bluuebunny/crossref_metadata_2025 huggingface dataset:
A high-efficient artificial bee colony algorithm with random neighborhood search and population state evaluation
Authors: Cao Yang , Wang Junlei
Published: October 2024

Artificial bee colony(ABC) algorithm performs well in the exploration process, but develops poorly in the exploitation process. How to balance the exploration and development of the algorithm during the evolution process has always been a challenge for the ABC algorithm.At the same time, for complex problems, the ABC algorithm may experience premature convergence or stagnation during the evolution process. To overcome these challenges, this paper proposes an effective variant of the ABC algorithm (random Neighborhood search Artificial Bee Colony with Population State Evaluation), referred to as NABC-PSE. In the NABC-PSE algorithm, a random neighborhood method is introduced, and different search strategies are designed for the employed bees and onlooker bees phases based on the best solution within the neighborhood. Additionally, a population state evaluation mechanism is added during the onlooker bee phase to allocate appropriate evolutionary strategies for the population when it becomes stagnant or converges prematurely. To address the issue of the roulette wheel mechanism where individual fitness becomes less distinct in the later stages of evolution, a selection strategy based on sorting is employed. Finally, to make more effective use of dimensional information, a greedy selection method is used to choose the dimensions for improvement.To validate the effectiveness of the algorithm, the NABC-PSE algorithm was tested on a set of 22 benchmark functions and compared with some other ABCs and several state-of-the-art algorithms. The results show that the proposed algorithm has high solution quality, fast global convergence rate.
Proposed Method of Acquiring Train Data for Early-Modern Japanese Printed Character Recognizers
Authors: Koiso Norie , Takemoto Yuki , Ishikawa Yu , Takata Masami
Published: October 2024

The National Diet Library's digital collection contains approximately 400,000 valuable books from the Meiji period to the early Showa period. These books are stored as image data and have not been converted into text. Therefore, the use of information is limited. Manual and automatic methods exist for texting early-modern Japanese printed books, but manual methods cost a fortune. Optical character recognition is used for automation, but the characteristics of early-modern Japanese printed characters and the differences in shape between early-modern Japanese printed characters and printed characters reduce the recognition rates. Therefore, developing a character recognition method specific to early-modern Japanese printed books is necessary. Collecting early-modern Japanese printed characters is also manual, and collecting several characters evenly is difficult. In this study, we propose a method to improve the accuracy of early-modern Japanese printed character recognition accuracy using images generated from early-modern Japanese printed characters. CycleGAN is used to generate images from early-modern Japanese printed characters. The generated image is incorporated into training data to create a character recognition model. The experiment demonstrated that the recognition rate improved using the generated images in the training data.
Critical period for first language acquisition may be shorter in autistic children than in typically developing children
Authors: Vyshedskiy Andrey , Marsiglio Allegra , Batham Sahil , Tagliavia Alessandro , Venkatesh Rohan , Tarakbay Anel , Mundhia Sagar , Urs Samarth , Khokhlovich Edward , Pinsky Eugene
Published: October 2024

The goal of this study was to differentiate between two hypotheses regarding syntactic-language comprehension deficits in autistic adults. One hypothesis suggests a persistent, age-independent barrier, such as sound hypersensitivity or social avoidance, which may hinder acquisition of syntax throughout life. Another hypothesis proposes an age-dependent factor, such as a shortened critical period for language acquisition. These hypotheses predict distinct trajectories for language learning-rates. The first hypothesis expects autistic individuals to consistently exhibit a slower learning-rate compared to neurotypical individuals across all ages. In contrast, the second hypothesis predicts that autistic individuals will initially acquire language at a rate comparable to their neurotypical peers but will experience an earlier decline in learning-rate. To test these predictions, we analyzed language learning-rates in 15,183 autistic and 138 neurotypical individuals, 2 to 22 years-of-age. At age 2, both groups showed comparable learning-rates. In neurotypical individuals, this rate remained stable from ages 2 to 7. However, in autistic individuals, the learning-rate began to decline exponentially starting as early as 2.3 years, with an earlier onset of decline observed in those with more severe autism. These findings strongly support the second hypothesis, indicating that language deficits in autism may be caused by a shortened critical period.
A SPR based fiber optic sensor for the development of Internet of Things (IoT) Centered Technologies
Authors: Aktar Mst Nargis , Basak Nilanjana , Biswas Shuvo , Abdullah Hasan , Uddin Muhammad Shahin
Published: October 2024

Photonic crystal fiber (PCF) is the crucial component of optical fiber. Today, PCF has sparked widespread interest because of its potential in sensor systems, photonic devices, and communication. However, the features of technologies are updating day by day, and to keep up with the latest features, optical fiber sensors are a key issue for the Internet of Things (IoT) technologies. The primary goal of the offered project is to design an optical sensor for IoT-compatible devices with maximum sensitivity and minimum loss. Therefore, this project presents a unique circular-shape PCF sensor based on surface plasmon resonance (SPR) for evaluating analyte refractive index (RI). With the utilization of the finite element approach, sensing capabilities of the proposed structure have been examined via numerical simulations incorporating an iterative optimization. However, in this configuration, several capillaries are collected and conducted to yield a circular-shape silica structure, then coating the flattened layer with a gold (Au) material. The gold material obtains the SPR pulse in the PCF’s broadcast spectrum. In this structure, the operating wavelength range of 0.94 − 0.62 µm yields efficient results. All the parameters are numerically simulated for the analyte, with RI = 1.34–1.37. After the simulation and formal analysis, the offered sensor gives the highest wavelength sensitivity response of 18403.59 nm/RIU and a minimum loss peak of 193.87 dB/cm. We believe the structural design can also be an appropriate candidate for biological and organic detection, as well as other IoT-based applications.
Exploring the Psychometric Properties of the Life Orientation Test-Revised Among Multiple Sclerosis Patients, Insights into Optimism
Authors: Yunier Broche-Pérez , M. Jiménez-Morales Rodneys , D. Díaz-Guerra Diego
Published: October 2024

Introduction: Optimism, defined as the tendency to expect positive outcomes and view challenges as manageable, plays a vital role in the lives of individuals with chronic illnesses, including multiple sclerosis. Given its potential benefits, measuring optimism through validated tools like the Life Orientation Test-Revised (LOT-R) is essential for both research and clinical practice.
Objective: This study aims to validate the LOT-R within a sample of MS patients, assessing its psychometric properties and exploring its potential utility in clinical settings.
Methods: This study included 179 patients with Relapsing-Remitting Multiple Sclerosis (PwMS). Confirmatory factor analysis (CFA) was performed to assess the factor structure of the LOT-R. Model fits were evaluated by the χ2/df value, comparative fit index (CFI), and root mean square error of approximation (RMSEA).
Results: The LOT-R showed good psychometric characteristics in our sample of PwMS. The CFA's two-factor model (optimism/pessimism) yielded a good model fit. Cronbach's alpha and McDonald’s omega were acceptable. Optimism was significantly correlated with quality-of-life scores, resilience, and fear of relapse scale.
Conclusions: The LOT-10 has satisfactory psychometric properties and is suitable for measuring dispositional optimism in Spanish-speaking patients with multiple sclerosis.
Hydrophilic and strength-softening characteristics of clay-rich rocks
Authors: Han Zongfang , Bu Mohua , Li Yuqiong , He Manchao
Published: October 2024

To better understand the mechanism of the strength weakening process of clay-rich rocks after interacting with water, the relationship between mineral composition, microscopic pore structure and gaseous water adsorption characteristics of clay-rich rocks was comprehensively analyzed by using X-ray diffraction (XRD), scanning electron microscopy (SEM) and mercury injection test. The results show a positive correlation between water absorption and both clay minerals and montmorillonite (MMT) content. The more complex the microporous structure is, the more pores in the diameter of 0.2 ~ 2µm accumulated, and the worse the water absorption capacity obtained. The innovation of this study lies in quantitatively calculating the weight coefficients of influencing factors, highlighting the contribution of pore structure and hydrophilic mineral composition to the strength of clay-rich rocks samples after water absorption, which was not covered in previous studies. The results show that the weight coefficients are fractal dimension of pores, effective porosity and clay mineral content in order. The clay minerals content is negatively correlated with the strength of the clay rocks after water absorption, that is, the presence of MMT is the key influencing factor of strength softening in this study, and the paper concludes with the results of molecular dynamics (MD) simulation to illustrate more intuitively the effect of hydrated MMT on strength. The research results provide a new insight to better understand the strength softening caused by water sensitivity of clay-rich rocks and to establish the correlation between the macroscopic mechanical behavior and the micromechanical mechanism.
Re-examining the Optimal Extent of Lymph Node Dissection for Colon Cancer using the Lymphadenectomy Index
Authors: Marunaka Yuta , Kiuchi Jun , Kuriu Yoshiaki , Arita Tomohiro , Shimizu Hiroki , Nanishi Kenji , Imamura Taisuke , Ohashi Takuma , Konishi Hirotaka , Yamamoto Yusuke , Morimura Ryo , Shiozaki Atsushi , Ikoma Hisashi , Kubota Takeshi , Fujiwara Hitoshi , Otsuji Eigo
Published: October 2024

The optimal extent of lymph node dissection in colon cancer surgery is specified in guidelines based on the results of past analyses. However, with advances in surgical techniques and multidisciplinary treatments, the clinical significance of dissecting each lymph node may change. In this study, we re-examined the optimal dissection range in each colon cancer localization. We retrospectively analyzed 788 cases of T1-T4 colon cancer who underwent radical resection between 2008 and 2018 at our hospital, and evaluated the Lymphadenectomy Index. No metastases to the main lymph node were found in T1 cases. In T2 cases, dissection effect to the main lymph node were observed in cases with tumors localized in the ascending colon and left side of the transverse colon. For tumors localized in the cecum, dissection was effective for lymph nodes in nodal station 213, in the right side of the transverse colon in station 211, in the descending colon in station 221, and in the sigmoid colon in station 231. These lymph nodes could have been considered out of scope for dissection if the Japanese guidelines were followed. In these cases, the extent of lymph node dissection should be carefully considered on a case-by-case basis.
Disulfidptosis-associated ferroptosis gene BCAT2 regulates c-MYC expression and promotes the malignant progression of epithelial ovarian cancer cells by interacting with GYS1
Authors: Tang Zhongyun , Ma Chao , Liu Chongdong
Published: October 2024

Purpose
Epithelial ovarian cancer (EOC) is a prevalent gynecological malignancy with a notoriously poor prognosis. Recent oncological research has highlighted ferroptosis and disulfidptosis as novel forms of cell death with potential therapeutic implications. However, the relationship between these processes and their role in EOC remains poorly understood.
Methods
Through comprehensive bioinformatics analyses, we identified six disulfidptosis-related ferroptosis genes in EOC samples. A prognostic model was developed utilizing these genes to assess their predictive power for EOC survival prognosis. We further investigated the dual role of BCAT2 in regulating ferroptosis and modulating GYS1, which is implicated in disulfidptosis. The influence of BCAT2 on cell proliferation, migration, and invasion was examined through its regulation of c-MYC and its impact on G2M phase and EMT-related proteins.
Results
Our findings reveal that BCAT2 plays a pivotal role in both ferroptosis and disulfidptosis in EOC. It not only regulates ferroptosis but also modulates GYS1, thereby influencing disulfidptosis. We observed a strong correlation between BCAT2 and GYS1 expression. Additionally, BCAT2's interaction with GYS1 extends its influence beyond ferroptosis, significantly disrupting disulfidptosis as well.
Conclusion
This study provides valuable insights into the complex interplay between disulfidptosis and ferroptosis in EOC, our findings underscore the potential of targeting BCAT2 and GYS1 as a therapeutic strategy for EOC.
Strategies for occupational recovery processes in individuals with bipolar disorder type I: a qualitative study.
Authors: Koene Juul , Maassen Eva , Lang Natasja van , Stel Jaap van der , Kupka Ralph , Weeghel Jaap van , Kroon Hans
Published: October 2024

Background. Employment is a challenging life domain for individuals with bipolar disorder (BD), illustrated by high unemployment numbers and various experienced problems within the workplace. While regaining a satisfactory level of occupational functioning is an important aspect of recovery, there is little qualitative research exploring occupational recovery in individuals with BD. The aim of this qualitative study was to gain insight in the strategies of patients and peer support workers with BD type I (BD-I) regarding their occupational functioning. Our second aim was to construct a conceptual model based on these experiences to provide further understanding of this aspect of recovery. In our study, inspired by Glaser and Strauss' constructivist Grounded Theory, we interviewed 21 patients and 15 peer support workers with BD-I about their occupational functioning experiences and strategies for dealing with difficulties, as well as their occupational recovery processes. We analysed the data through open, axial, and selective coding.
Results. The results showed one key theme and three categories of strategies implemented by individuals with BD-I: (1) organizing work, (2) self-regulatory actions in relation to employment, and (3) getting support. Based on the narratives of participants, we constructed a conceptual model to get a clearer understanding of their occupational recovery processes to manage challenges they encounter in their workplace.
Conclusion. The narratives of individuals with BD-I show that two types of recovery can be experienced in relation to work: recovery after an acute mood episode and a longer lasting recovery process that is intertwined with several aspects of daily working life. Strategies that individuals develop to regulate their work behaviour and their work environment aid in this recovery process.
Geospatial analysis of individuals with suspected diagnosis of leprosy and positive qPCR in an endemic region of Minas Gerais
Authors: Pinheiro Marcos Daniel Silva , Oliveira Nathan Guilherme , Rios Vladmir Machado , Takeishi Lucas Kenji , Batista Lavínia Cássia Ferreira , Branco Alexandre Castelo , Fairley Jessica K. , Oliveira Lorena Bruna Pereira , Baptista Ida Maria Foschiane Dias , Fraga Lucia Alves Oliveira
Published: October 2024

Background: to evaluate the geographic distribution of individuals with a suspected leprosy diagnosis (SLD) presenting a positive qPCR test residing in Governador Valadares/MG.
Methods: Between 2017 and 2021, dermal scraping samples were collected from the earlobes, elbows, and lesions of 200 individuals with SLD examined in CREDEN-PES. A geospatial analysis estimated the coverage of health units.
Results: It was found that 108 (54.0%) of the participants were female, with an average age of 55 years, and the majority lived in the urban area of the municipality. The qPCR test was positive in 94 (47.0%) samples evaluated, of which 49 (52.1%) were from female individuals and 45 (47.9%) were males. A heterogeneous distribution of individuals who presented a positive qPCR test in the municipality was observed. However, in the sectors with the highest number of individuals with SLD and positive in the qPCR test, there was a predominance of female, literate, black, or mixed-race residents. Furthermore, 58.8% of individuals with SLD and positive in the qPCR test did not have coverage at a health facility.
Conclusion: The lack of health unit coverage in places with more SLD and qPCR-positive individuals indicates the need to expand this coverage and implement active search, diagnostic suspicion, and treating leprosy in Primary Care. This would facilitate user access to the nearest.
Health service, thus making Secondary Care (CREDEN-PES) available to perform its role as a Specialized unit.
Measurement Uncertainty and Validation for Quantification of Marijuana Metabolite: (−)-11-nor-9-Carboxy-Δ9-THC in Human Urine by GC-MS/MS
Authors: Maurya Ashok Kumar , Sahu Puran Lal , Sahu Kapendra
Published: October 2024

Background:

Since the International Olympic Committee (IOC) was established,
sports doping control analyses have revealed a high rate of positive cases for cannabinoids.
Cannabinoids were banned in all sports where they were used in-competition as per the Prohibited
List published annually. Further, it was also included in the threshold drug category. Consequently,
developing a reliable method for urine Cannabinoids metabolite quantification plays
a pivotal role in sports dope testing.

Objective:

This work aimed to develop and validate a reliable, cost-effective, robust gas
chromatography-tandem mass spectrometry method for detecting (−)-11-nor-9-Carboxy-Δ9-
THC component in human urine samples, in compliance with ICH and WADA guidelines.

Methods:

The sample preparation was done by enzymatic hydrolysis for deconjugation, further
proceeded with solid phase extraction (SPE), liquid-liquid extraction (LLE), and using an
XAD2 column, and N-methyl trimethylsilyl trifluoroacetamide (MSTFA) for derivatization.

Results:

The linearity was obtained in a range of 50–300 ng/mL, and the correlation coefficient
was found to be higher than 0.99. Throughout the entire validation study, the difference in
Retention Time (RT) for the analyte, including the Internal Standard (IS), was shown to be less
than 1.0%. The quantification limit (LOQ) was calculated at a level of 50 ng/mL in human
urine samples for the 3 most abundant ion transitions. The detection limit (LOD) was
established at 4 ng/mL.

Conclusion:

The accuracy, precision, linearity, recovery, quantification limit, and selectivity
by GC-MS/MS technique were found acceptable and well satisfactory while following the ICH
guidelines. The developed method has been proven to be fit for purpose in accordance with the
enforced Guidelines of WADA.
Identification of Phytoconstituents from Natural Product Database as SIRT2 Inhibitors for Potential Role in Alzheimer’s Disease: An In-Silico Screening
Authors: Kumar Hitesh , Datusalia Ashok Kumar , Kumar Anoop , Khatik Gopal L.
Published: October 2024

Aim:

We aimed to conduct in silico screening of the potential phytoconstituent from a
natural product database to find SIRT2 inhibitors.

Background:

Alzheimer's disease (AD) is the most prevalent type of dementia, characterized by
behavioral and mental symptoms as well as a progressive loss of cognitive ability. Since SIRT2
may be detrimental to neurological illnesses, it is a prime target for research into SIRT2 inhibitors.

Objective:

To identify the SIRT2 inhibitors and their role in AD.

Methods:

We have utilized NPAtlas database and screened using pharmacophore-based virtual
screening, molecular docking, and simulation. The Natural Products Atlas provides unrestricted access
to various natural products derived from bacteria and fungi, allowing researchers to investigate
and visualize the extensive chemical diversity in the natural world.

Results:

From in silico screening data, we have found phytoconstituents that could function as
SIRT2 inhibitors. Six phytoconstituents were identified using pharmacophore-based virtual screening.
According to molecular docking, Kurasoin B outperformed the reference molecule regarding
binding energy. Kurasoin B exhibited a binding affinity of -12.543 kcal/mol, whereas the binding
affinity of the reference molecule was -12.089 kcal/mol. The Kurasoin B complex with SIRT2 was
determined to be stable throughout the simulation by performing MD simulation, with an RMSD of
2.88 (Å), whereas the reference and free protein displayed RMSDs of 3.74 and 4.70 (Å), respectively.

Conclusion:

In silico studies and data analysis, suggest that Kurasoin B may be able to suppress
the SIRT2 protein for managing AD.
Synergistic Action of Thymol-citral is Associated with Cell Cycle Arrest and Intracellular ROS Generation in A549 Cells
Authors: Balan Devasahayam Jaya , Kiruthiga Chandramohan , Jeyakumar Mahalingam , Devi Kasi Pandima
Published: October 2024

Objective:

NSCLC is the predominant form of lung cancer, often exhibiting resistance
to chemotherapy. Thymol and citral have shown promise as anticancer agents in different cancer
cell lines but have not been evaluated in combination against NSCLC. Hence, we planned to investigate
the anticancer effect of thymol-citral combination and explore its mechanisms of action
against A549 cells.

Methods:

A549 cells were exposed to varying concentrations of thymol and citral, alone and in
combination. Cell proliferation, plasma membrane integrity, apoptotic markers, reactive oxygen
species (ROS) levels, cell cycle distribution, senescence induction, and migration potential were
assessed. Additionally, in vitro safety was evaluated in human bronchial epithelial cells (HBECs)
and human red blood cells (RBCs).

Results:

Thymol and citral showed synergistic action against A549 cells, with a CI value of 0.75.
After 24 h, they induced apoptosis, caused G0/G1 phase arrest, and increased ROS levels, suggesting
oxidative stress as the mechanism. This combination also induced cell senescence, significantly
inhibited A549 cell migration, and was non-toxic to human RBCs and HBECs.

Conclusion:

Overall, the thymol-citral synergistic combination was found to be a safe and effective
therapy option for non-small cell lung cancer.
Corrigendum to: High-Throughput Sequencing Technology Assisted Investigation of the Correlation Between Intestinal Flora, Serum Biochemistry, Blood Lipids, and Tumour Markers in Patients with Gastric Cancer and Healthy Plateau Residents
Authors: Zhu Linghong , Wang Bo , Liu Linxun , Han Pei , Ji Li , Zhang Zilong , Zhang Jingni
Published: October 2024

The correct spelling of the author's name has been updated in the article titled “High-Throughput Sequencing Technology Assisted
Investigation of the Correlation Between Intestinal Flora, Serum Biochemistry, Blood Lipids, and Tumour Markers in
Patients with Gastric Cancer and Healthy Plateau Residents,” 2024, 27(7), 996-1010 [1].

The original article can be found online at https://www.eurekaselect.com/article/133442

Details of the correction:

• Original:

Author name: Linghong Zhou

• Corrected:

Author name: Linghong Zhu

We apologize for any inconvenience caused.
Uso de un digestato elaborado a partir de residuos orgánicos urbanos: evaluación de su efecto en el suelo y en un cultivo de Raphanus sativus L.
Authors: Rodriguez  Aristizabal Monica Alejandra , Yaya Lancheros Mary Luz , Cifuentes Olaya Brigitte Alexandra , Escobar Rojas Aidee Vanessa
Published: October 2024

Colombia, considerado un país de vocación agrícola y que históricamente ha dependido de productos agroquímicos para el acondicionamiento fisicoquímico, la fertilización y nutrición del suelo, así como para el control de plagas en los cultivos, no es ajeno a problemáticas como la degradación del suelo, la contaminación ambiental y la pérdida de biodiversidad como consecuencia del uso de estos productos, poniendo en riesgo la seguridad alimentaria.  Como alternativa, el uso de bioinsumos a base de microorganismos ha demostrado beneficios en el rendimiento y la sanidad de los cultivos. En ese contexto, este trabajo tuvo como objetivo evaluar el uso de un digestato elaborado con residuos orgánicos urbanos como acondicionador fisicoquímico del suelo. La metodología incluyó la caracterización fisicoquímica del digestato, análisis microbiológicos, pruebas de inocuidad, para detectar la presencia de Salmonella spp (Lignières, 1900) y huevos de helmintos, ensayos de fitotoxicidad en la germinación y un bioensayo con plántulas de Raphanus sativus L. Los resultados fisicoquímicos indicaron que el digestato es un líquido altamente salino y, en la aproximación a la diversidad microbiológica, se detectaron bacterias amilolíticas. En cuanto a la fitotoxicidad se demostró que el digestato no contiene sustancias que inhiban la germinación, según los análisis estadísticos de Bonferroni y Kruskal-Wallis. Sin embargo, el bioensayo mostró que el digestato no tuvo un impacto significativo en el acondicionamiento del suelo, ya que no se observó mejora en la altura, número de hojas o peso seco de las plántulas. De acuerdo con estos resultados, se concluyó que el digestato obtenido requiere ajustes en el proceso de elaboración. Se recomienda su uso en cultivos con ciclos fenológicos más largos, además de incluir la adición de inóculos microbianos que mejoren su efectividad, así como la mejora de sus propiedades, lo cual podría aumentar su potencial como biofertilizante.
Plurilingual Education in a Monolingualised Nation
Authors: Pearce Daniel Roy
Published: October 2024

This book explores alternative approaches to foreign language education in a context which is traditionally dominated by English-only approaches, and widely viewed as highly monolingual. It examines the practices of teachers and their assistants involved in plurilingual education in the first longitudinal exploration in the Japanese context.
Visual Mapping of Cultural Heritage and Tourism Studies in the Indian Context
Authors: Kavacık Saadet Zafer , Çınar Kevser , Sawant Madhuri
Published: October 2024

This paper aims to examine in detail the cultural heritage studies conducted in the context of India, with a specific focus on the intersection with tourism. The study conducts a bibliometric analysis of the journal articles on cultural heritage and tourism field in India in Web of Science (WoS) database. Bibliometric techniques such as bibliographic coupling, co-occurrence of author keywords, and co-occurrence of abstract terms were used. The study identifies 401 cultural heritage papers and 59 cultural heritage papers based on tourism in the Indian context for 1992-2023. Most of the analyzed papers are categorized under the Humanities Multidisciplinary category in WoS, focusing on Sustainable Cities and Communities in relation to the Sustainable Development Goals. In terms of cultural heritage studies, India, the United States, and England are the most productive nations, while in terms of tourism-based cultural heritage, India, Algeria, and Portugal are at the top. India, cultural heritage, tourism, and culture are among the top author keywords in the cultural heritage field. Therefore, that research fills this gap by performing a bibliometric analysis of publications on cultural heritage research articles in the Indian context published in the WoS database between 1992 and 2023.
Revival of the Aviation Industry in the Post-COVID Era - With Special Reference to Passengers Satisfaction in Domestic Airlines of India
Authors: Nandi Shampa , Srujana Thumma , Kedarisetty Ravi , Rohit Gunda
Published: October 2024

India is the ninth-largest global aviation market, handling 121 million domestic passengers and its contribution to national GDP is 5%(2). The aviation sector has been disrupted by the COVID-19 pandemic but since mid-2022, it started reviving as the severity of the pandemic gradually slowed down. Investors, Airlines, Government, and Regulators are extra cautious about the safety protocols, regulations and passengers satisfaction in the post-COVID era. So far, no research has studied the passengers satisfaction level with all the new initiatives taken by Indian domestic airlines. Our empirical study addresses this gap by adopting a mixed method based on a survey of 224 passengers and a content analysis of 300 online reviews on domestic airlines. Important crucial inflight measures impacting passenger satisfaction are assessed through the qualitative study based on passengers feedback using Importance-performance analysis. The study has also validated the impact of most crucial inflight experiences on satisfaction through an SEM model. The findings have shown that airline passengers are largely satisfied with the Relationship quality with crew members and Safety and in-flight services but are not comfortable and secure with the in-flight ambient factors.
Local Perspectives of the Relationships between Food and Tourism in the City of Girona (Catalonia, Spain)
Authors: Ginés-Ariza Paula , Noguer-Juncà Ester , Fusté-Forné Francesc
Published: October 2024

Food is playing an increasingly more relevant role in the development of tourism. While the link between local produce and the tourist experience is studied in rural regions, few studies have scrutinized the relevance of local food in urban areas. This research analyses the significance attached to the local product for food tourism in the city of Girona, north-eastern Catalonia. The study is based on a qualitative methodology which is focused on twelve semi-structured interviews conducted with local public and private food-based experts, including professionals from the hospitality, catering and gastronomic culture promotion sectors of Girona. Results show the relevance of identity products and local markets, and the potential of restaurants and events to create awareness and increase the visibility of local food. However, results also show that local products need to be effectively integrated into its food tourism system through collaboration and cooperation among public and private actors, to enhance the role of place as a source of local food and tourism attraction in urban areas. This also contributes to the relationships between the agri-food and the retail sector from the production to the consumption of food.
The Influence of Demographic Factors on Tourist Experiences at Sikkim Buddhist Monasteries
Authors: Wangmo Ashi Pempem , Dubey Arvind Kumar
Published: October 2024

This paper provides an analysis of tourists’ experience based on their demography. Sikkim is known to be a Buddhist state has incorporated religious sites in tourism. The monasteries in the state have not only attracted domestic tourists but international tourists as well. Tourists who visit solely for the purpose of religion mostly follow the Vajrayana sect of Buddhism. This study focuses on the aspect of religious tourism in the State of Sikkim. It takes into account the demography of the tourists and their effect on experience in monasteries situated within Sikkim. The demographic variable of tourists was categorized into gender, age, marital status, monthly income, educational qualification, occupation, and Sikkim monasteries profile of the tourists were the type of tour, Motivation for visiting religious sites, participation in or performed rituals in religious ceremony, accommodation of stay, duration of visit, means of bookings, monasteries visited while in Sikkim, means of information and recommendation of the site to others. Data was collected through primary and secondary sources. Data were collected from respondents through interviews and questionnaires based on the nominal scale. A total of 200 samples were gathered from diverse tourists visiting six of the Buddhist monasteries in Sikkim (Rumtek, Tashiding, Sangachoeling, Chorten, Pemayangtse and Dubdi monastery) utilizing the convenience sampling method. The collected questionnaires were analyzed with the application of independent sample T-test and one-way ANOVA. This study concluded that the demography of the tourists is essential in segregating and assessing what tourists expect from their visits to these monasteries. The study provides an overview of tourists visiting Sikkim religious sites, revealing diverse demography and motivations for tourists to visit monasteries. Hence, identifying the demography of the tourists needs to be given equal importance to enhance the future tourist experience.
DEEP ASSOCIATION RULE-BASED DIMENSIONALITY REDUCTION FOR BIG DATA ANALYTICS UNCOVERING COMPLEX PATTERNS AND IMPROVING EFFICIENCY
Authors:   Nandha College of Technology, India, S Nandagopal
Published: October 2024

In the realm of big data analytics, reducing data dimensionality is crucial for efficient processing and gaining meaningful insights. This paper introduces a novel approach that leverages deep association rule mining to uncover intricate patterns and associations within large datasets. By incorporating deep learning models, such as neural networks, our method captures complex and non-linear relationships that traditional techniques often overlook. The proposed framework involves preprocessing the data, creating embedding representations, training a deep learning model, extracting association rules, filtering and selecting relevant rules, and applying dimensionality reduction. The selected association rules serve as the basis for reducing the dimensionality of the original dataset, either by removing irrelevant variables or consolidating them into higher-level features. The efficacy of our approach is evaluated through experiments, showcasing improved efficiency and the preservation of meaningful information. This research presents a promising avenue for reducing data dimensionality in big data analytics, enhancing the scalability and interpretability of analysis outcomes.
ENSEMBLE MODEL - BASED BANKRUPTCY PREDICTION
Authors:   Pondicherry University, India, J Arumugam , S Raja Sekar ,   Pondicherry University, India, V Prasanna Venkatesan ,   Pondicherry University, India
Published: October 2024

Bankruptcy prediction is a crucial task in the determination of an organization’s economic condition, that is, whether it can meet its financial obligations or not. It is extensively researched because it includes a crucial impact on staff, customers, management, stockholders, bank disposition assessments, and profitableness. In recent years, Artificial Intelligence and Machine Learning techniques have been widely studied for bankruptcy prediction and Decision-making problems. When it comes to Machine Learning, Artificial Neural Networks perform really well and are extensively used for bankruptcy prediction since they have proven to be a good predictor in financial applications. various machine learning models are integrated into one called the ensemble technique. It lessens the bias and variance of the ml model. This improves prediction power. The proposed model operated on quantitative and qualitative datasets. This ensemble model finds key ratios and factors of Bankruptcy prediction. LR, decision tree, and Naive Bayes models were compared with the proposed model’s results. Model performance was evaluated on the validation set. Accuracy was taken as a metric for the model’s performance evaluation purpose. Logistic Regression has given 100% accuracy on the Qualitative Bankruptcy Data Set dataset, resulting in the Ensemble model also performing well.
AN INTER-DISCIPLINARY APPROACH TO AUTOMATION TECHNOLOGY IN FINANCE - WHAT CAN HISTORY, LAW AND DATA SCIENCE TEACH US?
Authors:   O.P. Jindal Global University, India, Jain Aditya Sushant
Published: October 2024

The year 2008 is etched in human history as the year of the ‘Global Financial Crises’. Post the crises, Historians and financial commentators alike rushed to impute blame. Some blamed securitizations, some the banks and some Lehman Brothers and AIG. However, in the midst of all of this humbug, a key epicentre of the crises escaped academic scrutiny; ‘Automation Technology’. The paper therefore aims to present an alternative view of financial history; one which impleads ‘automation technology in finance’ i.e., Risk Modelling Algorithms and RegTech. However, the underlying aim of this paper is to make a case against systemic automation bias in finance and to achieve that end, the paper employs an inter-disciplinary approach and uses history, law and data science to show case the multifarious perils of using automation technology blindfold in finance whilst also proposing possible solutions such as the incorporating of design thinking and systems theory in finance. Expired data sets, human assumptions, turning code in law, and a lack of standardized financial semantics as but some of these ‘perils’. On the law front; it presents a twofold challenge under constitutional and anti-trust law and aims to reconcile law and technology. Lastly the paper aims to guide regulators by categorizing multiple stages of technological complexity and recommends application of different regulatory approaches to regulating automation. Therefore, the paper shall maintain a ‘solution’ oriented approach throughout.
MACHINE LEARNING ALGORITHM FOR FINTECH INNOVATION IN BLOCKCHAIN APPLICATIONS
Authors:   Kalasalingam Academy of Research and Education, India, V Lakshmana Narayanan , G Ramesh Pandi ,   Kalasalingam Academy of Research and Education, India, K Kaleeswari ,   Pasumpon Muthuramalinga Thevar College, India, S Veni ,   Pasumpon Muthuramalinga Thevar College, India
Published: October 2024

The rapid growth of Fintech innovation and the widespread adoption of blockchain technologies have indeed had a transformative impact on the financial industry. In this paper, the focus is on the application of machine learning algorithms, specifically the Random Forest Regression algorithm, within the context of Fintech and blockchain. This research contributes to the advancement of machine learning techniques in the field of Fintech and blockchain. The Random Forest Regression algorithm utilizes ensemble learning, combining multiple decision trees to analyze complex financial data and make predictions on various outcomes. This algorithm has proven to be effective in addressing key challenges within the industry, such as predicting loan defaults, detecting fraud, and assessing risks. Through experimental evaluations and case studies, the paper demonstrates the effectiveness of the Random Forest Regression algorithm in enhancing Fintech innovation in blockchain applications. The algorithm improved accuracy, scalability, and interpretability enable financial institutions to make data-driven decisions and optimize their operations.
FORECASTING QUARTERLY RICE AND CORN PRODUCTION IN THE PHILIPPINES: A COMPARATIVE STUDY OF SEASONAL ARIMA AND HOLT-WINTERS MODELS
Authors:   University of Mindanao Digos College, Philippines, E. Parreño Samuel John
Published: October 2024

Rice and corn are essential crops for the Philippines, playing a critical role in the nation’s economy and food security. However, the agricultural sector faces challenges, including climate variability, land constraints, and the need for imports to meet growing demand. Accurate forecasting of rice and corn production is crucial for informed decision-making and resource allocation. This research applied Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winters exponential smoothing models to forecast rice and corn production. The study used quarterly production data from 1987 to 2023 obtained from the Philippine Statistics Authority. The Holt-Winters model with additive seasonality outperformed the SARIMA model for both rice and corn production, achieving lower Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) values. The findings have significant implications for policymakers, agricultural stakeholders, and commodity traders, guiding them in making informed decisions regarding import requirements. The volatility of global food prices and exchange rates can significantly impact the cost of imports, putting a strain on the country’s financial resources. Accurate forecasting models are essential for ensuring food sufficiency and making informed decisions on the amount of imports required. By adopting the Holt-Winters model and continuously improving forecasting methodologies, the Philippines can enhance food sufficiency and promote rural economic growth. The study highlighted the importance of accurate forecasting models in ensuring stable and sufficient rice and corn supplies to meet the nation’s growing demands, contributing to sustainable agricultural development and food security. Continuous research in agricultural forecasting methodologies is necessary to address the challenges posed by evolving agricultural dynamics and further enhance predictive accuracy.
Correction: Automated Psychotherapy in a Spaceflight Environment: Advantages, Drawbacks, and Unknowns (Preprint)
Authors: Smith Logan
Published: October 2024

UNSTRUCTURED

Automated Psychotherapy in a Spaceflight Environment: Advantages, Drawbacks, and Unknowns
The Effect of patients' Gratitude Expression on Doctors' Prosocial Behavior in Online medical consultation (Preprint)
Authors: Cao xianye , Liu yongmei , Dong Wei
Published: October 2024

BACKGROUND

The current online medical platforms frequently encounter instances where patients express gratitude towards doctors. However, there is a dearth of research elucidating the mechanisms underlying these expressions and their impact on the prosocial behavior of doctors. Given the significance of prosocial behavior in enhancing the quality of online medical services, it is imperative to investigate the influence of patient gratitude on the prosocial actions of doctors.

OBJECTIVE

The objective of this study is to construct a theoretical model that delineates the impact of patients' expressions of gratitude on the prosocial behavior of doctors within the context of online medical consultations. The study aims to scrutinize how gratitude, both paid and free, influences the way doctors engage with patients and offer medical advice, which is pivotal for the efficacy of online medical platforms.

METHODS

The study utilized data extracted from the Haodf Online Open Data Platform. After rigorous data processing, a comprehensive sample of 50,498 doctors was curated for analysis. To empirically validate the theoretical model, logarithmic regression models were employed. These models are adept at capturing the nuances of the relationship between the independent variables (expressions of gratitude) and the dependent variable (doctors' prosocial behavior).

RESULTS

The empirical analysis revealed that both paid expressions (αGifts=0.0070, P<.01) and free expressions(αThanks=0.0096, P<.01) of gratitude positively influence the prosocial behavior of doctors. Interestingly, the online experience of doctors was found to negatively moderate the effect of paid gratitude expressions (αGifts × Month=-0.0066, P<.01), suggesting that more experienced doctors may be less influenced by paid expressions of gratitude. Conversely, the impact of free gratitude expressions was amplified among doctors with greater online experience (αThanks × Month=0.007, P<.01). Additionally, the study identified a gender difference, with female doctors showing greater responsiveness to free gratitude expressions compared to their male doctors (αThanks × Woman=0.0072, P<.01), but a lower responsiveness to paid gratitude expressions(αGifts × Woman=-0.0108,P<.01).

CONCLUSIONS

The study concludes that expressions of gratitude, irrespective of being paid or free, significantly enhance the prosocial behavior of doctors in online medical consultations. The findings also underscore the moderating role of doctors' online experience and gender in the context of gratitude expressions. These insights are invaluable for online medical platforms seeking to foster more effective doctor-patient interactions and for patients aiming to engage doctors more constructively.
Examining BRCA previvors’ social media content creation as a form of self and community care: A qualitative interview study (Preprint)
Authors: Wellman Mariah L , Owens Camilla M , Holton Avery E , Kaphingst Kimberly A
Published: October 2024

BACKGROUND

Genetic testing has become a common way of identifying a woman’s risk of developing hereditary breast and ovarian cancer, however, not all medical providers have the necessary information to support patients interested in genetic testing, nor do they always have the proper information for patients once they have been diagnosed. Therefore, many previvors, the name of those who have tested positive for the BRCA genetic mutation, have taken to social media to inform others about the importance of genetic testing and explain to them how to understand their test results. Historically, those desiring to speak about their medical issues online have sought out structured support groups or chat rooms, however, many previvors today are instead posting on their own personal social media accounts and creating more niche communities.

OBJECTIVE

This study aimed to examine why BRCA previvors are sharing content on their personal social media accounts and how posting online in this way serves a purpose for their larger community.

METHODS

A total of 16 semi-structured interviews were conducted with individuals who post about their experience being diagnosed with the BRCA genetic mutation and their subsequent treatment on their personal social media accounts specifically for followers interested in their medical journey. The interviews were recorded, transcribed, and coded by an experienced qualitative researcher and a graduate student using inductive techniques and a reflexive thematic analysis was applied to the transcripts.

RESULTS

The results suggest BRCA previvors want to control the narrative around their personalized medical experiences rather than participating in existing groups or chat rooms. Controlling their own story, rather than adding to existing narratives, gives previvors a sense of control. It also allows them to set boundaries around the types of experiences they have online when sharing their medical journey. Finally, previvors said they feel they’re serving the larger BRCA community by each sharing their individual journeys to hopefully avoid stereotyping and homogenizing the experience of BRCA patients.

CONCLUSIONS

Research with the objective of understanding the experiences of BRCA previvors should include exploring how and why they talk about their journeys, especially due to the lack of knowledge BRCA previvors say many of their medical providers have. We suggest further research should examine how other BRCA patients, especially BIPOC patients, are navigating their own content creation, especially considering content moderation policies that social media platforms are continuing to implement that directly impact users’ ability to share about their medical experiences.