bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review: In vivo studies of bioceramics as bone substitute materials
Authors: Al‐allaq Ali A. , Kashan Jenan S. 
Published: December 2022

AbstractThe critical size of bone defects resulting from disease or fractures is a medical problem, usually unable to repair spontaneously by the body's healing mechanisms. Bioceramics are being used for bone tissue regeneration to stimulate the growth of bone cells and guide osseous remodeling. The three most common types of bioceramics used in bone tissue engineering (hydroxyapatite, bioactive glass, and tricalcium phosphate) were selected and studied in vivo animal models, exhibiting favorable bone formation with positive biocompatibility reactions for several animal models. In the study, an extensive review of research was conducted to assess the bone‐forming capabilities of scaffolds in bone defects and remodeling in vivo. This review aims to support a large‐scale assessment of the capabilities of in vivo studies to generate an optimal regenerative process based on an analysis of the results. In addition to providing an essential reference for the applications of bone tissue engineering, the review will assist in developing novel in vivo investigations.
Covalent organic frameworks as advanced materials in the application of chemical detection
Authors: Liu Junyan , Wang Junfeng , Wang Ying , Wang Yang 
Published: December 2022

AbstractWith the development of industrialization, chemical detection plays a vital role in many fields. As a new type of porous material, covalent organic frameworks (COF's) possess the characteristics of huge specific surface area, low density, great stability, and adjustable pore size. These characteristics make it a great prospect for chemical detection. In the article, we mainly show how to design several analytic platforms to achieve precise target detection by utilizing the special properties of COF's, put forward the relevant mechanisms of successful detections, and analyze the related parameters of analyte detection performance. Finally, the current challenges of chemical detection based on COF's are presented, and we also prospect the future research directions.
Associations between cancer‐related distress and fatigue in childhood cancer survivors: A longitudinal study
Authors: Vanrusselt Deveny , Sleurs Charlotte , Prikken Sofie , Raymaekers Koen , Verschueren Sabine , Lemiere Jurgen , Luyckx Koen , Uyttebroeck Anne 
Published: December 2022

AbstractBackground and AimsA chronic feeling of fatigue occurs in up to 85% of childhood cancer survivors (CCS). This phenomenon has a detrimental effect on quality of life, reintegration in daily life activities and psychosocial functioning of the patient. Therefore, it is important to elucidate potential individual risk and protective factors.MethodsCCS who were treated in the University Hospital of Leuven, completed two annual questionnaires on cancer‐related distress (fear of cancer recurrence and post‐traumatic stress, resilience and fatigue). Associations between distress and fatigue levels were examined by performing cross‐lagged panel analyses. Resilience was included as a potential moderator. These models included all within‐time associations, stability paths, and cross‐lagged paths. Gender and time since diagnosis were included as covariates.ResultsIn total, 110 CCS participated in this study, aged 14–25 years (average time since diagnosis 12.2 years; 41.8% boys; diagnosed with leukemia/lymphoma [49%], solid tumor [15%], brain tumor [16%] or other [20%]). Fear of cancer recurrence and post‐traumatic stress at baseline positively predicted fatigue 1 year later. Cross‐lagged panel analyses showed that resilience did not buffer the effect of fear of cancer recurrence on fatigue, in contrary to our expectations. Stability coefficients were high for all study variables.ConclusionThis study indicates associations between cancer‐related distress (fear of cancer recurrence and post‐traumatic stress), resilience and cancer‐related fatigue over time in CCS. Interventions to improve fatigue levels could be focusing on both tackling cancer‐related distress, while improving resilience levels as well.
Return to valued activities: Survivors' experiences of adaptation and growth after treatment for head and neck cancer
Authors: Gibson Chandrika , O’Connor Moira , White Rohen , Jackson Melanie , Baxi Siddhartha , Sheppard Dianne , Halkett Georgia K. B. 
Published: December 2022

AbstractObjectiveThe objective of this study was to explore the experiences of head and neck cancer (HNC) survivors who returned to valued activities to understand how they reconstruct their lives following HNC diagnosis and treatment.MethodsA qualitative research approach based on social constructionist theory was used. A total of 21 in‐depth semi‐structured interviews were conducted with adults diagnosed with any type of HNC in the previous 6 years. Reflexive thematic analysis was used to identify themes.ResultsHNC presents a unique trauma following which some survivors navigate paths back to meaningful activities. The experiences of HNC survivors who adapted to life after treatment described internal and external change and development, identified by three themes; Mindfulness; Gratitude; and Adaptation.ConclusionPeople diagnosed with HNC frequently experience lasting effects and other survivorship issues, however some survivors were able to return to valued activities and recreate a meaningful lifestyle reflecting the possibility of post traumatic growth. This study provides insight into the experiences of head and neck cancer survivors who were able to make meaning and find internal and external growth following treatment. These findings can be used to inform advanced communication skills training for oncology health professionals and psychoeducational courses for people diagnosed with head and neck cancer in the future.
Smoothed counting of 0–1 points in polyhedra
Authors: Barvinok Alexander 
Published: December 2022

AbstractGiven a system of linear equations in an ‐vector of 0–1 variables, we compute the expectation of , where is a vector of independent Bernoulli random variables and are constants. The algorithm runs in quasi‐polynomial time under some sparseness condition on the matrix of the system. The result is based on the absence of the zeros of the analytic continuation of the expectation for complex probabilities, which can also be interpreted as the absence of a phase transition in the Ising model with a sufficiently strong external field. We discuss applications to perfect matchings in hypergraphs and randomized rounding in discrete optimization.
Structural Engineering of BiVO4/CoFe MOF Heterostructures Boosting Charge Transfer for Efficient Photoelectrochemical Water Splitting
Authors: Yang Xin‐Yu , Chen Zong‐Wei , Yue Xin‐Zheng , Du Xin , Hou Xing‐Hui , Zhang Li‐Ying , Chen De‐Liang , Yi Sha‐Sha 
Published: December 2022

AbstractBoosting charge separation and transfer of photoanodes is crucial for providing high viability of photoelectrochemical hydrogen (H2) generation. Here, a structural engineering strategy is designed and synthesized for uniformly coating an ultrathin CoFe bimetal‐organic framework (CoFe MOF) layer over a BiVO4 photoanode for boosted charge separation and transfer. The photocurrent density of the optimized BiVO4/CoFe MOF(NA) photoanode reaches a value of 3.92 mA cm−2 at 1.23 V versus reversible hydrogen electrode (RHE), up to 6.03 times that of pristine BiVO4, due to the greatly increased efficiency of charge transfer and separation. In addition, this photoanode records one onset potential that is considerably shifted negatively when compared to BiVO4. Transient absorption spectroscopy reveals that the CoFe MOF(NA) prolongs charge recombination lifetime by blocking the hole‐transfer pathway from the BiVO4 to its surface trap states. This work sheds light on boosting charge separation and transfer through structural engineering to enhance the photocurrent of photoanodes for solar H2 production.
The effect of marble powder on physico‐mechanical and microstructural properties of kaolin‐based geopolymer pastes
Authors: Kaya Mehmet , Köksal Fuat , Bayram Muhammed , Nodehi Mehrab , Gencel Osman , Ozbakkaloglu Togay 
Published: December 2022

AbstractAs an alternative to ordinary Portland cement (OPC), alkali‐activated materials (AAMs) have more recently been studied and found to have certain suitability in reducing ecological footprint of OPC binding systems. Nonetheless, due to recent concerns over the availability of certain precursors used AAMs (such as the reduction of coal fly ash availability), this study utilized marble powder in various quantities to replace the naturally available kaolin as precursor. This composite use of natural precursors has been entertained to assimilate the production of carbon zero AAMs. To evaluate the physico‐mechanical and microstructural characteristics of the materials, 48 mixes with different sodium (Na) concentrations, curing temperatures, and marble powder content have been used. The results show that rising curing temperature is more effective than other variables, such as the Na and marble powder content on the physico‐mechanical performance of tested geopolymers. In this regard, it is found that a very high Na content can have adverse effect on the properties, potentially due to altered Na/Si, Na/Al ratio in the mixes. Furthermore, the inclusion of marble powder is found to be effective in decreasing the overall porosity up to ~31% and enhancing the physico‐mechanical properties of the specimens cured at 20 and 80°C. Nonetheless, results show that when specimens containing marble powder are exposed to higher curing temperatures (above 80°C) the presence of marble powder adversely affects physico‐mechanical properties. It is concluded that this phenomenon is caused by the dehydration of chemically bound water in higher temperatures when marble powder is used. This result is further confirmed by microstructural tests.
How do digital textbook platforms promote active learning in undergraduate biology courses?
Authors: Metcalf Leah E. , Bernacki Matthew L. , Bernacki Lucas E. 
Published: December 2022

AbstractDiscipline‐based educational researchers and institutions that provide guidance on Science, Technology, Engineering, and Mathematics instruction have long documented the impact of active learning strategies on student learning and achievement, the lack of incorporation of active learning into undergraduate instruction, and the languishing rates of progression through and completion of undergraduate degree programs. Most research on improving active learning has been found to focus on instructors and the ways they have promoted active learning in their course design. Our aim was to consider the ways that textbook publishers and the online learning platforms they have produced have provided resources to promote active learning. This content analysis has documented the degree to which the digital platform companions to four highly subscribed introductory biology textbooks have provided resources that promote (1) highlighting of informational texts, (2) self‐testing, and (3) generative strategies for learning, including self‐explanation, summarization, and elaboration. Digital platforms largely supported highlighting and self‐testing, but the features of these tools could have been improved to promote more productive engagement in the learning strategies and to provide more explicit instruction about and scaffolding of the practices. Resources that promoted additional generative strategies were more limited. Implications relevant to developers and instructors who wish to leverage digital resources to promote active learning are included and are grounded via empirical support of design and implementation choices.
COVID-19 and U.S. Schools: Using Data to Understand and Mitigate Inequities in Instruction and Learning
Authors: Hamilton Laura S. , Ercikan Kadriye 
Published: December 2022

AbstractShortly after the COVID-19 pandemic arrived in the United States, schools across the country had to enact significant, rapid changes to their instructional models, and schools varied widely in their access to the resources needed to support these efforts. Researchers across the U.S. quickly launched surveys, website reviews, and other data-collection methods to document these shifts. In this chapter, we draw on this research to describe the U.S. K-12 educational context, the policies states adopted, the practices and resources schools offered, and the potential effects on students’ academic, social, and emotional learning. In these discussions we draw particular attention to inequities in educational opportunities across schools serving different student populations. We then discuss how different sources of data will be needed to help identify educational needs and mitigate disparities in instruction and learning post-pandemic.
Covid-19 and Education on the Front Lines in Japan: What Caused Learning Disparities and How Did the Government and Schools Take Initiative?
Authors: Iwabuchi Kazuaki , Hodama Kouki , Onishi Yutaka , Miyazaki Shota , Nakae Sae , Suzuki Kan Hiroshi 
Published: December 2022

AbstractWhile the COVID-19 pandemic posed unprecedented challenges to the education system of Japan, the government and schools took necessary measures to combat the outbreak and ensure student learning continued. The temporary school closure, following the state of emergency, continued for 2 months, from April through May of 2020. Even after the declaration was lifted in May 2020, schools adopted the new-normal way of operations. By shortening the summer break and holding alternative classes, elementary, junior, and senior high schools, except for universities, returned to normal while the COVID-19 pandemic was settling down, and ended the semester regularly in December 2020. The temporary closure, however, led to a huge disparity in implementing online classes, depending on availability of personal laptops in schools. Many private schools, and a substantial number of public schools established by innovative local governments, such as Saga Prefecture and Shibuya Ward, were successful in transitioning to online learning. However, most public schools were unable to hold online courses due to the lack of facilities both in schools and at student households. Aware of the disparities, the government brought forward a policy initiative to distribute personal PCs to all elementary and junior high school students, and to supply high-speed IT networks to each school, with an expected completion of March 2021. In this chapter, we will explore various disparities in depth, particularly underlining the relationship between ICT environments in schools and the issue of school founders. Additionally, we provide an overview on how the government and schools coped with the crisis, capitalized on the policy initiatives, and utilized available resources. As a concluding remark, we aim to leave room for optimism by taking this pandemic as an opportunity to reconsider and reimagine education. Note: This chapter has nothing to do with operations of organizations that respective authors belong to, and the views expressed in this chapter do not represent organizations’, but are authors’ own.
Forecasting unemployment with Google Trends: age, gender and digital divide
Authors: Mulero Rodrigo , Garcia-Hiernaux Alfredo 
Published: December 2022

AbstractThis paper uses time series of job search queries from Google Trends to predict the unemployment in Spain. Within this framework, we study the effect of the so-called digital divide, by age and gender, from the predictions obtained with the Google Trends tool. Regarding males, our results evidence a digital divide effect in favor of the youngest unemployed. Conversely, the forecasts obtained for female and total unemployment clearly reject such effect. More interestingly, Google Trends queries turn out to be much better predictors for female than male unemployment, being this result robust to age groups. Additionally, the number of good predictors identified from the job search queries is also higher for women, suggesting that they are more likely to expand their job search through different queries.
Parameterisation of the GNSS troposphere tomography domain with optimisation of the nodes’ distribution
Authors: Trzcina Estera , Rohm Witold , Smolak Kamil 
Published: December 2022

AbstractWater vapour is a highly variable constituent of the troposphere; thus, its high-resolution measurements are of great importance to weather prediction systems. The Global Navigation Satellite Systems (GNSS) are operationally used in the estimation of the tropospheric state and assimilation of the results into the weather models. One of the GNSS techniques of troposphere sensing is tomography which provides 3-D fields of wet refractivity. The tomographic results have been successfully assimilated into the numerical weather models, showing the great potential of this technique. The GNSS tomography can be based on two different approaches to the parameterisation of the model’s domain, i.e. block (voxel-based) or grid (node-based) approach. Regardless of the parameterisation approach, the tomographic domain should be discretised, which is usually performed in a regular manner, with a grid resolution depending on the mean distance between the GNSS receivers. In this work, we propose a new parameterisation approach based on the optimisation of the tomographic nodes’ location, taking into account the non-uniform distribution of the GNSS information in the troposphere. The experiment was performed using a dense network of 16 low-cost multi-GNSS receivers located in Wrocław and its suburbs, with a mean distance of 3 km. Cross-validation of four different parameterisation approaches is presented. The validation is performed based on the Weather Research and Forecasting model as well as radiosonde observations. The new approach improves the results of wet refractivity estimation by 0.5–2 ppm in terms of RMSE, especially for altitudes of 0.5–2.0 km.
Intrinsic D614G and P681R/H mutations in SARS-CoV-2 VoCs Alpha, Delta, Omicron and viruses with D614G plus key signature mutations in spike protein alters fusogenicity and infectivity
Authors: Khatri Ritika , Siddqui Gazala , Sadhu Srikanth , Maithil Vikas , Vishwakarma Preeti , Lohiya Bharat , Goswami Abhishek , Ahmed Shubbir , Awasthi Amit , Samal Sweety 
Published: December 2022

AbstractThe SARS-CoV-2 virus has been rapidly evolving over the time and the genetic variation has led to the generation of Variants of Concerns (VoC), which have shown increased fitness. These VoC viruses contain the key mutations in the spike protein which have allowed better survival and evasion of host defense mechanisms. The D614G mutation in the spike domain is found in the majority of VoC; additionally, the P681R/H mutation at the S1/S2 furin cleavage site junction is also found to be highly conserved in major VoCs; Alpha, Delta, Omicron, and its’ current variants. The impact of these genetic alterations of the SARS-CoV-2 VoCs on the host cell entry, transmissibility, and infectivity has not been clearly identified. In our study, Delta and D614G + P681R synthetic double mutant pseudoviruses showed a significant increase in the cell entry, cell-to-cell fusion and infectivity. In contrast, the Omicron and P681H synthetic single mutant pseudoviruses showed TMPRSS2 independent cell entry, less fusion and infectivity as compared to Delta and D614G + P681R double mutants. Addition of exogenous trypsin further enhanced fusion in Delta viruses as compared to Omicron. Furthermore, Delta viruses showed susceptibility to both E64d and Camostat mesylate inhibitors suggesting, that the Delta virus could exploit both endosomal and TMPRSS2 dependent entry pathways as compared to the Omicron virus. Taken together, these results indicate that the D614G and P681R/H mutations in the spike protein are pivotal which might be favoring the VoC replication in different host compartments, and thus allowing a balance of mutation vs selection for better long-term adaptation.
Blind recovery of sources for multivariate space-time random fields
Authors: Muehlmann C. , De Iaco S. , Nordhausen K. 
Published: December 2022

AbstractWith advances in modern worlds technology, huge datasets that show dependencies in space as well as in time occur frequently in practice. As an example, several monitoring stations at different geographical locations track hourly concentration measurements of a number of air pollutants for several years. Such a dataset contains thousands of multivariate observations, thus, proper statistical analysis needs to account for dependencies in space and time between and among the different monitored variables. To simplify the consequent multivariate spatio-temporal statistical analysis it might be of interest to detect linear transformations of the original observations that result in straightforward interpretative, spatio-temporally uncorrelated processes that are also highly likely to have a real physical meaning. Blind source separation (BSS) represents a statistical methodology which has the aim to recover so-called latent processes, that exactly meet the former requirements. BSS was already successfully used in sole temporal and sole spatial applications with great success, but, it was not yet introduced for the spatio-temporal case. In this contribution, a reasonable and innovative generalization of BSS for multivariate space-time random fields (stBSS), under second-order stationarity, is proposed, together with two space-time extensions of the well-known algorithms for multiple unknown signals extraction (stAMUSE) and the second-order blind identification (stSOBI) which solve the formulated problem. Furthermore, symmetry and separability properties of the model are elaborated and connections to the space-time linear model of coregionalization and to the classical principal component analysis are drawn. Finally, the usefulness of the new methods is shown in a thorough simulation study and on a real environmental application.
Asterarcys quadricellulare (Chlorophyceae) protects H9c2 cardiomyoblasts from H2O2-induced oxidative stress
Authors: Saadaoui Imen , Bounnit Touria , Mraiche Fatima , Joseph Jensa M. , Cherif Maroua , Al-Jabri Hareb 
Published: December 2022

AbstractOxidative stress has recently been identified as an important mediator of cardiovascular diseases. The need to find efficient antioxidant molecules is essential in the disease’s prevention. Therefore, the present study aimed to evaluate the potential of microalgae bioactive in protecting H9c2 cardiomyoblasts from H2O2-induced oxidative stress. Four microalgal species were investigated for their antioxidant capacity. A qualitative assessment of oxidative stress in H9c2 cardiomyoblasts stained with DCFH-DA, treated with the highly active microalgae extracts, was performed. The protein expression of total caspase-3 was also examined to investigate whether the extract protects H9c2 cardimyoblasts from H2O2-induced apoptosis. High antioxidant activity was observed for the hexanoic extracts after 10 days of cultivation. Asterarcys quadricellulare exhibited the highest antioxidant capacity of 110.59 ± 1.75 mg TE g−1 dry weight and was tested against H9c2 cardiomyoblasts, which were initially subjected to H2O2-induced oxidative stress. This hexanoic extract protected against H2O2 induced oxidative stress with a similar scavenging capacity as N-Acetylcysteine. Furthermore, total caspase-3 was increased following treatment with the hexanoic extract, suggesting that A. quadricellulare also had anti-apoptotic properties. The outcome of our study highlighted the possible use of the local A. quadricellulare strain QUCCCM10 as a natural, safe, and efficient antioxidant to prevent cardiovascular diseases.