bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ranking resilience: assessing the impact of scientific performance and the expansion of the Times Higher Education Word University rankings on the position of Czech, Hungarian, Polish, and Slovak universities
Authors: Tóth Barbara , Motahari-Nezhad Hossein , Horseman Nicki , Berek László , Kovács Levente , Hölgyesi Áron , Péntek Márta , Mirjalili Seyedali , Gulácsi László , Zrubka Zsombor 
Published: October 2023

Abstract

University rankings are gaining importance worldwide. While the top-ranked universities are the subject of numerous academic publications, very little literature is available on universities in the lower two-thirds of the ranking list. In this study, we analysed the sensitivity of year to year changes in position in the Times Higher Education World University Rankings (THE) of universities from the Czech Republic, Hungary, Poland, and Slovakia using hypothetical scenarios of potential changes in their research outputs. A regression model was developed that quantifies the effect of the inclusion of institutions that are new to ranking as well as dropouts on the ranking list. We also developed a method to allow customized sensitivity analysis of the subsequent year's rank from an institution's projected research output, given its current rank and research output, assuming that other ranking indicators remain unchanged over 1–2 years. It should be noted that universities in the region have ranked below 800, and while research output has been increasing, it was observed that ranks worsen for most universities from these four countries. The field-weighted citation index and the total volume of publications had the highest effect on rankings, while the proportion of Scimago Q1 publications did not have a consistent effect on the projected next year's ranks. In most universities, the growth in research performance indicators were below the level that would be required to offset the rank changes due to the inclusion of new entrants in ranking. The findings of this research suggest that universities have to consider complex strategies to improve their ranking focusing on other activities than research such as reputation, internationalization, or industry income. With due caution, our results might be generalized to most of the universities below 800 in the THE. The rank prediction tool presented in this article is available online at https://hecon.uni-obuda.hu/en/rank-calculator/. JEL code I21, I23, I28
Taking stock of the pre-pandemic patterns of demographic and psychological antecedents of vaccination intention and behaviour – Results from representative surveys in 2016 and 2018
Authors: Eitze Sarah , Felgendreff Lisa , Seefeld Linda , Horstkötter Nina , Betsch Cornelia 
Published: October 2023

Abstract

Background: There are many reasons why people decide for or against vaccination. Besides socio-demographic characteristics, the 5C antecedents of vaccination (confidence, complacency, constraints, calculation and collective responsibility) are a helpful tool for identifying target groups and the public’s broader informational needs. In this study, the 5C antecedents were used to explain vaccination behaviour (a) in general over the last five years, (b) for specific vaccines and (c) for target groups, such as the elderly, parents, and healthcare workers. The intention to get an influenza vaccination was also analysed for certain target groups.
Methods: The 5C antecedents of vaccination, self-reported vaccination behaviour and intention to vaccinate were collected in two representative telephone surveys – one in 2016 (n1 = 5,012) and another in 2018 (n2 = 5,054). Logistic regressions reveal the predictive value of socio-demographic variables and psychological antecedents for vaccination behaviour and intention.
Results: Confidence in safety and effectiveness was always an important predictor. Furthermore, complacency (the underestimation of risk) and even structural barriers were important psychological predictors of vaccination behaviour. Overall, psychological antecedents had higher explanatory power than socio-demographic variables.
Conclusions: The pattern of vaccine hesitancy slightly differed between vaccinations and target groups, and an understanding of pre-pandemic patterns is urgently needed to detect changes in vaccine hesitancy patterns caused by the pandemic and to target vaccination deficits that it has caused.
Assessment of the childhood neurodevelopmental status based on the diagnosis of congenital or acquired hypothyroidism
Authors: Amirikandbon Zeinab , Moienafshar Atousa , Shariatpanahi Ghazal , Mojtahedi Sayed Yousef , Tavakolizadeh Reza 
Published: October 2023

Abstract
Background
Misdiagnosis and delay in the treatment of hypothyroidism, due to the role of thyroid hormone in the metabolism and neurodevelopment of children, can cause irreversible sequelae. This study was conducted to compare neurodevelopmental status of children with congenital or acquired hypothyroidism.
Methods
In a cohort study, neurodevelopmental status of two groups of 30 children with congenital or acquired hypothyroidism, was evaluated by the ages and stages questionnaire.
Results
There was no significant difference in childhood neurodevelopment, based on the diagnosis of congenital or acquired hypothyroidism. In congenital hypothyroidism, later diagnosis and lower thyroxine level were associated with neurodevelopmental disorders.
Conclusion
Neonatal diagnosis and early treatment of hypothyroidism can prevent late neurodevelopmental disorders.
Ecological flow research and optimal selection of the most ecologically relevant hydrologic indicators at the Jingjiang River's three outlets
Authors: Wang Hongxiang , Yan Yiyang , Huang Lintong , He Ning , Guo Wenxian 
Published: October 2023

Abstract

Scientific ecological hydrological indicators provide constraints that contribute to the healthy operation and restoration of river ecosystems. Daily flow data from three Jing River outlets (SongZiKou (SZK), TaiPingKou (TPK), and OuChiKou (OCK)) spanning 1955–2019 were used. We employed innovative methods, such as IHA–RVA and annual distribution, to establish ecological flow thresholds. Surplus and deficit indicators were used to analyze annual and seasonal runoff dynamics. The PCA/RVA method identified relevant hydrological indicators and assessed hydrological changes influenced by the Three Gorges Reservoir (TGR). Key findings include suitable ecological flow thresholds for the flood season (SZK/TPK/OCK – 218.6/94.5, 51.7/96.0, and 60.9–4,494.5 m3/s, respectively). The TGR impacted the flow duration curve, causing deficits during the flood season (up to 0.99, OCK) and surpluses in non-flood seasons (up to 5.04, OCK). The study assessed the Jing River watershed's response to hydrological changes, notably due to the reservoir's water storage and flow interruption during the dry season, revealing declining low pulse count (SDG) and duration (MTS) and increasing high pulse duration (GJP). This research employs innovative methods and hydrological indicators, enhancing understanding of Jing River watershed ecological hydrology, and offering essential data for water resource management and ecosystem health.
Nexus of land use land cover dynamics and extent of soil loss in the Panjkora River Basin of eastern Hindu Kush
Authors: Rahman Haseeb Ur , Shakir Muhammad 
Published: October 2023

Abstract

The increasing population, deforestation and conversion of agricultural land to the built-up areas are putting pressure on land resources. Moreover, among land degradation, soil loss is one of the common issues that has had adverse consequences for natural ecosystems, thus affecting livelihoods. The Panjkora River Basin is selected as the study area due to its very fragile soil and having shown regular soil loss activity. In the study area, the scientific communities are consistently insisting on monitoring the LULC changes and exploring the extent of soil loss. To achieve the stated objectives, the RUSLE approach was applied to generate maps of soil loss for the years 1990, 2005 and 2020. The analysis revealed that during the past three decades (1990–2020), the built-up areas have been increased by 20%. Contrary to this, a decrease of 3% in barren land, 2% in area under water, 3% in snow cover and 13% in area under vegetation have been recorded. The analysis further revealed that the maximum actual annual soil loss consistently increased from 5,195 tons/ha/year in 1990 to 6,247 tons/ha/year in 2005 and 8,297 tons/ha/year in 2020. This research implies that geospatial technologies are effective tools for modeling the erosion of soil.
Protection of the upper hemisphere of a critical information infrastructure facility
Authors: Loskutov I. A. , Repenko V. A. 
Published: October 2023

Objective. Structuring of publicly available information regarding the protection of the upper hemisphere of CII objects.Method. The following methods of scientific cognition are used: systematization, description, analysis, deduction. The article consists of three sections. First, an analysis of the current state of the issue of the need for protection from UAVs is carried out. Accounting is not only military infrastructure, but also civil. In addition, for analysis, the separation of drone attacks is carried out in order to physically destroy the CII object / its part or attack the technical component. In the second part of the work, the analysis of the regulatory framework of Russia and the EU countries is carried out. The greatest emphasis is placed on domestic legislation and the identification of problem areas in relation to the research topic. In the third part of the work, a draft of proposals for the protection of CII objects from threats emanating from UAVs is presented. To do this, the analysis of drone varieties is carried out, the requirements for the system of protection and search for intruders are determined.Result. The article investigates the problems of protecting CII objects from drone attacks. A constant increase in UAV attacks on civilian and military infrastructure was noted, problems of the regulatory framework of Russia in the direction were identified, a proposal for the protection of the upper hemisphere was developed.Conclusions. The conducted research is of an overview nature. The materials presented in the paper can serve as a basis for further research in the direction and for the development of relevant regulatory documents.
Additional functions and additional boundary conditions in heat conduction problems for multilayer bodies
Authors: Klebleev R. M. 
Published: October 2023

Objective. The purpose of the study is to develop a technique for obtaining an analytical solution to the thermal conductivity problem for a 2-layer plate under boundary conditions of the 1st kind.Method. The research method is based on the integral method. In this case, an additional function (DF), additional boundary conditions (ABC) and local coordinate systems are introduced. The DF describes the temperature over time at one of the points of the twolayer system. Its use reduces the partial differential equation to an ordinary equation. DKUs allow you to perform equations on boundaries.Result. It is shown that satisfying the equations on the boundaries leads to their fulfillment inside the domain. Note that additional boundary conditions are satisfied for any other method of obtaining analytical solutions. The only difference is that they are not accepted as conditions subject to separate consideration. An additional function is also a quantity that is determined by any other method of obtaining a solution. The only difference is that it is not singled out for separate consideration.Conclusion. It can be stated that the introduction of an additional function and additional boundary conditions does not distort the original formulation of the problem and is only a means to significantly simplify the process of obtaining an approximate analytical solution and the final expression for it.
Metabolic Profile of F1 Holstein × Zebu Lactating Dairy Cows Under Grazing Supplemented with Two Non-Protein Nitrogen Sources
Authors: Mora-Luna Robert Emilio , Herrera-Angulo Ana María , Eslava-Tovar José Fernando , Isea-Chávez Juan Carlos , Darghan Aquiles Enrique 
Published: October 2023

Pastures dedicated to cattle production in Venezuela have a low crude protein concentration. One of the nutritional strategies to correct the forage protein deficit is using non-protein nitrogen in the diet. To evaluate the effect of two non-protein nitrogen sources on the metabolic profile of lactating dairy cows, 31 F1 Holstein × Zebu multiparous cows averaging 419 ± 46 kg body weight and 17.1 ± 3.3 kg milk·animal·d-1 were randomly assigned to two treatments for 91 days: 1) 59 g·animal-1·d-1 of urea and 2) 64 g·animal-1·d-1 of Optigen II® as slow-release urea (SRU). The animals were grazing (2.12 AU·ha-1) on Urochloa decumbens, U. humidicola, and U. brizantha (7.98-9.61 % CP) and supplied with 4 kg·animal·d-1 of concentrate (15 % CP), and 108, 60, and 108 g·animal·d-1 of mineral, molasses, and bypass fat, respectively. Glucose, total protein, albumin, cholesterol, urea, and β-hydroxybutyrate concentrations, aspartate aminotransferase, and gamma-glutamyl transferase activities were determined in blood serum samples every 28 days. ANOVA analyzed data in a completely randomized design with repeated measures. There were no differences among treatments in the parameters investigated; however, collecting time influenced all of them. No treatment × time interactions were found except for albumin concentration, higher in urea at day 0. The results indicate that under the conditions assayed in the present work, Optigen II® offers no advantage over urea concerning blood indicators of energy and protein metabolism and hepatic functionality in dairy cows.
Using COVID-19 Vaccine Attitudes Found in Tweets to Predict Vaccine Perceptions in Traditional Surveys: Infodemiology Study
Authors: Sigalo Nekabari , Frias-Martinez Vanessa 
Published: October 2023

Background
Traditionally, surveys are conducted to answer questions related to public health but can be costly to execute. However, the information that researchers aim to extract from surveys could potentially be retrieved from social media, which possesses data that are highly accessible and lower in cost to collect.

Objective
This study aims to evaluate whether attitudes toward COVID-19 vaccines collected from the Household Pulse Survey (HPS) could be predicted using attitudes extracted from Twitter (subsequently rebranded X). Ultimately, this study aimed to determine whether Twitter can provide us with similar information to that observed in traditional surveys or whether saving money comes at the cost of losing rich data.

Methods
COVID-19 vaccine attitudes were extracted from the HPS conducted between January 6 and May 25, 2021. Twitter’s streaming application programming interface was used to collect COVID-19 vaccine tweets during the same period. A sentiment and emotion analysis of tweets was conducted to examine attitudes toward the COVID-19 vaccine on Twitter. Generalized linear models and generalized linear mixed models were used to evaluate the ability of COVID-19 vaccine attitudes on Twitter to predict vaccine attitudes in the HPS.

Results
The results revealed that vaccine perceptions expressed on Twitter performed well in predicting vaccine perceptions in the survey.

Conclusions
These findings suggest that the information researchers aim to extract from surveys could potentially also be retrieved from a more accessible data source, such as Twitter. Leveraging Twitter data alongside traditional surveys can provide a more comprehensive and nuanced understanding of COVID-19 vaccine perceptions, facilitating evidence-based decision-making and tailored public health strategies.
Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility Study
Authors: Sükei Emese , Romero-Medrano Lorena , de Leon-Martinez Santiago , Herrera López Jesús , Campaña-Montes Juan José , Olmos Pablo M , Baca-Garcia Enrique , Artés Antonio 
Published: October 2023

Background
Functional limitations are associated with poor clinical outcomes, higher mortality, and disability rates, especially in older adults. Continuous assessment of patients’ functionality is important for clinical practice; however, traditional questionnaire-based assessment methods are very time-consuming and infrequently used. Mobile sensing offers a great range of sources that can assess function and disability daily.

Objective
This work aims to prove the feasibility of an interpretable machine learning pipeline for predicting function and disability based on the World Health Organization Disability Assessment Schedule (WHODAS) 2.0 outcomes of clinical outpatients, using passively collected digital biomarkers.

Methods
One-month-long behavioral time-series data consisting of physical and digital activity descriptor variables were summarized using statistical measures (minimum, maximum, mean, median, SD, and IQR), creating 64 features that were used for prediction. We then applied a sequential feature selection to each WHODAS 2.0 domain (cognition, mobility, self-care, getting along, life activities, and participation) in order to find the most descriptive features for each domain. Finally, we predicted the WHODAS 2.0 functional domain scores using linear regression using the best feature subsets. We reported the mean absolute errors and the mean absolute percentage errors over 4 folds as goodness-of-fit statistics to evaluate the model and allow for between-domain performance comparison.

Results
Our machine learning–based models for predicting patients’ WHODAS functionality scores per domain achieved an average (across the 6 domains) mean absolute percentage error of 19.5%, varying between 14.86% (self-care domain) and 27.21% (life activities domain). We found that 5-19 features were sufficient for each domain, and the most relevant being the distance traveled, time spent at home, time spent walking, exercise time, and vehicle time.

Conclusions
Our findings show the feasibility of using machine learning–based methods to assess functional health solely from passively sensed mobile data. The feature selection step provides a set of interpretable features for each domain, ensuring better explainability to the models’ decisions—an important aspect in clinical practice.
Development of the Preferred Components for Co-Design in Research Guideline and Checklist: Protocol for a Scoping Review and a Modified Delphi Process
Authors: Munce Sarah EP , Steele Gray Carolyn , Pomeroy Beverley Claire , Bayley Mark , Kokorelias Kristina Marie , Luong Dorothy , Biddiss Elaine , Cave Trish , Bragge Peter , Chew-Graham Carolyn A , Colquhoun Heather , Dadich Ann , Dainty Katie N , Elliott Mark , Feng Patrick , Goldhar Jodeme , Hamilton Clayon B , Harvey Gillian , Kastner Monika , Kothari Anita , Langley Joe , Jeffs Lianne , Masterson Daniel , Nelson Michelle LA , Perrier Laure , Riley John , Sellen Kate , Seto Emily , Simpson Robert , Staniszewska Sophie , Srinivasan Vasanthi , Straus Sharon E , Tricco Andrea C , Kuluski Kerry 
Published: October 2023

Background
There is increasing evidence that co-design can lead to more engaging, acceptable, relevant, feasible, and even effective interventions. However, no guidance is provided on the specific designs and associated methods or methodologies involved in the process. We propose the development of the Preferred Components for Co-design in Research (PRECISE) guideline to enhance the consistency, transparency, and quality of reporting co-design studies used to develop complex health interventions.

Objective
The aim is to develop the first iteration of the PRECISE guideline. The purpose of the PRECISE guideline is to improve the consistency, transparency, and quality of reporting on studies that use co-design to develop complex health interventions.

Methods
The aim will be achieved by addressing the following objectives: to review and synthesize the literature on the models, theories, and frameworks used in the co-design of complex health interventions to identify their common elements (components, values or principles, associated methods and methodologies, and outcomes); and by using the results of the scoping review, prioritize the co-design components, values or principles, associated methods and methodologies, and outcomes to be included in the PRECISE guideline.

Results
The project has been funded by the Canadian Institutes of Health Research.

Conclusions
The collective results of this project will lead to a ready-to-implement PRECISE guideline that outlines a minimum set of items to include when reporting the co-design of complex health interventions. The PRECISE guideline will improve the consistency, transparency, and quality of reports of studies. Additionally, it will include guidance on how to enact or enable the values or principles of co-design for meaningful and collaborative solutions (interventions). PRECISE might also be used by peer reviewers and editors to improve the review of manuscripts involving co-design. Ultimately, the PRECISE guideline will facilitate more efficient use of new results about complex health intervention development and bring better returns on research investments.

International Registered Report Identifier (IRRID)
PRR1-10.2196/50463
Face and number plate recognition for car anti-theft
Authors: Truong Quoc Bao , Tran Tan-Loc , Nguyen Thanh Tan-Kiet , Nguyen Huu Cuong 
Published: October 2023

Smart parking systems along with that is continuous development of new technologies, are widely applied to improve our lives. It can also add new technologies with advanced functions making it a multi-functional management system. Thanks to the anti-theft technologies that are installed, modern cars are significantly more difficult to steal than they once were. However, electrical systems can still experience issues, though and malfunction at some point. This paper suggests using video image recognition technology, at car parks and parking lots as an anti-theft solution, alerting the presence of the non-owner of vehicle in the driver’s seat. The system automatically predicts whether the driver is valid with the registration number plate. The image of the car is captured by the camera at the entrance gates of the parking lot. The proposed algorithm includes face recognition in images, building a deep learning convolutional network that classifies faces (subscriber’s images); using Cascade trainer to train number plate object recognition, vehicle number recognition through character recognition technique. The system can recognize reality through a personal computer connected to the camera at the scene or through photos and video files. Result, the model can face recognition and match to license plate in at a moment.