bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dendrometers challenge the ‘moon wood concept’ by elucidating the absence of lunar cycles in tree stem radius oscillation
Authors: Tumajer Jan , Braun Sabine , Burger Andreas , Scharnweber Tobias , Smiljanic Marko , Walthert Lorenz , Zweifel Roman , Wilmking Martin 
Published: November 2023

AbstractWood is a sustainable natural resource and an important global commodity. According to the ‘moon wood theory’, the properties of wood, including its growth and water content, are believed to oscillate with the lunar cycle. Despite contradicting our current understanding of plant functioning, this theory is commonly exploited for marketing wooden products. To examine the moon wood theory, we applied a wavelet power transformation to series of 2,000,000 hourly stem radius records from dendrometers. We separated the influence of 74 consecutive lunar cycles and meteorological conditions on the stem variation of 62 trees and six species. We show that the dynamics of stem radius consist of overlapping oscillations with periods of 1 day, 6 months, and 1 year. These oscillations in stem dimensions were tightly coupled to oscillations in the series of air temperature and vapour pressure deficit. By contrast, we revealed no imprint of the lunar cycle on the stem radius variation of any species. We call for scepticism towards the moon wood theory, at least as far as the stem water content and radial growth are concerned. We foresee that similar studies employing robust scientific approaches will be increasingly needed in the future to cope with misleading concepts.
A novel directional-oriented method for predicting shear wave velocity through empirical rock physics relationship using geostatistics analysis
Authors: Makarian Esmael , Mirhashemi Maryam , Elyasi Ayub , Mansourian Danial , Falahat Reza , Radwan Ahmed E. , El-Aal Ahmed , Fan Cunhui , Li Hu 
Published: November 2023

AbstractThis study attempts to design a novel direction–oriented approach for estimating shear wave velocity (VS) through geostatistical methods (GM) using density employing geophysical log data. The research area involves three hydrocarbon wells drilled in carbonate reservoirs that are comprised of oil and water. Firstly, VSwas estimated using the four selected empirical rock physics relationships (ERR) in well A (target well), and then all results were evaluated by ten statistical benchmarks. All results show that the best ERR is Greenberg and Castagna, with R2 = 0.8104 and Correlation = 0.90, while Gardner's equation obtained the poorest results with R2 = 0.6766 and correlation = 0.82. Next, Gardner's method was improved through GM by employing Ordinary Kriging (OKr) in two directions in well A, and then Cross-Validation and Jack-knife methods (JKm and CVm, respectively) were used to assess OKr's performance and efficiency. Initially, CVm and JKm were employed to estimate Vs using the available density and its relationship with shear wave velocity, where the performance of CVm was better with R2 = 0.8865 and correlation = 0.94. In this step, some points from the original VSwere used to train the data. Finally, Vs was estimated through JKm and using the relationship between the shear wave velocity of two wells near the target well, including wells B and C; however, in this step, the original shear wave velocity of the target well was completely ignored. Reading the results, JKm could show excellent performance with R2 = 0.8503 and Corr = 0.922. In contrast to previous studies that used only Correlation and R-squared (R2), this study further provides accurate results by employing a wide range of statistical benchmarks to investigate all results. In contrast to traditional empirical rock physics relationships, the developed direction-oriented technique demonstrated improved predicted accuracy and robustness in the investigated carbonate field. This work demonstrates that GM can effectively estimate Vs and has a significant potential to enhance VSestimation using density.
Image denoising and segmentation model construction based on IWOA-PCNN
Authors: Zhang Xiaojun 
Published: November 2023

AbstractThe research suggests a method to improve the present pulse coupled neural network (PCNN), which has a complex structure and unsatisfactory performance in image denoising and image segmentation. Then, a multi strategy collaborative improvement whale optimization algorithm (WOA) is proposed, and an improved whale optimization algorithm (IWOA) is constructed. IWOA is used to find the optimal parameter values of PCNN to optimize PCNN. By combining the aforementioned components, the IWOA-PCNN model had the best image denoising performance, and the produced images were crisper and preserve more information. IWOA-PCNN processed pictures have an average PSNR of 35.87 and an average MSE of 0.24. The average processing time for photos with noise is typically 24.80 s, which is 7.30 s and 7.76 s faster than the WTGAN and IGA-NLM models, respectively. Additionally, the average NU value measures 0.947, and the average D value exceeds 1000. The aforementioned findings demonstrate that the suggested method can successfully enhance the PCNN, improving its capability for image denoising and image segmentation. This can, in part, encourage the use and advancement of the PCNN.
Synthesis, molecular docking, and in vivo antidiabetic evaluation of new benzylidene-2,4-thiazolidinediones as partial PPAR-γ agonists
Authors: Najmi Asim , Alam Md Shamsher , Thangavel Neelaveni , Taha Manal M. E. , Meraya Abdulkarim M. , Albratty Mohammed , Alhazmi Hassan A. , Ahsan Waquar , Haque Anzarul , Azam Faizul 
Published: November 2023

AbstractPeroxisome proliferator-activated receptor-γ (PPAR-γ) partial agonists or antagonists, also termed as selective PPAR-γ modulators, are more beneficial than full agonists because they can avoid the adverse effects associated with PPAR-γ full agonists, such as weight gain and congestive heart disorders, while retaining the antidiabetic efficiency. In this study, we designed and synthesized new benzylidene-thiazolidine-2,4-diones while keeping the acidic thiazolidinedione (TZD) ring at the center, which is in contrast with the typical pharmacophore of PPAR-γ agonists. Five compounds (5a–e) were designed and synthesized in moderate to good yields and were characterized using spectral techniques. The in vivo antidiabetic efficacy of the synthesized compounds was assessed on streptozotocin-induced diabetic mice using standard protocols, and their effect on weight gain was also studied. Molecular docking and molecular dynamics (MD) simulation studies were performed to investigate the binding interactions of the title compounds with the PPAR-γ receptor and to establish their binding mechanism. Antidiabetic activity results revealed that compounds 5d and 5e possess promising antidiabetic activity comparable with the standard drug rosiglitazone. No compound showed considerable effect on the body weight of animals after 21 days of administration, and the findings showed statistical difference (p < 0.05 to p < 0.0001) among the diabetic control and standard drug rosiglitazone groups. In molecular docking study, compounds 5c and 5d exhibited higher binding energies (− 10.1 and − 10.0 kcal/mol, respectively) than the native ligand, non-thiazolidinedione PPAR-γ partial agonist (nTZDpa) (− 9.8 kcal/mol). MD simulation further authenticated the stability of compound 5c-PPAR-γ complex over the 150 ns duration. The RMSD, RMSF, rGyr, SASA, and binding interactions of compound 5c-PPAR-γ complex were comparable to those of native ligand nTZDpa-PPAR-γ complex, suggesting that the title compounds have the potential to be developed as partial PPAR-γ agonists.
Plasticity-led evolution as an intrinsic property of developmental gene regulatory networks
Authors: Ng Eden Tian Hwa , Kinjo Akira R. 
Published: November 2023

AbstractThe modern evolutionary synthesis seemingly fails to explain how a population can survive a large environmental change: the pre-existence of heritable variants adapted to the novel environment is too opportunistic, whereas the search for new adaptive mutations after the environmental change is so slow that the population may go extinct. Plasticity-led evolution, the initial environmental induction of a novel adaptive phenotype followed by genetic accommodation, has been proposed to solve this problem. However, the mechanism enabling plasticity-led evolution remains unclear. Here, we present computational models that exhibit behaviors compatible with plasticity-led evolution by extending the Wagner model of gene regulatory networks. The models show adaptive plastic response and the uncovering of cryptic mutations under large environmental changes, followed by genetic accommodation. Moreover, these behaviors are consistently observed over distinct novel environments. We further show that environmental cues, developmental processes, and hierarchical regulation cooperatively amplify the above behaviors and accelerate evolution. These observations suggest plasticity-led evolution is a universal property of complex developmental systems independent of particular mutations.
Synergistic effect of perovskites and nitrogen-doped carbon hybrid materials for improving oxygen reduction reaction
Authors: Rohib R. , Rehman Saeed Ur , Lee Eunjik , Kim Changki , Lee Hyunjoon , Lee Seung-Bok , Park Gu-Gon 
Published: November 2023

AbstractA fundamental understanding of the electrochemical behavior of hybrid perovskite and nitrogen-doped (N-doped) carbon is essential for the development of perovskite-based electrocatalysts in various sustainable energy device applications. In particular, the selection and modification of suitable carbon support are important for enhancing the oxygen reduction reaction (ORR) of non-platinum group metal electrocatalysts in fuel cells. Herein, we address hybrid materials composed of three representative N-doped carbon supports (BP-2000, Vulcan XC-72 and P-CNF) with valid surface areas and different series of single, double and triple perovskites: Ba0.5Sr0.5Co0.8Fe0.2O3−δ, (Pr0.5Ba0.5)CoO3−δ, and Nd1.5Ba1.5CoFeMnO9−δ (NBCFM), respectively. The combination of NBCFM and N-doped BP-2000 produces a half-wave potential of 0.74 V and a current density of 5.42 mA cm−2 at 0.5 V versus reversible hydrogen electrode, comparable to those of the commercial Pt/C electrocatalyst (0.76 V, 5.21 mA cm−2). Based on physicochemical and electrochemical analyses, we have confirmed a significant improvement in the catalytic performance of low-conductivity perovskite catalyst in the ORR when nitrogen-doped carbon with enhanced electrical conductivity is introduced. Furthermore, it has been observed that nitrogen dopants play active sites, contributing to additional performance enhancement when hybridized with perovskite.
A comprehensive assessment of oral health, swallowing difficulty, and nutritional status in older nursing home residents
Authors: Chou Kuei-Ru , Huang Mao-Suan , Chiu Wan-Chun , Chen Yi-Hsiu , Chen Yu-Yoh , Xiao Qian , Yang Suh-Ching 
Published: November 2023

AbstractDeclines in oral consumption and swallowing function are common reasons which may elevate the risk of malnutrition in the older adults. This study aimed to provide valuable information and contribute to the existing body of knowledge in this field as well as highlight the importance of a comprehensive assessment of oral health, swallowing function, and nutritional status in long-term care residents. This was a cross-sectional study. Thirty-nine participants were recruited from a nursing home. The comprehensive assessment was evaluated in participants, including oral health (Oral Health Assessment Tool (OHAT)), swallowing function (Functional Oral Intake Scale (FOIS) and Eating Assessment Tool (EAT)-10), and nutritional status (Mini Nutritional Assessment-Short Form (MNA-SF). The average age of participants was 80.4 ± 11.7 years, and 46% of these older adults were found to be at the risk of malnutrition. There was a negative correlation between the OHAT and MNA-SF scores. In addition, subjects with poor oral health (OHAT score = 5~8), oral consumption of a modified diet (FOIS score = 4~6), and reduced swallowing function (EAT-10 score ≥ 3) were more likely to be at risk of malnutrition. A comprehensive evaluation of oral health and swallowing function was closely connected with the nutritional status of older nursing home dwellers.
Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection
Authors: Leon Raquel , Fabelo Himar , Ortega Samuel , Cruz-Guerrero Ines A. , Campos-Delgado Daniel Ulises , Szolna Adam , Piñeiro Juan F. , Espino Carlos , O’Shanahan Aruma J. , Hernandez Maria , Carrera David , Bisshopp Sara , Sosa Coralia , Balea-Fernandez Francisco J. , Morera Jesus , Clavo Bernardino , Callico Gustavo M. 
Published: November 2023

AbstractBrain surgery is one of the most common and effective treatments for brain tumour. However, neurosurgeons face the challenge of determining the boundaries of the tumour to achieve maximum resection, while avoiding damage to normal tissue that may cause neurological sequelae to patients. Hyperspectral (HS) imaging (HSI) has shown remarkable results as a diagnostic tool for tumour detection in different medical applications. In this work, we demonstrate, with a robust k-fold cross-validation approach, that HSI combined with the proposed processing framework is a promising intraoperative tool for in-vivo identification and delineation of brain tumours, including both primary (high-grade and low-grade) and secondary tumours. Analysis of the in-vivo brain database, consisting of 61 HS images from 34 different patients, achieve a highest median macro F1-Score result of 70.2 ± 7.9% on the test set using both spectral and spatial information. Here, we provide a benchmark based on machine learning for further developments in the field of in-vivo brain tumour detection and delineation using hyperspectral imaging to be used as a real-time decision support tool during neurosurgical workflows.
On the functional brain networks involved in tool-related action understanding
Authors: Federico Giovanni , Osiurak François , Ciccarelli Giuseppina , Ilardi Ciro Rosario , Cavaliere Carlo , Tramontano Liberatore , Alfano Vincenzo , Migliaccio Miriana , Di Cecca Angelica , Salvatore Marco , Brandimonte Maria Antonella 
Published: November 2023

AbstractTool-use skills represent a significant cognitive leap in human evolution, playing a crucial role in the emergence of complex technologies. Yet, the neural mechanisms underlying such capabilities are still debated. Here we explore with fMRI the functional brain networks involved in tool-related action understanding. Participants viewed images depicting action-consistent (e.g., nail-hammer) and action-inconsistent (e.g., scarf-hammer) object-tool pairs, under three conditions: semantic (recognizing the tools previously seen in the pairs), mechanical (assessing the usability of the pairs), and control (looking at the pairs without explicit tasks). During the observation of the pairs, task-based left-brain functional connectivity differed within conditions. Compared to the control, both the semantic and mechanical conditions exhibited co-activations in dorsal (precuneus) and ventro-dorsal (inferior frontal gyrus) regions. However, the semantic condition recruited medial and posterior temporal areas, whereas the mechanical condition engaged inferior parietal and posterior temporal regions. Also, when distinguishing action-consistent from action-inconsistent pairs, an extensive frontotemporal neural circuit was activated. These findings support recent accounts that view tool-related action understanding as the combined product of semantic and mechanical knowledge. Furthermore, they emphasize how the left inferior parietal and anterior temporal lobes might be considered as hubs for the cross-modal integration of physical and conceptual knowledge, respectively.
The formation of KV2.1 macro-clusters is required for sex-specific differences in L-type CaV1.2 clustering and function in arterial myocytes
Authors: Matsumoto Collin , O’Dwyer Samantha C. , Manning Declan , Hernandez-Hernandez Gonzalo , Rhana Paula , Fong Zhihui , Sato Daisuke , Clancy Colleen E. , Vierra Nicholas C. , Trimmer James S. , Fernando Santana L. 
Published: November 2023

AbstractIn arterial myocytes, the canonical function of voltage-gated CaV1.2 and KV2.1 channels is to induce myocyte contraction and relaxation through their responses to membrane depolarization, respectively. Paradoxically, KV2.1 also plays a sex-specific role by promoting the clustering and activity of CaV1.2 channels. However, the impact of KV2.1 protein organization on CaV1.2 function remains poorly understood. We discovered that KV2.1 forms micro-clusters, which can transform into large macro-clusters when a critical clustering site (S590) in the channel is phosphorylated in arterial myocytes. Notably, female myocytes exhibit greater phosphorylation of S590, and macro-cluster formation compared to males. Contrary to current models, the activity of KV2.1 channels seems unrelated to density or macro-clustering in arterial myocytes. Disrupting the KV2.1 clustering site (KV2.1S590A) eliminated KV2.1 macro-clustering and sex-specific differences in CaV1.2 cluster size and activity. We propose that the degree of KV2.1 clustering tunes CaV1.2 channel function in a sex-specific manner in arterial myocytes.
An atomically tailored chiral magnet with small skyrmions at room temperature
Authors: Liu Tao , Selcu Camelia M. , Wang Binbin , Bagués Núria , Wu Po-Kuan , Hartnett Timothy Q. , Cheng Shuyu , Pelekhov Denis , Bennett Roland A. , Corbett Joseph Perry , Repicky Jacob R. , McCullian Brendan , Chris Hammel P. , Gupta Jay A. , Randeria Mohit , Balachandran Prasanna V. , McComb David W. , Kawakami Roland K. 
Published: November 2023

AbstractCreating materials that do not exist in nature can lead to breakthroughs in science and technology. Magnetic skyrmions are topological excitations that have attracted great attention recently for their potential applications in low power, ultrahigh density memory. A major challenge has been to find materials that meet the dual requirement of small skyrmions stable at room temperature. Here we meet both these goals by developing epitaxial FeGe films with excess Fe using atomic layer molecular beam epitaxy (MBE) far from thermal equilibrium. Our atomic layer design permits the incorporation of 20% excess Fe while maintaining a non-centrosymmetric crystal structure supported by theoretical calculations and necessary for stabilizing skyrmions. We show that the Curie temperature is well above room temperature, and that the skyrmions have sizes down to 15 nm as imaged by Lorentz transmission electron microscopy (LTEM) and magnetic force microscopy (MFM). The presence of skyrmions coincides with a topological Hall effect-like resistivity. These atomically tailored materials hold promise for future ultrahigh density magnetic memory applications.
Association Between Social Determinants of Health and Communication Difficulties in Poststroke U.S. Hispanic and Non-Hispanic White Populations
Authors: Marte Manuel Jose , Addesso David , Kiran Swathi 
Published: November 2023

Purpose:
The relationship among ethnicity, social determinants of health (SDOH), and disparities in poststroke outcomes is complex, and the impact on communication difficulties is unclear. This study investigated the presence and nature of communication difficulties in poststroke non-Hispanic White (PsnHw) and Hispanic U.S. populations using population-level data.

Method:
We performed a cross-sectional analysis of 2,861 non-Hispanic White and 353 Hispanic poststroke respondents included in the 2014–2018 National Health Interview Survey. Respondents self-reported difficulties communicating in their usual language, in addition to providing information relating to demographics and lifestyle, health care access and utilization, health status, and SDOH. We used univariate statistics, generalized linear models, and an exploratory mediation analysis, to characterize the pattern of differences between these cohorts, examine associations between variables and communication difficulties, and determine the potential intermediate role of cumulative SDOH on the likelihood of reporting communication difficulties.

Results:
Findings indicated a more challenging life context for the poststroke Hispanic population due to SDOH disparities. Poverty and Internet use were associated with greater and lower odds of communication difficulties for PsnHw, respectively. The mediation analysis showed that ethnicity significantly affected communication difficulties, but only when mediated by SDOH. SDOH accounted for approximately two thirds of the total effect on reporting communication difficulties.

Conclusions:
This study underscores the need for uniform measures of SDOH in prospective research and for interventions aimed at mitigating health disparities through addressing disparities in SDOH. Future research should focus on evaluating the effectiveness of such strategies in diverse ethnic and socioeconomic poststroke populations.

Supplemental Material:

https://doi.org/10.23641/asha.24521419
Energy efficiency optimisation in massive multiple‐input, multiple‐output network for 5G applications using new quantum genetic algorithm
Authors: Sabaawi Abdulbasit M. A. , Almasaoodi Mohammed R. , El Gaily Sara , Imre Sándor 
Published: November 2023

AbstractDevising efficient optimisation methods has been a subject of great research attention since current evolving trends in communication networks, machine learning, and other cutting‐edge systems that need a fast and accurate optimised computational model. Classical computers became incapable of handling new optimisation problems posed by newly emerging trends. Quantum optimisation algorithms appear as alternative solutions. The existing bottleneck that restricts the use of the newly developed quantum strategies is the limited qubit size of the available quantum computers (the size of the most recent universal quantum computer is 433 qubits). A new quantum genetic algorithm (QGA) is proposed that handles the presented problem. A quantum extreme value searching algorithm and quantum blind computing framework are utilised to extend the search capabilities of the GA. The quantum genetic strategy is exploited to maximise energy efficiency at full spectral efficiency of massive multiple‐input, multiple‐output (M‐MIMO) technology as a toy example for pointing out the efficiency of the presented quantum strategy. The authors run extensive simulations and prove how the presented quantum method outperforms the existing classical genetic algorithm.