bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application and characterization of a novel PVDF-HFP/PVP polymer composite with MoO3 nanowires as a protective coating for wood
Authors: Žigon Jure , Centa Urška Gradišar , Remškar Maja , Humar Miha 
Published: March 2023

AbstractThe coatings on wood must sometimes give aesthetic and basic protection to wooden elements and prevent the development and transmission of microorganisms. Several polymers containing different nanoparticles have already been offered to day for this purpose. The research presents a novel poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)/polyvinylpyrrolidone (PVP) polymer composite with MoO3 nanowires with the ability to form coating films on wood. The films of the developed coating exhibit elastic behaviour, which depends on the coating film thickness [tested wet film thicknesses (90, 180 and 360) µm]. The coating showed the ability to interact well with the surface of common beech (Fagus sylvatica L.) wood, in terms of wetting (contact angles of 15.6°), fast spilling on the surface, good penetration of the coating in wood structure and formation of up to 40 µm-thick films with excellent pull-off adhesion strength (6 MPa). An increased roughness of wood coated with C + MoO3 was a consequence of wood etching by the dimethylformamide solvent present in the coating. Moreover, the presence of C + MoO3 on wood made it considerably more hydrophobic, with contact angle of water raising to 123° from initially 46° measured on uncoated wood. The irradiation of wood surfaces with ultra-violet light resulted in visible colour changes on both uncoated and coated wood. The wood coated with C + MoO3 has a good resistance to water, alcohol and dry heat (grade 3 to 4). The antimicrobial testing showed that the presence of MoO3 in the coating plays an important role in the resistance of the coated wood to blue-stain fungi and mould development. The developed PVDF-HFP/PVP/MoO3 coating has an excellent ability to interact with the wood surface and has the potential to be used as a protection for wood in sensitive environments.
Identifying activity level related movement features of children with ASD based on ADOS videos
Authors: Jin Xuemei , Zhu Huilin , Cao Wei , Zou Xiaobing , Chen Jiajia 
Published: March 2023

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder that affects about 2% of children. Due to the shortage of clinicians, there is an urgent demand for a convenient and effective tool based on regular videos to assess the symptom. Computer-aided technologies have become widely used in clinical diagnosis, simplifying the diagnosis process while saving time and standardizing the procedure. In this study, we proposed a computer vision-based motion trajectory detection approach assisted with machine learning techniques, facilitating an objective and effective way to extract participants’ movement features (MFs) to identify and evaluate children’s activity levels that correspond to clinicians’ professional ratings. The designed technique includes two key parts: (1) Extracting MFs of participants’ different body key points in various activities segmented from autism diagnostic observation schedule (ADOS) videos, and (2) Identifying the most relevant MFs through established correlations with existing data sets of participants’ activity level scores evaluated by clinicians. The research investigated two types of MFs, i.e., pixel distance (PD) and instantaneous pixel velocity (IPV), three participants’ body key points, i.e., neck, right wrist, and middle hip, and five activities, including Table-play, Birthday-party, Joint-attention, Balloon-play, and Bubble-play segmented from ADOS videos. Among different combinations, the high correlations with the activity level scores evaluated by the clinicians (greater than 0.6 with p < 0.001) were found in Table-play activity for both the PD-based MFs of all three studied key points and the IPV-based MFs of the right wrist key point. These MFs were identified as the most relevant ones that could be utilized as an auxiliary means for automating the evaluation of activity levels in the ASD assessment.
Maxillofacial fracture detection and classification in computed tomography images using convolutional neural network-based models
Authors: Warin Kritsasith , Limprasert Wasit , Suebnukarn Siriwan , Paipongna Teerawat , Jantana Patcharapon , Vicharueang Sothana 
Published: March 2023

AbstractThe purpose of this study was to evaluate the performance of convolutional neural network-based models for the detection and classification of maxillofacial fractures in computed tomography (CT) maxillofacial bone window images. A total of 3407 CT images, 2407 of which contained maxillofacial fractures, were retrospectively obtained from the regional trauma center from 2016 to 2020. Multiclass image classification models were created by using DenseNet-169 and ResNet-152. Multiclass object detection models were created by using faster R-CNN and YOLOv5. DenseNet-169 and ResNet-152 were trained to classify maxillofacial fractures into frontal, midface, mandibular and no fracture classes. Faster R-CNN and YOLOv5 were trained to automate the placement of bounding boxes to specifically detect fracture lines in each fracture class. The performance of each model was evaluated on an independent test dataset. The overall accuracy of the best multiclass classification model, DenseNet-169, was 0.70. The mean average precision of the best multiclass detection model, faster R-CNN, was 0.78. In conclusion, DenseNet-169 and faster R-CNN have potential for the detection and classification of maxillofacial fractures in CT images.
The effect of positive thinking on resilience and life satisfaction of older adults: a randomized controlled trial
Authors: Taherkhani Zahra , Kaveh Mohammad Hossein , Mani Arash , Ghahremani Leila , Khademi Khadijeh 
Published: March 2023

AbstractThe cumulative effects of adversity and unhappiness affect life satisfaction and quality of life in the growing older adult population. Most of the interventions aimed at improving the health and quality of life of older adults have adopted a problem-oriented or weakness-focused approach. However, a positive or strengths-focused approach can also have a virtuous but more effective capacity to contribute to the well-being and life satisfaction of older adults. Therefore, the present study was conducted to investigate the effect of positive thinking training on improving resilience and life satisfaction among older adults. A randomized controlled trial was conducted on 100 older adults with simple random sampling. The intervention group received 90-min weekly sessions for eight weeks on positive thinking training through written homework for reflection, group discussion, and media. The data were collected using Ingram and Wisnicki Positive Thinking Questionnaire, Connor-Davidson Resilience Scale, and Tobin Life Satisfaction Questionnaire at baseline and one week and two months after the training. The collected data were analyzed using descriptive and inferential statistics in SPSS software 26. P values below 0.05 were considered statistically significant. Positive thinking training led to better thinking (p < 0.001), higher resilience (p < 0.001), and greater life satisfaction (p < 0.001). The study's findings showed the effectiveness of the positive thinking training approach in improving resilience and life satisfaction in older adults. It is recommended to evaluate the long-term outcome in populations with different social, economic, and cultural statuses in future studies.
Detection of chemo-kinematical structures in Leo I
Authors: Alarcón Jara A. G. , Fellhauer M. , Simon J. , del Pino A. , Fu S. W. , Sohn S. T. 
Published: March 2023

Context. A variety of formation models for dwarf spheroidal (dSph) galaxies have been proposed in the literature, but generally they have not been quantitatively compared with observations.
Aims. We search for chemodynamical patterns in our observational data set and compare the results with mock galaxies consisting of pure random motions, and simulated dwarfs formed via the dissolving star cluster and tidal stirring models.
Methods. We made use of a new spectroscopic data set for the Milky Way dSph Leo I, combining 288 stars observed with Magellan/IMACS and existing Keck/DEIMOS data, to provide velocity and metallicity measurements for 953 Leo I member stars. We used a specially developed algorithm called BEACON to detect chemo-kinematical patterns in the observed and simulated data.
Results. After analysing the Leo I data, we report the detection of 14 candidate streams of stars that may have originated in disrupted star clusters. The angular momentum vectors of these streams are randomly oriented, consistent with the lack of rotation in Leo I. These results are consistent with the predictions of the dissolving cluster model. In contrast, we find fewer candidate stream signals in mock data sets that lack coherent motions ∼99% of the time. The chemodynamical analysis of the tidal stirring simulation produces streams that share a common orientation of their angular momenta, which is inconsistent with the Leo I data.
Conclusions. Even though it is very difficult to distinguish which of the detected streams are real and which are only noise, we can be certain that there are more streams detected in the observational data of Leo I than expected in pure random data.
Establishing 17-Hydroxyprogesterone Cutoff Values for Congenital
Adrenal Hyperplasia in Preterm, Low Birth Weight, and Sick
Newborns
Authors: Yoon Young Ahn , Woo Suhyeon , Kim Min-Sun , Kim Bohyun , Choi Young-Jin 
Published: March 2023

Abstract
Background Newborn screening for congenital adrenal hyperplasia (CAH) has
benefits with a high adoption rate worldwide. It also has problems of high false
positives, which can cause stress to the patient’s family with economic
losses and unnecessary visits of newborns to hospitals. Therefore, we
investigated the influence of birth weight (BW), gestational age (GA), and GA
with sampling time on 17-hydroxyprogesterone (17-OHP) concentration and
attempted to establish the 17-OHP cutoff values in preterm, low birth weight
(LBW), and sick newborns.
Methods Newborns (n=1,071) born between October 2020 and January
2022 were screened for CAH. Samples from neonates were collected on filter paper
with the heel prick method. 17-OHP concentration was measured by time-resolved
immunofluorescence with an AutoDELFIA Neonatal 17-hydroxyprogesteron kit and
grouped in relation to BW, GA, and GA with sampling time.
Results The median age of newborns at neonatal sample collection was 6
days. 17-OHP concentration showed a statistically significant negative
correlation with BW (r=−0.488, p<0.001)
and GA (r=−0.560, p<0.001). Full-term and
preterm subgroups had a similar decreasing tendency of 17-OHP concentration with
increasing sampling time. Application of newly establishing cutoff criteria
significantly reduced recall rates to 1.16%, 0.9%, and
1.75% according to each criterion of BW, GA, and GA with sampling time,
respectively.
Conclusions This study presents new 17-OHP cutoff values for preterm, LBW,
and sick newborns. These data in our laboratory can be used as a reference by
other laboratories for establishing new cutoff criteria to help lower the high
recall rate and reduce unnecessary follow-up tests.
Synthetic Utility of the Vilsmeier–Haack Reagent in Organic Synthesis
Authors: Singh Fateh V. , Dohi Toshifumi , Kumar Ravi , Neena Neena , Chaudhri Vishwas , China Hideyasu 
Published: March 2023

AbstractThe Vilsmeier–Haack reaction has historically been a topic of significant interest to organic chemists, and it continues to attract considerable attention. The reaction itself provides a facile route towards a large number of aromatic and heteroaromatic systems. The Vilsmeier–Haack reagent, generated from amides and halides, is found to be very important in organic synthesis. This account highlights recent developments in the synthetic utility of the Vilsmeier–Haack reagent.1	Introduction2	Formylation3	Formylation and Chlorination4	Formylation and Acetylation5	Chlorination6	ortho-Formylation7	Miscellaneous8	Conclusions
Mathematics in the Spanish press: a case study of the 18th century journal Semanario de Salamanca
Authors: Madrid María José , León-Mantero Carmen , Casas-Rosal Jose Carlos , Maz-Machado Alexander 
Published: March 2023

AbstractOld mathematics books and textbooks have always been sources of relevant information for researchers working on the history of mathematics and mathematics education. However, helpful information about this field can also be found in journals, ministerial decrees, or notes. Consequently, this article analyzes the contents related to mathematics or mathematics education in an 18th-century weekly journal published in the Spanish city of Salamanca, Semanario de Salamanca. To this end, we conducted a qualitative and descriptive investigation using a content analysis technique, which is widely used in research in this related area. Our results show that despite the fact that the weekly publication under investigation was specialized neither in mathematics nor in science, it included mathematical problems and solutions, mathematical texts, job advertisements for mathematics teachers, mathematics book reviews, and opinions about mathematics. Therefore, the present work expands knowledge of the presence and dissemination of mathematics and mathematics education in 18th-century Spanish society.
Mid-wave infrared sensitized InGaAs using intraband transition in doped colloidal II–VI nanocrystals
Authors: Khalili Adrien , Cavallo Mariarosa , Dang Tung Huu , Dabard Corentin , Zhang Huichen , Bossavit Erwan , Abadie Claire , Prado Yoann , Xu Xiang Zhen , Ithurria Sandrine , Vincent Grégory , Coinon Christophe , Desplanque Ludovic , Lhuillier Emmanuel 
Published: March 2023

Narrow bandgap nanocrystals (NCs) are now used as infrared light absorbers, making them competitors to epitaxially grown semiconductors. However, these two types of materials could benefit from one another. While bulk materials are more effective in transporting carriers and give a high degree of doping tunability, NCs offer a larger spectral tunability without lattice-matching constraints. Here, we investigate the potential of sensitizing InGaAs in the mid-wave infrared throughout the intraband transition of self-doped HgSe NCs. Our device geometry enables the design of a photodiode remaining mostly unreported for intraband-absorbing NCs. Finally, this strategy allows for more effective cooling and preserves the detectivity above 108 Jones up to 200 K, making it closer to cryo-free operation for mid-infrared NC-based sensors.
Identifying opportunities to optimise the electronic medical record for allied health professionals: a concept mapping study
Authors: Schwarz Maria , Ward Elizabeth C. , Coccetti Anne , Simmons Joshua , Burrett Sara , Juffs Philip , Perkins Kristy , Foley Jasmine 
Published: March 2023

Objective To utilise a concept mapping process to identify key opportunities for electronic medical record (EMR) optimisation for allied health professionals (AHPs). Methods A total of 26 participants (allied health managers, clinicians and healthcare consumers) completed the concept mapping process, which included generating statements, and then subsequently sorting all statements into groups, and also ranking each statement for importance and changeability (0 = not important/changeable, 4 extremely important/changeable). Multivariate analysis and multidimensional scaling were then used to identify core priorities for digital optimisation. Results Participants generated 98 discrete statements that were grouped into 13 conceptual clusters. Of these, 36 statements were subsequently determined to fall within the ‘green zone’ on the Go-Zone plot of importance and changeability (changeability ≥2.44, importance ≥2.79), and formed the set of key optimisation priorities. Clusters with the most items in the Go-Zone plot were ‘training and business rules’ and ‘service statistics.’ Conclusion Concept mapping facilitated identification of 36 key optimisation priorities considered both changeable and important to assist EMR optimisation for AHPs. Addressing these priorities requires action related to end-user skills and training, EMR system capacity, and streamlining of governance and collaboration for the optimisation process.
Africa’s new urban spaces: deindustrialisation, infrastructure-led development and real estate frontiers
Authors: Gillespie Tom , Schindler Seth 
Published: March 2023

ABSTRACT
Many African governments have embraced centralised spatial planning and the construction of large-scale connective infrastructure as a means to synergise industrialisation and functional urban development. This article examines the tensions between these economic and urban development objectives in Ghana and Kenya. Infrastructure-led development in both cases has fuelled extended and unplanned urbanisation and the production of new frontiers for real estate investment. However, the evidence indicates that it has failed to contribute to processes of structural transformation. This argument advances debates about the tensions between supply chain and rentier capitalism and problematises the assumed relationship between infrastructure-led development and industrialisation.
Novel lead-connection technology for thin-film temperature sensors with arbitrary electrode lengths
Authors: E Mingfeng , Cui Yunxian , Guo Shuning , Liu Hui , Ding Wanyu , Yin Junwei 
Published: March 2023

Abstract
Traditional thin-film thermocouples (TFTCs) have limitations in measuring real surface temperature changes in aircraft because the connection between the nanofilm and the leads can easily fail. Despite this, how to improve this weak connection has rarely been addressed in previous studies. In this study, a lead-embedded alumina ceramic substrate is proposed to improve the durability of TFTCs. Multi-layer two-dimensional nanofilms with different thin-film electrode lengths were prepared on a substrate using DC-pulsed magnetron sputtering. Furthermore, the effect of the thin-film electrode length on the sensitivity, response time and measurement error of the sensor was investigated. The electrode length did not affect the sensitivity and response time; however, as it was increased, the temperature measurement error decreased. In addition, the static and dynamic performance, repeatability, measurement accuracy and service lifetime of the developed sensor were verified. The results show that the sensor has high sensitivity and linearity and good repeatability, with the response time being in microseconds. The sensor can continue to operate at 500 °C for more than 2 h with no signal interruption. The sensor’s reported accuracy is 0.43% at 300 °C.
Ultra-thin ZrO2 overcoating on CuO-ZnO-Al2O3 catalyst by atomic layer deposition for improved catalytic performance of CO2 hydrogenation to dimethyl ether
Authors: Fan Xiao , Jin Baitang , He Xiaoqing , Li Shiguang , Liang Xinhua 
Published: March 2023

Abstract
An ultra-thin overcoating of zirconium oxide (ZrO2) film on CuO-ZnO-Al2O3 (CZA) catalysts by atomic layer deposition (ALD) was proved to enhance the catalytic performance of CZA/HZSM-5 (H form of Zeolite Socony Mobil-5) bifunctional catalysts for hydrogenation of CO2 to dimethyl ether (DME). Under optimal reaction conditions (i.e. 240 °C and 2.8 MPa), the yield of product DME increased from 17.22% for the bare CZA/HZSM-5 catalysts, to 18.40% for the CZA catalyst after 5 cycles of ZrO2 ALD with HZSM-5 catalyst. All the catalysts modified by ZrO2 ALD displayed significantly improved catalytic stability of hydrogenation of CO2 to DME reaction, compared to that of CZA/HZSM-5 bifunctional catalysts. The loss of DME yield in 100 h of reaction was greatly mitigated from 6.20% (loss of absolute value) to 3.01% for the CZA catalyst with 20 cycles of ZrO2 ALD overcoating. Characterizations including hydrogen temperature programmed reduction, x-ray powder diffraction, and x-ray photoelectron spectroscopy revealed that there was strong interaction between Cu active centers and ZrO2.
Preparation and Properties of Copper-Based Composites Containing Nb1-x(Ti/Ta)xSe2
Authors: Ji Qing , Shi Qin , Wu Ping 
Published: March 2023

Abstract
In this study, copper-based-Nb1-x(Ti/Ta)xSe2 composites were prepared by powder metallurgy, and Nb1-x(Ti/Ta)xSe2 copper-based composites with different Ti/Ta doping atomic fractions were studied. physical, electrical and tribological properties. Among them, the doping amount of Ti and Ta has an important influence on the properties of the composite material. The doping amount of Ti can improve the mechanical, electrical and tribological properties of copper matrix composites within a certain range, especially when the doping amount of Ti is At 10at.%, the copper matrix composites exhibited excellent tribological properties. The addition of Ta greatly improved the tribological properties of the composites, and with the increase of Ta doping content, the friction coefficient of the copper-based composites gradually decreased. The research shows that the copper-based Nb1-x(Ti/Ta)xSe2 composite is a very promising new composite material.
Time Series Prediction Method of Metrics of Dispatching Automation System Based on AI Platform
Authors: Wan Xiong , Shen Jialing , Kong Yanru , Huang Xinjian , Lao Yinyin , Ji Xuechun 
Published: March 2023

Abstract
In view of the shortcomings of manual operation mode and passive anomaly perception in the current dispatching automation system, this paper provides a time series prediction method for the metrics of the dispatching automation system based on the artificial intelligence platform. Firstly, based on the collected metrics of the dispatching automation system, the time series prediction algorithm of metrics based on Long Short-Term Memory(LSTM) and LightGBM(LGB) combined model is studied. Then, the algorithm is integrated into a one-stop graphical interactive modeling tool and the model training process is drawn. Through the task is automatic split and distributed model training is automatically carried out on a regular basis. Then, the AI model service sharing technology based on Kubernetes is used to realize the model service release and automatic update, and the platform interactive development component is used to realize automatic online prediction and rolling iterative update. Finally, the actual data of the system metrics is used for example analysis, and the results show that the proposed method can realize the advance prediction of the system metrics, and realize the whole process automatic integration model training and prediction based on the artificial intelligence platform, and effectively improve the model training efficiency, meet the real-time and security requirements of the dispatching automation system, and is more suitable for engineering application scenarios.
Sliding Window Pooling Extreme Learning Machine Based Capacity Prediction of Lithium-ion Batteries
Authors: Han Caiyun , Yuan Huimei 
Published: March 2023

Abstract
Lithium batteries have been widely used in various fields. Accurately predicting the remaining useful life (RUL) of batteries is greatly significant for the safety, reliability and health management of batteries. Based on the measured parameters in the process of charge and discharge of battery, the extraction method of singular value decomposition (SVD) is used to get the health indicators (HIs) related to capacity. And the traditional extreme learning machine (ELM) method has been used to predict the RUL of lithium battery, but the prediction results are divergent, random and low precision. Therefore, this paper proposes sliding window pooling ELM (SW-PELM) method to solve these problems by adding a sliding window and pooling connections. The simulation experiment was carried out through the data of lithium-ion battery from three different research institutions. Experimental results show that the proposed algorithm can well improve the divergence and random ELM prediction results, and has higher prediction accuracy compared with other improved ELM algorithms.