bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shortening mechanisms in construction morphology: the Russian spec-N construction
Authors: Nesset Tore , Björklund Martina , Sokolova Svetlana 
Published: October 2024

AbstractThis study presents an in-depth analysis of Russian stub compounds in spec ‘special’ and their competition with the corresponding full adjective special’nyj ‘special’ followed by a noun. Couched in Construction Morphology the corpus-based analysis addresses four understudied areas in theoretical and Russian morphology: shortening mechanisms, competition between morphological words and multiword expressions, blocking, and compounding in Russian. It is argued that shortening mechanisms create words that are more than stylistic variants of the corresponding longer constructions, although full synonymy may occur under specific conditions. The diachronic and synchronic motivation of the shortening mechanism under scrutiny is analyzed in terms of economy, extravagance and expressiveness. Blocking is demonstrated to be statistical (involving tendencies rather than categorical rules) and bidirectional, whereby a morphological construction may be favored over a syntactic construction and vice versa. The proposed analysis adds to the knowledge of stub compounds in Russian and demonstrates how a wide variety of generalizations can be adequately accounted for in Construction Morphology.
Is the continuity of the therapist–patient relationship relevant for the discharge outcome in orthopaedic physical rehabilitation?
Authors: Platano D. , Tedeschi R. , Tonini G. , Capone S. , Morri M. , Magli A. O. , Raffa D. , Benedetti M. G. 
Published: October 2024

AbstractContinuity of care has been linked to patient satisfaction and self-reported outcomes. Following hip fractures in the elderly, rehabilitation aims at restoring patients’ mobility and independence at the pre-fracture level and at the earliest possible time. Despite the potential role of physiotherapists’ continuity on functional outcomes, this correlation has not yet been studied in an acute orthopaedic setting. Guaranteeing the presence of the same physical therapist on individual patients is challenging from an organizational point of view. An observational retrospective study was conducted on 129 aged patients (84 ± 8 years) who underwent surgery for proximal hip fracture. Indicators of outcomes were ILOA score at discharge, length of stay and achievement of rehabilitation goals as defined by the Individual Rehabilitation Project. The number of physical therapists taking care of patients was monitored during the patient’s hospital stay. No correlation was found between the number of physical therapists and functional goals at discharge. The frequent change of physical therapists providing rehabilitation to elderly patients who underwent surgery for hip fragile fracture is not related to functional outcomes.
Nonthermal fluctuations accelerate biomolecular motors
Authors: Ariga Takayuki 
Published: October 2024

AbstractIntracellular transport is essential for maintaining cellular function. This process is driven by different mechanisms in prokaryotic and eukaryotic cells. In small prokaryotic cells, diffusion is the primary means of transport, while larger eukaryotic cells also rely on active transport by molecular motors such as kinesin and dynein. Recently, it has become evident that, in addition to diffusion based on thermal fluctuations (Brownian motion), which was conventionally considered a diffusion mechanism within living cells, nonthermal fluctuations generated by metabolic activities play a crucial role in intracellular diffusion. Similarly, while molecular motors have been proposed to exploit thermal fluctuations in the environment following the direct observation and manipulation of single molecules, they have also been reported to utilize nonthermal fluctuations in recent years. This review begins with a brief overview of the historical knowledge of diffusive intracellular transport, which has been extended from the thermal fluctuations to the nonthermal fluctuations generated by metabolic activity. It then introduces recent findings on how nonthermal fluctuations accelerate the motion of molecular motors and discusses future perspectives on the general effects of these fluctuations on molecules in living cells.
Genome-Wide DNA Methylation Profiling Reveals Low Methylation Variability in Moyamoya Disease
Authors: Tokairin Kikutaro , Ito Masaki , Lee Alex G. , Teo Mario , He Shihao , Cheng Michelle Y. , Steinberg Gary K. 
Published: October 2024

AbstractMoyamoya disease (MMD) is a chronic cerebrovascular disorder that can lead to stroke and neurological dysfunctions. Given the largely sporadic nature and the role of gene-environment interactions in various diseases, we examined epigenetic modifications in MMD. We performed genome-wide DNA methylation using Illumina 850 K Methylation EPIC BeadChip, in two racially distinct adult female cohorts: a non-Asian cohort (13 MMD patients and 7 healthy controls) and an Asian cohort (14 MMD patients and 3 healthy controls). An additional external cohort with both sexes (females: 5 MMD patients and 5 healthy controls, males: 5 MMD patients and 5 healthy controls) was included for validation. Our findings revealed strikingly low DNA methylation variability between MMD patients and healthy controls, in both MMD female cohorts. In the non-Asian cohort, only 6 probes showed increased variability versus 647 probes that showed decreased variability. Similarly, in the Asian cohort, the MMD group also displayed a reduced methylation variability across all 2845 probes. Subsequent analysis showed that these differentially variable probes are located on genes involved in key biological processes such as methylation and transcription, DNA repair, cytoskeletal remodeling, natural killer cell signaling, cellular growth, and migration. These findings mark the first observation of low methylation variability in any disease, contrasting with the high variability observed in other disorders. This reduced methylation variability in MMD may hinder patients’ adaptability to environmental shifts, such as hemodynamic stress, thereby influencing vascular homeostasis and contributing to MMD pathology. These findings offer new insights into the mechanisms of MMD and potential treatment strategies.
SARS-CoV-2 Spike Protein Exacerbates Thromboembolic Cerebrovascular Complications in Humanized ACE2 Mouse Model
Authors: Heath Stan P. , Hermanns Veronica C. , Coucha Maha , Abdelsaid Mohammed 
Published: October 2024

AbstractCOVID-19 increases the risk for acute ischemic stroke, yet the molecular mechanisms are unclear and remain unresolved medical challenges. We hypothesize that the SARS-CoV-2 spike protein exacerbates stroke and cerebrovascular complications by increasing coagulation and decreasing fibrinolysis by disrupting the renin-angiotensin-aldosterone system (RAAS). A thromboembolic model was induced in humanized ACE2 knock-in mice after one week of SARS-CoV-2 spike protein injection. hACE2 mice were treated with Losartan, an angiotensin receptor (AT1R) blocker, immediately after spike protein injection. Cerebral blood flow and infarct size were compared between groups. Vascular-contributes to cognitive impairments and dementia was assessed using a Novel object recognition test. Tissue factor-III and plasminogen activator inhibitor-1 were measured using immunoblotting to assess coagulation and fibrinolysis. Human brain microvascular endothelial cells (HBMEC) were exposed to hypoxia with/without SARS-CoV-2 spike protein to mimic ischemic conditions and assessed for inflammation, RAAS balance, coagulation, and fibrinolysis. Our results showed that the SARS-CoV-2 spike protein caused an imbalance in the RAAS that increased the inflammatory signal and decreased the RAAS protective arm. SARS-CoV-2 spike protein increased coagulation and decreased fibrinolysis when coincident with ischemic insult, which was accompanied by a decrease in cerebral blood flow, an increase in neuronal death, and a decline in cognitive function. Losartan treatment restored RAAS balance and reduced spike protein-induced effects. SARS-CoV-2 spike protein exacerbates inflammation and hypercoagulation, leading to increased neurovascular damage and cognitive dysfunction. However, the AT1R blocker, Losartan, restored the RAAS balance and reduced COVID-19-induced thromboembolic cerebrovascular complications.
How Do Multiplicative and Relational Thinking Contribute to Multidigit Division?
Authors: Schulz Andreas 
Published: October 2024

Abstract
Multiplicative thinking (MT), relational thinking (RT), and multidigit division are highly important for facilitating the transition from arithmetic to algebra in the middle grades. The present study analyzed the extent to which the contribution of MT to multidigit division was mediated by 472 fourth- and fifth-grade students’ RT and how their RT supported the use of multiple and clever shortcut strategies for multidigit division. The MT measurement instrument mapped the progression from additive to multiplicative thinking in two proficiency levels, and the RT measurement instrument operationalized the progression from understanding and using relationships between numbers to understanding and using relationships between terms in four proficiency levels. RT was a complete mediator of the impact of MT on multidigit division and had a particularly strong influence on the use of 10 × N patterns and advanced strategies, including shortcut strategies.
Diversifying Skin Tone Representation in Medical School Dermatology Curriculum
Authors: Barzallo Devin , Ofori-Darko Afua A. , Perez Ashley M. , DiSano Katherine 
Published: October 2024

AbstractThe lack of diversity in medical education contributes to disparities in dermatologic health outcomes, particularly for patients of color. This study evaluates second-year medical students’ comfort in diagnosing conditions in skin of color (SOC) and explores strategies to improve their confidence. We hypothesize that a curriculum enriched with SOC representation will enhance diagnostic skills. Surveys from Fall 2020 and Fall 2022 showed increased student comfort in diagnosing SOC. Fall 2022 students, exposed to more diverse dermatologic photos, demonstrated greater confidence. These findings underscore the necessity of integrating SOC content into medical curricula to address healthcare disparities.
What’s the Future for Science in the New Zealand Curriculum?
Authors: Stewart Georgina Tuari , Eames Chris , Hipkins Rose , Cheng Maurice M. W. , Birdsall Sally , Buntting Cathy , Carpendale Jared , Edwards Richard , Hunt Davina , Swanson Carolyn 
Published: October 2024

AbstractThis commentary article considers the current contentious debates over the national school science curriculum in Aoteaora New Zealand. The co-authors of this commentary are members of a group of science teacher educators and science education researchers who met recently to discuss concerns over aspects of these debates in the context of a wider political contest over the control and direction of education policy.
Changes in the Perception of Error Announcements from the German Two-Tier Enforcement
Authors: Berninger Marc 
Published: October 2024

Abstract
When the German financial reporting enforcement was introduced in 2004, the legislator chose an innovative approach: He combined a private enforcement institution with a governmental agency while sanctioning was carried out solely by publicly announcing identified accounting errors. Subsequently, investors were confronted with up to then unprecedented ‘error announcements’ from the enforcement system. For a sample of 213 announcements from 2006 to 2019, the paper analyzes the adaptation process of investors to this new information. While significant negative market reactions around the announcement dates can be found for the whole observation period, the results also show that the investors’ views of the error announcements change over time. Especially in the early years, the observed market reactions are strongly linked to the impact of the accounting error on the firm’s financial situation. This link weakens over time and factors related to the nature of the error become more important to investors. In particular, errors that are attributable to the unjustifiable application of professional judgment lead to significantly more negative effects.
Predicting Multiple Outcomes Associated with Frailty based on Imbalanced Multi-label Classification
Authors: Tarekegn Adane Nega , Michalak Krzysztof , Costa Giuseppe , Ricceri Fulvio , Giacobini Mario 
Published: October 2024

AbstractFrailty syndrome is prevalent among the elderly, often linked to chronic diseases and resulting in various adverse health outcomes. Existing research has predominantly focused on predicting individual frailty-related outcomes. However, this paper takes a novel approach by framing frailty as a multi-label learning problem, aiming to predict multiple adverse outcomes simultaneously. In the context of multi-label classification, dealing with imbalanced label distribution poses inherent challenges to multi-label prediction. To address this issue, our study proposes a hybrid resampling approach tailored for handling imbalance problems in the multi-label scenario. The proposed resampling technique and prediction tasks were applied to a high-dimensional real-life medical dataset comprising individuals aged 65 years and above. Several multi-label algorithms were employed in the experiment, and their performance was evaluated using multi-label metrics. The results obtained through our proposed approach revealed that the best-performing prediction model achieved an average precision score of 83%. These findings underscore the effectiveness of our method in predicting multiple frailty outcomes from a complex and imbalanced multi-label dataset.
Incomplete Objectives in Decision Making: How Omitting Objectives Affects Identifying the Most Promising Alternative
Authors: Abdeen Sara J. M. , Methling Florian , von Nitzsch Rüdiger 
Published: October 2024

AbstractResearch has shown that decision-makers omit a significant number of their objectives when making a decision. This study examines the consequences of incomplete objectives on decision making, i.e., how does omitting objectives affect identifying the most promising alternative? We investigate this question using a dataset of 945 observed decisions. These decisions were developed by students using the decision-skills and training tool entscheidungsnavi.com. The tool guides students in a step-by-step process based on value-focused thinking, multi-attribute utility theory, and debiasing methods. Results show that omitting objectives significantly reduces the chances of identifying the most promising alternative. Hence, neglecting only 20% of the objectives is sufficient to mislead more than one in four decisions. We have found three factors that influence this risk of misidentifying the most promising alternative: (1) the weight of the omitted objectives; (2) the consensus on the best alternative across all objectives; and (3) the consensus on the ranking of all alternatives across all objectives.
Multi-label semantic segmentation of magnetic resonance images of the prostate gland
Authors: Locherer Mark , Bonenberger Christopher , Ertel Wolfgang , Hadaschik Boris , Stumm Kristina , Schneider Markus , Radtke Jan Philipp 
Published: October 2024

AbstractProstate segmentation is a substantial factor in the diagnostic pathway of suspicious prostate lesions. Medical doctors are assisted by computer-aided detection and diagnosis systems systems and methods derived from artificial intelligence deep learning-based systems have to be trained on existing data. Especially freely available labeled prostate magnetic resonance imaging data is rare. With regard to this problem, we show a method to combine two existing small datasets to form a bigger one. We present a data processing pipeline consisting of a cascaded network architecture that is able to perform multi-label semantic segmentation, hence, capable of classifying each pixel in a $$\textrm{T}_{2}$$

T
2

-weighted image not only to one class but to a subset of the prostate zones and classes of interest. This delivers richer information such as overlapping zones that are key to medical radiological examination. Additionally, we describe how to integrate expert knowledge in our deep learning system. To increase data variety for training and evaluation we use image augmentation on our two datasets—a freely available dataset and our new open-source dataset. To combine the datasets we denoise the contourings in our dataset by using an effective yet simple algorithm based on standard computer vision methods only. The performance of the presented methodology is compared and evaluated using the dice score metric and 5-fold cross-validation on all datasets. Although we trained on tiny datasets our method achieves excellent segmentation quality and is even able to detect prostate cancer. Our method to combine the two datasets reduces segmentation errors and increases data variety. The proposed architecture significantly improves performance by including expert knowledge via feature-map concatenation. On the initiative for collaborative computer vision benchmarking dataset we achieve on average dice scores of approximately 91% for the whole prostate gland, 67% for the peripheral zone and 75% for the prostate central gland. We find that image augmentation except contrast limited adaptive histogram equalisation did not have much influence on the segmentation quality. Derived and enhanced from existing methods we present an approach that is able to deliver multi-label semantic segmentation results for prostate magnetic resonance imaging. This approach is simple and could be applied to other applications of deep learning as well. It improves the segmentation results by a large margin. Once tweaked to the data, our denoising and combination algorithm delivers robust and accurate results even on data with segmentation errors.
Efficacy of sevoflurane flush out and activated charcoal filtration—a bench study
Authors: Mörtl Maximilian , Schwaiger Daniel , Lederer Wolfgang , Weiss Florentin , Chawaguta Anesu , Wiesenhofer Helmut , Mayhew Chris A. , Ruzsanyi Veronika 
Published: October 2024

Abstract
Purpose
A bench study to assess the elimination of sevoflurane from an anesthetic workstation using three different processing methods.

Methods
Sevoflurane concentrations from samples of the inspiratory breathing hose and air samples from within the investigation room were assessed during predetermined flush out intervals using Gas Chromatography-Ion Mobility Spectrometry. The primary objective was to determine the time to reach concentrations below 5 ppmv.

Results
Reduction of sevoflurane volume concentrations below a threshold of 5 ppmv was achieved within the first minute after removal of the vaporizer and the complete exchange of the soda and the breathing system and within the 15 min measurement interval after inclusion of two activated charcoal filters without a 90 s of flushing and without changing of the breathing hoses as required by the manufacturer.

Conclusions
Complete removal of the vaporizer and an exchange of the soda and the ventilation unit most quickly reduced sevoflurane concentrations, but the total processing interval may exceed 30 min. Inserted activated charcoal filters without a previous 90 s of flushing and without changing the breathing hoses followed by flushing only with raised fresh gas flow allow ventilation below trigger threshold to be reached within due time.
Q vs A proximities in construed modes of learning: Excitement and performance of university students in China’s Northeast
Authors: Zhao Xuanwei , Xie Mingyi , Michael Kathy 
Published: October 2024

AbstractThis study explores how Q-proximity and A-proximity affect the student's learning excitement and performance, and how they differ in these effects. Using the Construal Level Theory (CLT), a questionnaire was designed with multiple models (in which the student owns the Q, A, both or neither). The study then factored Qs and As to obtain two respective proximities and link them to excitement and performance scores. Based on 590 useful questionnaire responses, the study identified the following findings, 1. with structural equation modelling (SEM) both Q and A proximities encouraged student learning excitement, although the A excitement was greater than the Q excitement and 2. the Q-proximity decreases performance whilst the A-proximity increases performance. Additionally, the study used multiple analyses of individual learning modes concerning excitement and performance. The results of the multiple regression analysis appear to be consistent with the research of Malik (Current Psychology 43:545–564, 2024), and the inclusion of AI (Artificial Intelligence) learning modes. The main conclusion of the study is that Chinese learners prefer answers to the questions in their learning, teaching and application of knowledge.
Counterfactual discriminative micro-expression recognition
Authors: Li Yong , Liu Menglin , Lao Lingjie , Wang Yuanzhi , Cui Zhen 
Published: October 2024

AbstractMicro-expressions are spontaneous, rapid and subtle facial movements that can hardly be suppressed or fabricated. Micro-expression recognition (MER) is one of the most challenging topics in affective computing. It aims to recognize subtle facial movements which are quite difficult for humans to perceive in a fleeting period. Recently, many deep learning-based MER methods have been developed. However, how to effectively capture subtle temporal variations for robust MER still perplexes us. We propose a counterfactual discriminative micro-expression recognition (CoDER) method to effectively learn the slight temporal variations for video-based MER. To explicitly capture the causality from temporal dynamics hidden in the micro-expression (ME) sequence, we propose ME counterfactual reasoning by comparing the effects of the facts w.r.t. original ME sequences and the counterfactuals w.r.t. counterfactually-revised ME sequences, and then perform causality-aware prediction to encourage the model to learn those latent ME temporal cues. Extensive experiments on four widely-used ME databases demonstrate the effectiveness of CoDER, which results in comparable and superior MER performance compared with that of the state-of-the-art methods. The visualization results show that CoDER successfully perceives the meaningful temporal variations in sequential faces.