bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enlightenment of the Mariana Fore‐arc Sedimentary Basin Evolution to the Subduction Process
Authors: XING Lei , LI Qianqian , MENG Qingwei , LIU Huaishan , WEI Jia , LÜ Boran , ZHOU Heng 
Published: November 2021

AbstractThe Mariana subduction structure is a hot topic in ocean‐ocean subduction zone research, and its subduction mechanism has attracted wide attention from experts and scholars in China and abroad. Based on the multi‐channel seismic data of survey line MGL1204 in the Mariana fore‐arc and DSDP ocean drilling data, this paper studies the development and evolution characteristics of the structure and strata in the Cenozoic Mariana fore‐arc sedimentary basin. The Cenozoic strata are divided into six seismic sequences, with the possible era of each seismic sequence discerned, and the relationship between fault development and earthquakes analyzed. The episodic activity of the volcanic chain of the Mariana island arc is thought to control the tectonic and stratigraphic development pattern of the Cenozoic sedimentary basin in the fore‐arc. Between 16°N–19°N and 146°E–151°E, the maximum thickness of the sedimentary center of the Cenozoic fore‐arc sedimentary basin in Mariana is about 2360 m. Normal faults are developed in the area and some broke to the seabed, indicating that the Mariana island arc is still in the post‐arc expansion stage. The application of multi‐channel seismic sections in structural and stratigraphic evolution study is an important means to elucidating the Mariana subduction mechanism.
Big data feature selection using fish and frog optimization
Authors: R. P. S. Manikandan , A. M. Kalpana 
Published: November 2021

AbstractBig data denotes a large amount of data which includes a wide range of such methodologies like big data collection, storage, analysis, and managing the data. Every data collected in this process (homogeneous or heterogeneous considered as data), we called as big data. In this article, fish colony and their social behavior are used recently for developing an algorithm, we called as novel represented as fish swarm optimization algorithm (FSOA), which is based on the fish swarm and its behavior while search for food. The shuffled frog leaping algorithm (SFLA) is one which we introduced recently for finding near optimal solutions. The technique of Hybrid FSO‐SFLA is used here for evaluating performance in big data queries.
Adaptive partitioning‐based copy‐move image forgery detection using optimal enabled deep neuro‐fuzzy network
Authors: Mariappan Geetha , Satish Aravapalli Rama , Reddy P. V. Bhaskar , Maram Balajee 
Published: November 2021

AbstractThe emergence of photo editing applications, like Adobe Photoshop, has manipulated the operation of digital images into a simple task. However, these manipulations of images misrepresent the content of the original image for misleading the public. Various copy move forgery detection techniques are developed, but these show less robustness on the image with noise and blurring. This article develops an optimization‐driven deep learning technique for image forgery detection. The purpose is to develop a copy‐move image forgery detection technique using a deep neuro‐fuzzy network and a newly developed optimization algorithm. Here, adaptive partitioning is adapted using a rectangular search for splitting the image into different parts. In addition, the features like local Gabor XOR pattern and Texton features are extracted from the partition. Furthermore, the forgery is detected using the deep neuro‐fuzzy network. Finally, the deep neuro‐fuzzy network training is performed using the proposed multi‐verse invasive weed optimization (MVIWO) technique. The proposed MVIWO method will be newly designed by integrating the multi‐verse optimizer and invasive weed optimization technique. Thus, the copy‐move image forgery detection is effectively performed using the proposed MVIWO‐based deep neuro‐fuzzy network. The developed MVIWO‐based deep neuro‐fuzzy network offers superior performance with the highest specificity of 93.54%, highest accuracy of 94.01%, and highest sensitivity of 97.75%.
Recruitment contributions and natal fidelity in tributary rivers of the Grand Lake, Oklahoma, Paddlefish stock
Authors: Schooley Jason D. , Whitledge Gregory W. , Scarnecchia Dennis L. 
Published: November 2021

AbstractMicrochemistry of sectioned dentary (lower jaw) bones was used to determine natal river (Neosho, Spring or Elk River) of paddlefish Polyodon spathula (Walbaum) in the economically important snag fishery in Grand Lake, northeastern Oklahoma, and to assess the relative importance of the tributary rivers as sources of recruits to the fishery. Geological differences between the Neosho River and Spring River watersheds resulted in large differences in water strontium:calcium (Sr:Ca) ratios reflected in dentary Sr:Ca for paddlefish from each river. Dentary core Sr:Ca signatures were used to infer natal river for paddlefish harvested over the period 2008–2018. Most harvested fish (87%) were identified as Neosho River origin, and 7% were within the predicted range for Spring River origin (6% undetermined). Relative frequencies of Neosho River and Spring River‐origin fish (the latter, all ≤10%) differed among cohorts but did not differ among years, locations or sexes. Results corroborate a sonar survey of spawning substrates that concluded that the Neosho River has higher potential value for paddlefish spawning and recruitment than the Spring River. No evidence of natal river fidelity was found. Results highlight the importance of maintaining habitat conditions and inform harvest management regulations required for paddlefish spawning, recruitment and sustainability.
Natural forests promote phosphorus retention in soil
Authors: Yu Zhen , Guoyi Zhou , Liu Lei , Manzoni Stefano , Ciais Philippe , Goll Daniel , Peñuelas Josep , Sardans Jordi , Wang Wantong , Zhu Jie , Li Lin , Yan Junhua , Liu Juxiu , Tang Xuli 
Published: November 2021

AbstractSoil phosphorus (P) availability often limits plant productivity. Classical theories suggest that total P content declines at the temporal scale of pedogenesis, and ecosystems develop toward the efficient use of scarce P during succession. However, the trajectory of ecosystem P within shorter time scales of succession remains unclear. We analyzed changes to P pools at the early (I), middle (II), and late (III) stages of growth of plantation forests (PFs) and the successional stages of natural forests (NFs) at 1969 sites in China. We found significantly lower P contents at later growth stages compared to earlier ones in the PF (p < .05), but higher contents at late successional stages than in earlier stages in the NF (p < .05). Our results indicate that increasing P demand of natural vegetation during succession, may raise, retain, and accumulate P from deeper soil layers. In contrast, ecosystem P in PF was depleted by the more rapidly increasing demand outpacing the development of a P‐efficient system. We advocate for more studies to illuminate the mechanisms for determining the divergent changes, which would improve forest management and avoid the vast degradation of PF ecosystems suffering from the ongoing depletion of P.
Combining ability and selection for agronomic and nutritional traits in Urochloa spp. hybrids
Authors: Gouveia Beatriz Tomé , Mateus Rogério Gonçalves , Barrios Sanzio Carvalho Lima , do Valle Cacilda Borges , de Sousa Bueno Filho Júlio Sílvio , Fernando Rios Esteban , Dias Alexandre Menezes , Rodrigues Nunes José Airton 
Published: November 2021

AbstractThe Urochloa spp. breeding program at EMBRAPA‐Brazil targets the development of apomictic hybrids to improve animal performance, while reducing the environmental impact of livestock. In summary, breeders perform multiple crosses between apomictic and sexual parents, and screen progeny to perform selections for agronomic and nutritional traits across several harvests, years and locations. Thus, choosing the right parents and the cross combinations is crucial for the success of the breeding program. The objectives of this study were to: (i) estimate the general (GCA) and specific (SCA) combining ability, and contribution of additive and nonadditive effects, from a partial diallel cross design between three apomictic and ten sexual parents, for agronomical and nutritional traits in Urochloa spp.; (ii) assess genetic gain for all traits by selecting for yield of high nutritional value leaf mass (NLM); (iii) characterize the genotype profiles using genotype by yield*trait (GYT) biplot analysis. A total of 1380 interspecific hybrids from 29 full‐sib progenies were evaluated and then the hybrid selection was performed based on studentized best linear unbiased prediction of NLM. The 10% top‐performing hybrids were used in the GYT analysis using NLM as the basic variable. There was a predominance of nonadditive effects on the phenotypic expression of agronomic and nutritional value traits. The GCA was observed only for some traits in sexual parents, whereas SCA was observed in all traits. The selection based on NLM provided favorable gains for most of the agronomic traits and GYT biplot analysis was efficient to characterize genotype profiles.
Development and validation of a supervised deep learning algorithm for automated whole‐slide programmed death‐ligand 1 tumour proportion score assessment in non‐small cell lung cancer
Authors: Hondelink Liesbeth M , Hüyük Melek , Postmus Pieter E , Smit Vincent T H B M , Blom Sami , von der Thüsen Jan H , Cohen Danielle 
Published: November 2021

AimsImmunohistochemical programmed death‐ligand 1 (PD‐L1) staining to predict responsiveness to immunotherapy in patients with advanced non‐small cell lung cancer (NSCLC) has several drawbacks: a robust gold standard is lacking, and there is substantial interobserver and intraobserver variance, with up to 20% discordance around cutoff points. The aim of this study was to develop a new deep learning‐based PD‐L1 tumour proportion score (TPS) algorithm, trained and validated on a routine diagnostic dataset of digitised PD‐L1 (22C3, laboratory‐developed test)‐stained samples.Methods and resultsWe designed a fully supervised deep learning algorithm for whole‐slide PD‐L1 assessment, consisting of four sequential convolutional neural networks (CNNs), using aiforia create software. We included 199 whole slide images (WSIs) of ‘routine diagnostic’ histology samples from stage IV NSCLC patients, and trained the algorithm by using a training set of 60 representative cases. We validated the algorithm by comparing the algorithm TPS with the reference score in a held‐out validation set. The algorithm had similar concordance with the reference score (79%) as the pathologists had with one another (75%). The intraclass coefficient was 0.96 and Cohen’s κ coefficient was 0.69 for the algorithm. Around the 1% and 50% cutoff points, concordance was also similar between pathologists and the algorithm.ConclusionsWe designed a new, deep learning‐based PD‐L1 TPS algorithm that is similarly able to assess PD‐L1 expression in daily routine diagnostic cases as pathologists. Successful validation on routine diagnostic WSIs and detailed visual feedback show that this algorithm meets the requirements for functioning as a ‘scoring assistant’.
Formation mechanism and microhardness characterization of the ultrasonic hardening layer in cementitious materials
Authors: Shi Yong , Wang Lihui , Zhang Zhanrong , Yang Liguo 
Published: November 2021

AbstractUltrasonic surface treatment (UST) is a novel treatment method to improve the durability of cementitious materials, resulting in the formation of an ultrasonic hardening layer (UHL). The UHL acts as an effective natural coating, offering penetration and erosion protection. However, the formation mechanism and the quantitative characterization of the UHL have not been studied, and the validity of the UST on the top and side surfaces of cementitious materials is still unknown. Therefore, in this study, we investigated and proposed a formation mechanism for the UHL, and defined a transition layer between the UHL and the matrix. We also utilized HV microhardness testing to provide an effective quantitative characterization method for the UHL. Finally, using a set of custom‐designed ultrasonic molds, we confirmed the validity of the UST on the top and side surfaces of the cementitious materials.
Vacuolar ATPase subunit F is critical for larval survival in Henosepilachna vigintioctopunctata
Authors: Zeng Jie , Kang Wei‐Nan , Jin Lin , Anjum Ahmad Ali , Li Guo‐Qing 
Published: November 2021

AbstractVacuolar ATPase (vATPase) is an important proton pump in insect tissues including gut and Malpighian tubule. Subunit F, one of the 16 subunits of the vATPase holoenzyme, is not well characterized. Here, we found that two HvvATPaseF isoforms were highly expressed in the hindgut and Malpighian tubules (MT) in the 28‐spotted lady‐beetle Henosepilachna vigintioctopunctata, an agricultural pest that feeds on Solanaceae and Cucurbitaceae. Knockdown of both HvvATPaseF variants by RNA interference (RNAi) delayed larval growth and negatively affected ecdysis and adult emergence. In the midgut, RNAi treatment resulted in the disappearance of peritrophic membrane, the reduction in the size and the impaired integrity of the gut, which was associated with sparse principle cells and an increase in TUNEL‐ and EdU‐positive cells. Whereas the MT were opaque and the tubule lumens were full of urine in dsegfp‐fed larvae, the tubules were clear and the tubule lumens were empty in the dsvATPaseF‐fed larvae. HvvATPaseF knockdown was also associated with a decrease in the abundance of the fat body and the levels of glucose, trehalose, triglyceride, total soluble amino acids and proteins, and an increase in glycogen. Consistent with the known effects of sugars on chitin formation, both the expression level of a chitin biosynthesis gene and the thickness of the head capsule cuticle were reduced in the HvvATPaseF‐depleted beetles. Our results demonstrated that subunit F plays an essential role in H. vigintioctopunctata development.
Factors associated with postpartum resumption of sexual intercourse among women in China: A retrospective multicenter study
Authors: Fan Xiaorong , Zhou Fang , Li Yuyan , Xia Wei , Che Yan ,   PPC Study Group
Published: November 2021

AbstractObjectiveTo examine the prevalence and factors associated with early resumption of sexual intercourse among postnatal women in China.MethodWe conducted a retrospective multicenter study of 15 834 postpartum women from 60 hospitals in 15 different locations across China. Data were obtained from questionnaires administered to the participants. All dates were analyzed using a one‐way ANOVA and two‐level Cox multiple linear regression models.ResultsMore than half of the participating women (55.9%) resumed sexual intercourse by 3 months postpartum. The independent variables associated with the postpartum resumption of sexual intercourse included sociodemographic characteristics (age, geographic location, educational attainment) and medical histories, including the previous abortion (incorporate with spontaneous and voluntary abortion) frequency, menstrual recovery, exclusive breastfeeding, and number of living children (p < 0.05).ConclusionMore than half of the women in this study resumed sexual intercourse within 3 months postpartum. Women with a lower educational attainment and from the western regions of China were more likely to resume sexual intercourse earlier. Increasing age, delayed recovery of menses, and exclusive breastfeeding were associated with a delayed resumption of sexual intercourse. Women who had greater experience with abortion or the number of living children resumed sexual intercourse earlier than their counterparts.
Recess and Overweight and Obesity in Children 5‐11 Years of Age: 2013‐2016 National Health and Nutrition Examination Survey*
Authors: Rogers Chakene D. , Richardson Michael R. , Churilla James R. 
Published: November 2021

ABSTRACTBACKGROUNDRecess has been shown to increase total daily energy expenditure, which may favorably impact body mass index by decreasing adiposity. This study examines associations between recess participation and adiposity.METHODSThe study sample included male (N = 1434) and female (N = 1409) children 5 to 11 years of age participating in the 2013‐2016 National Health and Nutrition Examination Survey. Overweight and obesity were defined using age‐ and sex‐specific percentiles. Recess participation interview questions were answered via proxy response.RESULTSCompared to a referent group participating in recess 5 days/week for >30 minutes/day and independent of demographic and behavioral factors, analysis revealed significantly greater odds of obesity in females reporting no recess participation (odds ratio 1.80; 95% confidence interval, 1.03‐3.15, p = .03). Furthermore, minority females were consistently found to possess greater odds of overweight and obesity independent of recess participation time. Only Mexican American boys were found to have greater odds of obesity independent of participation recess time.CONCLUSIONSIn a large nationally representative sample of US children, reporting no recess was associated with significantly greater odds of obesity in females. Minority females were also more likely to be overweight and obese and Mexican American boys are more likely to be obese independent of recess participation time.
Grasslands half‐full: investigating drivers of spatial heterogeneity in ungulate occurrence in Indian Terai
Authors: Rastogi S. , Chanchani P. , Sankaran M. , Warrier R. 
Published: November 2021

AbstractGrassland ecosystems have declined in their extent globally, driving declines in wild ungulate populations. Even within the remnant grasslands, ungulate distribution is highly heterogeneous for reasons that are not well understood. This in turn undermines both local and landscape level conservation efforts for these often‐neglected ecosystems and the herbivores they support. We investigated grassland‐ungulate relationships in the Terai region of North India, where wild ungulates are patchily distributed across alluvial grasslands, a besieged ecosystem. Specifically, we posited that spatial variation in grassland habitat use by swamp deer (Rucervus duvaucelii duvaucelii), hog deer (Axis porcinus) and spotted deer (Axis axis) would be explained by community composition, palatability of key grasses, and fire and flooding regimes in grasslands. Hierarchical clustering and multivariate ordination revealed that three dominant tall‐grass communities and the narrowly distributed and more palatable short grass Cynodon‐Oryza community were only marginally influenced by fire and flood histories. Ungulate habitat use, assessed using occupancy models for spatially correlated data, indicated that hog deer were ubiquitously distributed across the grasslands in the park (habitat use probability, ᴪ = 0.92, se = 0.05) utilizing a diverse range of grassland types, while spotted deer (ᴪ = 0.80, se = 0.17) and swamp deer (ᴪ = 0.45, se = 0.10) occurrence within grasslands was relatively lower. Grass height and grassland extent positively influenced habitat use of swamp deer and spotted deer, respectively. However, grassland community composition, fire history, flood history and palatability were relatively uninformative predictors of fine‐scale habitat use. Our study provides a robust baseline for future monitoring of grasslands and ungulates as well as insights for the design and implementation of grassland management interventions.
The legal status of Particularly Sensitive Sea Areas (PSSAs): Challenges and improvements for PSSA resolutions
Authors: Choi Junghwan 
Published: November 2021

AbstractAs an area‐based management tool, the concept of the Particularly Sensitive Sea Area (PSSA) has played a significant role in protecting the marine environment and marine ecosystems from threats posed by international shipping activities. The International Maritime Organization (IMO) allows a coastal State to adopt various associated protective measures in a proposed PSSA for the protection of the marine environment and the conservation of biological diversity. Yet PSSAs remain controversial, as they are based on IMO resolutions, which are not legally binding. To examine the legal status of a PSSA, this article analyses the legal effects of IMO resolutions, their relationship with Part XII of the United Nations Convention on the Law of the Sea, and the application of the precautionary principle. Furthermore, the article examines limitations of PSSAs and suggests how the effectiveness of PSSAs in preventing vessel‐source pollution could be strengthened. The article concludes by referring to the necessity of revision of the PSSA resolutions to clarify the legal status of PSSAs.
Comparing Virtual and Face-to-Face Team Collaboration: Insights From an Agent-Based Simulation
Authors: Singh Harshika , Cascini Gaetano , McComb Christopher 
Published: November 2021

Abstract
The ongoing COVID-19 pandemic has accelerated the acceptance of virtual team collaboration as a replacement for face-to-face collaboration. Unlike face-to-face collaboration, virtual collaboration has different factors like technology mediation influencing communication that affects a team’s processes. However, there is a lack of rigorous research that assesses the impact of virtual teaming on the engineering design process. Therefore, the current study investigates the effect of virtual team collaboration on design outcomes by means of the MILANO (Model of Influence, Learning, and Norms in Organizations) framework. To tailor MILANO for virtual collaboration, this paper first presents an empirical study of human design teams, that shows how the model parameters for face-to-face collaboration (like self-efficacy, perceived influencers, perceived degree of influence, trust and familiarity) must be modified. The empirical study also shows the positive impact of effective communication on conflict resolution, task cohesion and the model parameters listed above. The simulation results for both virtual and face-to-face collaboration show how design outcomes differ with collaboration mode.
Data Augmentation for Roller Bearing Health Indicator Estimation Using Multi-Channel Frequency Data Representations
Authors: Hendriks Jacob , Dumond Patrick 
Published: November 2021

Abstract
This paper demonstrates various data augmentation techniques that can be used when working with limited run-to-failure data to estimate health indicators related to the remaining useful life of roller bearings. The PRONOSTIA bearing prognosis dataset is used for benchmarking data augmentation techniques. The input to the networks are multi-dimensional frequency representations obtained by combining the spectra taken from two accelerometers. Data augmentation techniques are adapted from other machine learning fields and include adding Gaussian noise, region masking, masking noise, and pitch shifting. Augmented datasets are used in training a conventional CNN architecture comprising two convolutional and pooling layer sequences with batch normalization. Results from individually separating each bearing’s data for the purpose of validation shows that all methods, except pitch shifting, give improved validation accuracy on average. Masking noise and region masking both show the added benefit of dataset regularization by giving results that are more consistent after repeatedly training each configuration with new randomly generated augmented datasets. It is shown that gradually deteriorating bearings and bearings with abrupt failure are not treated significantly differently by the augmentation techniques.