bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid evaluation of habitat connectivity change to safeguard multispecies persistence in human-transformed landscapes
Authors: Oehri Jacqueline , Wood Sylvia L. R. , Touratier Eluna , Leung Brian , Gonzalez Andrew 
Published: September 2024

AbstractFollowing the adoption of the Post-2020 Kunming-Montreal Global Biodiversity Framework (KM-GBF) of the Convention on Biological Diversity (CBD) there is a clear science-policy need to protect habitat connectivity and track its change over time to safeguard biodiversity and inform conservation planning. In response to this need we describe an analytical, multi-indicator and multispecies approach for the rapid assessment of habitat connectivity at fine spatial grain and at the extent of an entire ecoregion. Out of 68 connectivity indicators we found through a literature review, we identified a key-set of six indicators that align with the Essential Biodiversity Variables framework and are suitable to guide rapid action for connectivity and conservation targets in the KM-GBF. Using these selected indicators, we mapped and evaluated connectivity change from 2011 to 2021 across the ecoregion of the St-Lawrence Lowlands in Quebec (~ 30,000 km2) for seven ecoprofile species representing regional forest habitat needs. For most of these species, trends over the last decade indicate a decline in effective connected area and metapopulation carrying capacity, via a division of large contiguous habitat into smaller fragments, whereas on average, habitat area slightly increased. These results highlight that temporal changes in habitat area and connectivity are not necessarily correlated and the urgent need to conserve and restore connectivity to meet targets under the KM-GBF. We provide an R-tool to support our general approach, which enables a comprehensive evaluation of connectivity for regional spatial planning for biodiversity in regions with moderate to high human disturbance.
Assessing the Performance of Flux Imbalance Prediction Models Using Large Eddy Simulations Over Heterogeneous Land Surfaces
Authors: Zhang Lijie , Poll Stefan , Kollet Stefan 
Published: September 2024

AbstractAccurate representation of heat fluxes is crucial for understanding land–atmosphere interactions and improving atmospheric simulations. However, a common issue arises with flux imbalance, where the measured turbulent heat flux tends to be underestimated due to the nonlocal effects of atmospheric secondary circulations. This study evaluated four flux imbalance prediction models by analyzing data from large eddy simulations performed over heterogeneous land surfaces. For that, a checkerboard pattern of soil moisture was used to define the lower boundary conditions for the atmosphere, across heterogeneity scales ranging from 50 m to 2.4 km. The results show that the selected models can effectively predict flux imbalance when provided with proper semi-empirical factors. The presence of two distinct secondary circulations, thermally-induced mesoscale circulation and turbulent organized structures, account for the nonlinear effect of the heterogeneity scale on the flux imbalance, but it does not affect the performance of the selected models. This study suggests that the flux imbalance prediction models are useful for improving e.g. eddy-covariance measurements. Additionally, a quadrant analysis showed an increasing difference between ejections and sweeps with height, which explains the decrease and increase of the turbulent heat flux and flux imbalance, respectively, and underscores the importance of accounting for vertical variations in turbulent fluxes to represent atmospheric processes accurately.
Impact of deep eutectic solvent pre-treatment on the extraction of cellulose nanofibers
Authors: Baraka Farida , Erdocia Xabier , Velazco-Cabral Ivan , Hernández-Ramos Fabio , Dávila-Rodríguez Izaskun , Maugin Marine , Labidi Jalel 
Published: September 2024

AbstractDeep Eutectic Solvents (DESs) have emerged as promising eco-friendly pre-treatment agents for lignocellulosic biomass, offering considerable advantages for the nanofibrillation process. This study investigates the impact of DESs on cellulose fibers morphology, focusing on solubilization phenomena in the amorphous regions that may facilitate cellulose nanofiber production. The pre-treatment process combining a DES (triethylmethylammonium chloride and imidazole, TEMA:IMD) with microwave (MW) energy was optimized to enhance the solubility of cellulosic fibers. A response surface methodology (RSM) was employed to optimize the DES-MW-assisted pre-treatment. Results show that the reaction time and the temperature significantly influence the solubility of cellulosic fibers. The optimized conditions resulted in cellulose fibers with low content of hemicellulose and lignin, high crystallinity index, and improved thermal stability. The effectiveness of DES-MW pre-treatment in producing cellulose nanofibers (CNFs) from native and pre-treated fibers was investigated. Cellulose fibers pre-treated with a DES yielded CNFs with a narrower diameter distribution. Overall, optimized DES-MW pre-treatment offers a promising strategy for the efficient and sustainable extraction of CNFs.
Exploring physical education teachers’ willingness and barriers to integrating digital technology in their lessons
Authors: Saiz-González Pablo , Sierra-Díaz Jacob , Iglesias Damián , Fernandez-Rio Javier 
Published: September 2024

AbstractThe use of digital technologies to support learning in physical education (PE) has grown in recent years. However, little is known about what teachers think when PE meets technology in the digital era. The purpose of this descriptive study was to use a carefully constructed, face-validated, and pilot-tested web survey to identify PE teachers’ willingness and barriers to integrating digital technology in their lessons. A total of 265 PE teachers returned completed surveys. The results showed a widespread interest in the use of digital technology in the school context, as well as in promoting the transfer of learning to the out-of-school context. Also, PE teachers expressed some reasons for interest in its use related to (a) learning and assessment, (b) physical activity, (c) teaching support, (d) communication with families and (e) teamwork among students inside and outside the class. In contrast to these interests and attitudes, teachers identified five major barriers that might be limiting the introduction of digital technology in PE: (a) not having sufficient access to technological resources, (b) not having received the necessary training to use it effectively, (c) lack of institutional support, (d) lack of time to effectively introduce it and (f) students’ data privacy. The findings of this study suggest the implementation of measures that can address the identified barriers to facilitate the incorporation of digital technology in PE. Understanding teachers' perceptions regarding the delivery of digital technology in schools may help guide future research and policy to support digital technology in PE lessons.
From Hands to Mind: How Gesture, Emotional Valence, and Individual Differences Impact Narrative Recall
Authors: Thakore Kavya , Das Trisha , Jahan Shamma , Sweller Naomi 
Published: September 2024

AbstractNarrative recall and comprehension are important lifelong skills. While gesturing may improve recall by alleviating cognitive load, it may be differentially beneficial, depending on task and individual characteristics. While research on gesture’s effects on a variety of task modalities is burgeoning, effects on recall of narratives read aloud are under-examined. Further, emotional valence and individual differences in verbal memory may affect recall, through effects on task difficulty. If gesturing lightens cognitive load, it may be more beneficial for harder tasks, namely for narratives lacking emotional content and for individuals with poorer verbal memory. Across two studies, impacts of gesture production, emotional valence, and individual differences on narrative recall were evaluated. In Study 1, participants (N = 100) read aloud three emotive narratives (positive, negative, neutral) while either instructed to gesture or receiving no gesture instructions. Gesture production hindered recall, particularly for those with higher verbal memory. Emotion benefited recall, with enhanced recall of the negative narrative and impaired recall for the neutral narrative. In Study 2, following a measure of individual propensity to gesture, participants (N = 98) similarly read aloud three emotive narratives. Instructions to gesture hindered recall for participants with a lower propensity to gesture, and emotional narratives again saw enhanced recall relative to the neutral narrative. Propensity to gesture and verbal memory were positively associated with narrative comprehension. Results suggest instructions to produce gestures may for some individuals hinder recall for self-guided learners when studying written texts, while emotional content benefits recall.
Tilapia as a model fish for biomonitoring of metal pollution in dams associated with mining watersheds: contrasting diagnosis from different tissues and health risk assessment
Authors: Páez-Osuna Federico , Espinoza Aldivar Castro , Figueroa Eduardo Tirado , Saucedo Barrón César J. , Bergés-Tiznado Magdalena E. 
Published: September 2024

AbstractTilapia is a model fish species used as a pollution biomonitor due to its tolerance and availability in many contaminated sites. Blue tilapia Oreochromis aureus specimens (n = 320) were collected in eleven dams influenced by mining in the SE Gulf of California region (dams 1, 2 and, 3 comprise 55 mining sites; dam 4 comprises 8; dams 6, 8, 10, and 11, ≤ 6; and dams 5, 7, and 9 include 19, 20, and 16 mining sites, respectively). Cadmium, Cu, Pb, and Zn concentrations were analyzed in the muscle, liver, gills, and guts to identify metal pollution and evaluate risks and seasonal changes. The distinct tissues exhibited different metal accumulation capacities, therefore allowed develop a diagnosis comparative between the eleven dams. In general, metal concentrations were higher in dams 1, 2, 5, and 9, which are associated with more mining sites in their sub-basins. The four metals exhibited the highest levels in the tilapia liver in dams 1 and 2, which can be related to the present and past mining activity in the lower watershed (55 sites) and the geothermal activity in these dams. In general, Zn exhibited the highest level in the tilapia livers from dams 1, 2, 3, 4, 5, and 10 compared to the maximum mean (220 µg/g) concentrations previously recorded. The non-carcinogenic risks indicated that the Pb risk was enhanced when the intake was ≥ 231.5 g week−1 of tilapia muscle, indicating a potential risk of adverse health effects for the entire population.
Constraining mapping class group homomorphisms using finite subgroups
Authors: Chen Lei , Lanier Justin 
Published: September 2024

AbstractWe classify homomorphisms from mapping class groups by using arguments involving finite subgroups. First, we give a new proof of a result of Aramayona–Souto that all homomorphisms between certain mapping class groups of closed surfaces are trivial. Second, we show that only finitely many mapping class groups of closed surfaces have nontrivial homomorphisms to $$\text {Homeo}(\mathbb {S}^n)$$

Homeo
(

S

n

)

for any n, where $$\mathbb {S}^n$$

S

n

is the n-sphere. We also effectivize this result for small values of n; for instance, we prove that every homomorphism from $$\text {Mod}(S_g)$$

Mod
(

S
g

)

to $$\text {Homeo}(\mathbb {S}^2)$$

Homeo
(

S

2

)

or $$\text {Homeo}(\mathbb {S}^3)$$

Homeo
(

S

3

)

is trivial if $$g\ge 3$$

g
≥
3

, extending a result of Franks–Handel.
The Autism Program Environment Rating Scale in Swedish Primary School: Cultural Adaptation and Content Validation
Authors: Wenneborg Klara , Pettersson Roll Lise , Bölte Sven , Odom Samuel , Bejnö Hampus 
Published: September 2024

AbstractThere is a recognized need to improve inclusive learning environments for autistic children in primary school settings in Sweden. This study aimed to translate, cross-culturally adapt, and assess the content validity of the Swedish primary school version of the Autism Program Environment Scale (APERS), originally developed to evaluate autism program quality in educational settings in the United States. Following the translation into Swedish and the first cultural adaptation of the APERS, a content panel group of 14 professionals rated its content validity. Four of the content panel members also participated in individual interviews that provided a qualitative evaluation of the instrument’s content validity. Finally, the authors piloted the APERS in 10 Swedish primary school classrooms to assess its feasibility. The ratings and qualitative information from the content panel members indicated a substantial need for the Swedish APERS in primary school, resulting in the culturally adapted APERS-Primary-Sweden (SE). The instrument demonstrated a high level of cross-cultural content validity for assessing the quality of the learning environment for students with autism in Swedish primary school settings. The pilot testing of the instrument resulted in further cultural adaptations. In conclusion, APERS-Primary-SE is a comprehensive scale that can be used to assess the quality of primary school learning environments for children with autism in Sweden. Further research is needed to evaluate the adapted instrument’s effectiveness in improving the learning environment in Swedish primary school classrooms.
Multiferroic properties of electrospun CoFe2O4–(Ba0.95Ca0.05)(Ti0.89Sn0.11)O3 nanocomposites for magnetoelectric and magnetic field sensing applications
Authors: Hadouch Youness , Abdallah Nayad , Mezzane Daoud , Amjoud M’barek , Dolocan Voicu , Hoummada Khalid , Novak Nikola , Razumnaya Anna , Rozic Brigita , Fisinger Val , Ursic Hana , Laguta Valentin , Kutnjak Zdravko , El Marssi Mimoun 
Published: September 2024

AbstractMultiferroic CoFe2O4–Ba0.95Ca0.05Ti0.89Sn0.11O3 composite nanofibers (CFO–BCTSn NFs) were synthesized using a sol–gel electrospinning method. Scanning electron microscopy revealed the morphology of the composites, with fiber diameters ranging from 120 to 150 nm. Transmission electron microscopy confirmed the structure of the nanofibers, while X-ray diffraction, Raman spectroscopy, and high-resolution transmission electron microscopy verified the formation of the spinel structure of CFO and the perovskite structure of BCTSn, with no additional phases detected. The magnetic properties of the CFO–BCTSn NFs were demonstrated by magnetic hysteresis loops (M-H), and piezoresponse force microscopy confirmed their piezoelectricity. Magnetoelectric coupling was evidenced by comparing the M-H hysteresis loops of electrically poled and unpoled CFO–BCTSn NFs samples. These composite nanofibers have the potential to be utilized in innovative, lead-free magnetoelectric and magnetic field sensing technologies at the nanoscale.
A multi-lingual sign language recognition system using machine learning
Authors: Najib Fatma M. 
Published: September 2024

AbstractRecently, automatic sign language recognition field gets a great attention. Machine learning algorithms are mainly used to recognize hand gestures. Most of recent studies train their machine learning model using a specific sign language of a specific country such as the American Sign Language. In this paper, we propose a multi-lingual sign language system based machine learning that is called Multi-lingual Sign Languages Interpreter (MSLI) system. MSLI trains a machine learning model based on hand signs of multiple languages. It can detect the language of the input signs and their labels. In a case of input testing signs with the same language, the proposed system can provide two-steps recognition, where it only detects the language of the first sign, and then the rest signs are tested according to the recognized language. Also, MSLI can provide separate classification of signs per each language. Experiments were performed using 11 datasets with different languages. Separate and combined classification was performed on the input data. Experimental results show the accuracy of the proposed system. Training accuracy of the proposed system over most of the used separate different sign language datasets is approximately ranged from 90 to 100%. Also, most classification accuracy results of the test data of the separate datasets exceeded 90%. The combined classification of proposed MSLI archived training accuracy of 95.87% and testing accuracy of 92.33%.
A computer-vision based framework for virtual 3D garment reconstruction
Authors: Dang Ying , Ruan Wan Tao , Xi Long , Tang Wen 
Published: September 2024

AbstractExisting 3D garment reconstruction methods are difficult to implement for online fashion design and e-commerce or special applications. This paper proposes a novel computer-vision framework for 3D garment digital reconstruction, which aims to reconstruct high-quality and realistic virtual 3D garments with fabric mechanic properties for 3D virtual try-on. The new segmentation scheme is proposed to separate the 3D garment point clouds from background points, which is suitable for 3D human shapes and is adaptive for different 3D garment models in different scenes. The new Statistical Outlier Removal algorithm and the learning-based method PointCleanNet are combined to remove noise and outliers in 3D garment point clouds, which provides high-fidelity and high-quality 3D garment point clouds. The 3D garment meshes are then reconstructed from their corresponding point clouds with a modified rolling ball algorithm. Finally, the meshes are improved and converted into physics-based virtual try-on 3D garments with fabric mechanic properties added, which enables the assessment of different body shapes with varied sizes for the same reconstructed 3D garment. Comparison experiments demonstrate that our framework achieves high-quality and realistic 3D garment reconstruction and accurate 3D virtual try-on from 2D garment images. We also demonstrate the proposed framework on a large range of various garments to show this approach has a great potential for garment future technology, such as online garment shopping, garment design and manufacturing.
Ethnicity in neuro-oncology research: How are we doing and how can we do better?
Authors: Baig Mirza Asfand , Fayez Feras , Rashed Sami , Burn Layla , Evans Zachariah M. , Karagozlu Zekiye , Vastani Amisha , Lavrador Jose Pedro , Vergani Francesco , Gullan Richard , Bhangoo Ranjeev , Ashkan Keyoumars 
Published: September 2024

Abstract
Purpose
This study systematically reviews and meta-analyses the extent of ethnic minority representation in neuro-oncology Phase III and IV clinical trials, explores the effect of ethnicity on outcomes, and identifies predictors for the inclusion of ethnicity data in publications.

Methods
Adhering to PRISMA guidelines, we conducted a comprehensive literature search across multiple databases, on Phase III and IV trials in neuro-oncology that reported on adult and/or paediatric subjects. Through meta-analysis, we synthesized information on overall survival, event-free survival, and the incidence of adverse outcomes across ethnicities.

Results
From 448 identified articles, a fraction reported ethnicity data, with an even smaller number providing outcome data stratified by ethnicity. Most study participants were identified as White, underscoring a significant underrepresentation of minorities. Our meta-analysis did not reveal significant outcome differences by ethnicity, which may be attributed to the limited and inadequate reporting of data. Predictors for including ethnicity data were identified, including trials in North America(OR2.39, 95%CI 1.18–5.12, p < 0.02),trials of drugs or biologic agents(OR 5.28, 95%CI 1.43–3.42, p < 0.05),and trials funded by charities(OR 2.28, 95% CI 1.04–5.27, p < 0.05) or pharmaceutical companies(OR 3.98, 95% CI 1.60–10.0, p < 0.005).

Conclusion
The underrepresentation of minorities in neuro-oncology clinical trials and the inadequately characterized impact of ethnicity on treatment outcomes highlight a critical need for more inclusive recruitment strategies and improved reporting standards. Change is necessary to ensure trials reflect the diversity of the patient population, which is essential for developing tailored strategies and improving outcomes. Future research should prioritize understanding the role of ethnicity in neuro-oncology to facilitate personalized treatment approaches.
Determinants of long-term survival in patients with IDH-mutant gliomas
Authors: Katzendobler Sophie , Niedermeyer Sebastian , Blobner Jens , Trumm Christoph , Harter Patrick N. , von Baumgarten Louisa , Stoecklein Veit M. , Tonn Joerg-Christian , Weller Michael , Thon Niklas , Weller Jonathan 
Published: September 2024

Abstract
Background
Survival times of patients with IDH-mutant gliomas are variable and can extend to decades. Many studies provide progression-free rather than overall survival times and prognostic factors remain ill-defined. Here we explored characteristics of short- and long-term survivors within a cohort of patients with extended follow-up.

Methods
This single-center, case-control study included 86 patients diagnosed between 1998 and 2023 who either died within 6 years after diagnosis or survived at least 15 years. Patient characteristics and prognostic factors were stratified by short- (< 6 years) versus long-term (≥ 15 years) survival.

Results
Forty-seven patients (55%) diagnosed with astrocytoma and 39 patients (45%) with oligodendroglioma were included retrospectively. Median follow-up of the survivors was 16.6 years (range 15-28.9). Thirty-four deaths (40%) had been reported at database closure. Long-term survival was associated with CNS WHO grade 2 (p < 0.01), smaller tumor volumes (p = 0.01), lack of contrast enhancement (p < 0.01), wait-and-scan strategies (p < 0.01) and female sex (p = 0.04). In multivariate analyses for oligodendroglioma, larger T2 tumor volumes were associated with shorter survival (HR 1.02; 95% CI 1.01–1.05; p = 0.04). In patients with astrocytoma, lack of contrast enhancement (HR 0.38; 95% CI 0.15–0.94; p = 0.04) and wait-and-scan strategies (HR 5.75; 95% CI 1.66–26.61; p = 0.01) were associated with longer survival.

Conclusion
Large T2 tumor volume and contrast enhancement may be important risk factors for shorter survival, while age might be of lesser importance. Wait-and-scan strategies may yield excellent long-term survival in some patients with astrocytoma.
Incommensurability, the sequence argument, and the Pareto principle
Authors: Arrhenius Gustaf , Stefánsson H. Orri 
Published: September 2024

AbstractParfit (Theoria 82:110–127, 2016) responded to the Sequence Argument for the Repugnant Conclusion by introducing imprecise equality. However, Parfit’s notion of imprecise equality lacked structure. Hájek and Rabinowicz (2022) improved on Parfit’s proposal in this regard, by introducing a notion of degrees of incommensurability. Although Hájek and Rabinowicz’s proposal is a step forward, and may help solve many paradoxes, it can only avoid the Repugnant Conclusion at great cost. First, there is a sequential argument for the Repugnant Conclusion that uses weaker and intuitively more compelling assumptions than the Sequence Argument, and which Hájek and Rabinowicz’s proposal only undermines, in a principled way, by allowing for implausible weight to be put on the disvalue of inequality. Second, if Hájek and Rabinowicz do put such implausible weight on the disvalue of inequality, then they will have to accept that a population A is not worse than another same sized population B even though everyone in B is better off than anyone in A.