precision, multiwavelength linear-polarization observations of the bright B9 (or A0) star ϵ Sagittarii. The polarization shows the distinctive wavelength dependence expected for a rapidly rotating star. Analysis of the polarization data reveals an angular rotation rate ω (=Ω/Ωcrit) of 0.995 or greater, the highest yet measured for a star in our Galaxy. An additional wavelength-independent polarization component is attributed to electron scattering in a low-density, edge-on gas disk that also produces the narrow absorption components seen in the spectrum. Several properties of the star (polarization due to a disk, occasional weak Hα emission, and multiple periodicities seen in space photometry) resemble those of Be stars, but the level of activity in all cases is much lower than that of typical Be stars. The stellar properties are inconsistent with single-rotating-star evolutionary tracks, indicating that it is most likely a product of binary interaction. The star is an excellent candidate for observation by interferometry, optical spectropolarimetry to detect the Öhman effect, and ultraviolet polarimetry, any of which would allow its extreme rotation to be tested and its stellar properties to be refined.
FAST Detection of OH Emission in the Carbon-rich Planetary Nebula NGC 7027
Authors: Ouyang Xu-Jia , Zhang Yong , Zhang Chuan-Peng , Jiang Peng , Nakashima Jun-ichi , Chen Xi , Qiao Hai-Hua , Zhang Xu-Ying , Sun Hao-Min , Li Xiao-Hu , Zijlstra Albert
Published: August 2024

We present the first detection of the ground-state OH emission line at 1612 MHz toward the prototypical carbon-rich planetary nebula (PN) NGC 7027, utilizing the newly installed ultrawideband (UWB) receiver of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). This emission is likely to originate from the interface of the neutral shell and the ionized region. The other three ground-state OH lines at 1665, 1667, and 1721 MHz are observed in absorption and have velocities well matched with that of HCO+ absorption. We infer that the OH absorption is from the outer shell of NGC 7027, although the possibility that they are associated with a foreground cloud cannot be completely ruled out. All the OH lines exhibit a single blueshifted component with respect to the central star. The formation of OH in carbon-rich environments might be via photodissociation-induced chemical processes. Our observations offer significant constraints for chemical simulations, and they underscore the potent capability of the UWB receiver of FAST to search for nascent PNe.
Hidden in the blow - a matrix to characterise cetaceans’ respiratory microbiome: short-finned pilot whale as case study
Authors: Santos Beatriz , Afonso Luís , Alves Filipe , Dinis Ana , Ferreira Rita , Correia Ana M. , Valente Raul , Gil Ágatha , Castro Luis Filipe C. , Sousa-Pinto Isabel , Rosso Massimiliano , Centelleghe Cinzia , Mazzariol Sandro , Magalhães Catarina , Tomasino Maria Paola
Published: August 2024

Cetaceans are key sentinel species of marine ecosystems and ocean health, being a strategic taxonomic group that evaluates the well-being of aquatic habitats and detects harmful environmental trends. Respiratory diseases are amongst the main causes of death in these animals, so identifying the microbiome community in their exhaled breath condensates (EBC), i.e. blow, has been proposed as a key biomarker for assessing respiratory health. Yet, to characterise microbiomes related to these animals’ respiratory tract and use them as a proxy for health status, it is necessary to develop baseline data on the microorganisms associated with cetaceans. Here, the short-finned pilot whale (SFPW, Globicephala macrorhynchus) was used as a case study to validate the most suitable primer set to explore the prokaryotic diversity of the cetaceans’ respiratory tract. DNA extracted from blow samples (n = 12) of animals off Madeira Island was sequenced to amplify both V3-V4 and V4-V5 hypervariable regions of the 16S rRNA gene, using the same sequencing platform (Illumina MiSeq). Independently of the primer set used, all blows shared Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria phyla in their composition. V3-V4 resulted in a higher diversity of taxa with relative abundance above 1%, whereas the V4-V5 primers captured a higher number of microbial Amplicon Sequence Variants, detecting the rare microbial biosphere with pathogen potential. Additionally, it captured the core microbiome more efficiently. Thus, this study provides a detailed characterisation of SFPW respiratory-associated microbial communities, strengthening the idea of sociality influencing microbiome composition in the respiratory tract. Moreover, it supports the use of blow as a relevant biomarker for the physiological state of the airways in free-ranging cetaceans.
Statistical inference for the bathtub-shaped distribution using balanced and unbalanced sampling techniques
Authors: Hassan Nuran M. , Nagy M. , Dutta Subhankar
Published: August 2024

In order to reduce errors and enhance precision while estimating the unknown parameters of the distributions, it is crucial to choose a representative sample. The common estimation methods that estimate the parameters associated with the bathtub-shaped distribution include maximum likelihood (ML), maximum product of spacings estimation (MPSE), and Cramér-von Mises estimation (CME) methods. However, four modifications are used with the sample selection technique. They are simple random sampling (SRS), ranked set sampling (RSS), maximum ranked set sampling (MaxRSS), and double ranked set sampling (DBRSS), which is due to small sample sizes. Based on the estimation methods such as ML, MPSE, and CME, the ranked set sampling techniques do not have simple functions to manage them. The MaxRSS matrix has variable dimensions but requires fewer observations than RSS. DBRSS requires a greater number of observations than MaxRSS and RSS. According to simulation studies, the RSS, MaxRSS, and DBRSS estimators were more effective than the SRS estimator for different sample sizes. Additionally, MaxRSS was discovered to be the most efficient RSS-based technique. Other techniques, however, proved more effective than RSS for high mean squared errors. The CM method estimated the true values of the parameters more accurately and with smaller biases than ML and MPSE. The MPSE method was also found to have significant biases and to be less accurate in estimating the values of the parameters when compared to the other estimate methods. Finally, two datasets demonstrated how the bathtub-shaped distribution could be feasible based on different sampling techniques.
Efficiency conditions in multiple-objective optimal control models under generalized hypotheses
Authors: Treanţă Savin , Marghescu Cristina-Florentina , Matei Laura-Gabriela
Published: August 2024

Since not every problem in optimization theory involves convex functionals, in this study, we introduced new classes of generalized convex functionals. More precisely, under generalized hypotheses, we stated new efficiency conditions associated with a class of multiple-objective optimal control models. To this end, we first defined the $ G_{\theta} $-Fritz John problem and, by considering it, we established a link between the solutions of $ G_{\theta} $-Fritz John problem and efficient solutions of the considered model $ (P) $. In addition, we formulated the $ G_{\theta} $-necessary efficiency conditions for a feasible solution in $ (P) $. After that, we established a connection between the newly defined concept of $ G_{\theta}-KT $ points to $ (P) $ and the efficient solutions of $ (P) $. Finally, we turned our attention to the $ G_{\theta} $-sufficient efficiency conditions for a feasible solution to $ (P) $. More precisely, we established that any feasible solution to $ (P) $ will be an efficient solution if the assumption of $ G_{\theta} $-convexity (and/or $ G_{\theta} $-quasiconvexity, $ G_{\theta} $-strictly quasiconvexity, $ G_{\theta} $-monotonic quasiconvexity) is imposed on the involved functionals.
Revitalization of cultural heritage in the digital era: A case study in Taiwan
Authors: Ng Wai-Kit , Chen Chun-Liang , Huang Yu-Hui
Published: August 2024

Cultural heritage organizations worldwide face daunting challenges, grappling with workforce shortages and financial constraints that often result in service closures, postponements, or cancellations. In response to these difficulties, we delved into the evolving interaction between cultural heritage sites and society, especially considering the profound socio-economic repercussions of the global pandemic at these sites. We scrutinized the dynamic heritage of community engagement, with a particular focus on pioneering methods to augment the participation and awareness of younger individuals. We focused on innovative methods to enhance the involvement and awareness of young individuals. Employing a comprehensive content analysis through a multiple case study approach, cultural heritage initiatives in Taiwan were investigated, emphasizing the pivotal role of technology and digital platforms in engaging young audiences. Using a comprehensive content analysis approach within a multiple case study framework, we examined various cultural heritage initiatives in Taiwan. Notably, we accentuated the crucial role played by technology and digital platforms in captivating younger audiences. Through theoretical sampling and triangulation methods, including semi-structured interviews, secondary sources, and participant observation, we sought to obtain a holistic understanding of the subject matter. The research findings underscore the pivotal importance of digital experiences as supplements to physical presence, providing a gateway to cultural heritage exploration. Moreover, we advocate for heritage sites to harness digital platforms effectively, encouraging collaborations with external partners to enrich visitor experiences. We also offer valuable recommendations aimed at enhancing customer engagement and communication with the younger demographic, thus making significant contributions to the cultural heritage sector in Asia. Furthermore, this research signifies a notable transition from traditional physical service design to online platforms, leveraging technology to inspire and engage diverse generations. By embracing digital tools, cultural heritage sites not only attract new visitors but also retain the interest of existing ones amidst an ever-evolving societal landscape. Ultimately, this study sheds light on the imperative nature of cultural heritage preservation and adaptation in the face of contemporary challenges, emphasizing the need for innovation and resilience in this vital sector.
Effects of planting density on branching habit in common and Tartary buckwheat
Authors: Kasajima Shinya , Watanabe Wakana , Kitade Maki , Itoh Hirotake
Published: August 2024

This study investigated the effects of planting density on the branching habit of common and Tartary buckwheat. A field experiment was conducted using a split-plot design with three replicates, comparing sparse (67 plants m−2), moderate (111 plants m−2), and dense (222 plants m−2) planting densities in ‘Kitawasesoba’ (common) and ‘Manten-Kirari’ (Tartary) buckwheat varieties. Growth characteristics were examined at the stages of flower bud appearance, full flowering, and maturity. Results revealed that planting density had no significant effect on main stem length but showed significant effects on the number of branches in both species. As planting density increased, the number of branches decreased, with Tartary buckwheat exhibiting more significant changes in response to planting density than common buckwheat. The number of flower clusters on branches also decreased with increasing planting density. These findings suggest a potential role for branching plasticity in adapting to different planting densities while maintaining stable yields and indicate the importance of developing ideotypes with optimal branching habits for both species. This research contributes to a better understanding of buckwheat ideotypes and can contribute to future breeding efforts and crop management practices.
A Historical Review on the Oldest Documented Buckwheat Use in Korea
Authors: Park Cheol Ho , Park Min Ook
Published: August 2024

‘Hyangyakgugeubbang’ has been known as the oldest literature on buckwheat in Korea written in the time of King Gokong, old Korean dynasty. However, by ‘Genesis of Koguryo dynasty’ copied by Mr. Chang Hwa Park, it has been known that buckwheat has been used in Korea from Koguryo dynasty which was a former era of old Korean dynasty. Unfortunately, the original book of ‘Genesis of Koguryo’ has not been kept and thus historians have not approved the copied book as an official history book. Therefore, the oldest record on buckwheat use in Korea has not been recognized as the oldest book on buckwheat in Korea. So, Hyangyakgugeubbang’ is still officially the oldest book on buckwheat in Korea.
Climate Finance and Economic Development
Authors: Sharma Suraj , Biswas Bappaditya
Published: August 2024

This study examines the Environmental Kuznets Curve (EKC) hypothesis, which suggests that carbon and greenhouse gas emissions initially rise with urbanization and industrialization but eventually decrease as economic development progresses. Focusing on India and G7 countries from 2003 to 2022, the analysis employs the PMG-ARDL model to investigate short-run convergence in carbon and total greenhouse gas emissions. The findings indicate significant convergence in emissions for both India and the G7, suggesting similar emission patterns over time. The study also reveals that domestic credit to private firms is significantly and positively associated with increased emissions, highlighting the role of financial development in environmental degradation. Conversely, alternative energy sources and labor contributions are found to significantly reduce carbon emissions in the long run. These results underscore the complexity of balancing economic development with environmental sustainability and the critical importance of policy measures that promote green energy and sustainable practices.
Corruption and Environmental Degradation
Authors: Kaur Harmanpreet , Singh Karambir , Kaur Arvinder
Published: August 2024

This study explores the links between environmental degradation, corruption, and obstacles to effective climate action. It highlights how corruption undermines legal systems, fosters illegal activities, and hinders resource distribution, worsening environmental damage. The report emphasizes that corruption impedes climate policy implementation and projects through financial mismanagement, bribery, and regulatory capture, obstructing the low-carbon transition and eroding public trust. To address these challenges, the study proposes a multifaceted approach, incorporating robust anti-corruption laws, transparent governance, and international cooperation. Strengthening institutional structures, promoting accountability, and enhancing civil society's role in monitoring climate actions are essential. Cultivating integrity and ethical conduct in both public and private sectors is crucial. The conclusion underscores the necessity of understanding and addressing the interconnectedness of corruption, environmental degradation, and climate challenges through a comprehensive, collective effort.
CSR Objectives and Public Institute Management in the Republic of Slovenia
Authors: Pramanik Sabyasachi
Published: August 2024

The main focus of this chapter is the manner in which some significant human rights are granted via managerial choices made in public institutions. While the phrase corporate social responsibility (CSR) generally refers to companies, the study suggests that CSR encompasses a broader range of groups, not only commercial enterprises. There is no official form of profit organization (i.e., corporation or company) in public institutions. These include establishments like elementary, grammar, and high schools; graduate and postgraduate schools (public universities); public hospitals (general hospitals and clinical centers); research centers; old people's homes or nursing homes; theaters; public radio and television; public health insurance and mandatory retirement insurance; and so on. Many human rights are addressed via the social services that are offered by government agencies. Bridging human rights with corporate social responsibility emphasizes the need for public institutions to make constructive contributions to society.
An In-Depth Examination of the Application Gap and Infrastructure Landscape of Information Communication Technology in Ethiopian Public Organizations
Authors: Mishra Nilamadhab , Nayak Rudra Kalyan , Habtemariam Getachew Mekuria , Tripathy Ramamani , Esseynew Seblewongel , Motwani Anand , Rout Saroja Kumar
Published: August 2024

This case-based analysis delves into the intricate web of challenges surrounding the adoption and utilization of information communication technology (ICT) in Ethiopian governmental organizations. By employing a comprehensive framework, the study aims to identify and dissect the prevailing application gap, elucidating the factors contributing to the existing disparities in ICT implementation across various government sectors. The research adopts a qualitative approach, leveraging case studies from diverse governmental organizations to capture the nuanced intricacies of the current ICT landscape. The findings from this study contribute valuable insights to policymakers, organizational leaders, and ICT professionals, offering pragmatic recommendations to bridge the application gap and enhance the ICT infrastructure in Ethiopian governmental organizations.
Conflict Resolution Through Ethical Leadership and Legal Frameworks in Global Organizations
Authors: Jay Ashli D. , Hilton Marsha
Published: August 2024

This work explores the integration of ethical leadership and legal frameworks in conflict resolution within organizations. By combining ethical principles with compliance to legal standards, organizations can create robust conflict resolution strategies that not only address disputes effectively but also prevent them by fostering a culture of transparency, accountability, and fairness. The study highlights various models and frameworks, practical strategies, and case studies from leading companies like Google and Barclays to demonstrate the tangible benefits of this integrated approach. Key findings reveal that such integration reduces conflict frequency, enhances employee satisfaction, and strengthens organizational reputation. The work also discusses the challenges of aligning ethical and legal standards, provides recommendations for practitioners, and emphasizes the importance of continuous improvement and adaptation in conflict resolution practices. This comprehensive approach ensures sustainable organizational outcomes and positions companies for long-term success.
Transformative Mediation as a Tool for Facilitated Conversations in Intrapersonal and Interpersonal Conflicts
Authors: Hilton Marsha
Published: August 2024

This study explores the integration of psychological insights into conflict resolution practices in multicultural cities. Through case studies in New York, London, Toronto, and Sydney, the research examines the role of emotional intelligence, cognitive flexibility, and transformative mediation in resolving conflicts. The methodology includes qualitative case study analysis, with data collected through interviews, focus groups, observations, and document analysis. Key findings highlight common themes such as the influence of stress, cultural identity, and facilitated conversations in conflict dynamics. The study underscores the importance of tailored conflict resolution strategies that consider psychological factors and cultural contexts. Implications for future research and practical applications in various settings are discussed, emphasizing the need for continuous adaptation and culturally sensitive approaches in conflict resolution practices.
Peace-Oriented Leadership Training Predicts School Board Members' Effectiveness
Authors: Pollack Jeremy , Parks-Stamm ELizabeth
Published: August 2024

School boards in the United States have become a battleground for contentious local and national issues. As elected officials, school board members often lack training in leadership and conflict resolution. Training that does exist often fails to develop the competencies that research in peace psychology suggests are essential to building positive peace. The authors present a framework derived from peace psychology and the organizational literature including three social psychological needs (i.e., trust, inclusion, and psychological safety; TIS) and five competencies that help meet these needs (patience, engagement, appreciation, curiosity, and empowerment; PEACE). They surveyed 72 school board members from 36+ towns in Maine about their training, competencies, preparedness, effectiveness, positive relationships, and feelings of being emotionally drained. Regression analyses confirmed the importance of formal training for their preparedness and effectiveness.
Data Mining and Knowledge Discovery
Authors: Mishra Akshat Shree , Vijaya J.
Published: August 2024

This chapter proposal aims to explore the transformative potential of data mining and knowledge discovery in healthcare, focusing on optimizing healthcare computing systems, integrating technologies like AI and IoT, and emphasizing patient-centric care. It delves into precision medicine, disease pathways, and current trends in health and disease, while addressing concerns around privacy, biases, and responsible data use. The methodology includes a systematic review of healthcare computing systems and real-world case studies. The chapter advocates for interdisciplinary collaboration and ethical frameworks, concluding with a discussion on future directions and challenges to inspire a future of data-driven, patient-centered healthcare.
Artificial Intelligence in Records Structures Research
Authors: Immaculate Rexi Jenifer P. , Rajakumaran M. , Dennis Ananth A. , Markkandeyan S. , Gokila R. G.
Published: August 2024

AI has received expanded interest from the data systems (IS) studies network in recent years. There is, however, a developing difficulty that studies on AI should enjoy a loss of cumulative building of information, which has overshadowed IS research formerly. This look at addresses this subject, by way of engaging in a scientific literature overview of AI studies in IS between 2005 and 2020. The seek approach ended in 1877 research, of which 98 had been diagnosed as primary research and a synthesise of key issues which might be pertinent to this take a look at is presented. In doing so, this has a look at makes important contributions, namely (i) an identification of the modern mentioned enterprise price and contributions of AI, (ii) research and sensible implications on the use of AI and (iii) opportunities for destiny AI studies inside the shape of the AI research.
Early Detection of Skin Cancer Using Convolutional Neural Networks
Authors: Bose Shukraditya , Megala G. , Valluvan Raghupathyraj
Published: August 2024

The substantial health risks associated with skin cancer make early detection techniques imperative. In this work, we investigate using convolutional neural networks (CNNs) to identify skin cancer. By utilizing the vast HAM10000 dataset comprising various skin lesion images, we aim to create a robust artificial intelligence model to classify pictures accurately. Our approach preprocesses image data, adjusts the Xception architecture, and uses data augmentation techniques to improve model performance. The model's efficacy is evaluated using accuracy, precision, recall, and F1-score metrics. With possible benefits for bettering patient outcomes and healthcare delivery, this research advances automated diagnostic tools for skin cancer detection.
Efficient Brain Tumor Classification With Optimized Hybrid Deep Neural Networks
Authors: Sanjay V. , Megala G. , Balaji Vuppala
Published: August 2024

Segmentation is an important stage in the processing of images. Following pre-processing, segmentation methods are used to isolate the tumor region from the MRI images. It's one of the most crucial CAD procedures from the perspective of medical imaging. The challenges in segmenting the tumor area is overcome by using the semantic segmentation method, in which each pixel in an image receives a name or classification. It is used to recognize collections of pixels that stand in for different categories. Semantic Segmentation is proposed which is used to separate the tumor region and then the deep learning classification is done using Augmented Radial Basis Function Network (ARBFNs) based deep learning, Long Short Term Based Recurrent Neural Network (LSTM-RNN) methodology and Regularized Convolutional Neural Network with Dimensionally Reduction Module (RCNN-DRM) architecture. The proposed algorithm providing 95% accuracy on training data.
Review on Facial Emotion Recognition Using Deep Learning With Multiple Databases
Authors: Mal Hari Prasad , Swarnalatha P. , Kaneswaran Anantharajah , Prabu S.
Published: August 2024

Facial expression-based automatic emotion recognition is an intriguing field of study that has been presented and used in a variety of contexts, including human-machine interfaces, safety, and health. In order to improve computer predictions, researchers in this field are interested in creating methods for interpreting, coding, and extracting facial expressions. Deep learning has been incredibly successful, and as a result, its various architectures are being used to improve performance. This paper aims to investigate recent advances in deep learning-based automatic facial emotion recognition (FER). We highlight the contributions addressed, the architecture, and the databases employed. We also demonstrate the advancement by contrasting the suggested approaches with the outcomes attained. This paper aims to assist and direct researchers by reviewing current literature and offering perspectives to advance this field.
Myeloid-Derived Suppressor Cells and Macrophage Polarization in Cancer Immunotherapy
Authors: Hosseini Mohammad-Salar , Akbarzadeh Mohammad Amin , Jadidi-Niaragh Farhad
Published: August 2024

Myeloid-derived suppressor cells (MDSCs) and macrophage polarization are key functional components of the immune system in shaping the tumor microenvironment (TME) and modulating immune responses. MDSCs, characterized by their heterogeneity and potent immunosuppressive functions, negatively affect anti-tumor immunity by inhibiting T cell activation, promoting regulatory T cell (Treg) expansion, and enhancing tumor growth and metastasis. Similarly, macrophage polarization into M1 (classically activated) and M2 (alternatively activated) phenotypes significantly influences tumor progression, with M2 macrophages facilitating immunosuppression, angiogenesis, and tissue remodeling. Therapeutic strategies targeting these cells focus on depleting MDSCs, reprogramming macrophages from the M2 to M1 phenotype, and disrupting their recruitment and activation signals within the TME. This chapter explores the complex biology of MDSCs and polarized macrophages, their interactions within the TME, their impact on cancer progression and treatment outcomes, and the future landscape of this field.
Exploring the Indian Solid Waste Regime in 2024
Authors: Dhaundhiyal Chandramauli , Kholiya Deepak , Vinayak Siddhi , Dhaundiyal Nulaa
Published: August 2024

This research aims to contribute to the development of literature and policy analysis required for the development of a comprehensive and integrated SWM system in Tier 2 cities, aligning with the national goals of cleanliness and public health. The chapter has two main objectives. The first objective is to deconstruct the policy framework governing SWM in the chosen Tier 2 city. The case study approach helps highlight potential disconnects between policy and on-ground practices. The study explores the infrastructure limitations in Tier 2 cities, including and not limited to insufficient funding, outdated technology, and limited waste processing capacity. The chapter concludes by suggesting areas for further research and offering policy recommendations for bridging policy gaps, bolstering infrastructure, and fostering community engagement in SWM. Future research can delve deeper into specific aspects of the framework. Additionally, the learnings from this study can potentially inform practical solutions for managing solid waste in developing nations facing similar challenges.
Selective Garbage Collection as a Model for Addressing Solid Waste Accumulation
Authors: Musendekwa Menard
Published: August 2024

This chapter investigates the effectiveness of selective garbage collection as a model for addressing solid waste accumulation and advocates for increased municipal participation in solid waste management and recycling in Zimbabwe. Solid waste management presents a significant challenge in Zimbabwe, exacerbated by rapid urbanization and population growth. Conventional waste management practices have proven inadequate in managing the escalating volumes of waste, leading to environmental degradation, public health risks, and economic burdens. In response to these challenges, selective garbage collection has emerged as a promising approach to waste management, involving the sorting of waste at its point of origin into different categories such as recyclables, organic waste, and non-recyclables.
Innovative Approaches to Sustainable Waste Management and Energy Generation in Developing Nations
Authors: Verma Sunil Kumar , Singh Devendra , Misra Sankalp
Published: August 2024

Across the globe, solid waste is regarded as one of the main contaminants of surface and freshwater. The primary causes of solid waste generation are the world's expanding population, urbanization, and industrialization. This has grown to be a significant issue with regional and global ramifications. Globally, 2.01 BT (billion tons) of municipal solid garbage are produced annually, of which over 33% need to be managed environmentally. To solve this, achieving sustainability requires effective solid waste management, particularly when it comes to recycling waste goods. Only 16% of waste can be recycled in low-income countries, compared to 51% in high-income countries. Environmental and societal issues can only get worse when solid waste management techniques are inadequate. To address these problems, solid waste is converted to energy via thermochemical and biochemical processes. An in-depth examination of energy recovery and solid waste management in developing nations is given in this chapter.
Stress Among the Undergraduate Students in Public Universities in Kenya
Authors: Onderi Peter Omae , Moracha Samson N. O. , Opondo Christine Mwajuma , Omare Justine Momanyi
Published: August 2024

Stress is an emotional feeling of tension. Stress is the body's reaction to a challenge or demand. The arising struggles of life in developing countries of the world has led to the increase of stress in instructions of higher learning. The purpose of this study is to find out the major causes of stress amongst students of higher learning in public universities in Kenya. The study investigated the causes of stress. The study sample consisted of undergraduate students from public universities. Based on the study findings university students face a lot of stress. The stressors are academic stress, financial stress, relationships, family conflicts, and uncertain future. The study recommended constant guidance and counseling for the students, parents, and guardians.
Leveraging Natural Language Processing for Enhanced Text Analysis in Business Intelligence
Authors: Hidayatullah Ahmad Fathan , Kalinaki Kassim , Gul Haji , Yusuf Rufai Zakari , Shafik Wasswa
Published: August 2024

Business intelligence (BI) is crucial for informed decision-making, optimizing operations, and gaining a competitive edge. The rapid growth of unstructured text data has created a need for advanced text analysis techniques in BI. Natural language processing (NLP) is essential for analyzing unstructured textual data. This chapter covers foundational NLP techniques for text analysis, the role of text analysis in BI, and challenges and opportunities in this area. Real-world applications of NLP in BI demonstrate how organizations use NLP-driven text analysis to gain insights, improve customer experience, and anticipate market trends. Future directions and emerging trends, including multimodal learning, contextualized embeddings, conversational AI, explainable AI, federated learning, and knowledge graph integration, were explored. These advancements enhance the scalability, interpretability, and privacy of NLP-driven BI systems, enabling organizations to derive deeper insights and drive innovation in data-driven business landscapes.
Analyzing Public Concerns on Mpox Using Natural Language Processing and Text Mining Approaches
Authors: Anoop V. S.
Published: August 2024

The World Health Organization (WHO) officially designated Mpox (Monkeypox) as a Public Health Emergency of International Concern on July 23, 2022. Since early May 2022, numerous endemic countries have been reporting the spread of Mpox, with alarming mortality rates have accompanied. This situation has prompted extensive discussions and deliberations among the general public through various social media platforms and health forums.This study proposes a natural language processing approach, specifically employing topic modeling techniques, to extract and analyze the public sentiments and perspectives regarding the escalating Mpox cases on a global scale. The results revealed several themes related to Mpox transmission, such as Mpox symptoms, international travel, government interventions, and homophobia from the user-generated content. The results further confirm that the general public has many stigmas and fears about the Mpox virus, which is prevalent in almost all topics.
Exploring Artificial Intelligence Techniques for Diabetic Retinopathy Detection
Authors: Vijayalakshmi A. , Unnisa Sarwath , Joshi Hemlata
Published: August 2024

There is a notable increase in the prevalence of Diabetic Retinopathy (DR) globally. This increase is caused due to type2 diabetes, diabetes mellitus (DM). Among people, diabetes leads to vision loss or Diabetic Retinopathy. Early detection is very much necessary for timely intervention and appropriate treatment on vision loss among diabetic patients. This chapter explores how Artificial Intelligence (AI) methods are helpful in automated detection of diabetic retinopathy. In this chapter deep learning algorithm is proposed that is used to extract important features from retinal images and classify the images to identify the presence of DR. The model is evaluated using various metrics like specificity, sensitivity etc. The results of the case study provide an AI driven solution to existing methods used to identify DR and this can improve the early detection and appropriate treatment at the right time.
Visual Vigilance on a Smart Approach to Melanoma Prediction via Image Mastery
Authors: Packiamary M. , Muthukumaravel A.
Published: August 2024

A crucial component of melanoma prediction via picture mastery is visual attentiveness. Changes in moles and skin lesions are often used to visually identify melanoma, a dangerous type of skin cancer. However, melanoma detection properly requires a sharp eye and a thorough comprehension of visual clues. Through proficiency in analyzing pictures of skin lesions, medical practitioners may improve their capacity to identify melanoma and take early action. Using artificial intelligence algorithms and cutting-edge imaging technology is a clever strategy for melanoma prediction. With the use of these techniques, one may examine enormous collections of photos of skin lesions to find trends and traits that point to melanoma. Healthcare professionals may increase the predicted accuracy of these algorithms and provide patients at risk of melanoma with more prompt therapies by continually training and improving them. Healthcare personnel need to continue their education and training in order to practice appropriate visual vigilance, in addition to technology improvements. Clinicians may improve their capacity to identify subtle symptoms of melanoma and make well-informed choices regarding patient treatment by remaining up to speed on the latest research and best practices in the field. In summary, visual vigilance is critical in the prediction of melanoma, and the ability to interpret skin lesion pictures correctly is critical for prompt diagnosis and treatment. Healthcare practitioners may enhance the prognosis of patients at risk of melanoma by implementing a strategic strategy that integrates cutting-edge imaging technology, artificial intelligence, and continuous education.
Quale configurazione?
Authors: Mancuso Martina , Di Giacomo Giovanna
Published: August 2024

Le autrici si propongono di mettere in dialogo alcune controversie teoriche e pratiche presenti in Psicoanalisi della Relazione e, più in generale nell’ambito della psicoterapia psicoanalitica, attraverso il confronto tra due psicoanalisti, Psi1 e Psi2. I due clinici discutono approfonditamente il concetto di ‘configurazione’ in psicoanalisi della relazione, interrogandosi sul suo significato e sull’applicazione clinica, evidenziando la complessità del metodo. Il dibattito si apre sul concetto di trauma, su dove si collochi rispetto alla configurazione dell’Io-Soggetto. Psi1 mette in rilievo il carattere insaturo dei meta-criteri, avvertendo sull’autoreferenzialità teorica, mentre Psi2 si concentra sull’importanza della pratica clinica e sulla comprensione della specificità del paziente. Attraverso questo confronto, le autrici offrono una visione aperta e flessibile della prospettiva clinica, proponendosi di rispettare l’unicità di ogni individuo.
Commento al libro ‘La terapia psicodinamica è efficace? Il dibattito e le evidenze empiriche’
Authors: Marchesini Silvia
Published: August 2024

In questo libro Paolo Migone raccoglie alcuni articoli sul tema dell’efficacia della terapia psicodinamica pubblicati negli anni sulle pagine di Psicoterapia e Scienze Umane. Dopo una introduzione in cui presenta il libro e un primo capitolo in cui discute questioni generali sul problema della ricerca in psicoterapia (cosa significa ricerca ‘scientifica’ in psicoterapia e la differenza tra ricerca clinica ed empirica, la questione della replicabilità con anche un esempio clinico, e cenni sulla storia del movimento di ricerca in psicoterapia), vi sono i restanti nove capitoli.[...]
Abstract 18: Circulating cell free long-noncoding RNA (PVT1 and MALAT1) expression in determining malignancy in indeterminate category of thyroid nodules
Authors: Dutta Susmita , Tarafdar Soham , Bhattcharya Nitai P , Mukhopadhyay Pradip , Sujoy
Published: August 2024

Background: Molecular genetics is useful in indeterminate thyroid nodules. Long non-coding RNA (lncRNA) has possible role in tumorogenesis of various cancers.

Objective: We determined expression of lncRNA from plasma in individuals with indeterminate thyroid nodules.

Methods: Patients underwent ultrasonography (USG) and guided FNAC, surgery (where indicated). Total RNA was extracted from plasma using standard kits and expression of specific lncRNA was determined by quantitative RT-PCR. Initially a cutoff was determined by comparing ÄCt of benign, malignant with healthy controls and it this was validated in indeterminate category.

Results: FNA (n =182) suggested benign (n= 97) and malignant (n=31) and they underwent histopathological confirmation. PVT1 & MALAT1 lncRNA were significantly up regulated in malignant cases compared to healthy and benign group. A PVT1 (ÄCt) cut-off of 2.29, AUC of 0.995 (95% CI, 0.98-1.0) and a MALAT1 (ÄCt) cut-off of 3.33, AUC of 0.997 (95% CI, 0.99-1.0) was established to predict malignant nodules. Using this cut-off in indeterminate nodules (n=54w) were able to determine malignancy (sensitivity and specificity for PVT1 was 93.5%, 95.6% and for MALAT1 was 77.4% and 100% respectively.

Conclusion: PVT1 & MALAT1 expression from plasma could help in differentiating malignant from benign thyroid nodules in indeterminate thyroid nodules.