bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stroke survivors’ experiences with rebuilding life in the community and exercising at home: A qualitative study
Authors: van Dongen Lisa , Hafsteinsdóttir Thóra B. , Parker Ethna , Bjartmarz Ingibjörg , Hjaltadóttir Ingibjörg , Jónsdóttir Helga 
Published: March 2021

AbstractAimThis study aimed to explore how stroke survivors deal with stroke‐related impairments when rebuilding their lives in the community and their experiences of exercising at home.DesignAn explorative and descriptive qualitative study.MethodsA purposive sample of ten stroke survivors residing at home was recruited to explore experiences of rebuilding their lives in the community and exercising at home. One focus group interview was conducted followed by semi‐structured interviews. Data were analysed using thematic analysis.ResultsThree main themes were identified: “Framing exercise within the context of everyday life” describes how stroke survivors integrate exercise in everyday activities with varying success and the social importance of exercising; “Managing the challenges of physical impairment” describes the taxing undertakings in daily living, loss of concentration and identity; “Long‐term challenges of everyday life” describes how the stroke survivors manage depression and live with a sense of uncertainty.
Self‐compassion influences the caring behaviour and compassion competence among saudi nursing students: A multi‐university study
Authors: Alquwez Nahed , Cruz Jonas Preposi , Al Thobaity Abdulellah , Almazan Joseph , Alabdulaziz Hawa , Alshammari Farhan , Albloushi Monirah , Tumala Regie , Albougami Abdulrahman 
Published: March 2021

AbstractAimThis research investigated the perceptions of Saudi nursing students regarding self‐compassion and examined its influence on their caring behaviour and compassion competence.DesignThis is a quantitative and cross‐sectional study.MethodsThis multiuniversity study surveyed a convenience sample of 961 nursing using the Self‐compassion Scale, Compassion Competence Scale and Caring Behavior Inventory‐16 version. Standard multiple analysis was performed separately for caring behaviour and compassion competence as dependent variables. For both models, the self‐compassion dimensions and the demographic variables were considered predictor variables.ResultsThe students reported their self‐compassion moderately, with mindfulness receiving the highest mean and self‐judgment receiving the lowest mean. Significant differences were observed on self‐compassion of students between universities. Caring behaviour and compassion competence were also rated moderately by the students. “Self‐kindness” and “common humanity” were identified as significant predictors of caring behaviour, whereas “self‐kindness,” “self‐judgment,” “common humanity” and “mindfulness” were significant predictors of compassion competence.
Deep Learning for Hyperbolic Conservation Laws with Non‐convex Flux
Authors: Minbashian Hadi , Giesselmann Jan 
Published: March 2021

AbstractIn this work, we investigate the capabilities of deep neural networks for solving hyperbolic conservation laws with non‐convex flux functions. The behaviour of solutions to these problems depends on the underlying small‐scale regularization. In many applications concerning phase transition phenomena, the regularization terms consist of diffusion and dispersion which are kept in balance in the limit. This may lead to the development of both classical and non‐classical (or undercompressive) shock waves at the same time which makes the development of approximation schemes that converge towards the appropriate weak solution of these problems challenging. Here, we consider a scalar conservation law with cubic flux function as a toy model and present preliminary results of an ongoing work to study the capabilities of a deep learning algorithm called PINNs proposed in [1] for solving this problem. It consists of a feed‐forward network with a hyperbolic tangent activation function along with an additional layer to enforce the differential equation.
Deep learning of multibody minimal coordinates
Authors: Angeli Andrea , Naets Frank , Desmet Wim 
Published: March 2021

AbstractMultibody systems [1] are the state‐of‐the‐art tool to model complex mechanical mechanisms. However, they typically include redundant coordinates plus constraints, leading to differential algebraic equations for the dynamics which require dedicated integration schemes and control/estimation algorithms.In the deep learning field, autoencoders are a particular neural network class with a symmetric structure to perform a nonlinear dimensionality reduction. In fact, they can be seen as a non‐linear extension of principal component analysis [2].In this work, it is proposed to use an autoencoder to reduce a general multibody model to minimal coordinates, eliminating the constraints. The obtained decoder function is used to perform a non‐linear projection of the multibody coordinates:

urn:x-wiley:16177061:media:PAMM202000348:pamm202000348-math-0001

where

are respectively the encoder and decoder neural network functions, while

are respectively the obtained minimal coordinates and reconstructed full multibody coordinates.The novelty is that the autoencoder training includes the multibody physics information [3]. In this way, the autoencoder does not only perform a dimensionality reduction of the original coordinates but can be used for model order reduction. The obtained reduced‐order model consists of ordinary differential equations (with respect to the original differential algebraic equations) and can be used to perform dynamic simulations and easily coupled with standard estimation algorithms for state‐estimation.A typical application example is a mechanism with closed‐loops, such as a car suspension, for which no analytical expression is available to reduce the full multibody model to minimal coordinates. The introduced physics‐informed neural network allows to reduce the model and combine it with an augmented extended Kalman filtering scheme [4], in order to estimate difficult‐to‐measure inputs or parameters in the system.In a first application, the model in combination with measured strut displacement or acceleration, allows to estimate the strut force, in addition to the body full coordinates in position, velocity and acceleration. The rationale is reported in the figure below.rationale.pngThe Flanders Innovation & Entrepreneurship Agency within the IMPROVED project and the AI impulse program of the Flemish Government are gratefully acknowledged for their support.
Multi‐fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces
Authors: Romor Francesco , Tezzele Marco , Rozza Gianluigi 
Published: March 2021

AbstractGaussian processes are employed for non‐parametric regression in a Bayesian setting. They generalize linear regression embedding the inputs in a latent manifold inside an infinite‐dimensional reproducing kernel Hilbert space. We can augment the inputs with the observations of low‐fidelity models in order to learn a more expressive latent manifold and thus increment the model's accuracy. This can be realized recursively with a chain of Gaussian processes with incrementally higher fidelity. We would like to extend these multi‐fidelity model realizations to case studies affected by an high‐dimensional input space but with a low intrinsic dimensionality. In this cases physical supported or purely numerical low‐order models are still affected by the curse of dimensionality when queried for responses. When the model's gradients information is provided, the presence of an active subspace can be exploited to design low‐fidelity response surfaces and thus enable Gaussian process multi‐fidelity regression, without the need to perform new simulations. This is particularly useful in the case of data scarcity. In this work we present a multi‐fidelity approach involving active subspaces and we test it on two different high‐dimensional benchmarks.
Data‐Driven Learning of Reduced‐Order Dynamics for a Parametrized Shallow Water Equation
Authors: Yıldız Süleyman , Goyal Pawan , Benner Peter , Karasözen Bülent 
Published: March 2021

AbstractA non‐intrusive data‐driven model order reduction method is introduced that learns low‐dimensional dynamical models for a parametrized non‐traditional shallow water equation (NTSWE) [1]. The reduced‐order model is learnt by setting an appropriate least‐squares optimization problem [2] in a low‐dimensional subspace. The non‐intrusive model order reduction framework is extended to a parametric case using the parameter dependency at the level of the partial differential equation. The efficiency of the proposed non‐intrusive method is illustrated to construct reduced‐order models for NTSWE and compared with an intrusive method, proper orthogonal decomposition with Galerkin projection. Furthermore the predictability of both models outside the range of the training data is discussed.
Abrasive wear and dynamic–mechanical behavior of marble dust filled bagasse fiber reinforced hybrid polymer composites
Authors: Singh Tej , Puri Manish , Tejyan Sachin , Ravi Ravi Kant 
Published: March 2021

AbstractThe present study investigated the influence of waste materials on physico‐mechanical, dynamic mechanical, and abrasive wear behavior of polymer composites. The composites were manufactured by varying the waste bagasse fiber (2.5, 5, 7.5, and 10 wt%) in fixed marble dust (15 wt%) filled epoxy resin. The void content of the composite found to decrease, whereas density, impact energy, and flexural strength were found to increase with the increase of waste bagasse fiber loading. The hardness and tensile strength were first increased, and after attaining highest values for 7.5 wt% fiber content, both decreased with another fiber loading. Damping properties such as storage modulus, loss modulus, and damping factor were evaluated utilizing dynamic mechanical analyzer. Results showed that the composites with 10 wt% waste bagasse fiber loading exhibited highest viscoelastic properties. Moreover, the dry sand abrasive wear behavior of fabricated composites was designed to study the impact of fiber loading, sliding distance, and load using the Taguchi method. The analysis reveals that the sliding distance contributes the most toward abrasive wear of the composites, with a contribution of 58.70%. 7.5 wt% waste bagasse fiber, 400 m sliding distance, and 5 N load resulted in a most wear‐resistant combination. Finally, the abraded composite surfaces were examined using scanning electron microscopy to study the possible wear mechanisms.
Profiling and quantitation of alkaloids in different parts of Sophora alopecuroides L. extracts by high‐performance liquid chromatography with electrospray ionisation ion mobility spectrometry detection
Authors: Jia Xu , Zhang Hanghang , Jiang Xiangfu , Lu Yaling , Liu Wenjie , Yu Jianna 
Published: March 2021

AbstractIntroductionAmbient pressure electrospray ionisation ion mobility spectrometry coupled to high‐performance liquid chromatography (HPLC) was used to detect alkaloids from different parts of Sophora alopecuroides L. extracts. Multiplexing ion mobility spectrometry (IMS) was used to improve the signal‐to‐noise ratio while maintaining high resolving power for the detecting of eluents from HPLC separation.Material and methodsThe alkaloids profile and distribution are demonstrated by retention time‐drift time two‐dimensional spaces, and the contents of five major alkaloids including sophoridine, sophocarpine, cytisine, aloperine, and matrine were determined in the leaf, skin, stem, seed kernel, and seed husk using the HPLC‐IMS method. This method offers extra separation ability to isomers such as matrine and sophocarpine, which can be difficult to distinguish by mass spectrometry.ResultsThe reduced mobilities for cytisine, sophoridine, sophocarpine, matrine, and aloperine are 0.828, 0.718, 0.731, 0.725, and 0.769 cm2/V/s, respectively. The limits of detection are 0.553, 0.488, 0.479, 0.484, and 0.513 ug/mL. This method adds extra separation ability to HPLC to resolve co‐eluted peaks and provides another qualitative parameter besides HPLC retention time.
Characterization of nanocellulose from Indica rice straw as reinforcing agent in epoxy‐based nanocomposites
Authors: Mamat Razali Nur Amira , Ismail Muhamad Fareez , Abdul Aziz Fauziah 
Published: March 2021

AbstractThe extraction of nanocellulose from agro‐waste have received wide attention in nanocomposite technologies. This research unravels physico‐chemical characteristics of cellulose from Malaysia Indica rice straw, and the derived cellulose nanocrystal (CNC) by hydrochloric acid (HCl) hydrolysis. The CNC was subjected to field emission scanning electron microscopy (FESEM) and/or transmission electron microscopy (TEM) and Fourier transformed infrared (FTIR) studies. Furthermore, X‐ray diffraction (XRD) and small‐angle X‐ray scattering (SAXS) were compared with TEM for the CNC lateral crystal size. Subsequently, CNC reinforced epoxy laminates for Kevlar were prepared and tested for their tensile properties. While FTIR analysis confirmed the monoclinic cellulose structure of the isolated CNC, XRD, and SAXS were compared with TEM for the CNC lateral crystal size. Hydrolysis of the cellulose sample yielded 40.87% of CNC with 4.8 nm in width and a needle‐shaped nature. The extracted CNC has relatively low crystallinity (56.12%) but interestingly low crystallite size with an average crystallite size of 1.69 nm (XRD) and 4.18 nm (SAXS). Furthermore, an addition of just 1 wt% of CNC to epoxy composite increased the strength of Kevlar by over 300% and the elastic modulus by nearly three‐fold. Nanocellulose obtained from rice straw have great potential as reinforcing agents for the manufacture of nanocomposites.
Sodium doping of solution‐processed amine‐thiol based CIGS solar cells by thermal evaporation of NaCl
Authors: Uličná Soňa , Welch Liam M. , Abbas Ali , Togay Mustafa , Tsai Vincent , Betts Tom R. , Malkov Andrei V. , Walls John M. , Bowers Jake W. 
Published: March 2021

AbstractPoor crystallinity, high degree of porosity and rough surfaces are the main drawbacks of solution‐processed CIGS absorbers resulting in lower power conversion efficiencies when compared to vacuum‐based CIGS solar cells. Therefore, promoting absorber grain growth is key to further improve solution‐based solar cell performance. The effect of alkali elements such as Na in CIGS absorbers is generally recognised to have beneficial effects not only on the absorber opto‐electronic properties but also on the grain growth. In this work, thermal evaporation of a thin layer of NaCl prior to selenisation resulted in absorbers with significantly larger CIGS grains than previously seen with Na diffusing directly from the from soda‐lime glass substrate. NaCl is non‐toxic, abundant and readily available compound that has not been typically used as an evaporation source, but rather as an additive into CIGS precursor solution. The effect of Na on these solution‐processed CIGS devices was primarily observed in the spectacular morphological changes leading to improved carrier collection and minority carrier lifetimes, but less on the absorber doping. Transmission electron microscopy (TEM) revealed voids forming around large CIGS grains upon NaCl addition and these had a negative effect on inter‐grain carrier transport. Nonetheless, the resulting device performance doubled from 5% to 10% with addition of Na using this doping approach; however, a compromise between the optimum grain growth and optimum electronic properties had to be made. This study demonstrates a novel, simple and effective Na‐doping strategy for CIGS absorbers and reveals the current limitations of the Na‐doping in solution‐processed atmospherically deposited cells.
Examining congruence in parent–teacher perceptions of middle school supports for students and families
Authors: Garbacz S. Andrew , Santiago Rachel T. , Kosty Derek , Zahn Miranda , Stormshak Elizabeth A. , Smolkowski Keith , Seeley John R. 
Published: March 2021

AbstractThe purpose of this study was to examine parent–teacher congruent perceptions of middle school structures to support parent monitoring of children's behavior. We examined family educational involvement and school's communication and support to families as predictors of congruence, as well as congruence as a predictor of children following school rules and expectations. Participants were 415 teachers and 5003 parents across 40 public middle schools in the northwest region of the United States. Mixed‐effects regression was used to examine the cross‐sectional data. School size and student eligibility of free or reduced price school lunch were included as school‐level covariates. Results suggested that higher levels of teacher‐reported family involvement and school communication and support to families were significantly associated with greater parent–teacher congruence. In addition, results suggested that greater parent–teacher congruence was significantly associated with higher levels of teacher‐report of children following school rules and expectations. Implications for research on parent–teacher congruence and family–school collaboration are discussed at the school system level in terms of parent monitoring of children's behavior. Practical applications are reviewed for public middle schools.
LGBTQ student experiences in schools from 2009–2019: A systematic review of study characteristics and recommendations for prevention and intervention in school psychology journals
Authors: Abreu Roberto L. , Audette Lillian , Mitchell Y'Londa , Simpson Ina , Ward Jessica , Ackerman Lindsay , Gonzalez Kirsten A. , Washington Katherine 
Published: March 2021

AbstractThe present systematic review analyzes ways in which empirical studies in the field of school psychology have studied the experiences of lesbian, gay, bisexual, transgender, and queer (LGBTQ) students in the past decade (2009–2019). Results from 23 studies revealed an over‐representation of quantitative studies conducted mostly in the United States and an over‐representation of majority White, cisgender, and high school participants across studies. Results also showed that studies in the last decade have: (a) focused on exploring negative attitudes and behaviors toward LGBTQ students and the outcomes of these attitudes and behaviors, (b) provided direction on how to support LGBTQ students in schools, and (c) analyzed the effects of bystanders and perpetrators on the well‐being of LGBTQ students. In addition, this review revealed ways in which studies in school psychology journals present prevention and intervention practices for creating a safe environment for LGBTQ students, including: (a) policies that focus on the inclusion and protection of LGBTQ students, (b) training for faculty and other school staff to promote LGBTQ students' safety, and (c) curriculum and extracurricular activities that address LGBTQ issues. We provide recommendations for improving the experiences of LGBTQ students in schools such as involving community stakeholders in drafting affirming policies.
What do French school staff know about young carers? A qualitative study about their perceptions
Authors: Justin Pauline , Dorard Géraldine , Vioulac Christel , Leu Agnes , Untas Aurélie 
Published: March 2021

AbstractYoung carers (YCs) are children and adolescents who provide a significant help to family member(s) with a disease or a disability. They often remain hidden, especially in France where awareness levels and policy responses regarding YC are just emerging. Several studies show that YC often have difficulties at school because of their situation. However, school staff seems to have difficulties to identify and support YC. The aim of this study was to explore schools teachers and other professionals' levels of awareness and their perceptions of the potential impacts of caring on pupil attainment, achievement, and wellbeing. Thirty‐three professionals working with pupils from 6 to 18 years old (primary, secondary, and high schools) took part in a semi‐structured interview and in a short phone interview. The results showed that almost all had already met a YC. Despite knowledge and perceptions of potential impacts for their pupils, few undertook actions to support them. Healthcare professionals and school counsellors seemed more aware of these situations than teachers and more prone to offer support. These results underline the need to enhance all school staff's knowledge about YC and help them develop appropriate support.
Adaptability and ‘CandidatusLiberibacter asiaticus’ titres of Diaphorina citri adults on three weed species in China
Authors: Lu Huilin , Fang Xiaoduan , Wu Fengnian , Ouyang Gecheng 
Published: March 2021

AbstractBACKGROUNDDiaphorina citri is a vector of ‘Candidatus Liberibacter asiaticus’ (CLas), which is associated with citrus huanglongbing (HLB). In this study, the adaptability and CLas titres of D. citri adults on three weed species, namely, Ageratum conyzoides, Solanum nigrum and Praxelis clematidea, which are widely distributed in citrus orchards in China, were determined.RESULTSD. citri selected S. nigrum preferentially over the other weed species. The longest survival times of D. citri adults on A. conyzoides, S. nigrum and P. clematidea were 48, 41 and 11 days, respectively. On S. nigrum, the survivorship of females was significantly higher than that of males. The CLas titres of D. citri adults feeding on the three weeds for 1 week increased significantly during autumn but did not change significantly during spring. Conversely, the titres of adults on citrus increased significantly during spring but did not change significantly during autumn.CONCLUSIOND. citri exhibited different adaptabilities to the three weed species, but the CLas titres of D. citri adults did not decrease on any of the weeds. These results suggested that the three weed species could help dispersing of D. citri and transmission of CLas while ideal host conditions were scarce or absent. © 2021 Society of Chemical Industry.
Phytotherapy in the management of denture stomatitis: A systematic review and meta‐analysis of randomized controlled trials
Authors: Shui Yusen , Li Jingya , Lyu Xiaoying , Wang Yan 
Published: March 2021

Medicinal plant extracts are commonly applied for infectious diseases and are perceived as alternatives to conventional antimicrobial agents. We aimed to confirm the efficacy of phytotherapy for denture stomatitis compared with conventional therapies and placebo. A comprehensive literature search was conducted in Pubmed, Embase, Cochrane Library (CENTRAL), Scopus, and Web of Science, in addition to manual searching. Randomized controlled trials (RCTs) published in English, and studying the treatment of denture stomatitis with herbal medicines, were included. The outcome measures included the relief of clinical signs, reduced Candida colony counts, adverse effects, and patient satisfaction. Nineteen RCTs were included for a systematic review based on selection criteria. Two of them were analyzed using a random‐effects model. There was no difference in the relief of clinical signs (odds ratio (OR) = 0.96; 95% confidence interval (CI): 0.43–2.15) and microbiological improvement (OR = 1.74; 95% CI: 0.55–5.45) between propolis and miconazole. Most of the included studies showed that phytomedicines had fewer side effects and more patient satisfaction than antifungals or disinfectants. However, further RCTs with more standardly prepared herbal formulations are required to verify the clinical efficacy of phytotherapy as an alternative or adjunctive therapy for denture stomatitis.