bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bone marrow mesenchymal stem cells derived exosomal Lnc TUG1 promotes bone fracture recovery via miR-22-5p/Anxa8 axis
Authors: Li Wei , Li Lihong , Cui Rui , Chen Xiaoqing , Hu Haifeng , Qiu Yuyu 
Published: March 2023

AbstractBone fracture healing is a complex physiologic process that involves changes in the expression of several thousand genes. Long noncoding RNAs (lncRNAs) may have critical biological roles in this process. The objectives of the present study were to determine whether BMSC-derived exosomal lncTUG1 can enhance osteogenic differentiation and thereby promoting bone fracture recovery and to investigate its potential mechanisms of action. Bone marrow mesenchymal stromal cells were isolated from mice and cultured for the following experiments. After adipogenic and osteogenic differentiation induction, Oil Red O, alizarin red S, and alkaline phosphatase staining solutions were applied to confirm the formation of lipid droplets and calcium nodules. Western blotting analyses, real-time reverse transcription PCR assays, luciferase reporter were performed to confirm relative RNA and protein expressions and luciferase activities of transfected cells. RNA pull-down and RNA immunoprecipitation assays were also carried to verify the interaction between lncTUG1 and miR-22-5p. Additionally, a mouse model of closed femoral fractures was generated to evaluate the in vivo effect of increased lncTUG1 on fracture healing. BMSC-derived exosomal lncTUG1 enhanced the activity of osteoblasts. Overexpression of miR-22-5p reversed the osteopromoting effect of increased lncTUG1. The knockdown of Anxa8 reversed the osteogenic effect of miR-22-5p inhibitors, indicating an interaction between Anxa8 and miR-22-5p. Upregulation of lncTUG1 could promote the fracture recovery in vivo. In conclusion, the present study highlights the functional importance of BMSC-derived exosomal lncTUG1 in the process of bone fracture recovery.
Parents’ Reported Satisfaction of Their Children’s Assessment and Diagnoses of ASD: A Cross-Country Systematic Literature Review
Authors: Small Roxanne , Belluigi Dina Zoe 
Published: March 2023

AbstractThis paper represents a systematic review of peer-reviewed articles which included reports of parental dis/satisfaction about their child’s autism spectrum disorder (ASD) assessment and diagnoses. Five themes emerged which are visualised in evidence maps: country comparisons of parental dis/satisfaction; factors which enhanced satisfaction; barriers which prohibited satisfaction; differences in national diagnostic methodology; and the chronology of diagnoses across countries. Evidence gaps indicate the lack of unified approaches to the diagnostic process; underrepresentation of such research showing a geographical spread; a lack of unified approaches to the diagnostic process; and where a significantly higher reporting of dissatisfied outcomes was documented. Results indicate that higher parental dissatisfaction is linked to those whose children had undergone the ASD diagnostic process, and those experiencing negative cultural stigmas prior to, or throughout, their child’s ASD diagnosis.
How ploughing and frictional melting regulate ice-skating friction
Authors: Du Feng , Ke Peng , Hong Ping 
Published: March 2023

AbstractThe slipperiness of ice is well known while, for ice skating, its mechanism still needs further investigation, where the complex interactions including the thermal conduction of the skate—meltwater—ice system, the ploughing and the frictional melting of ice to the friction force are still unclear. This study presents a theoretical framework and a simplified analytical solution to unveil the friction mechanism when a curved skate sliding on ice. The theory is validated by experiments and the effects of these various factors, including the sliding velocity, the ice temperature, the supporting weight, and the geometry of the skate blade to the friction are revealed in detail. This study finds that the contribution of friction force from the ploughing deformation through skate indentation and that from the fluid friction through the shear motion of the meltwater layer is comparable with each other, which thus clarifies how the ploughing deformation of the ice substrate together with its frictional melting regulates the friction during skating.
A modified model of Lundberg-Palmgren rolling contact fatigue formula considering the effects of surface treatments
Authors: Zhang Boyu , Liu Huaiju , Wei Peitang , Guagliano Mario , Hou Shengwen 
Published: March 2023

AbstractThe Lundberg-Palmgren (L-P) fatigue life formula, as a statistical fatigue theory, has been widely used in the industry. However, its direct applicability is limited to the components treated by surface strengthening technologies. Rolling contact fatigue tests and surface integrity measurements of American Iron and Steel Institute (AISI) 9310 rollers with several surface treatments were performed to address this issue. Based on these results, a modified L-P fatigue model was proposed, enabling the consideration of surface modification including surface roughness, residual stress, and hardening introduced by different surface treatments. Compared with the original L-P fatigue formula, its results are more accurate for surface strengthened specimens. Furthermore, this method can assess the contact fatigue life of gears treated by surface strengthening techniques.
Exploring the Social Determinants of Mental Health by Race and Ethnicity in Army Wives
Authors: Dodge Jessica , Sullivan Kathrine , Miech Edward , Clomax Adriane , Riviere Lyndon , Castro Carl 
Published: March 2023

Abstract
Objective
To explore the social determinants of mental health (SDoMH) by race/ethnicity in a sample with equal access to healthcare. Using an adaptation of the World Health Organization’s SDoMH Framework, this secondary analysis examines the socio-economic factors that make up the SDoMH by race/ethnicity.

Method
This paper employed configurational comparative methods (CCMs) to analyze various racial/ethnic subsets from quantitative survey data from (N = 327) active-duty Army wives. Data was collected in 2012 by Walter Reed Army Institute of Research.

Results
Initial exploratory analysis revealed the highest-scoring factors for each racial/ethnic subgroup: non-Hispanic Black: employment and a history of adverse childhood events (ACEs); Hispanic: living off post and a recent childbirth; junior enlisted non-Hispanic White: high work-family conflict and ACEs; non-Hispanic other race: high work-family conflict and not having a military history. Final analysis showed four models consistently explained clinically significant depression symptoms and four models consistently explained the absence of clinical depression symptoms, providing a solution for each racial/ethnic minority group (non-Hispanic Black, Hispanic, junior enlisted non-Hispanic White, and non-Hispanic other).

Discussion
These findings highlight that Army wives are not a monolithic group, despite their collective exposure to military-specific stressors. These findings also highlight the potential for applying configurational approaches to gain new insights into mental health outcomes for social science and clinical researchers.
Putative circulating adipose tissue-derived stem cells, obesity, and metabolic syndrome features
Authors: Bonora B. M. , Cappellari R. , Albiero M. , Prevedello L. , Foletto M. , Vettor R. , Avogaro A. , Fadini G. P. 
Published: March 2023

Abstract
Purpose
In mice, adipose tissue-derived stem cells (ASCs) reach the systemic circulation and establish ectopic adipose depots fostering insulin resistance, but whether this occurs in humans is unknown. We examined circulating ASCs in individuals with various combination of metabolic syndrome traits.

Methods

We enrolled patients attending a routine metabolic evaluation or scheduled for bariatric surgery. We quantified ASCs as CD34+CD45−CD31−(CD36+) cells in the stromal vascular fraction of subcutaneous and visceral adipose tissue samples and examined the presence and frequency of putative ASCs in peripheral blood.

Results

We included 111 patients (mean age 59 years, 55% males), 40 of whom were scheduled for bariatric surgery. The population of CD34+CD45−CD31− ASCs was significantly more frequent in visceral than subcutaneous adipose depots (10.4 vs 4.1% of the stromal vascular fraction; p < 0.001), but not correlated with BMI or metabolic syndrome traits. The same phenotype of ASCs was detectable in peripheral blood of 58.6% of patients. Those with detectable circulating ASCs had significantly higher BMI (37.8 vs 33.3 kg/m2; p = 0.003) and waist (111.2 vs 105.4 cm; p = 0.001), but no difference in other metabolic syndrome traits (p = 0.84). After bariatric surgery, patients with detectable circulating ASCs had greater BMI reductions at 6 months (− 10.4 vs − 7.8 kg/m2; p = 0.014).

Conclusion

Presence of putative circulating ASCs, antigenically similar to those observed in the adipose tissue, is associated with greater adiposity and larger BMI reduction after surgery, but not with clinical signs of metabolic impairment. The role of circulating ASCs in adipose tissue biology and systemic metabolism deserves further investigation.
A random elite ensemble learning swarm optimizer for high-dimensional optimization
Authors: Yang Qiang , Song Gong-Wei , Gao Xu-Dong , Lu Zhen-Yu , Jeon Sang-Woon , Zhang Jun 
Published: March 2023

AbstractHigh-dimensional optimization problems are increasingly pervasive in real-world applications nowadays and become harder and harder to optimize due to increasingly interacting variables. To tackle such problems effectively, this paper designs a random elite ensemble learning swarm optimizer (REELSO) by taking inspiration from human observational learning theory. First, this optimizer partitions particles in the current swarm into two exclusive groups: the elite group consisting of the top best particles and the non-elite group containing the rest based on their fitness values. Next, it employs particles in the elite group to build random elite neighbors for each particle in the non-elite group to form a positive learning environment for the non-elite particle to observe. Subsequently, the non-elite particle is updated by cognitively learning from the best elite among the neighbors and collectively learning from all elites in the environment. For one thing, each non-elite particle is directed by superior ones, and thus the convergence of the swarm could be guaranteed. For another, the elite learning environment is randomly formed for each non-elite particle, and hence high swarm diversity could be maintained. Finally, this paper further devises a dynamic partition strategy to divide the swarm into the two groups dynamically during the evolution, so that the swarm gradually changes from exploring the immense solution space to exploiting the found optimal areas without serious diversity loss. With the above mechanisms, the devised REELSO is expected to explore the search space and exploit the found optimal areas properly. Abundant experiments on two popularly used high-dimensional benchmark sets prove that the devised optimizer performs competitively with or even significantly outperforms several state-of-the-art approaches designed for high-dimensional optimization.
Quantification study of mental load state based on AHP–TOPSIS integration extended with cloud model: methodological and experimental research
Authors: Zheng Xin , Hao Tengteng , Wang Huiyu , Xu Kaili 
Published: March 2023

AbstractMental load affects the work efficiency and mental health of operators, and it has a vital effect on the efficiency and reliability of human–machine systems. In this study, the evaluation index system of operators’ mental load was used to quantitatively evaluate the mental load state of workers. The system was established by selecting indices from the operators’ physiological parameters, subjective feelings, and time perception. We propose an extended cloud evaluation model of mental load states that combines cloud model (CM) theory with analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) and provides mental load levels. An energetic material initiation experiment was conducted to evaluate the mental load state of the operators using the proposed method, and the results of a fuzzy comprehensive evaluation and subjective questionnaire were used to verify the performance of the method. The results show that the extended CM evaluation method scientifically and reliably quantified the mental load state. Applying the AHP-TOPSIS integration extended with the CM theory evaluation method in mental load state evaluation provides a new scientific method for studying the quantification of the mental load state and occupational health of workers in hazardous environments. The results of this study are a reference for assessing the mental state of personnel and analyzing occupational suitability for dangerous posts.
Land Surface Temperature Relationship with the Land Use/Land Cover Indices Leading to Thermal Field Variation in the Turkish Republic of Northern Cyprus
Authors: García David Hidalgo , Riza Müge , Díaz Julián Arco 
Published: March 2023

AbstractThe increase in the Land Surface Temperature (LST) caused by global warming and extreme weather events is significantly increasing Urban Hot Spots (UHS) while impacting the environmental quality within urban areas. In this research, with the help of Landsat 5, 7, and 8 satellite images, the evolution of Land Use/Cover (LULC), LST, and Surface Urban Heat Island (SUHI) in the Turkish Republic of Northern Cyprus (TRNC) between the years 1985 and 2020 is examined. The main aim is to evaluate how these variables, together with the Normalized Difference Built-up Index (NDBI), Urban Index (UI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Built Index, and Proportion Vegetation (PV) have influenced the variability of the UHS and the level of thermal comfort according to the Thermal Field Variance Index (UTFVI). The results report significant average rises of the variables: LST (6.62 °C), SUHI (0.97 °C), UHS (8.61%) of the UI and NDBI indices and class 6 of UTFVI (88.53%) that are related to the variability of the LULC corroborated by statistical analysis. Our results provide valuable information on the future development of urban areas in Northern Cyprus to make them more resilient and sustainable to rising temperatures.
Carbon-Based Electrodes for Advanced Zinc-Air Batteries: Oxygen-Catalytic Site Regulation and Nanostructure Design
Authors: Shao Wenjie , Yan Rui , Zhou Mi , Ma Lang , Roth Christina , Ma Tian , Cao Sujiao , Cheng Chong , Yin Bo , Li Shuang 
Published: March 2023

AbstractZn-air batteries are highly attractive for direct chemical-to-electrical energy conversion and for solving the energy crisis and environmental problems. Designing efficient oxygen electrodes has been considered one of the most critical steps in the development of advanced Zn-air batteries because of the sluggish kinetics of the oxygen reduction reaction and the oxygen evolution reaction. In recent years, nanostructured carbon-based electrodes with large surface areas, efficient oxygen-catalytic centers, and hierarchically porous matrices have provided significant opportunities to optimize the performance of the oxygen electrodes in both primary and rechargeable Zn-air batteries. In this review, we provide a comprehensive summary of the reported nanostructured carbon-based electrodes for advanced Zn-air batteries in terms of tailoring the oxygen-catalytic sites and designing carbon supports. The versatile synthetic strategies, characterization methods, and in-depth understanding of the relationships between the oxygen-catalytic sites/nanostructures and the oxygen electrode performance are systematically summarized. Furthermore, we also briefly outline recent progress in engineering flexible and high-power Zn-air batteries. Ultimately, a thorough discussion of current primary challenges and future perspectives on the rational design of nanostructured carbon-based oxygen electrodes is given, thus providing inspiration for the future prosperity of fast-kinetic and efficient Zn-air batteries in a broad range of energy fields.
Graphical Abstract
Understanding Digital Inequality: A Theoretical Kaleidoscope
Authors: Kuhn Caroline , Khoo Su-Ming , Czerniewicz Laura , Lilley Warren , Bute Swati , Crean Aisling , Abegglen Sandra , Burns Tom , Sinfield Sandra , Jandrić Petar , Knox Jeremy , MacKenzie Alison 
Published: March 2023

AbstractThe pandemic affected more than 1.5 billion students and youth, and the most vulnerable learners were hit hardest, making digital inequality in educational settings impossible to overlook. Given this reality, we, all educators, came together to find ways to understand and address some of these inequalities. As a product of this collaboration, we propose a methodological toolkit: a theoretical kaleidoscope to examine and critique the constitutive elements and dimensions of digital inequalities. We argue that such a tool is helpful when a critical attitude to examine ‘the ideology of digitalism’, its concomitant inequalities, and the huge losses it entails for human flourishing seems urgent. In the paper, we describe different theoretical approaches that can be used for the kaleidoscope. We give relevant examples of each theory. We argue that the postdigital does not mean that the digital is over, rather that it has mutated into new power structures that are less evident but no less insidious as they continue to govern socio-technical infrastructures, geopolitics, and markets. In this sense, it is vital to find tools that allow us to shed light on such invisible and pervasive power structures and the consequences in the daily lives of so many.
Using Design-Based Research for a Technological Intervention to Promote Parental Involvement in Kindergarten
Authors: Laranjeiro Dionísia , Antunes Maria João , Santos Paula 
Published: March 2023

AbstractParental involvement in preschool education is widely recognized as an important factor in skills development, school outcomes and lifelong success, and can be promoted through digital technologies, which offer new forms of communication and collaboration between parents and educators, and new learning opportunities for children. This research aimed to develop and test a digital platform with communication and content sharing functionalities between parents and educators, and to assess the impact of using the platform in three participating institutions. The research question guiding the efforts was: what features and contents should a multimedia platform have to promote parental involvement in the learning of children who attend kindergarten? The research was developed according to a design-based research methodology, and the parents and educators were involved in all phases of the process: preliminary study, development and evaluation. The results showed that the sharing of activities carried out with children in kindergarten and a private messaging service were the most valued functionalities. Regarding local impact, different results were obtained in each kindergarten, related to the roles assumed by the users within the platform, and previous practices of using technologies for parental involvement.
Coat protein of rice stripe virus enhances autophagy activity through interaction with cytosolic glyceraldehyde-3-phosphate dehydrogenases, a negative regulator of plant autophagy
Authors: Zhao Wanying , Wang Li , Li Lipeng , Zhou Tong , Yan Fei , Zhang Heng , Zhu Ying , Andika Ida Bagus , Sun Liying 
Published: March 2023

AbstractViral infection commonly induces autophagy, leading to antiviral responses or conversely, promoting viral infection or replication. In this study, using the experimental plant Nicotiana benthamiana, we demonstrated that the rice stripe virus (RSV) coat protein (CP) enhanced autophagic activity through interaction with cytosolic glyceraldehyde-3-phosphate dehydrogenase 2 (GAPC2), a negative regulator of plant autophagy that binds to an autophagy key factor, autophagy-related protein 3 (ATG3). Competitive pull-down and co-immunoprecipitation (Co-IP)assays showed that RSV CP activated autophagy by disrupting the interaction between GAPC2 and ATG3. An RSV CP mutant that was unable to bind GAPC2 failed to disrupt the interaction between GAPC2 and ATG3 and therefore lost its ability to induce autophagy. RSV CP enhanced the autophagic degradation of a viral movement protein (MP) encoded by a heterologous virus, citrus leaf blotch virus (CLBV). However, the autophagic degradation of RSV-encoded MP and RNA-silencing suppressor (NS3) proteins was inhibited in the presence of CP, suggesting that RSV CP can protect MP and NS3 against autophagic degradation. Moreover, in the presence of MP, RSV CP could induce the autophagic degradation of a remorin protein (NbREM1), which negatively regulates RSV infection through the inhibition of viral cell-to-cell movement. Overall, our results suggest that RSV CP induces a selective autophagy to suppress the antiviral factors while protecting RSV-encoded viral proteins against autophagic degradation through an as-yet-unknown mechanism. This study showed that RSV CP plays dual roles in the autophagy-related interaction between plants and viruses.
An Efficient GAN-Based Multi-classification Approach for Financial Time Series Volatility Trend Prediction
Authors: Liu Lei , Pei Zheng , Chen Peng , Luo Hang , Gao Zhisheng , Feng Kang , Gan Zhihao 
Published: March 2023

AbstractDeep learning has achieved tremendous success in various applications owing to its robust feature representations of complex high-dimensional nonlinear data. Financial time-series prediction is no exception. Hence, the volatility trend prediction in financial time series (FTS) has been an active topic for several decades. Inspired by generative adversarial networks (GAN), which have been studied extensively in image processing and have achieved excellent results, we present the ordinal regression GAN for financial volatility trends (ORGAN-FVT) method for the end-to-end multi-classification task of FTS. An improved generative model based on convolutional long short-term memory (ConvLSTM) and multilayer perceptron (MLP) is proposed to capture temporal features effectively and mine the data distribution of volatility trends (short, neutral, and long) from given FTS data. Meanwhile, ordinal regression is leveraged for the discriminator to improve the multi-classification performance, making the model more practical. Finally, we empirically compare ORGAN-FVT with several state-of-the-art approaches on three real-world stock datasets: MICROSOFT(MSFT), Tesla(TSLA), and The People’s Insurance Company of China(PAICC). ORGAN-FVT demonstrated significantly better AUC and F1 scores, at most 20.81% higher than its competitors.