bluuebunny/crossref_metadata_2025_split huggingface dataset:
Source–sink dynamics assists the maintenance of a pollinating wasp
Authors: Tong Xin , Ding Yuan‐Yuan , Deng Jun‐Yin , Wang Rong , Chen Xiao‐Yong 
Published: August 2021

AbstractDispersal that unites spatially subdivided populations into a metapopulation with source–sink dynamics is crucial for species persistence in fragmented landscapes. Understanding such dynamics for pollinators is particularly urgent owing to the ongoing global pollination crisis. Here, we investigated the population structure and source–sink dynamics of a pollinating wasp (Wiebesia sp. 3) of Ficus pumila in the Zhoushan Archipelago of China. We found significant asymmetry in the pairwise migrant numbers for 22 of 28 cases on the historical timescale, but only two on the contemporary timescale. Despite a small population size, the sole island not colonized by a superior competitor wasp (Wiebesia sp. 1) consistently behaved as a net exporter of migrants, supplying large sinks. Comparable levels of genetic diversity, with few private alleles and low genetic differentiation (total Fst: 0.03; pairwise Fst: 0.0005–0.0791), were revealed among all the islands. There was a significant isolation‐by‐distance pattern caused mainly by migration between the competition‐free island and other islands, otherwise the pattern was negligible. The clustering analysis failed to detect multiple gene pools for the whole region. Thus, the sinks were most probably organized into a patchy population. Moreover, the estimates of effective population sizes were comparable between the two timescales. Thus the source–sink dynamics embedded within a well‐connected population network may allow Wiebesia sp. 3 to persist at a competitive disadvantage. This study provides evidence that metapopulations in the real world may be complicated and changeable over time, highlighting the necessity to study such metapopulations in detail.
Tikanga rua: Bicultural spatial governance in Aotearoa New Zealand
Authors: Dionisio Rita , Macfarlane Angus Hikairo 
Published: August 2021

AbstractThis editorial introduction outlines the political and intellectual territory for a Special Issue on Tikanga rua: bicultural spatial governance in Aotearoa New Zealand. The term ‘spatial governance’ refers to deliberative systems with an impact on social and spatial outcomes, including environmental management, town planning, urban design and city‐making. Authentic tikanga rua bicultural spatial governance delivers processes and outcomes aligned with the perspectives, values and knowledge of both tangata whenua (people of the land) and tangata Tiriti (people of the Treaty). The research discussed in the Special Issue traverses multiple geographies and contexts and demonstrates the manifold possibilities for biculturalism in contemporary spatial governance. This introduction summarises the contents of each of the substantive papers and provides a Māori‐English glossary to assist readers with the key terms used within the issue.
Pangenome of white lupin provides insights into the diversity of the species
Authors: Hufnagel Bárbara , Soriano Alexandre , Taylor Jemma , Divol Fanchon , Kroc Magdalena , Sanders Heather , Yeheyis Likawent , Nelson Matthew , Péret Benjamin 
Published: August 2021

SummaryWhite lupin is an old crop with renewed interest due to its seed high protein content and high nutritional value. Despite a long domestication history in the Mediterranean basin, modern breeding efforts have been fairly scarce. Recent sequencing of its genome has provided tools for further description of genetic resources but detailed characterization of genomic diversity is still missing. Here, we report the genome sequencing of 39 accessions that were used to establish a white lupin pangenome. We defined 32 068 core genes that are present in all individuals and 14 822 that are absent in some and may represent a gene pool for breeding for improved productivity, grain quality, and stress adaptation. We used this new pangenome resource to identify candidate genes for alkaloid synthesis, a key grain quality trait. The white lupin pangenome provides a novel genetic resource to better understand how domestication has shaped the genomic variability within this crop. Thus, this pangenome resource is an important step towards the effective and efficient genetic improvement of white lupin to help meet the rapidly growing demand for plant protein sources for human and animal consumption.
Screening and identification of Cucurbita germplasm resistant to Xanthomonas cucurbitae, incitant of cucurbit bacterial spot
Authors: Sulley Salisu , Huang Yali , Hind Sarah R. , Babadoost Mohammed 
Published: August 2021

AbstractBacterial spot of cucurbits, caused by Xanthomonas cucurbitae, is an emerging disease of cucurbits. This study was conducted to identify Cucurbita species that are resistant to X. cucurbitae. We developed a reliable method for inoculating cucurbit plants by spraying plants with X. cucurbitae suspensions containing carborundum. Symptoms of the disease developed within 7 days after inoculation. Subsequently, we evaluated the virulence of six isolates of X. cucurbitae in the greenhouse and observed that X. cucurbitae isolated from cucurbit fields in Illinois, Michigan, Kansas, Ohio, and Wisconsin were more virulent than the reference ATCC 23378 strain. Then, we screened 81 commercial cultivars of gourds, pumpkins, and squashes, as well as 300 Cucurbita spp. accessions, for their resistance to X. cucurbitae under greenhouse and field conditions. In the greenhouse study, all commercial cultivars and some of the accessions developed typical symptoms of bacterial spot disease, while some of the accessions developed fewer lesions. In the field studies, infection of leaves and fruits was caused by both natural inoculum and spray‐inoculation of plants with a suspension of the X. cucurbitae isolate from Illinois. Among 300 accessions tested, 9 and 21 accessions were classified as resistant and less resistant, respectively. Resistant and less resistant accessions belong to the species Cucurbita maxima, C. maxima subsp. maxima, C. maxima subsp. andreana, and C. okeechobeensis subsp. martinezii. This is the first report of potential resistance to bacterial spot of cucurbits.
Sarracenia purpurea glycerol‐3‐phosphate acyltransferase 5 confers plant tolerance to high humidity in Arabidopsis thaliana
Authors: Hsu Yi‐Feng , Yan Jiawen , Song Yu , Zheng Min 
Published: August 2021

ABSTRACTSuberin, as a lipid polyester barrier, limits the movement of gas, water, and solutes, and plays important roles in plant protection and growth. In this study, a CDS encoding glycerol‐3‐phosphate acyltransferase 5 (GPAT5) was cloned from Sarracenia purpurea to investigate the gene function. SpGPAT5 shares 72% identity and 80% similarity to AtGPAT5 that is required for suberin synthesis. Fluorol Yellow 088 staining showed that the S. purpurea pitcher (specific leaf) tube contained more suberin in the adaxial surface compared to the lid, and SpGPAT5 transcripts were detected in the pitcher. Previous reported Atgpat5‐1 phenotypes were complemented with SpGPAT5 showing that the Atgpat5‐1 seed coat had increased permeability of tetrazolium red and the mutant was sensitive to salt. We also found that SpGPAT5 was able to revert the hyperhydric phenotype of Atgpat5‐1 under high humidity. Thus, this study suggests that SpGPAT5 can functionally replace AtGPAT5 and contributes to plant tolerance to high humidity, which maybe assist in understanding the role of suberin‐associated waxes in S. purpurea pitchers for water retention.
The COVID‐19 pandemic and the search for structure: Social media and conspiracy theories
Authors: Dow Benjamin J. , Johnson Amber L. , Wang Cynthia S. , Whitson Jennifer , Menon Tanya 
Published: August 2021

AbstractThe study outlines a model for how the COVID‐19 pandemic has uniquely exacerbated the propagation of conspiracy beliefs and subsequent harmful behaviors. The pandemic has led to widespread disruption of cognitive and social structures. As people face these disruptions they turn online seeking alternative cognitive and social structures. Once there, social media radicalizes beliefs, increasing contagion (rapid spread) and stickiness (resistance to change) of conspiracy theories. As conspiracy theories are reinforced in online communities, social norms develop, translating conspiracy beliefs into real‐world action. These real‐world exchanges are then posted back on social media, where they are further reinforced and amplified, and the cycle continues. In the broader population, this process draws attention to conspiracy theories and those who confidently espouse them. This attention can drive perceptions that conspiracy beliefs are less fringe and more popular, potentially normalizing such beliefs for the mainstream. We conclude by considering interventions and future research to address this seemingly intractable problem.
Microstructure Alteration in the High-Speed Machining of Titanium Alloy Involved With Tool Wear and Cryogenic Condition
Authors: Li Xin , Zhang Xueping , Shivpuri Rajiv 
Published: August 2021

Abstract
The microstructure alteration generated in the high-speed machining of titanium alloy has significant influence on the performance, quality and service life of production. The prediction of grain size or phase distribution based on physics mechanism or the regression of experimental data have been reported in the process of static or quasi-static state. However, it is still a challenge to predict the phase transformation and grain growth process in machining accurately and effectively since it has characteristics of high strain, strain rate and temperature. In this paper, a novel FEM-based model involving with the microstructure alteration was introduced and implemented to predict finial grain size or phase result in the high-speed machining of Ti-6Al-4V alloys especially at the machined surface. The phase transformation process was proposed and discussed by considering tool wear and cryogenic condition at machined surface, while the microstructure results were displayed on the chip in the previous works. Firstly, the phase volume fraction and grain size were modelled by experimental data. Then the simulation based on the self-consistent method (SCM) was used to output strain and temperature distribution. Thirdly, the phase volume fraction and grain size expressions were transmitted into subroutine programs and the microstructure alteration process under the different cutting conditions were showed in the FE results. The simulation results of temperature, phase fraction and strain were compared against previous simulation or experiment results in published papers revealing good agreement. The proposed model was further to investigate the influence of tool wear and cutting temperature on machined surface. The results indicated that the tool wear increased heat at the flank face significantly resulting to β phase increasing and grain growth at machined surface and the cryogenic condition would lower temperature gradient as well as stress gradient contributing to reduce roughness and residual stress.
Ultrasonic Vibration-Assisted Laser Directed Energy Deposition of B4C-Ti Composite: Effect of Laser Power and Ultrasonic Vibration
Authors: Li Yunze , Zhang Dongzhe , Cong Weilong 
Published: August 2021

Abstract
Compared with pure titanium, ceramic reinforced titanium matrix composites (TMCs) have the advantages of higher microhardness, higher wear resistance, and better load endurance properties, which enable their further applications under severe friction and cyclic loading conditions. B4C-Ti composite, as a kind of TMCs, has been fabricated by laser directed energy deposition (DED) technology. However, there are still some problems needed to be solved. First, the B4C particles are not fully melted. It suppresses the reactions between B4C and titanium and reduced the generation of TiB and TiC during the fabrication, which deteriorates the hardness of the B4C-Ti composite. Second, the reinforcement materials are not evenly distributed in the titanium matrix, which damages the performance of the B4C-Ti composite. In this study, B4C-Ti composite parts are fabricated by the ultrasonic vibration-assisted laser DED process. The effects of laser power and ultrasonic vibration on the phase compositions, microstructure, and hardness are investigated.
Investigating Optimal Parameter Combination for Friction Stir Spot Welding on AL7075-T6: Engineering Robust Design Approach
Authors: Jakobsen Jan-Tore , Ratnayake R. M. Chandima , Sætre Sem Sølve , Neverdal Arnfinn 
Published: August 2021

Abstract
Friction stir spot welding (FSSW) is a solid-state joining technique which is used to weld alloys that has a low weldability such as the 2000 and 7000 series aluminum alloy. The marine, automotive and aerospace industry benefits using this method as the need for weight reduction and fuel economy make the use of aluminum and other light metals necessary. The purpose of this study is to find the optimum parameters and the ultimate failure load for FSSW welded specimens in a basic lap configuration. Two coupons of AA7075-T6 with a dimension of 210 × 30 × 0.8 mm and 210 × 30 × 1.6 mm were welded using a self-made FSSW machine rebuild for the purpose of this project. The experiment was performed using engineering robust design approach to investigate the optimal parameter combinations that provides optimal joint performance. Experiments has been carried out using the Taguchi L9 orthogonal arrays with 4 factors and 3 levels. The factors and levels were chosen as follows: pin length in the interwall 1.2 mm to 1.6 mm, shoulder depth 0 to 0.4 mm, dwell time 1 sec to 2.5 sec and tool rotation speed 1800 rpm to 2600 rpm. The joint performance has been evaluated considering the ultimate tensile load. Tensile testing of weldments was carried out using an Instron Universal Testing Machine. To estimate the error variance for the factor effects and variance of the predicted error analysis of variance (ANOVA) was performed. The mathematical framework anticipated an ultimate failure load of 3286N, and the verification run confirmed the predicted result by an average of 3215N. The optimum parameters were found to be a pin length of 1.4 mm, shoulder depth of 0.4 mm, dwell time at 2.5 sec and a rotational speed of 2200 RPM. The ANOVA showed that the shoulder depth was the dominant factor influencing 87.9 % of the variation of the signal-to-noise ratio (S/N).
Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network
Authors: Guo Shenghan , Wang Dali , Chen Jian , Feng Zhili , Guo Weihong “Grace” 
Published: August 2021

Abstract
Resistance spot welding (RSW) is a widely adopted joining technique in automotive industry. Recent advancement in sensing technology makes it possible to collect thermal videos of the weld nugget during RSW using an infrared camera. The effective and timely analysis of such thermal videos has the potential of enabling in-situ nondestructive evaluation (NDE) of the weld nugget by predicting nugget thickness and diameter. Deep learning (DL) has demonstrated to be effective in analyzing imaging data in many applications. However, the thermal videos in RSW present unique data-level challenges that compromise the effectiveness of most pre-trained DL models. We propose a novel image segmentation method for handling the RSW thermal videos to improve the prediction performance of DL models in RSW. The proposed method transforms raw thermal videos into spatial-temporal instances in four steps: video-wise normalization, removal of uninformative images, watershed segmentation, and spatial-temporal instance construction. The extracted spatial-temporal instances serve as the input data for training a DL-based NDE model. The proposed method is able to extract high-quality data with spatial-temporal correlations in the thermal videos, while being robust to the impact of unknown surface emissivity. Our case studies demonstrate that the proposed method achieves better prediction of nugget thickness and diameter than predicting without the transformation.
Thermal Monitoring and Modeling of Ti-6Al-4V Thin Wall Temperature Distribution During Blown Powder Laser Directed Energy Deposition
Authors: Paudel Basil J. , Marshall Garrett J. , Thompson Scott M. 
Published: August 2021

Abstract
The effects of Ti-6Al-4V part size on its temperature distribution during the blown-powder directed energy deposition-laser (DED-L) process was investigated through dual-thermographic monitoring and a unique modeling technique. Results demonstrate that the duration of dwell times are a significant contributing factor affecting the rate at which a steady-state temperature field is achieved. Longer walls took significantly more layers/time to achieve a uniform temperature profile. Maximum and average melt pool temperatures appear to be near independent of part size at a steady state. Finite element simulation results show that a quasi-steady melt pool temperature may be unique to a layer, especially for layers near the substrate. Layer-wise steady melt pool temperatures were achieved within the first few seconds of track scanning. A proposed fin modeling-based temperature distribution was found to predict the thermal profile in a ‘substrate affected zone’ (SAZ) along the scan direction within 5%. A method to predict the onset of the SAZ has also been proposed. Process parameters used for the DED-L of component volumes are not necessarily optimal for thin-walled structures due to their significantly lower thermal capacity.
Photodiode-Based In-Process Monitoring of Part-to-Part Gap and Weld Penetration Depth in Remote Laser Welding of Copper-to-Steel Battery Tab Connectors
Authors: Chianese Giovanni , Franciosa Pasquale , Nolte Jonas , Ceglarek Darek , Patalano Stanislao 
Published: August 2021

Abstract
This paper addresses in-process monitoring of part-to-part gap and weld penetration depth using photodiode-based signals during Remote Laser Welding (RLW) of battery tab connectors. Photodiode-based monitoring has been largely implemented for structural welds due to its relatively low cost and ease of automation. However, the application of photodiode-based monitoring to RLW of thin foils of dissimilar metals for battery tab connectors remains an unexplored area of research and will be addressed in this paper. Motivated by the high variability during the welding process of thin foils of dissimilar metals, this paper aims to evaluate the photodiode-based signals to determine if variations in weld quality can be isolated and diagnosed. The main focus is in diagnosing defective weld conditions caused by part-to-part gap variations and/or excessive weld penetration depth. Photodiode-based signals have been collected during RLW of copper-to-steel thin foils lap joint (Ni-plated copper 300 μm to Ni-plated steel 300 μm). The methodology is based on the evaluation of the energy intensity and scatter level of the signals. The energy intensity gives information about the amount of radiation emitted during the welding process, and the scatter level is associated to the accumulated and un-controlled variations. Findings indicated that part-to-part gap variations can be diagnosed by observing the step-change in the plasma signal, with no significant contribution given by the back-reflection. Results further suggested that over-penetration corresponds to significant increment of the scatter level in the sensor signals. Opportunities for automatic isolation and diagnosis of defective welds based on supervised machine learning will be discussed throughout the paper.
Parametric Control of Melting Gel Morphology and Chemistry via Electrospray Deposition
Authors: Grzenda Michael , Gamboa Arielle , Mercado James , Lei Lin , Guzman Jennifer , Klein Lisa C. , Jitianu Andrei , Singer Jonathan P. 
Published: August 2021

Abstract
Melting gels are a class of hybrid organic-inorganic, silica-based sol-gels which are solid below their glass transition temperatures, near room temperature, but show thermoplastic behavior when heated. While this phase change can be repeated multiple times, heating the gel past its consolidation temperature, typically above 130 °C, initiates an irreversible reaction that produces highly crosslinked glassy organic/inorganic materials via hydrolysis and polycondensation. This ability makes melting gels uniquely compatible with processing techniques inaccessible to other sol-gels. By properly tuning their properties, it should be possible to create protective coatings for electronics and anti-corrosive coatings for metals that are highly hydrophobic and insulating. However, melting gel consolidation reactions are highly dependent on charge interactions, raising the question of how these materials will respond to a processing technique, like electrospray deposition (ESD), which is dependent on charge delivery. In this study, we focus on the role that substrate temperature and charge polarity play on film morphology, consolidation chemistry, and surface properties when processing via ESD. Optical images, film thickness measurements, and FTIR were used to characterize the sprayed melting gel with the goal of developing a robust processing space for producing highly cross linked, hydrophobic, dielectric coatings.
Tool Wear Analysis of MTConnect Production Data
Authors: Stock David , Mukhopadhyay Aditi , Potter Rob , Henderson Andy 
Published: August 2021

Abstract
This paper presents the analysis of data collected using the MTConnect protocol from a lathe with a Computer Numerical Control (CNC). The purpose of the analysis is to determine an estimated cutting tool life and generate a model for calculating a real-time proxy of cutting tool wear. Various streams were used like spindle load, NC program blocks, the mode, execution etc. The novelty of this approach is that no information about the machining process, beyond the data provided by the machine, was necessary to determine the tool’s expected life. This method relies on the facts that a) it is generally accepted cutting loads increase with tool wear and b) that many CNC machines rely on a small set of regularly run CNC programs. These facts are leveraged to extract the total load for each run of each program on the machine, creating a dataset which is a good indicator of tool wear and replacement. The presented methodology has four key steps: extracting cycle metadata from the machine execution data; computing the integrated spindle loads for every cycle; normalizing the integrated spindle loads between different programs; extracting tool wear rates and changes from the resulting dataset. It is shown that the method can successfully extract the signature of tool wear under a common set of circumstances which are discussed in detail.