bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring new methods to analyse spatial impact distributions on debris‐flow fans using data from south‐western British Columbia
Authors: Zubrycky Sophia , Mitchell Andrew , McDougall Scott , Strouth Alex , Clague John J. , Menounos Brian 
Published: July 2021

AbstractPredicting the spatial impact of debris flows on fans is challenging due to complex runout behaviour. Debris flow mobility is highly variable and flows can sporadically avulse the channel. For hazard and risk assessments, practitioners typically base the probability of spatial impact or avulsion on their experience and expert judgement. To support decision‐making with empirical observations, we studied spatial impact distributions on 30 active debris‐flow fans in south‐western British Columbia, Canada. We mapped 146 debris‐flow impact areas over an average observation period of 74 years using orthorectified airphotos, satellite imagery, topographic base maps, LiDAR data, orthophotos, and field observations. We devised a graphical method to convert our geospatial mapping into spatial impact heat maps normalized by fan boundaries, enabling comparison of runout distributions across different fans. About 90% of the mapped debris flows reached beyond the mid‐points of fans, while less than 10% avulsed more than half‐way across the fan relative to the previous flow path. Most avulsions initiated at distances of 20% to 40% of the maximum fan length from the fan apex and upstream of the fan intersection point. Large volume events tend to be more mobile in the down‐fan direction, but the relation between volume and cross‐fan runout (e.g., avulsions) is more complex. Differences in spatial impact distributions can be explained, in part, by the degree of fan incision and whether a fan is truncated at its toe by a river or lake. There were no significant differences in spatial impact distributions based on the geology of the source area, sediment supply condition, or hydrogeomorphic process classification.
Design and performance test of variable diameter threshing drum of combine harvester
Authors: Su Zhan , Ding Zhao , Tian Liquan , Lin Xue , Wang Zhiming 
Published: July 2021

AbstractDuring the rice harvesting process of combine harvester, it is necessary to adjust the working parameters of the threshing device in time according to working conditions to ensure operational efficiency and performance. This paper designs a variable diameter threshing drum, develops a device for diameter regulation with self‐locking function, and its installation process and working principle are introduced in detail. A force analysis and modal analysis were carried out on the device for diameter adjustment of variable diameter threshing drum. It aims to ensure that the design dimensions of the constant speed spiral disc and claws in the device for diameter adjustment are in compliance with the self‐locking conditions, and effectively ensure the reliability of the device for diameter adjustment. A field experiment was carried out to check the reliability of the developed system. A regression analysis model takes the feeding rate, threshing gap and drum speed as influencing factors. The grain separation loss rate and damage rate as performance indexes were established, and calculations for multiple target optimization were performed. The experimental results showed that the threshing gap could be adjusted in real time according to the different feeding rates of the variable diameter threshing drum.
Classification of type 2 diabetes mellitus with or without cognitive impairment from healthy controls using high‐order functional connectivity
Authors: Chen Yuna , Zhou Zhen , Liang Yi , Tan Xin , Li Yifan , Qin Chunhong , Feng Yue , Ma Xiaomeng , Mo Zhanhao , Xia Jing , Zhang Han , Qiu Shijun , Shen Dinggang 
Published: July 2021

AbstractType 2 diabetes mellitus (T2DM) is associated with cognitive impairment and may progress to dementia. However, the brain functional mechanism of T2DM‐related dementia is still less understood. Recent resting‐state functional magnetic resonance imaging functional connectivity (FC) studies have proved its potential value in the study of T2DM with cognitive impairment (T2DM‐CI). However, they mainly used a mass‐univariate statistical analysis that was not suitable to reveal the altered FC “pattern” in T2DM‐CI, due to lower sensitivity. In this study, we proposed to use high‐order FC to reveal the abnormal connectomics pattern in T2DM‐CI with a multivariate, machine learning‐based strategy. We also investigated whether such patterns were different between T2DM‐CI and T2DM without cognitive impairment (T2DM‐noCI) to better understand T2DM‐induced cognitive impairment, on 23 T2DM‐CI and 27 T2DM‐noCI patients, as well as 50 healthy controls (HC). We first built the large‐scale high‐order brain networks based on temporal synchronization of the dynamic FC time series among multiple brain region pairs and then used this information to classify the T2DM‐CI (as well as T2DM‐noCI) from the matched HC based on support vector machine. Our model achieved an accuracy of 79.17% in T2DM‐CI versus HC differentiation, but only 59.62% in T2DM‐noCI versus HC classification. We found abnormal high‐order FC patterns in T2DM‐CI compared to HC, which was different from that in T2DM‐noCI. Our study indicates that there could be widespread connectivity alterations underlying the T2DM‐induced cognitive impairment. The results help to better understand the changes in the central neural system due to T2DM.
Exploiting epigenetic dependencies in ovarian cancer therapy
Authors: Coughlan Aisling Y. , Testa Giuseppe 
Published: July 2021

AbstractOvarian cancer therapy has remained fundamentally unchanged for 50 years, with surgery and chemotherapy still the frontline treatments. Typically asymptomatic until advanced stages, ovarian cancer is known as “the silent killer.” Consequently, it has one of the worst 5‐year survival rates, as low as 30%. The most frequent driver mutations are found in well‐defined tumor suppressors, such as p53 and BRCA1/2. In recent years, it has become clear that, like the majority of other cancers, many epigenetic regulators are altered in ovarian cancer, including EZH2, SMARCA2/4 and ARID1A. Disruption of epigenetic regulators often leads to loss of transcriptional control, aberrant cell fate trajectories and disruption of senescence, apoptotic and proliferation pathways. These mitotically inherited epigenetic alterations are particularly promising targets for therapy as they are largely reversible. Consequently, many drugs targeting chromatin modifiers and other epigenetic regulators are at various stages of clinical trials for other cancers. Understanding the mechanisms by which ovarian cancer‐specific epigenetic processes are disrupted in patients can allow for informed targeting of epigenetic pathways tailored for each patient. In recent years, there have been groundbreaking new advances in disease modeling through ovarian cancer organoids; these models, alongside single‐cell transcriptomic and epigenomic technologies, allow the elucidation of the epigenetic pathways deregulated in ovarian cancer. As a result, ovarian cancer therapy may finally be ready to advance to next‐generation treatments. Here, we review the major developments in ovarian cancer, including genetics, model systems and technologies available for their study and the implications of applying epigenetic therapies to ovarian cancer.
Osteoblastic response to biomaterials surfaces: Extracellular matrix proteomic analysis
Authors: Graeff Marcia Sirlene Zardin , Tokuhara Cintia Kazuko , Sanches Mariana Liessa Rovis , Buzalaf Marília Afonso Rabelo , Rocha Luis Augusto , de Oliveira Rodrigo Cardoso 
Published: July 2021

AbstractThe cellular response to surfaces is mediated, among other factors, by the extracellular matrix (ECM). However, little is known about the ECM proteome during mineralization. Our objective was to compare the ECM composition formed by osteoblast on different materials surfaces with proteomic analysis. Three types of biomaterial surfaces (pure titanium, anodized titanium, and zirconia) were used. Osteoblasts (MC3T3 linage) cells were cultivated on the biomaterials for 7, 14, and 21 days with the osteogenic medium. For the proteomic analysis, the specimens were washed, decellularized, and the ECM was collected. The majority of the typical ECM proteins, out of a total of 24 proteins identified, was expressed and regulated equally on the three biomaterials tested. Alpha‐1,4 glucan phosphorylase was found to be down‐regulated on zirconia on the seventh day, while at the same time, glycogen phosphorylase brain form was up‐regulated on anodized titanium, both when compared with pure titanium (ratio: 1.06 and 0.97, respectively). And after 14 days of culture, glycogen phosphorylase brain form was downregulated on zirconia when compared with pure titanium (ratio: 0.90), suggesting the influence of material surface roughness and chemical composition on energy metabolism. Proteins related to bone development like Transforming growth factor beta‐3 and Fibroblast growth factor 8 were found exclusively on pure titanium on the 21st day. Altogether, our results show a possible influence of material surfaces on the composition of ECM.
Rational design of pincer‐nickel complexes for catalytic cyanomethylation of benzaldehyde: A systematic DFT study
Authors: Dutta Moumita , Srivastava Hemant Kumar , Kumar Akshai 
Published: July 2021

AbstractThe current study dwells upon the efforts to computationally probe a phosphine‐free pincer‐nickel complex that would demonstrate an efficiency better than the reported phosphine‐based pincer‐nickel complex (iPr2POCNEt2)Ni(CH2CN) for cyanomethylation reaction. For this purpose, the mechanism of cyanomethylation of benzaldehyde was studied quantum mechanically for a series of 11 pincer‐nickel complexes. The energetics of various intermediates and transition states involved in the catalytic cycle for each catalyst was compared with the corresponding energetics of the Miller's catalyst (iPr2POCNEt2)Ni(CH2CN) that is reported to accomplish the cyanomethylation at room temperature. While pincer complexes (iPr4NNN)Ni(CH2CN) and (iPr4NCN)Ni(CH2CN) containing strong σ‐donating amines were found to fare poorly, pincer‐nickel complexes (iPr2NCN)Ni(CH2CN) and (dmPheboxNCN)Ni(CH2CN) based on weaker σ‐donating imines had energetics more favorable than the reported efficient catalyst (iPr2POCNEt2)Ni(CH2CN). While strong trans‐influencing C as the pincer central atom was found to be pivotal for lowering the cyanomethylation kinetics, presence of a poor trans‐influencing N proved to be detrimental on the overall energetics.
Exploring mindfulness and artworks/drawings to predict dental students’ performance
Authors: Grazziotin‐Soares Renata , Ardenghi Diego Machado 
Published: July 2021

AbstractPurpose/ObjectivesTo explore and assess self‐reported trait mindfulness and artwork/drawings as tools to predict students’ performance.MethodsThis longitudinal study explored whether year 2 dental students’ artwork/drawings produced during the first week of a preclinical endodontics course and Mindfulness Attention Awareness Scale (MAAS) scores could be used as a predictor of performance (grades/rank) at the end of the course. A convergent design of mixed methods approaches was used to integrate the quantitative and qualitative datasets. Qualitative analysis consisted of a multilayered process of thematic analysis of artwork/drawings that was used to generate codes, categories, and themes—according to lower and higher students’ grades. Quantitative analysis consisted of statistical correlation between mindfulness scores and final grades. Findings were independently analyzed and further merged to answer our research question.ResultsThe bivariate analysis found nonsignificant relationship between students’ grades/rank and mindfulness scores: Pearson's correlation r = –0.097 (p = 0.578) and Spearman's correlation rho = 0.120 (p = 0.494). Codes, categories, and themes resulting from graphical data collected from the artwork/drawings strongly suggested that the higher students’ grades group depicted solutions to deal with negative feelings/emotions and presented traits of confidence to reach goals. Artworks produced from students with lower grades left questions, such as in relation to competency in dentistry, unanswered, but at the same time, they seemed to perceive everything as emotion related. Upon merging the findings, we recognized more image components suggestive of positive feelings exuding from the artworks/drawings of higher grades group; but an increase in mindfulness was not associated with increase (or decrease) in final grade.ConclusionFeelings/emotions represented in the artwork/drawings produced in the beginning of the course predicted students’ performance at the end of the course; however, self‐reported trait mindfulness was not correlated with performance.
Students’ perception of 3D video microscope use in preclinical fixed prosthodontics: A comparative study
Authors: Sadid‐Zadeh Ramtin , Li Rui , Arany Hema , Deluca Joseph 
Published: July 2021

AbstractObjectivesThe purpose of this study was to determine how students perceived the use of a 3D video microscope (3D VM), in comparison to conventional methods, for providing instruction on fixed prosthodontics procedures and issuing feedback on student performance.MethodsFrom May until December of 2020, University at Buffalo School of Dental Medicine's second‐year students were introduced to fixed prosthodontics. During May and June, a 3D VM was used to live‐stream psychomotor skill demonstrations via a web‐based software. After each procedure, students were asked to complete a short survey regarding their experience with the training. From August until December 2020, students received feedback via: 1. The conventional method, in which faculty use magnification loupes to assess student's perfromance. 2. A 3D VM. Irrespective of the method used, feedback was given following the same defined rubrics. At the conclusion of the semester, students completed a survey comparing their experiences in receiving instruction and feedback. The data were gathered and analyzed descriptively. The chi‐square test (α = .05) was used to gauge if students’ gender had an impact on their perception of feedback methods.ResultsMore than 94% of students participated in the surveys. The majority of students had a positive reaction toward the use of the 3D VM for live web‐based training. In regard to receiving feedback, 63% opined that the 3D VM was more effective than the conventional method. Additionally, 80% of students felt that the 3D VM was effective in maintaining physical distance during skill evaluations.ConclusionThis study examined the use of a 3D VM for teaching psychomotor skills and providing student feedback and compared it to the conventional method. It was found that the use of the 3D VM was perceived positively by students. Gender had no significant impact on students’ attitudes toward the teaching and feedback methods.
Bringing HIV services to key populations and their communities in Tanzania: from pilot to scale
Authors: Maruyama Haruka , Franks Julie , Laki Damian , Msumi Omari , Makyao Neema , Rwabiyago Oscar E , Rabkin Miriam , Kagashe Magreth J , El‐Sadr Wafaa M 
Published: July 2021

AbstractIntroductionDespite the global scale‐up of HIV testing, prevention and treatment, these services remain inaccessible to groups most vulnerable to HIV. Globally, most new HIV infections are concentrated among members of key populations (KP), including female sex workers, men who have sex with men, transgender people, people who inject drugs and their sexual partners. These populations lag in access to HIV prevention and antiretroviral therapy (ART) and have less favourable HIV outcomes compared to the general population. Intersecting behavioural and structural factors contribute to these gaps in service access for at‐risk KP and those living with HIV; corresponding comprehensive approaches to improving service delivery for KP are urgently needed. Differentiated service delivery (DSD) models tailor HIV programmes to the needs and preferences of specific groups but are rarely implemented at scale for KP. We describe the FIKIA Project, which implemented innovative approaches to scaling up DSD models to reach and engage KP in Tanzania.MethodsThe FIKIA Project worked with diverse KP communities in Tanzania to tailor HIV services to their needs and to pair healthcare workers with trained peer educators and expert client counsellors to expand uptake of community‐based HIV testing and ART services. We analysed routine aggregate project data from 2016 to 2020 to describe project implementation, outcomes and best practices.Results and discussionThe FIKIA Project conducted 1,831,441 HIV tests in community settings; of the 98,349 (5.4%) individuals with new HIV diagnoses, 89,640 (91.1%) initiated ART. The project reached substantial numbers of KP: 203,233 received HIV tests, 28,830 (14.2%) received a new HIV diagnosis and 25,170 KP (87.3%) initiated ART at the point of diagnosis. Over time, HIV testing increased by 1.6 times overall (2.3 times among KP), HIV diagnoses increased by 8.7 times (10.9 times among KP) and ART initiation at the point of diagnosis increased from 80.0% to 95.9% overall (from 69.6% to 94.9% among KP).ConclusionsOver four years, the FIKIA Project scaled up HIV testing, diagnosis and treatment by using DSD principles to design services that meet the needs of KP and their communities.
Internet of things platform for energy management in multi‐microgrid system to enhance power quality: ARBFNOCS technique
Authors: Vinjamuri Usha Rani , Burthi Loveswara Rao 
Published: July 2021

AbstractThis manuscript proposes an Internet of Things (IoT) platform for energy management (EM) in multi‐microgrid (MMG) system to enhance the power quality with hybrid method. The proposed method is the consolidation of opposition based crow search optimizer (OCSO) and radial basis functional neural network (RBFNN), hence it called RBFNOCS technique. The main aim of this manuscript is to optimally managing the power and resources of distribution system (DS) by constantly track the data from IoT‐based communication framework. In the proposed work, every devices of home is interfaced with data acquisition module (DAM) that is IoT object along unique IP address resultant in large mesh wireless network. Here, the IoT‐based communication framework is used for facilitating the development of a demand response (DR) energy management system (EMS) for distribution system. The transmitted data is processed by RBFNOCS technique. By utilizing the RBFNOCS method, the active with reactive power processing for optimal capacity unbalance compensation smart VSIs share the obtainable neutral current (NC). Likewise, the DS IoT framework enhances these networks flexibility and gives feasible use of obtainable resources. Moreover, the RBFNOCS method is responsible for satisfying the total supply with energy demand. The proposed model is activated in MATLAB/Simulink site and the performance is compared with existing models, namely improved artificial bee colony, squirrel search algorithm and gravitational search algorithm based artificial neural network (SOGSNN), GOAPSNN, fruit fly optimization, and FORDF technique. When compared with the existing methods, the efficiency of the RBFNOCS method is 93.4501%.
Modeling and performance evaluation of antennas coated using monolayer graphene in the millimeter and sub‐millimeter wave bands
Authors: Gatte Mohammed Taih , Soh Ping Jack , Kadhim Rasim Azeez , Abd Haider J. , Ahmad R. Badlishah 
Published: July 2021

AbstractIn the applications of millimeter and sub‐millimeter wave, the conductivity of metal parts in electronic devices can easily degrade when conventional metals like copper are employed. Furthermore, oxidation may arise when such devices are utilized in severe environmental conditions. To avoid this, conventional conductors such as copper can be coated with other non‐active materials to inhibit this problem. Monolayer graphene is used in this study as a coating layers for copper in millimeter‐wave antennas. Two types of graphene coatings are investigated: non‐doped and doped monolayer graphene. These coatings can either be used as the patch, ground or both conducting layers of a microstrip patch antenna. Results showed that coating using doped graphene improves the performance of antenna in terms of gain, radiated power and radiation efficiency by 11.81%, 8.48%, and 11.48%, respectively, compared to antennas made using copper and coated using gold and non‐doped graphene at millimeter‐wave frequencies. Meanwhile, at sub‐millimeter wave frequencies, the metal (copper and gold)‐based antenna showed worse performance compared to millimeter waves. Furthermore, coating of the conducting elements for the sub‐millimeter wave antenna using doped and non‐doped graphene improved gain, radiated power and radiation efficiency by 33.94%, 32.73%, and 32.01%, respectively, for the coating with doped graphene, and about 14.87%, 16.56%, and 15.72% for the coating with non‐doped graphene. This indicates the suitability of graphene‐based antennas in both frequency bands and the expected levels of improvements for different parameters when these antenna elements are coated with doped and non‐doped graphene.
Bias‐corrections on aridity index simulations of climate models by observational constraints
Authors: Yu Haipeng , Zhang Qiang , Wei Yun , Liu Chenxi , Ren Yu , Yue Ping , Zhou Jie 
Published: July 2021

AbstractAridity Index (AI) indicates the balance between water supply and water demand on the atmosphere–land interface. Despite continuous improvements, coupled climate models still have significant systematic errors in simulating AI in terms of temporal and spatial variabilities. One of the approaches to bias‐correct simulations is extracting the linear relationship between historical observations and model outputs by utilizing the empirical orthogonal function (EOF). In this study, the methodology of ensemble EOF‐based bias‐correction by observational constraints is developed based on previous bias‐correction approach, with the improvement on seeking the optimal combinations of the leading modes with sensitivity test and replacing the certain correction with the ensemble means of optimal members. In verification, the ensemble mean of Coupled Model Intercomparison Project phase 5 (CMIP5‐EM) is bias‐corrected towards the CPC/GLDAS observations, and the extracted leading modes present high correlations with internal climate variability. By cross‐validation and posteriori independent validation of hindcasts over the historical period (1948–2005), the ensemble EOF‐based bias‐correction could better present spatial patterns compared to the CMIP5‐EM after systematic bias‐correction, as indicated by the anomaly correlation and the root mean square error. The verifications also indicate that the temporal variability in aridity over different dryland regions is much closer to that in the observations and that the dryland subtype changes are improved significantly by bias‐corrections. Besides, another observational dataset of UDel/CRU is applied to assess the uncertainty on different datasets and the improvement on skill scores is robust. The above results verify that the ensemble EOF‐based bias‐corrections provide better reference for assessing and projecting global aridity changes by climate models.