bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the multiple drivers of vegetation cover evolution in the Taihangshan-Yanshan region
Authors: Yan Feng , Guo Xinyu , Zhang Yuwen , Shan Jing , Miao Zihan , Li Chenyang , Huang Xuehan , Pang Jiao , Chen Yaheng 
Published: July 2024

AbstractThe Taihangshan-Yanshan region (TYR) is an important ecological barrier area for Beijing-Tianjin-Hebei, and the effectiveness of its ecological restoration and protection is of great significance to the ecological security pattern of North China. Based on the FVC data from 2000 to 2021, residual analysis, parametric optimal geodetector technique (OPGD) and multi-scale geographically weighted regression analysis (MGWR) were used to clarify the the multivariate driving mechanism of the evolution of FVC in the TYR. Results show that: (1) FVC changes in the TYR show a slowly fluctuating upward trend, with an average growth rate of 0.02/10a, and a spatial pattern of "high in the northwest and low in the southeast"; more than half of the FVC increased during the 22-year period. (2) The results of residual analysis showed that the effects of temperature and precipitation on FVC were very limited, and a considerable proportion (80.80% and 76.78%) of the improved and degraded areas were influenced by other factors. (3) The results of OPGD showed that the main influencing factors of the spatial differentiation of FVC included evapotranspiration, surface temperature, land use type, nighttime light intensity, soil type, and vegetation type (q > 0.2); The explanatory rates of the two-factor interactions were greater than those of the single factor, which showed either nonlinear enhancement or bifactorial enhancement, among which, the interaction of evapotranspiration with mean air and surface temperature has the strongest effect on the spatial and temporal evolution of FVC (q = 0.75). Surface temperature between 4.98 and 10.4 °C, evapotranspiration between 638 and 762 mm/a, and nighttime light between 1.96 and 7.78 lm/m2 favoured an increase in vegetation cover, and vegetation developed on lysimetric soils was more inclined to be of high cover. (4) The correlation between each variable and FVC showed different performance, GDP, elevation, slope and FVC showed significant positive correlation in most regions, while population size, urban population proportion, GDP proportion of primary and secondary industries, and nighttime light intensity all showed negative correlation with FVC to different degrees. The results can provide data for formulating regional environmental protection and restoration policies.
Research on reliability mapping of 5G low orbit constellation network slice based on deep reinforcement learning
Authors: Xiao Yunjie , Li Nan , Yu Jiangtao , Zhao Baozhu , Chen Dawei , Wei Zhengrong 
Published: July 2024

AbstractReliability mapping of 5G low orbit constellation network slice is an important means to ensure link network communication. The problem of state space explosion is a typical problem. The deep reinforcement learning method is introduced. Under the 5G low orbit constellation integrated network architecture based on software definition network (SDN) and network function virtualization (NFV), the resource requirements and resource constraints of the virtual network function (VNF) are comprehensively considered to build the 5G low orbit constellation network slice reliability mapping model, and the reliability mapping model parameters are trained and learned by using deep reinforcement learning, solve the problem of state space explosion in the reliability mapping process of 5G low orbit constellation network slices. In addition, node backup and link backup strategies based on importance are adopted to solve the problem that VNF/link reliability is difficult to meet in the reliability mapping process of 5G low orbit constellation network slice. The experimental results show that this method improves the network throughput, packet loss rate and intra slice traffic of 5G low orbit constellation, and can completely repair network faults within 0.3 s; For different number of 5G low orbit constellation network slicing requests, the reliability of this method remains above 98%; For SFC with different lengths, the average network delay of this method is less than 0.15 s.
Activation of cellular antioxidative stress and migration activities by purified components from immortalized stem cells from human exfoliated deciduous teeth
Authors: Shu Yujing , Otake Masato , Seta Yasuhiro , Hori Keigo , Kuramochi Akiko , Ohba Yoshio , Teramura Yuji 
Published: July 2024

AbstractAlthough stem cell-based regenerative medicine has been extensively studied, it remains difficult to reconstruct three dimensional tissues and organs in combination with vascular systems in vitro. One clinically successful therapy is transplantation of mesenchymal stem cells (MSC) into patients with graft versus host disease. However, transplanted cells are immediately damaged and destroyed because of innate immune reactions provoked by thrombogenic inflammation, and patients need to take immunosuppressive drugs for the immunological regulation of allogeneic cells. This reduces the benefits of stem cell transplantation. Therefore, alternative therapies are more realistic options for clinical use. In this study, we aimed to take advantage of the therapeutic efficacy of MSC and use multiple cytokines released from MSC, that is, stem cells from human exfoliated deciduous teeth (SHEDs). Here, we purified components from conditioned media of immortalized SHED (IM-SHED-CM) and evaluated the activities of intracellular dehydrogenase, cell migration, and antioxidative stress by studying the cells. The immortalization of SHED could make the stable supply of CM possible. We found that the fractionated component of 50–100 kD from IM-SHED-CM had higher efficacy than the original IM-SHED-CM in terms of intracellular dehydrogenase and cell migration in which intracellular signal transduction was activated via receptor tyrosine kinases, and the glutathione peroxidase and reductase system was highly active. Although antioxidative stress activities in the fractionated component of 50–100 kD had slightly lower than that of original IM-SHE-CM, the fraction still had the activity. Thus, the use of fractionated components of 50–100 kD from IM-SHED-CM could be an alternative choice for MSC transplantation because the purified components from CM could maintain the effect of cytokines from SHED.
Subfoveal choroidal thickness increases after excimer laser-assisted penetrating keratoplasty but not after excimer laser-assisted deep anterior lamellar keratoplasty
Authors: Aljundi Wissam , Daas Loay , Munteanu Cristian , Seitz Berthold , Abdin Alaa Din 
Published: July 2024

AbstractTo evaluate the impact of excimer laser-assisted deep anterior lamellar keratoplasty (Exc-DALK) and excimer laser-assisted penetrating keratoplasty (Exc-PKP) on subfoveal choroidal thickness (SFCT) in eyes with advanced keratoconus. A retrospective comparative clinical study, which compares the outcomes of 24 eyes treated with Exc-DALK (G1) against matched group of 43 eyes treated with Exc-PKP (G2) at both 2 months (T1) and 2 years (T2) postoperatively. Main outcomes included best-corrected visual acuity (BCVA), central macular thickness (CMT), and SFCT. Preoperatively, there were no significant differences between both groups regarding BCVA, CMT or SFCT (p > 0.05). There were no significant differences between both groups regarding BCVA at both follow-ups (p > 0.05). There were no significant differences between both groups regarding CMT at both follow-ups (p > 0.05). SFCT was higher in G2 than G1 at both follow-ups (p < 0.01). Compared to preoperative SFCT, there were no significant changes in SFCT in G1 at both follow-ups (p > 0.05). In G2, SFCT increased significantly at T1 (p < 0.01) and did not differ significantly at T2 (p = 0.17). SFCT increased significantly after Exc-PKP but not after Exc-DALK, which might indicate that Exc-DALK affects the choroid less and thus could represent a less traumatic approach to ocular tissue than Exc-PKP.
Automatic summarization model based on clustering algorithm
Authors: Dai Wenzhuo , He Qing 
Published: July 2024

AbstractExtractive document summary is usually seen as a sequence labeling task, which the summary is formulated by sentences from the original document. However, the selected sentences usually are high redundancy in semantic space, so that the composed summary are high semantic redundancy. To alleviate this problem, we propose a model to reduce the semantic redundancy of summary by introducing the cluster algorithm to select difference sentences in semantic space and we improve the base BERT to score sentences. We evaluate our model and perform significance testing using ROUGE on the CNN/DailyMail datasets compare with six baselines, which include two traditional methods and four state-of-art deep learning model. The results validate the effectiveness of our approach, which leverages K-means algorithm to produce more accurate and less repeat sentences in semantic summaries.
DSnet: a new dual-branch network for hippocampus subfield segmentation
Authors: Zhu Hancan , Cheng Wangang , Hu Keli , He Guanghua 
Published: July 2024

AbstractThe hippocampus is a critical component of the brain and is associated with many neurological disorders. It can be further subdivided into several subfields, and accurate segmentation of these subfields is of great significance for diagnosis and research. However, the structures of hippocampal subfields are irregular and have complex boundaries, and their voxel values are close to surrounding brain tissues, making the segmentation task highly challenging. Currently, many automatic segmentation tools exist for hippocampal subfield segmentation, but they suffer from high time costs and low segmentation accuracy. In this paper, we propose a new dual-branch segmentation network structure (DSnet) based on deep learning for hippocampal subfield segmentation. While traditional convolutional neural network-based methods are effective in capturing hierarchical structures, they struggle to establish long-term dependencies. The DSnet integrates the Transformer architecture and a hybrid attention mechanism, enhancing the network’s global perceptual capabilities. Moreover, the dual-branch structure of DSnet leverages the segmentation results of the hippocampal region to facilitate the segmentation of its subfields. We validate the efficacy of our algorithm on the public Kulaga-Yoskovitz dataset. Experimental results indicate that our method is more effective in segmenting hippocampal subfields than conventional single-branch network structures. Compared to the classic 3D U-Net, our proposed DSnet improves the average Dice accuracy of hippocampal subfield segmentation by 0.57%.
Expression perceptive fields explain individual differences in the recognition of facial emotions
Authors: Murray Thomas , Binetti Nicola , Venkataramaiyer Raghav , Namboodiri Vinay , Cosker Darren , Viding Essi , Mareschal Isabelle 
Published: July 2024

AbstractHumans can use the facial expressions of another to infer their emotional state, although it remains unknown how this process occurs. Here we suppose the presence of perceptive fields within expression space, analogous to feature-tuned receptive-fields of early visual cortex. We developed genetic algorithms to explore a multidimensional space of possible expressions and identify those that individuals associated with different emotions. We next defined perceptive fields as probabilistic maps within expression space, and found that they could predict the emotions that individuals infer from expressions presented in a separate task. We found profound individual variability in their size, location, and specificity, and that individuals with more similar perceptive fields had similar interpretations of the emotion communicated by an expression, providing possible channels for social communication. Modelling perceptive fields therefore provides a predictive framework in which to understand how individuals infer emotions from facial expressions.
Unlocking therapeutic potential: exploring cross-talk among emerging nuclear receptors to combat metabolic dysfunction in steatotic liver disease
Authors: Antwi Milton Boaheng , Jennings Ariann , Lefere Sander , Clarisse Dorien , Geerts Anja , Devisscher Lindsey , De Bosscher Karolien 
Published: July 2024

AbstractNuclear receptors (NRs) regulate cellular processes and serve as key targets in treating metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (MASH). Their ability to interact and influence each other’s signaling pathways introduces a complex yet underexplored dimension in the pharmacotherapy of MASLD and MASH. This review delineates the emerging NRs in this field—estrogen-related receptor alpha (ERRα), glucocorticoid receptor (GR), estrogen receptor alpha (ERα), liver receptor homolog-1 (LRH-1), and vitamin D receptor (VDR)—and their interplay with established NRs, including peroxisome proliferator-activated receptors (PPARα, PPARβ/δ, PPARγ), farnesoid X receptor (FXR), liver X receptors (LXR), hepatocyte nuclear factor 4α (HNF4α), and thyroid hormone receptor beta (THRβ). We discuss their collective impact on hepatic lipid metabolism, inflammation, fibrosis, and glucose homeostasis. We explore recent findings on dual NR crosstalk, via direct and indirect mechanisms, and discuss the potential of targeting receptor pathways using selective agonists, inverse agonists, antagonists, or specific modulators to combat MASLD and MASH. Elucidating NR interactions opens up new avenues for targeted therapies, emphasizing the critical need for further research in the evolving field of hepatology.
The Compartmental Tongue
Authors: Wrench Alan A. 
Published: July 2024

Purpose:
Tongue anatomy and function is widely described as consisting of four extrinsic muscles to control position and four intrinsic muscles to control shape. This myoarchitecture cannot, however, explain independent tongue body and blade movement nor accurately model the subtlety of observed lingual shapes. This study presents the case for a finer neuromuscular structure and functional description.

Method:
Using the theoretical framework of the partitioning hypothesis, evidence for neuromuscular compartments of each of the lingual muscles was discerned by reviewing studies of lingual anatomy, hypoglossal nerve staining, hypoglossal motoneuron axon tracing, muscle fiber type distribution, and electromyography. Muscle fibers of the visible human female were manually traced to produce a three-dimensional atlas of muscular compartments. A kinematic study was undertaken to determine the degree of independent movement between different parts of the tongue. A simple biomechanical model was used to demonstrate how synergistic groups of compartments can control sectors of the tongue.

Results:
Results indicated as many as 10 compartments of genioglossus, two each of superior and inferior longitudinal, eight of styloglossus, three of hyoglossus, and six each of transversus and verticalis, while palatoglossus may not have a significant role in tongue function. Kinematic analysis indicated independent control of five sectors of the tongue body, and biomechanical modeling demonstrated how this control may be achieved.

Conclusion:
Evidence is presented for a lingual structure based on neuromuscular compartments, which work together to position and shape sectors of the tongue and independently control tongue body and blade.
Demonstration of Epstein-Barr Virus by In Situ Hybridization in
Papillary Thyroid Carcinomas Developing on Background of Hashimoto’s
Thyroiditis
Authors: Karaarslan Serap , Kasap Esin , İpek Fatma Nur , Akyıldız Mahir 
Published: July 2024

Abstract
Aim This study aimed to demonstrate the role of Epstein-Barr Virus (EBV)
in papillary thyroid carcinomas (PTC) developing on the background of
Hashimotoʼs thyroiditis (HT).
Methods The presence of EBV in tumoral tissue, lymphocytes, and
peritumoral normal thyroid tissue was investigated using the in situ
hybridization method in paraffin blocks. The subtypes of PTC, tumor diameter,
TNM stage, multifocality, invasion of thyroid capsule, perineural invasion, and
muscular tissue invasion were identified and compared according to EBV
involvement.
Results Eighty-one patients with HT diagnosis, with 93.8% (n=76) female
and 6.2% (n=5) male, were included in the study. Papillary microcarcinoma was
the pathological diagnosis in 24.2% (n=15) of the cases. EBV was identified in
58.06% (n=36) of the tumor cells nuclei, 58.06% (n=36) in the tumor cell
cytoplasm, 16.12% (n=10) in tumor infiltrative lymphocytes, and 53.2% (n=33) in
normal parenchymal follicle epithelial cells (NPFEC). In the T2 stage, the rate
of EBV nuclear positivity in patients was significantly higher (p=0.034). The
classic variant of papillary carcinoma was accompanied by a significantly higher
rate of EBV-negative NPFEC (67.6%, p=0.049). In multifocal tumors, EBV
positivity was found to be significantly higher in lymphocytes in the
surrounding tissues (58.3%, p=0.034).
Conclusion A significant increase in EBV positivity in the surrounding
tissue lymphocytes was observed in multifocal PTC developing on a background of
HT. This suggests a possible association between HT and EBV.
For the love of acronyms: An analysis of terminology and acronyms used in AAI research 2013–2023
Authors: Green Freya L.L. , Dahlman Mikaela L. , Lomness Arielle , Binfet John-Tyler 
Published: July 2024

Abstract

The involvement of animals to assist or facilitate activities, education, or therapy has become increasingly popular. As we recognize animals’ roles in ameliorating well-being and educational outcomes, researchers and programmers are developing a variety of animal-assisted programs. This diversification has seen the adoption of a plethora of terms and acronyms. Many researchers have pointed out this over-abundance of terms and their inconsistent use, arguing that this creates confusion within the field. The aims of this article were threefold: (1) To identify commonly used terms in animal-assisted intervention (AAI) research; (2) to document their use by frequency; and (3) discuss the benefits and obstacles of the abundance of terms and acronyms in the field. A search of peer-reviewed articles published in English from 2013 to 2023 was conducted across four databases: PsycInfo, Education Source, ERIC, and Scopus to collate articles related to human-animal interactions (HAIs). Records were de-duplicated in Covidence and screened at title/abstract level by two independent reviewers for relevance to AAIs. The resulting articles (
N
= 1934) were subsequently coded to track terminology. A total of 1414 distinct terms were identified, the majority of which (77.8%,
n
= 1100) were used only once between 2013 and 2023. Only 48 terms (3.4%) were used in the literature more than 10 times. Analysis also provided insight into frequently used terms, the most prevalent of which were “animal-assisted therapy” (8.70%, used 376 times), “animal-assisted interventions” (7.45%, used 322 times), and “therapy dog” (5.06%, used 219 times). Trends across 10 years reveal that specific terms have increased (e.g., “animal-assisted intervention”) or decreased (e.g., “hippotherapy”) in popularity but that the average number of terms used per article remains stable. Despite calls from HAI researchers to reduce redundant terms and improve the accuracy and consistency in the language used, there remains a surplus of terms in the field. This holds implications for AAI researchers, programmers, and individuals gaining interest in AAIs.
Animal-assisted interventions in a farm setting: Integrating global perspectives, social work, and ecological approaches for overall welfare
Authors: Spett Dana , West Abigail , Fava Zoe , Lavoie Bonnie , Rodgers-Rivera Zoraida 
Published: July 2024

Abstract
The focus of the article is the integration of global perspectives, social work, and ecological approaches in animal-assisted interventions in a farm setting, presenting a model that addresses animal, human, and environmental welfare. The authors use a literature review and case scenario illustrating this model that suggests that welfare can be achieved through the simultaneous consideration of the following realms: Global initiatives of One Health and United Nations Sustainable Development Goals, the Five Domains of Animal Welfare, social work theory and practice, and regenerative agriculture. Future research should include the practice of this model in a fashion that allows collecting and studying the outcomes for animals, humans, and the environment involved.
Holographic vacuum energy regularization and corrected entropy of de Sitter space
Authors: Jalalzadeh S , Moradpour H , Tebyanian H 
Published: July 2024

Abstract
We propose that the spectrum of the surface area of the apparent horizon (AH) of de Sitter (dS) spacetime leads to corrected temperature and entropy of the dS spacetime, offering new insights into its thermodynamic properties. This is done by employing the spectrum of the AH radius, acquired from the Wheeler–DeWitt (WDW) equation, together with the Stefan–Boltzmann law, the time-energy uncertainty relation, and the unified first law of thermodynamics.
Implementing active learning in a teaching–learning sequence on rolling motion for mechanical engineers
Authors: Carli Marta 
Published: July 2024

Abstract
In this work, we describe a teaching–learning sequence (TLS) on rolling motion, designed and implemented within a Physics 1 course for Mechanical Engineers. The TLS was grounded in Physics Education Research findings and employed active learning strategies, particularly simulation-based exercises that included both conceptual questions and quantitative tasks. We detail and reflect on the development process of the TLS, focussing in particular on the alignment between the identified learning goals and the proposed instructional activities. We present data on students’ attainment of these learning goals, utilizing a post-instruction conceptual survey and an analysis of students’ performance in the final exam. Our research aims to contribute to the implementation of research-based, active learning sequences in large-enrollment contexts, specifically in those courses where both conceptual understanding and formal problem solving are valued.
Non-ultralocal classical r-matrix structure for 1+1 field analogue of elliptic Calogero–Moser model
Authors: Zotov Andrei 
Published: July 2024

Abstract
We consider 1+1 field generalization of the elliptic Calogero–Moser model. It is shown that the Lax connection satisfies the classical non-ultralocal r-matrix structure of Maillet type. Next, we consider 1+1 field analogue of the spin Calogero–Moser model and its multipole (or multispin) extension. Finally, we discuss the field analogue of the classical IRF-Vertex correspondence, which relates utralocal and non-ultralocal r-matrix structures.
Hitting probabilities for fast stochastic search*
Authors: Linn Samantha , Lawley Sean D 
Published: July 2024

AbstractMany physical phenomena are modeled as stochastic searchers looking for targets. In these models, the probability that a searcher finds a particular target, its so-called hitting probability, is often of considerable interest. In this work we determine hitting probabilities for stochastic search processes conditioned on being faster than a random short time. Such times have been used to model stochastic resetting or stochastic inactivation. These results apply to any search process, diffusive or otherwise, whose unconditional short-time behavior can be adequately approximated, which we characterize for broad classes of stochastic search. We illustrate these results in several examples and show that the conditional hitting probabilities depend predominantly on the relative geodesic lengths between the initial position of the searcher and the targets. Finally, we apply these results to a canonical evidence accumulation model for decision making.