bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends in Natural Language Understanding with sentence representation and sentiment analysis
Authors: Guminska Urszula , Poniszewska-Maranda Aneta , Ochelska-Mierzejewska Joanna 
Published: November 2023

Abstract
Natural Language Processing (NLP) is a crucial branch of artificial intelligence that examines how people and computers communicate through natural language. The majority of NLP research focuses on the fundamental methods that enable humans to understand and generate words, phrases, sentences, and the whole documents. The primary focus of the studies in this area concentrate on English as the common language used by scientists. Unfortunately, this language has a very straightforward structure. It indicates that most of the techniques that are very successful for documents in English do not work equally well for texts in other niche languages.

To investigate the existing studies on Natural Language Understanding (NLU), a Systematic Literature Review (SLR) was performed. Through our deep research on NLU and its extensions, 46 studies were selected mentioning 38 machine learning, 3 hybrid and 4 knowledge-based approaches to NLU.

The paper presents the systematized knowledge along with a critical analysis of existing research, both for text processing in English and for other native languages. It shows the solutions and reasoning of researchers, and compiles the advantages and disadvantages of the presented solutions.
Variable selection for inhomogeneous spatio-temporal Poisson point processes
Authors: Choiruddin Achmad , Gonz\'alez Jonatan , Mateu Jorge , Fadlurohman Alwan , Waagepetersen Rasmus 
Published: November 2023

Abstract
Spatio-temporal point pattern data are becoming prevalent in many scientific disciplines. We model the first-order intensity of spatio-temporal point pattern data, considering the intensity as a parametric log-linear function of spatial, temporal, and spatio-temporal covariates. Dealing with spatio-temporal covariates brings computational and methodological challenges compared to the purely spatial case. We extend regularisation methods to perform variable selection for spatial point processes to the spatio-temporal case to obtain parsimonious and more interpretable models. Using our proposed methodology, we conduct two simulation studies and examine an application to criminal activity in the Kennedy district of Bogota. In the application, we consider a spatio-temporal point pattern of crime locations and many spatial, temporal, and spatio-temporal covariates related to urban places, environmental factors, and further space-time factors. The intensity function of vehicle thefts is estimated, considering other crimes as covariate information. The proposed methodology offers a comprehensive approach for analysing spatio-temporal point pattern crime data, capturing complex relationships between covariates and crime occurrences over space and time.
Multi-group cooperative evolutionary optimization algorithm combined with quantum entanglement on cross fields
Authors: Lian Zhaoyang , Si Bailu 
Published: November 2023

Abstract
Swarm intelligence algorithm is a bionic random probability heuristic search algorithm, which is a kind of algorithm that transforms the collective behaviors in biological study into engineering application in practice. In this paper, a multi-group cooperative evolutionary optimization algorithm was proposed by referring to the interaction behaviors of species diversity and stability in the ecosystem. First, the group updating mechanism of the traditional seeking and tracking mode with dynamic population update mechanism were adopted. The multi-population interactive update group and the quantum entanglement update group were introduced to guide the algorithm to approach the global optimal solution gradually. Second, the proposed bionic algorithm was extended to cross field applications. The algorithm was applied to 33 test functions of open CEC dataset, its application fields were and extended to robot routing optimization of grid map, vehicle scheduling optimization of dairy enterprise, location optimization of logistics center, and plasma trajectory planning optimization, and the competitive results were achieved.
Influenza and pneumococcal vaccine hesitancy in the elderly population: Results from two representative surveys in Germany
Authors: Heinemeier Dorothee , Schmid Philipp , Eitze Sarah , Betsch Cornelia ,   Vaccination60+ study group
Published: November 2023

Abstract

Background
The reasons for low vaccine acceptance in the elderly population are largely unknown – despite the great need of vaccines in this risk group. Moreover, while many studies assess the impact of factors surrounding vaccination, such as sociodemographic information, psychological factors, such as vaccine-specific attitudes, are not sufficiently used in the research of vaccination behavior and interventions. This article assesses the psychological antecedents of influenza and pneumococcal vaccination in the elderly and assesses the relative impact of psychological vs. sociodemographic and other factors surrounding vaccination, on vaccination behavior.
Methods
A cross-sectional telephone survey, representative of age, gender and rural/urban residence, was conducted with N = 701 German participants > 60 years of age, during the influenza season of 2016–17. Multiple logistic regressions were conducted to identify the relevant determinants of vaccination behavior.
Results
Results show unique patterns in the psychological antecedents: while confidence, the belief in the effectiveness of vaccination and calculation, the need for information, complacency, the lack of risk perception and constraints, and perceived practical barriers to vaccination predicted influenza vaccination behavior, only complacency predicted pneumococcal vaccination behavior. The amount of explained variance in influenza vaccination behavior nearly doubles when psychological antecedents of vaccination are taken into account, beyond other factors surrounding vaccination. However, the effect was smaller for pneumococcal vaccination behavior. The results are compared to a subnational sample.
Conclusions
Understanding the psychological drivers of vaccination can help to plan interventions effectively.
Trial registration:
Deutsches Register Klinische Studien (German Clinical Trials Register) DRKS00012653. Registered 24.11.2017. Retrospectively registered.
Modulation of antioxidant enzyme B166 isoforms 1 and 5 expressions by SREBP1-a links ROS elimination to lipid metabolism in glioblastoma cells
Authors: Cheung Cindy , Kong Fanhua , Wang Bingwu 
Published: November 2023

Abstract
Antioxidant enzyme B166 (B166) - mediated detoxification of H2O2 into water and oxygen is a pivotal process to sustain a favorable redox homeostasis in mitochondria and suppress cell death. Here, we identify that B166 is highly expressed in GBM tumor tissues and a potential novel biomarker to predict unfavorable prognosis of GBM patients. GBM cells upregulate the expression of B166 via SREBP1-a-mediated transcription and reduce the endogenous ROS levels, maintaining the cellular redox homeostasis and normal morpho-function of mitochondria. SREBP1 knock down decreases B166 expression on both RNA and protein levels. We reveal that overexpression of SREBP1-aN, the active form of SREBP1-a, increases B166 isoform 1 (V1) and 5 (V5) levels in the mitochondria and nucleus, respectively. Pharmacological suppression of SREBP1 or genetic inhibition of B166 disrupts the redox homeostasis, leading to the generation of high levels of oxidative stress, which in turn causes dramatic damages to the mitochondria and kills GBM cells ultimately. We show that SREBF1 level is strongly associated with B166, FASN and SCD expression in patients’ tumor tissues of GBM cohort from TCGA and protein levels of SREBP1 and B166 are significantly correlated in our PHGBM cohort. Thus, targeting B166 could be a promising therapeutic approach for GBM.
Enhancing Predictive Accuracy: Impact of Feature Selection on Heart Disease Prediction With Machine Learning Models
Authors: Aradan John F , Pawar Arti 
Published: November 2023

Abstract
This research paper builds upon previous work titled "Prediction of Cardiovascular Diseases using Machine Learning Algorithms" by the same authors. The paper investigates the impact of applying feature selection methods (filter and wrapper) and cross-validation on the efficiency of four models: SVM, Decision Tree, Random Forest, and Neural Network. The findings demonstrate that implementing these techniques improved the efficiency of the models compared to the bare models. This study contributes to the field of cardiovascular disease prediction and provides insights into the importance of feature selection and cross-validation in machine learning modeling.
Level of Uptake and Influencing Factors of Long Acting Reversible Contraception among Post-abortion Women in Uganda
Authors: Enyamitoit Samson Ralph , Byonanuwe Simon , Kahimakazi Irene , Almenares Ubarnell , Sentongo Emmanuel , Latortue Jean W. , Okello Maxwell , Tornes Yarine Fajardo 
Published: November 2023

Abstract

Background
Women in sub-Saharan Africa often fail to obtain or use modern contraceptives, particularly Long Acting Reversible Methods (LARC), for many reasons. Women rely primarily on traditional and short-acting contraceptives which are prone to incorrect or inconsistent use and failure. In Uganda, utilization of modern contraceptives has steadily increased from 8–35% over the last decade. However, LARC use has remained as low as 7.8% and could be worse in specific sites. Whereas unsafe abortions contribute up to 26% of all maternal deaths in Uganda, there is limited use of effective contraceptive methods such as LARC.
Methods
An institutional based cross-sectional study involving 317 post abortion patients admitted at the gynecology ward of Hoima Regional Referral Hospital (HRRH) in western Uganda were enrolled between January 2022 and April 2022. Interviewer-administered questionnaires were used to collect data. Descriptive statistics and binary logistic regression analyses to assess for factors influencing uptake of LARC among post abortion women were conducted using STATA 14.2. Variables in final multivariate model were significant when p < 0.05. The measure of association was reported as odds ratios with corresponding 95% confidence interval and p-value.
Results
The level of uptake of LARC was 38.9%. The most commonly taken up LARC was implant at 79%. Family income (AOR = 5.65, CI: 2.594–15.862, p = 0.001), previous history of LARC (AOR = 4.8, CI: 2.828–8.054, p < 0.0001), previous use of any other contraceptives other than LARC (AOR = 3.1, CI: 1.57–5.39, p = 0.004), fear of complications (AOR = 0.29, CI: 0.176–0.732, p < 0.0001), fear of process of insertion or removal (AOR = 0.53, CI: 0.213–0.961, p < 0.0001) and an opposing partner to the method (AOR = 4.10, CI: 1.90–6.910, p = 0.006) were found to independently influence uptake of LARC among post abortion women admitted at HRRH
Conclusions
The level of uptake of LARC remains low in this area. Improving family incomes, partner involvement and mass sensitization regarding LARC will go a long way in promoting LARC use among post abortion women in this area.
Study of outdoor rainwater drainage pollution in a hospital
Authors: Fang Ming , Chen Chunhu , Ding Xinren , Qian Zhen 
Published: November 2023

Abstract

The outdoor rainwater drainage pollution in a large general hospital poses considerable threats to the environment and our health. A systematic analysis method was summarized in the investigation practice. Results showed that the pipe network damage caused by uneven geological settlement was the main reason for the pollution of the rainwater pipe network in the hospital. Countermeasures such as settlement repair and geological foundation reinforcement, rainwater and sewage pipeline transformation, the repair of mixed connection of rainwater and sewage pipes and polluted water sources, drainage health safety in isolated areas, and emergency storage tanks were discussed. After implementing the measures, the NH3-N measured value was within 0.82 mg/L, and the average removal rate was 97.4%. The chemical oxygen demand (COD) concentration also decreased significantly with an average of 12 mg/L and the average removal rate was 91.8%. The results show that the reconstruction can effectively deal with the problem of outdoor rainwater drainage pollution in the hospital. The study has specific engineering reference significance for medical building drainage system's health and safety research.
Nutritional Values of Foxtail Millet (Setaria italica) and other Millets Used for Common Diseases and Management
Authors: Maharajan Theivanayagam , Duraipandiyan Veeramuthu , Krishna Thumadath Palayullaparambil Ajeesh , Soosaimanickam Mariapackiam 
Published: November 2023

Abstract:The ever-increasing population and malnutrition in tropical and sub-tropical countries upsurge the demand and security for poor people’s food and nutrition. In erratic climatic conditions, millets can survive as they require less water, short cultivation period and are somewhat tolerant to biotic (bacteria and fungi) and biotic stresses (drought, salinity, nutrient deficiency, etc). Millets possess several nutrient rich components and several health benefits. Despite having superior nutritional, health and agricultural advantages, millets have not received their due attention. Among the millets, foxtail millet is one of the major millets in terms of its second in global production and millets’ yield, quality, and quantity are affected by various diseases. This review provides an overview of the origin and distribution of eight millets, their morphological characteristics with chemical composition, potential health benefits and the fungal, bacterial and viral diseases affecting the growth and yield of millets and their effective management in the framework of ensuring food and nutritional securities in the tropical and sub-tropical countries.
Classification and Immune Function of Coelomocytes in Echinoderms
Authors: Xue Zhuang , Peng Tingting , Wang Wei 
Published: November 2023

Abstract:
The top taxonomic position among non-chordate invertebrates, which make up the evolutionary
connection between invertebrates and vertebrates, is held by echinoderms. Their immune
responses rely on coelomocyte activity functioning concurrently with a range of humoral components
that directly interact with invasive pathogens. However, markedly lower numbers of systematic
reviews of the classification and immune function of coelomocytes have been performed
compared with those of vertebrates. Studying echinoderm coelomocytes continues to be an important
evolutionary vantage point for determining the origins of bilaterian immunity as well as
the principles behind the adaptive immune system of vertebrates. This article reviews the classifications
and immune functions of coelomocytes (sea urchin, sea cucumber and sea star). It summarizes
the research progress on immune-related genes/proteins, signal transduction pathways and
effector molecules in echinoderms according to the recent literature. This summary provides a
theoretical basis for studying coelomocytes and disease control in echinoderms. In the future, a
variety of methods and techniques should be used and combined with the surface receptors of
cells to study the classification and function of coelomocytes of echinoderms.
Internet Usage: A Crutch for Postgraduate Students with Poor Mental Health
Authors: Nemalladinne Sharon Sucharitha Gold 
Published: November 2023

Background:
The intricacies of developing internet systems endowed with serendipity and surprises and the relationships among internet users as individuals and collectives have attracted the attention of several researchers from various disciplines to examine the emergent phenomena. The present study seeks to understand internet usage in the realm of psychology, where it has a profound effect on the mental health of the individual. Numerous studies have indicated that internet usage results in poor mental health and that it is responsible for psychological problems. However, on the contrary, the present study seeks to examine if the internet is being used as a mental support system for those with issues of mental health.

Aims:
This study aims to understand the predictive value of mental health in calculating internet usage among postgraduate students.

Objectives:
The objective of this study is to identify whether mental health and internet usage vary with gender, to explore the relationship between mental health and internet usage, and to identify if internet usage may be predicted through mental health.

Methods:
The sample of the study consisted of N= 1040 drawn from postgraduate students studying in various universities of Andhra Pradesh and Telangana in India. It is not only a gender representative but also a socio-economic representative of Indian society. The Mental Health Inventory and the Internet Addiction Scale were the tools used for the collection of data.

Results:
The results obtained were analysed using SPSS. The findings t (1035) = -3.43, p = 0.001 suggested a significant difference among the genders pertaining to mental health, and t (1031) = 7.72, p < 0.001 revealed gender difference in internet usage. Results of Pearson’s correlation analysis revealed a negative and significant correlation with r = -0.212 (p <.01). Regression analysis depicted that internet usage could be predicted through mental well-being significantly at t (1035) = 11.96, F = 48.71, and p < 0.001.

Conclusion:
There is a significant gender difference in mental health and internet usage. Mental health and internet usage have a significant negative correlation. Internet usage can be predicted through the mental health of an individual.
A Video Game Intervention to Prevent Opioid Misuse Among Older Adolescents: Development and Preimplementation Study
Authors: Aneni Kammarauche , Fernandes Claudia-Santi F , Hoerner Lily A , Szapary Claire , Pendergrass Boomer Tyra M , Fiellin Lynn E 
Published: November 2023

Background
Opioid misuse and mental disorders are highly comorbid conditions. The ongoing substance misuse and mental health crises among adolescents in the United States underscores the importance of widely scalable substance misuse preventive interventions that also address mental health risks. Serious video games offer an engaging, widely scalable method for delivering and implementing preventive interventions. However, there are no video game interventions that focus on preventing opioid misuse among older adolescents, and there are limited existing video game interventions that address mental health.

Objective
This study aims to develop and conduct a formative evaluation of a video game intervention to prevent opioid misuse and promote mental health among adolescents aged 16-19 years (PlaySmart). We conducted formative work in preparation for a subsequent randomized controlled trial.

Methods
We conducted development and formative evaluation of PlaySmart in 3 phases (development, playtesting, and preimplementation) through individual interviews and focus groups with multiple stakeholders (adolescents: n=103; school-based health care providers: n=51; and addiction treatment providers: n=6). PlaySmart content development was informed by the health belief model, the theory of planned behavior, and social cognitive theory. User-centered design principles informed the approach to development and play testing. The Exploration, Preparation, Implementation, and Sustainability framework informed preimplementation activities. Thematic analysis was used to identify themes from interviews and focus groups that informed PlaySmart game content and approaches to future implementation of PlaySmart.

Results
We developed a novel video game PlaySmart for older adolescents that addresses the risk and protective factors for opioid misuse and mental health. Nine themes emerged from the focus groups that provided information regarding game content. Playtesting revealed areas of the game that required improvement, which were modified for the final game. Preimplementation focus groups identified potential barriers and facilitators for implementing PlaySmart in school settings.

Conclusions
PlaySmart offers a promising digital intervention to address the current opioid and mental health crises among adolescents in a scalable manner.
Investigating the Potential for RGB and Hyperspectral Imaging to Enhance Selection for Cadmium Uptake in Carrot
Authors: Zapf Kathleen , Simon Philipp , Lee Linda , Yang Yang , Oh Sungchan , Hoagland Lori 
Published: November 2023

Carrot (Daucus carota L.) can take up high concentrations of
toxic heavy metals like cadmium (Cd) and store them in their edible
taproots, leading to food safety risks. Cd poisoning in humans is
strongly linked to damage to the liver, lungs, and bones, as well as
prostate, kidney, pancreatic, and testicular cancer. Cd may also be
detrimental to carrot plant growth and nutrient content. A potential way
to address this challenge is to select for carrot varieties with lower
uptake, however, this is difficult because plants generally exhibit few
visible signs of Cd stress. The goal of this study was to determine if
hyperspectral imaging can be used as a tool to screen for carrot
breeding lines that can withstand Cd stress and restrict uptake, thereby
accelerating breeding efforts. To accomplish this goal, we grew 6 carrot
breeding lines previously shown to differ in their tendency to
accumulate toxic heavy metals like Cd at Purdue’s Ag Alumni Phenotyping
Facility (AAPF). Carrots were either treated or not with cadmium
chloride (CdCl), and imaged with red-green-blue (RGB)
and hyperspectral cameras throughout their growth. After 2 months,
plants were destructively harvested and Cd and other elements were
quantified using ICP.
Results of this study verified differences in the uptake of Cd and other
elements between the carrot lines, and several reflectance values and
vegetative indices have potential to detect Cd stress in carrot plants.
Healthy urban food
Authors: De Marchi Marta , Tosi Maria Chiara 
Published: November 2023

Food is a territorial system closely linked to public health, social equity and land policy. Eating habits are at the root of both incidence of cardiovascular diseases and phenomena of malnutrition. Food often entails social inequity and is acquiring, directly and indirectly, ever greater relevance in the tools of territorial government.
The Cities2030 project is being developed, financed by the European Horizon 2020 programme. The methodology agreed upon by the partners envisages the involvement of all interest groups and actors of the food system arena, through the installation of urban Policy and Living Labs.
The University Iuav of Venice, is involved in the development of two Labs in the Veneto region: one in the city of Vicenza, the other in the Venice lagoon. Working in these two cases will make it possible to reflect on very different food systems, even though they are geographically close.