bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of an algorithm for identifying patients undergoing dialysis from patients with advanced chronic kidney disease
Authors: Imaizumi Takahiro , Yokota Takashi , Funakoshi Kouta , Yasuda Kazushi , Hattori Akiko , Morohashi Akemi , Kusakabe Tatsumi , Shojima Masumi , Nagamine Sayoko , Nakano Toshiaki , Huang Yong , Morinaga Hiroshi , Ohta Miki , Nagashima Satomi , Inoue Ryusuke , Nakamura Naoki , Ota Hideki , Maruyama Tatsuya , Gobara Hideo , Endoh Akira , Ando Masahiko , Shiratori Yoshimune , Maruyama Shoichi 
Published: January 2025

Abstract
Background
Identifying patients on dialysis among those with an estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m2 remains challenging. To facilitate clinical research in advanced chronic kidney disease (CKD) using electronic health records, we aimed to develop algorithms to identify dialysis patients using laboratory data obtained in routine practice.

Methods
We collected clinical data of patients with an eGFR < 15 mL/min/1.73 m2 from six clinical research core hospitals across Japan: four hospitals for the derivation cohort and two for the validation cohort. The candidate factors for the classification models were identified using logistic regression with stepwise backward selection. To ensure transplant patients were not included in the non-dialysis population, we excluded individuals with the disease code Z94.0.

Results
We collected data from 1142 patients, with 640 (56%) currently undergoing hemodialysis or peritoneal dialysis (PD), including 426 of 763 patients in the derivation cohort and 214 of 379 patients in the validation cohort. The prescription of PD solutions perfectly identified patients undergoing dialysis. After excluding patients prescribed PD solutions, seven laboratory parameters were included in the algorithm. The areas under the receiver operation characteristic curve were 0.95 and 0.98 and the positive and negative predictive values were 90.9% and 91.4% in the derivation cohort and 96.2% and 94.6% in the validation cohort, respectively. The calibrations were almost linear.

Conclusions
We identified patients on dialysis among those with an eGFR < 15 ml/min/1.73 m2. This study paves the way for database research in nephrology, especially for patients with non-dialysis-dependent advanced CKD.
Does the law make a difference? a longitudinal study on accessibility compliance of Norwegian municipality websites
Authors: Inal Yavuz , Torkildsby Anne Britt 
Published: January 2025

AbstractThis study explored the effect of current regulations on web accessibility compliance for public services in Norway. We evaluated all municipality websites over the course of three years: during the transition period in 2022 (i.e., following the government’s announcement of the new regulations), immediately after the given deadline in 2023, and one year after the regulations came into force in 2024. Evaluations were performed using an automated tool, namely WAVE. In the last evaluation, we also conducted a cognitive walkthrough - via a keyboard and screen reader - on randomly selected websites to better understand changes in their accessibility compliance. The results showed significant differences in detected accessibility issues between the evaluation periods, indicating a positive outlook for continuous improvement and refinement over time. However, most websites still had accessibility violations in the final evaluation round, and hence, the results conclude that the rate of progress is insufficient to achieve web accessibility. This leads us to discuss the importance of raising awareness of and educating everyone in the ecosystem to complement the accessibility regulations, paving the way for a more equal and inclusive digital society.
Improving Real Estate Investment Trusts (REITs) time-series prediction accuracy using machine learning and technical analysis indicators
Authors: Habbab Fatim Z. , Kampouridis Michael , Papastylianou Tasos 
Published: January 2025

Abstract
The primary goal of investors who include Real Estate Investment Trusts (REITs) in their portfolios is to achieve better returns while reducing the overall risk of their investments. REITs are entities responsible for owning and managing real estate properties. To achieve greater returns while reducing risk, it is essential to accurately predict future REIT prices. This study explores the predictive capability of five different machine learning algorithms used to predict REIT prices. These algorithms include Ordinary Least Squares Linear Regression, Support Vector Regression, k-Nearest Neighbours Regression, Extreme Gradient Boosting, and Long/Short-Term Memory Neural Networks. Additionally, historical REIT prices are supplemented with Technical Analysis indicators (TAIs) to aid in price predictions. While TA indicators are commonly used in stock market forecasting, their application in the context of REITs has remained relatively unexplored. The study applied these algorithms to predict future prices for 30 REITs from the United States, United Kingdom, and Australia, along with 30 stocks and 30 bonds. After obtaining our price predictions, we employ a Genetic Algorithm (GA) to optimise weights of a diversified portfolio. Our results reveal several key findings: (i) all machine learning algorithms demonstrated low average and standard deviation values in the error rate distributions, outperforming commonly used statistical benchmarks such as Holt’s Linear Trend Method (HLTM), Trigonometric Box-Cox Autoregressive Time Series (TBATS), and Autoregressive Integrated Moving Average (ARIMA); (ii) incorporating Technical Analysis indicators in the ML algorithms resulted in a significant reduction in prediction errors, up to 60% in some cases; and (iii) a multi-asset portfolio constructed using predictions that incorporated Technical Analysis indicators outperformed a portfolio based solely on predictions derived from past prices. Furthermore, this study employed Shapley Value-based techniques, specifically SHAP and SAGE, to analyse the importance of the features used in the analysis. These techniques provided additional evidence of the value added by Technical Analysis indicators in this context.
A systematic survey on human pose estimation: upstream and downstream tasks, approaches, lightweight models, and prospects
Authors: Gao Zheyan , Chen Jinyan , Liu Yuxin , Jin Yucheng , Tian Dingxiaofei 
Published: January 2025

Abstract
In recent years, human pose estimation has been widely studied as a branch task of computer vision. Human pose estimation plays an important role in the development of medicine, fitness, virtual reality, and other fields. Early human pose estimation technology used traditional manual modeling methods. Recently, human pose estimation technology has developed rapidly using deep learning. This study not only reviews the basic research of human pose estimation but also summarizes the latest cutting-edge technologies. In addition to systematically summarizing the human pose estimation technology, this article also extends to the upstream and downstream tasks of human pose estimation, which shows the positioning of human pose estimation technology more intuitively. In particular, considering the issues regarding computer resources and challenges concerning model performance faced by human pose estimation, the lightweight human pose estimation models and the transformer-based human pose estimation models are summarized in this paper. In general, this article classifies human pose estimation technology around types of methods, 2D or 3D representation of outputs, the number of people, views, and temporal information. Meanwhile, classic datasets and targeted datasets are mentioned in this paper, as well as metrics applied to these datasets. Finally, we generalize the current challenges and possible development of human pose estimation technology in the future.
Application of deep learning for high-throughput phenotyping of seed: a review
Authors: Jin Chen , Zhou Lei , Pu Yuanyuan , Zhang Chu , Qi Hengnian , Zhao Yiying 
Published: January 2025

Abstract
Seed quality is of great importance for agricultural cultivation. High-throughput phenotyping techniques can collect magnificent seed information in a rapid and non-destructive manner. Emerging deep learning technology brings new opportunities for effectively processing massive and diverse data from seeds and evaluating their quality. This article comprehensively reviews the principle of several high-throughput phenotyping techniques for non-destructively collection of seed information. In addition, recent research studies on the application of deep learning-based approaches for seed quality inspection are reviewed and summarized, including variety classification and grading, seed damage detection, components prediction, seed cleanliness, vitality assessment, etc. This review illustrates that the combination of deep learning and high-throughput phenotyping techniques can be a promising tool for collection of various phenotype information of seeds, which can be used for effective evaluation of seed quality in industrial practical applications, such as seed breeding, seed quality inspection and management, and seed selection as a food source.
Intensive Outreach for Mental Health: Young People’s Experiences of an Intensive Outreach Model on Recovery and Engagement
Authors: Bellairs-Walsh India , Nichterlein Maria , Assan Ben , Stargatt Robyn 
Published: January 2025

AbstractEngagement with traditional mental health services can be particularly challenging for young people experiencing severe and complex mental health problems. Assertive community treatment-based services providing mobile outreach, such as Intensive Mobile Youth Outreach Services (IMYOS), operate across Australia to support these young people’s mental health needs in the transition to adulthood. Past research on IMYOS has focused on quantitative outcome measures, and young people’s experiences of this type of model are poorly understood. This study explored youth service users’ experiences of an IMYOS program, focusing on the model and intervention aspects perceived as barriers and facilitators to their overall recovery and service engagement. Semi-structured, in-depth interviewing was undertaken with nine young people aged 16–19 years (M = 17.61 years) who were current or recent service users of an IMYOS program in Melbourne, Australia. Data were analysed using thematic analysis. Having a therapeutic space, clinicians’ specialised expertise, use of an outreach and community-oriented approach, and care continuity and availability across settings were program aspects identified by young people as facilitating their recovery and service engagement. Program aspects perceived as barriers to recovery and engagement were clinical unsuitability and ineffectiveness of the program and interventions, and conflicts between personal autonomy and assertive care. Young people’s perceptions of clinical suitability and therapeutic relevance influenced their evaluations of the overall effectiveness of the IMYOS service, which subsequently impacted their engagement. The findings provide opportunities for IMYOS clinicians to enhance young people’s recovery and engagement outcomes and have implications for the improvement of this innovative service for at-risk young people.
Infectious disease hospitalization after receipt of human papillomavirus vaccine: a nationwide register-based cohort study among Danish, Finnish, Norwegian, and Swedish girls
Authors: Laake Ida , Feiring Berit , Gehrt Lise , Englund Hélène , Lahdenkari Mika , Sørup Signe , Nieminen Heta , Trogstad Lill 
Published: January 2025

Abstract
It has been suggested that non-live vaccines may increase susceptibility to non-targeted infections and that such deleterious non-specific effects are more pronounced in girls. We investigated whether receipt of non-live vaccine against human papillomavirus (HPV) was associated with increased risk of infectious disease hospitalization. A nationwide cohort study based on detailed individual-level data from national registries was performed in Denmark, Finland, Norway, and Sweden. The cohort consisted of girls aged 11–14 years in Denmark, Finland, and Norway, and 10–14 years in Sweden. Cox regression, with extensive control for potential confounders, was used to assess whether risk of infectious disease hospitalization with at least one overnight stay differed according to time-varying HPV vaccination status. In total, 754 458 girls were included in the analysis. The infectious disease hospitalization rate (per 10 000 person years) was 44.1 in Denmark, 35.7 in Finland, 37.1 in Norway, and 28.5 in Sweden. Comparing HPV-vaccinated with HPV-unvaccinated person time, the adjusted hazard ratio (95% confidence interval) was 0.81 (0.72, 0.90) in Denmark, 0.69 (0.60, 0.80) in Finland, 0.76 (0.66, 0.88) in Norway, and 0.59 (0.49, 0.71) in Sweden. Decreased risk was observed regardless of number of doses, except in Norway, where risk among girls with only one dose did not differ from risk among unvaccinated girls. Receipt of HPV vaccine was consistently associated with decreased risk of infectious disease hospitalization among girls in the Nordic countries. Our study does not support that HPV vaccines have deleterious non-specific effects.
Nonconvex Quasi-Variational Inequalities: Stability Analysis and Application to Numerical Optimization
Authors: Dutta Joydeep , Lafhim Lahoussine , Zemkoho Alain , Zhou Shenglong 
Published: January 2025

Abstract
We consider a parametric quasi-variational inequality (QVI) without any convexity assumption. Using the concept of optimal value function, we transform the problem into that of solving a nonsmooth system of inequalities. Based on this reformulation, new coderivative estimates as well as robust stability conditions for the optimal solution map of this QVI are developed. Also, for an optimization problem with QVI constraint, necessary optimality conditions are constructed and subsequently, a tailored semismooth Newton-type method is designed, implemented, and tested on a wide range of optimization examples from the literature. In addition to the fact that our approach does not require convexity, its coderivative and stability analysis do not involve second order derivatives, and subsequently, the proposed Newton scheme does not need third order derivatives, as it is the case for some previous works in the literature.
Uranium separation from urine matrix using amidoximated crosslinked polyacrylonitrile adsorbent
Authors: Prabhu S. P. , Kanjilal Amit , Gondane Sonali , Sawant P. D. , Kumar Awadhesh , Chaudhury Probal , Kulkarni M. S. 
Published: January 2025

AbstractA rapid radiochemical separation method was developed for the assessment of uranium in urine using indigenously synthesised amidoximated crosslinked polyacrylonitrile (ACPAN) adsorbent. The synthesised adsorbent exhibited a high uranium adsorption capacity for urine samples conditioned at pH 2. The reusability of the ACPAN adsorbent was demonstrated by its stable adsorption capacity for ultra-trace levels of uranium over multiple cycles. The standardized method complied ANSI 13.30 radio bioassay performance criteria, validating the suitability of this novel technique for precise determination of uranium in urine. The method developed is rapid, sensitive, and can be applied for emergency bioassay of uranium in urine.
Tunnel wash water in a cold climate: characteristics, ecotoxicological risk, and effect of sedimentation
Authors: Sossalla Nadine A. , Uhl Wolfgang , Vistnes Hanne , Rathnaweera Subhash Srikantha , Vik Eilen Arctander , Meyn Thomas 
Published: January 2025

Abstract
The characterization of tunnel wash water (TWW) from 12 Norwegian tunnels showed very high concentrations of total suspended solids (TSS), metals, and polycyclic aromatic hydrocarbons (PAHs). Iron (Fe), aluminum (Al), and manganese (Mn) were mainly particle-associated. They are efficiently removed by sedimentation, while the dissolved concentrations of toxic metals like Cu, Zn, and As did not change. Polycyclic aromatic hydrocarbon (PAH) concentration was higher in the dissolved than in the particulate fraction. Sedimentation treatment reduced the particulate share by about 50%. In contrast to metals, the dissolved fraction decreased by about 90% during sedimentation, most probably due to adsorption to particles that are subsequently removed during the process. The concentration levels of 8 out of 16 PAHs, Cu, Zn, and As resulted in a water quality classification of poor or very poor. Acute toxic effects could be expected after short-term exposition. After sedimentation, this was the case for only two PAHs because more harmful compounds with three to six rings were preferably removed. These may adsorb better to particles than PAHs with two rings. No change was observed for the metals. A closer evaluation of secondary treatments of TWW, including conventional technology and mobile solutions, is therefore recommended. Finally, indications for a seasonal pollution variation have been seen, mainly related to the use of salt as a de-icing agent in road maintenance.

Graphical Abstract
Hydrogen-Bonding-Crosslinked Polyzwitterionic Hydrogels with Extreme Stretchability, Ultralow Hysteresis, Self-adhesion, and Antifreezing Performance as Flexible Self-powered Electronic Devices
Authors: Bao Siyu , Wang Hongying , Liu Baocheng , Huang Chenhao , Deng Jingguo , Ren Wenjie , Li Yongmao , Yang Jianhai 
Published: January 2025

AbstractFlexible strain sensors have received tremendous attention because of their potential applications as wearable sensing devices. However, the integration of key functions into a single sensor, such as high stretchability, low hysteresis, self-adhesion, and excellent antifreezing performance, remains an unmet challenge. In this respect, zwitterionic hydrogels have emerged as ideal material candidates for breaking through the above dilemma. The mechanical properties of most reported zwitterionic hydrogels, however, are relatively poor, significantly restricting their use under load-bearing conditions. Traditional improvement approaches often involve complex preparation processes, making large-scale production challenging. Additionally, zwitterionic hydrogels prepared with chemical crosslinkers are typically fragile and prone to irreversible deformation under large strains, resulting in the slow recovery of structure and function. To fundamentally enhance the mechanical properties of pure zwitterionic hydrogels, the most effective approach is the regulation of the chemical structure of zwitterionic monomers through a targeted design strategy. This study employed a novel zwitterionic monomer carboxybetaine urethane acrylate (CBUTA), which contained one urethane group and one carboxybetaine group on its side chain. Through the direct polymerization of ultrahigh concentration monomer solutions without adding any chemical crosslinker, we successfully developed pure zwitterionic supramolecular hydrogels with significantly enhanced mechanical properties, self-adhesive behavior, and antifreezing performance. Most importantly, the resultant zwitterionic hydrogels exhibited high tensile strength and toughness and displayed ultralow hysteresis under strain conditions up to 1100%. This outstanding performance was attributed to the unique liquid–liquid phase separation phenomenon induced by the ultrahigh concentration of CBUTA monomers in an aqueous solution, as well as the enhanced polymer chain entanglement and the strong hydrogen bonds between urethane groups on the side chains. The potential application of hydrogels in strain sensors and high-performance triboelectric nanogenerators was further explored. Overall, this work provides a promising strategy for developing pure zwitterionic hydrogels for flexible strain sensors and self-powered electronic devices.
A new species and a new combination in Stenandriopsis (Acanthaceae) from Madagascar
Authors: Darbyshire Iain , Callmander Martin W. , Randriamamonjy Nomentsoa J. E. 
Published: January 2025

SummaryA new species of the palaeotropical genus Stenandriopsis S.Moore (Acanthaceae) is described from Daraina region (Loky-Manambato) in northeastern Madagascar, and named S. darainensis I.Darbysh. & Callm. It is compared to the most similar species morphologically, S. boivinii (S.Moore) Benoist, and notes on its habitat preferences and conservation status (extinction risk) are provided — it is assessed using IUCN criteria as Vulnerable [VU D2]. In addition, Stenandriopsis leptostachys Benoist var. longifolia Benoist from southern Madagascar is re-elevated to full species status and a new combination in Stenandriopsis is made for this taxon, Stenandriopsis longifolia (Benoist) I.Darbysh. & Callm.
Early clinical outcomes of transcatheter aortic valve implantation using the NAVITOR system
Authors: Fujita Kosuke , Matsumura Koichiro , Sugimoto Keishiro , Onishi Kyohei , Kakehi Kazuyoshi , Yoshida Ayano , Kawamura Takayuki , Yasuda Masakazu , Matsuzoe Hiroki , Mizutani Kazuki , Miyoshi Tatsuya , Ueno Masafumi , Sakaguchi Genichi , Nakazawa Gaku 
Published: January 2025

AbstractTranscatheter aortic valve implantation (TAVI) using the NAVITOR system has been relatively underreported due to its recent introduction in Japan. This study aimed to assess the short-term outcomes of TAVI with the NAVITOR in real-world clinical practice. Patients with severe aortic stenosis who underwent TAVI using the NAVITOR system at our institution between December 2022 and December 2023 were prospectively enrolled. We evaluated the 30-day post-TAVI outcomes using the Valve Academic Research Consortium 3 (VARC-3). Among 32 consecutive patients (mean age, 84 years; 19% female), technical success was achieved in 31 (96.8%). One patient developed a subclavian artery vascular dissection, requiring balloon angioplasty during the TAVI procedure, and another received a permanent pacemaker due to persistent advanced atrioventricular block. At the 30-day follow-up, device success was achieved in 31 (96.8%) patients, with early safety observed in 27 (84.3%). One patient experienced sudden unexplained death after discharge. None of the patients experienced myocardial infarction, valve embolisation, life-threatening bleeding, or acute kidney injury within 30 days after the procedure. Echocardiographic follow-up showed a median effective orifice area index of 1.26 ± 0.27. Contrast-enhanced computed tomography was performed in 19 patients 30 days after the procedure, revealing hypo-attenuated leaflet thickening (HALT) in 10 (52.6%). Although the 30-day outcomes of TAVI using the NAVITOR system appeared promising, a relatively high incidence of HALT was observed.
Graphical Abstract
Novel neo-clerodane diterpenoids from Teucrium quadrifarium and their anti-ferroptosis effect
Authors: Wang Huan , Liu Han-Fei , Yang Xiao-Qiao , Liao Yu-Qiong , Pan Fen-Cong , Li Jin-Yu , Lou Hua-Yong , Pan Wei-Dong 
Published: January 2025

AbstractTeucrifarides A–D (1–4), four previously unreported neo-clerodane-type diterpenoids, combined with sixteen known analogs (5–20), were purified from Teucrium quadrifarium. The absolute forma of compounds 1–4 were determined via spectroscopic and ECD calculation methods, together with X-ray crystallography experiments. Among them, compound 1 possessed a 5,20-epoxy ring featuring a unique cage-like 12-oxatricyclo [5.3.2.01,6]undecane skeleton. Meanwhile, 2 incorporated a 6,20-epoxy ring with a novel 12-oxatricyclo [6.2.2.02,7]undecane skeleton. Compounds 1 and 12 exhibited significant inhibitory effects against HT-22 cells ferroptosis induced by RSL3, with EC50 values of 11.8 ± 1.0 μM, and 4.52 ± 1.24 μM, respectively. Moreover, ROS accumulation in HT22 cells treated with compound 1 was also observed.
Graphical Abstract