bluuebunny/crossref_metadata_2025_split huggingface dataset:
Valvular heart disease in patients with cardiac amyloidosis
Authors: Aimo Alberto , Camerini Lara , Fabiani Iacopo , Morfino Paolo , Panichella Giorgia , Barison Andrea , Pucci Angela , Castiglione Vincenzo , Vergaro Giuseppe , Sinagra Gianfranco , Emdin Michele 
Published: September 2023

AbstractCardiac amyloidosis (CA) is an underdiagnosed condition caused by the deposition of misfolded proteins, namely immunoglobulin light chains and transthyretin, in the extracellular spaces of the heart. Any cardiovascular structure can be affected by amyloid infiltration, including the valves. Amyloid accumulation within the cardiac valves may lead to their structural and functional impairment, with a profound impact on patients’ prognosis and quality of life. The most common forms of valvular disease in CA are aortic stenosis (AS), mitral regurgitation (MR), and tricuspid regurgitation (TR). CA and AS share similar risk factors, disease mechanisms, and remodeling patterns, which make their diagnosis particularly challenging. Patients with both CA and AS experience worse outcomes than CA or AS alone, and transcatheter aortic valve replacement may represent a useful therapeutic strategy in this population. Data on MR and TR are quite limited and mainly coming from case reports or small series. This review paper will summarize our current understanding on the epidemiology, disease mechanisms, echocardiographic features, clinical implications, and therapeutic options of AS, MR, and TR in patients with CA.
Assessing the state of technology education in primary schools: a systematic review of the last 2 decades
Authors: Pappa Christina Ioanna , Georgiou Despoina , Pittich Daniel 
Published: September 2023

AbstractThis study reports on a systematic review of the current status of technology education in primary schools and the terminology used in the fields of technology and engineering education. Additionally, this review highlights crucial aspects of teaching and learning that must not be overlooked when outlining the current state of technology and engineering education, such as students’ and teachers’ personal factors, classroom communication, and teacher professional growth. Following PRISMA guidelines, two electronic databases were reviewed, Web of Science and Education Resources Information Center. The literature search identified a total of 1206 papers, 125 from Web of Science and 1081 from ERIC. After applying the inclusion and exclusion criteria, 33 papers were selected and evaluated in depth. The results show that research on technology education in primary schools is a growing field of interest but fragmented in focus. Our review is the first to indicate the wide range of technology and engineering education definitions. We also highlight the large heterogeneity of studies focusing on students’ and teachers’ personal factors and classroom interactions, a finding that may be explained by the unclear concepts and aims of technology and engineering curricula. This study contributes to and supports research and policymaking to better understand the current status, heterogeneities, and challenges in technology and engineering education in primary schools. In addition, we provide first insights to support professional development efforts targeting teachers’ technology acceptance and improvement of their technology-related teaching practices.
Emotional Prototypicality Ratings for 636 Chinese Words: A Database of Chinese Words with Affective Information
Authors: Zheng Ruiyao , Zhang Meng , Guo Taomei , Guasch Marc , Ferré Pilar 
Published: September 2023

AbstractExemplars of concepts vary in their degree of prototypicality. This is also true for emotion concepts. This study presents prototypicality ratings for a large set of Chinese words. The database contains 636 potential Chinese emotion words (i.e., words that directly express particular emotions, like “高兴 happy” and “哀愁 sad”), from different grammatical categories. Native Chinese speakers rated the words in terms of emotional prototypicality. The database also contains values for valence, arousal, and emotionality. The analyses of the ratings revealed that 502 out of 636 words had a high prototypicality value (value equal to or above three on a 1-to-5 scale), the most prototypical words being negative and high-arousal words. The analyses also indicated that the emotional prototypicality of a word was positively related to both arousal and emotionality, and negatively related to valence. Among these variables, arousal was the most important contributor. Similar results have been found in studies conducted in other languages. This will be a useful resource for researchers interested in studying emotion words in the Chinese language and for those interested in cross-linguistic comparisons.
An overview of mindfulness theories applied to tourism: systematic review update and bibliometric analysis
Authors: Iacob Vivien , de Jesus Saúl Neves , Carmo Cláudia 
Published: September 2023

AbstractThis paper presents a systematic review update regarding mindfulness theories applied to tourism, complemented with a bibliometric analysis. Scientific studies listed in the WOS, SCOPUS, PubMed and PsycInfo databases were analysed using PRISMA guidelines. Twenty-five studies were selected for review from 670 records identified. In recent years, mindfulness has proved to be a promising area of research in tourism, and the number of published studies is increasing. The findings reveal a positive association between mindfulness and tourism experiences, suggesting that tourists who adopt states of mindfulness during their travels benefit from increased pro-environmental behaviours, satisfaction levels, and memorable experiences, leading to destination loyalty. This study provides an in-depth overview of the literature, and helps redress the lack of bibliometric studies in this field. It also identifies common areas of current research interest, offers insights into commonly studied themes, and seeks to raise awareness about the relevance of the concept of mindfulness in tourist experiences and well-being by suggesting implications for research and tourism management.
An overview of consensus models for group decision-making and group recommender systems
Authors: Tran Thi Ngoc Trang , Felfernig Alexander , Le Viet Man 
Published: September 2023

AbstractGroup decision-making processes can be supported by group recommender systems that help groups of users obtain satisfying decision outcomes. These systems integrate a consensus-achieving process, allowing group members to discuss with each other on the potential items, adapt their opinions accordingly, and achieve an agreement on a selected item. Such a process, therefore, helps to generate group recommendations with a high satisfaction level of group members. Our article provides a rigorous review of the existing consensus approaches to group decision-making. These approaches are classified depending on the applied consensus models such asreference domainwhere a set of group members or items is selected for calculating consensus measures,coincidence methodthat calculates the consensus degree between group members depending on the coincidence concept,operatorsthat aggregate user preferences,guidance measureswhere the consensus-achieving process is guided by different consensus measures, andrecommendation generationandindividual centralitythat enhance the role of a moderator or a leader in the consensus-achieving process. Further consensus techniques for group decision-making in heterogeneous and large-scale groups are also discussed in this article. Besides, to provide an overall landscape of consensus approaches, we also discuss new consensus models in group recommender systems. These models attempt to improve basic aggregation strategies, further consider social relationship interactions, and provide group members with intuitive descriptions regarding the current consensus state of the group. Finally, we point out challenges and discuss open topics for future work.
Estimation of Mean Velocity Upstream and Downstream of a Bridge Model Using Metaheuristic Regression Methods
Authors: Kisi Ozgur , Ardiçlioğlu Mehmet , Hadi Arzu M. W. , Kuriqi Alban , Kulls Christoph 
Published: September 2023

AbstractThis study compares four data-driven methods, Gaussian process regression (GPR), multivariate adaptive regression spline (MARS), M5 model tree (M5Tree), and multilinear regression (MLR), in estimating mean velocity upstream and downstream of bridges. Data were obtained through multiple experiments in a rectangular laboratory flume with glass walls 9.5 m long, 0.6 m wide, and 0.6 m deep. Four different bridge models were placed at the 6th meter of the channel to determine the average velocities upstream and downstream. Different data-driven models were implemented with different combinations of effective parameters as input. They were evaluated and compared using root mean square error (RMSE), mean absolute relative error (MARE), and Nash–Sutcliffe efficiency (NSE). The results showed that the MARS had the best efficiency in estimating the mean velocity upstream of the bridge model. At the same time, the M5Tree provided the highest performance in estimating the mean velocity downstream. The MARS method improved the estimation accuracy of GPR, M5Tree, and MLR in the test phase by 23.8%, 45.1%, and 47.4% concerning the RMSE at the upstream. The M5Tree provided better RMSE accuracy of 31.8%, 70.4%, and 75.5% at the downstream compared to MARS, GPR, and MLR, respectively. The study recommends the MARS and M5Tree for estimating mean velocities upstream and downstream of the bridge.
Electrochemical biostimulation of aerobic metabolic TCE degradation in a bioaugmentation approach
Authors: Hertle Steffen , de Boni Nick , Schell Heico , Tiehm Andreas 
Published: September 2023

AbstractChloroethenes are globally prevalent groundwater contaminants. Since 2014, TCE has been shown to be degradable in an aerobic metabolic process where it is used as sole energy source and growth substrate by a mixed bacteria culture (SF culture). In 2019, the SF culture was shown to be successfully used in bioaugmentation approaches under field-relevant conditions. In this study, a combined bio-/electro-approach to stimulate the TCE degradation by the SF culture was investigated in laboratory experiments. Column experiments were set up to compare a bioaugmentation approach with an electrochemical biostimulated bioaugmentation approach. Low strength direct current increased the amount of degraded TCE to about 150 % of the control. Through lowering the inflow concentration of oxygen, the effect of the electro-biostimulation in a low oxygen setting confirmed the potential of the bio-electro process for treatment of oxygen-deprived, TCE-contaminated sites.
Automated Gaze-Based Identification of Students’ Strategies in Histogram Tasks through an Interpretable Mathematical Model and a Machine Learning Algorithm
Authors: Boels Lonneke , Moreno-Esteva Enrique Garcia , Bakker Arthur , Drijvers Paul 
Published: September 2023

AbstractAs a first step toward automatic feedback based on students’ strategies for solving histogram tasks we investigated how strategy recognition can be automated based on students’ gazes. A previous study showed how students’ task-specific strategies can be inferred from their gazes. The research question addressed in the present article is how data science tools (interpretable mathematical models and machine learning analyses) can be used to automatically identify students’ task-specific strategies from students’ gazes on single histograms. We report on a study of cognitive behavior that uses data science methods to analyze its data. The study consisted of three phases: (1) using a supervised machine learning algorithm (MLA) that provided a baseline for the next step, (2) designing an interpretable mathematical model (IMM), and (3) comparing the results. For the first phase, we used random forest as a classification method implemented in a software package (Wolfram Research Mathematica, ‘Classify Function’) that automates many aspects of the data handling, including creating features and initially choosing the MLA for this classification. The results of the random forests (1) provided a baseline to which we compared the results of our IMM (2). The previous study revealed that students’ horizontal or vertical gaze patterns on the graph area were indicative of most students’ strategies on single histograms. The IMM captures these in a model. The MLA (1) performed well but is a black box. The IMM (2) is transparent, performed well, and is theoretically meaningful. The comparison (3) showed that the MLA and IMM identified the same task-solving strategies. The results allow for the future design of teacher dashboards that report which students use what strategy, or for immediate, personalized feedback during online learning, homework, or massive open online courses (MOOCs) through measuring eye movements, for example, with a webcam.
Contributions of Intraspecific Variation to Drought Tolerance in Trees
Authors: Gazol Antonio , Fajardo Alex , Camarero J. Julio 
Published: September 2023

Abstract
Purpose of Review
The capacity of woody plants to cope with climate change depends on their adjustments to changing environmental conditions by phenotypic plasticity or by genotypic changes (i.e., local adaptation). To determine whether intraspecific trait variation (ITV) translates into resistance or tolerance to drought and eventually how it relates to performance when facing drought, we reviewed the recent literature on the intraspecific variation in woody plant functional traits along aridity gradients.

Recent Findings
At the intraspecific level, functional traits vary along aridity gradients, but this variation depends on the considered trait and species. While ITV is ubiquitous and of relevant magnitude, its relationship with tree performance in the case of growth or survival is unclear and very idiosyncratic.

Summary
ITV varies along aridity gradients and, for several traits, is of comparable magnitude as interspecific trait variation. However, the relationship between ITV and tree performance is not consistent among species. This makes the use of ITV challenging when quantifying its contribution to drought tolerance.
Micro–Nano Water Film Enabled High-Performance Interfacial Solar Evaporation
Authors: Yu Zhen , Su Yuqing , Gu Ruonan , Wu Wei , Li Yangxi , Cheng Shaoan 
Published: September 2023

AbstractInterfacial solar evaporation holds great promise to address the freshwater shortage. However, most interfacial solar evaporators are always filled with water throughout the evaporation process, thus bringing unavoidable heat loss. Herein, we propose a novel interfacial evaporation structure based on the micro–nano water film, which demonstrates significantly improved evaporation performance, as experimentally verified by polypyrrole- and polydopamine-coated polydimethylsiloxane sponge. The 2D evaporator based on the as-prepared sponge realizes an enhanced evaporation rate of 2.18 kg m−2 h−1 under 1 sun by fine-tuning the interfacial micro–nano water film. Then, a homemade device with an enhanced condensation function is engineered for outdoor clean water production. Throughout a continuous test for 40 days, this device demonstrates a high water production rate (WPR) of 15.9–19.4 kg kW−1 h−1 m−2. Based on the outdoor outcomes, we further establish a multi-objective model to assess the global WPR. It is predicted that a 1 m2 device can produce at most 7.8 kg of clean water per day, which could meet the daily drinking water needs of 3 people. Finally, this technology could greatly alleviate the current water and energy crisis through further large-scale applications.
Artificial Intelligence-Enabled Mode-Locked Fiber Laser: A Review
Authors: Ma Qiuying , Yu Haoyang 
Published: September 2023

AbstractOwing to their compactness, robustness, low cost, high stability, and diffraction-limited beam quality, mode-locked fiber lasers play an indispensable role in micro/nanomanufacturing, precision metrology, laser spectroscopy, LiDAR, biomedical imaging, optical communication, and soliton physics. Mode-locked fiber lasers are a highly complex nonlinear optical system, and understanding the underlying physical mechanisms or the flexible manipulation of ultrafast laser output is challenging. The traditional research paradigm often relies on known physical models, sophisticated numerical calculations, and exploratory experimental attempts. However, when dealing with several complex issues, these traditional approaches often face limitations and struggles in finding effective solutions. As an emerging data-driven analysis and processing technology, artificial intelligence (AI) has brought new insights into the development of mode-locked fiber lasers. This review highlights the areas where AI exhibits potential in accelerating the development of mode-locked fiber lasers, including nonlinear dynamics prediction, ultrashort pulse characterization, inverse design, and automatic control of mode-locked fiber lasers. Furthermore, the challenges and potential future development are discussed.
Genetische Analyse beim Prostatakarzinom – wer darf was machen?
Authors: Hassler Melanie R. 
Published: September 2023

ZusammenfassungGenetische Analysen an Patienten mit fortgeschrittenem Prostatakrebs entwickelten sich in den letzten Jahren zu einem wichtigen Bestandteil der Diagnostik. Aufgrund der sensiblen Daten und potenziellen Auswirkungen auf Familienmitglieder bei Feststellung einer Disposition zu einer hereditären Krebserkrankung erließen sowohl Deutschland als auch Österreich gesetzliche Regelungen, um sicherzustellen, dass solche Analysen auf sichere, ethische und verantwortungsvolle Weise durchgeführt werden. Die Vorschriften in beiden Ländern sehen vor, dass sich die Betroffenen vor der Durchführung eines Gentests einer genetischen Beratung unterziehen und dass die Tests von zugelassenen Labors durchgeführt werden, welche die in den jeweiligen Gentestgesetzen festgelegten Qualitäts- und Sicherheitsstandards erfüllen. Obwohl es einige Unterschiede zwischen den rechtlichen Rahmenbedingungen in den beiden Ländern gibt, weisen sie viele Gemeinsamkeiten auf und sollen die Gesundheit und das Wohlbefinden von Personen schützen, die sich einer genetischen Analyse bei Prostatakrebs unterziehen.
Validation of a Fast LC-PDA Method for the Quantification of Cannabinoids in Commercial Tea Samples
Authors: Mouton Michaela , Gerber Minja , Van der Kooy Frank 
Published: September 2023

AbstractCannabis and cannabinoids are currently being used to treat a wide variety of medical conditions including, but not limited to, cancer, epilepsy, and pain management. Since the legalization of cannabis-containing (mainly cannabidiol) products, in many countries, and the subsequent upsurge in the number of available commercial products, an increased need exists for a fast and reliable quality control method. Here, we describe the development and validation of a fast (7.5 min) and reliable method for the quantification of cannabidiol and tetrahydrocannabinol, and their respective acid precursors, cannabidiolic acid and tetrahydrocannabinolic acid, in ten commercial tea products using LC-PDA. Due to the lipophilic nature of cannabinoids, all tea samples were also prepared according to the manufacturer’s recommendations and analyzed with the validated method. By extracting the tea samples with acetonitrile, it was found that the actual cannabidiol content in all products tested deviated significantly from their label claims by having as much as 80% less than claimed. By preparing the samples as described on the packaging, no cannabidiol could be detected, indicating that boiling or hot water fails to extract any significant amount of cannabidiol present in these products. It can therefore be concluded that based on the lipophilic nature of cannabidiol, very little to no cannabidiol will be consumed when these products are used as prescribed and therefore may nullify the various health claims made for these popular products.
Graphical Abstract
A causal roadmap for generating high-quality real-world evidence
Authors: Dang Lauren E. , Gruber Susan , Lee Hana , Dahabreh Issa J. , Stuart Elizabeth A. , Williamson Brian D. , Wyss Richard , Díaz Iván , Ghosh Debashis , Kıcıman Emre , Alemayehu Demissie , Hoffman Katherine L. , Vossen Carla Y. , Huml Raymond A. , Ravn Henrik , Kvist Kajsa , Pratley Richard , Shih Mei-Chiung , Pennello Gene , Martin David , Waddy Salina P. , Barr Charles E. , Akacha Mouna , Buse John B. , van der Laan Mark , Petersen Maya 
Published: September 2023

AbstractIncreasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. TheCausal Roadmapis an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, theRoadmapcan help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend theCausal Roadmapframework for use by clinical and translational researchers; three companion papers demonstrate applications of theCausal Roadmapfor specific use cases.
A systematic investigation into the effect of roughness on self-propelled swimming plates
Authors: Massey J.M.O. , Ganapathisubramani B. , Weymouth G.D. 
Published: September 2023

This study examines the effects of surface topography on the flow and performance of a self-propelled swimming (SPS) body. We consider a thin flat plate with an egg-carton roughness texture undergoing prescribed undulatory swimming kinematics at Strouhal number

$0.3$

and tail amplitude to length ratio

$0.1$

; we use plate Reynolds numbers

$Re=6$

, 12 and

$24\times 10^3$

, and focus on

$12\,000$

. As the roughness wavelength is decreased, we find that the undulation wave speed must be increased to overcome the additional drag from the roughness and maintain SPS. Correspondingly, the extra wave speed raises the power required to maintain SPS, making the swimmer less efficient. To decouple the roughness and the kinematics, we compare the rough plates to equivalent smooth cases by matching the kinematic conditions. We find that all but the longest roughness wavelengths reduce the required swimming power and the unsteady amplitude of the forces when compared to a smooth plate undergoing identical kinematics. Additionally, roughness can enhance flow enstrophy by up to 116 % compared to the smooth cases without a corresponding spike in forces; this suggests that the increased mixing is not due to increased vorticity production at the wall. Instead, the enstrophy is found to peak strongly when the roughness wavelength is approximately twice the boundary layer thickness over the

$Re$

range, indicating the roughness induces large-scale secondary flow structures that extend to the edge of the boundary layer. This study reveals the nonlinear interaction between roughness and kinematics beyond a simple increase or decrease in drag, illustrating that roughness studies on static shapes do not transfer directly to unsteady swimmers.