bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced multi-step brazing for fabrication of a divertor heat removal component
Authors: Tokitani M. , Hamaji Y. , Hiraoka Y. , Masuzaki S. , Tamura H. , Noto H. , Tanaka T. , Tsuneyoshi T. , Tsuji Y. , Muroga T. , Sagara A. , Design Group the FFHR 
Published: January 2021

Abstract
The advanced fabrication method named advanced multi-step brazing (AMSB) has been developed for fabrication of a tungsten (W)/copper alloy divertor heat removal component in a fusion reactor. The principle of AMSB is repetitive application of the advanced brazing technique (ABT). The ABT was originally developed in our previous work for jointing of W and oxide dispersion strengthened copper alloy (ODS-Cu: GlidCop®) with the BNi-6 (Ni-11%P) filler material. The special feature of the AMSB is that the leak-tight joint of GlidCop® (GlidCop®/GlidCop®) and of stainless steel (SUS) and GlidCop® (SUS/GlidCop®) can be realized by application of the ABT. Therefore, the AMSB enables production of a leak-tight sealing structure with the appropriate lid material such as GlidCop® or SUS for a pre-processed rectangle-shaped cooling flow path channel. The rectangle-shaped cooling flow path channel has an advantage regarding its heat removal capability. Another special feature of the AMSB is that the physical properties of the AMSB joint has strong tolerance against the repetitive brazing heat cycle. Thus, repetitive application of the ABT does not cause any undesired effects on the leak tightness of the GlidCop®/GlidCop® and the SUS/GlidCop®. The new AMSB type component with the rectangle-shaped fluid flow path and the V-shaped staggered rib structure were successfully produced; therein a pre-processed rectangle-shaped cooling flow path channel was sealed with a GlidCop® and SUS lid structure with leak-tight conditions. The component showed excellent heat removal capability under reactor-relevant conditions with ∼30 MW m−2.
A machine-learning approach to human footprint index estimation with applications to sustainable development
Authors: Keys Patrick W , Barnes Elizabeth A , Carter Neil H 
Published: January 2021

Abstract
The human footprint index (HFI) is an extensively used tool for interpreting the accelerating pressure of humanity on Earth. Up to now, the process of creating the HFI has required significant data and modeling, and updated versions of the index often lag the present day by many years. Here we introduce a near-present, global-scale machine learning-based HFI (ml-HFI) which is capable of routine update using satellite imagery alone. We present the most up-to-date map of the HFI, and document changes in human pressure during the past 20 years (2000–2019). Moreover, we demonstrate its utility as a monitoring tool for the United Nations Sustainable Development Goal 15 (SDG15), ‘Life on Land’, which aims to foster sustainable development while conserving biodiversity. We identify 43 countries that are making progress toward SDG15 while also experiencing increases in their ml-HFI. We examine a subset of these in the context of conservation policies that may or may not enable continued progress toward SDG15. This has immediate policy relevance, since the majority of countries globally are not on track to achieve Goal 15 by the declared deadline of 2030. Moving forward, the ml-HFI may be used for ongoing monitoring and evaluation support toward the twin goals of fostering a thriving society and global Earth system.
Assessment on the impact of FSP process parameters on microstructural, mechanical and wear behaviour of FSPed AA6082
Authors: M Sivanesh Prabhu , Elayaperumal A , Arulvel S , Wasim Khan M 
Published: January 2021

Abstract
The present research work demonstrates the effect of friction stir process (FSP) and its process parameters (rotation speed and travel speed) on the microstructure evaluation, microhardness and wear behaviour of FSPed AA6082. The microstructure characterization of the processed samples was examined using the Optical Microscope (OM). Dry sliding wear test was carried out by varying the sliding velocity (0.5, 0.75 and 1.0 m s−1) and applied load (5, 10 and 15N) using the pin on disc apparatus. Wear mechanisms experienced by the FSPed AA6082 were mapped, and the optimal FSP and wear parameters have been determined using Taguchi analysis. The results showed that there is a significant improvement in the microhardness (92 HV

0.3) and wear resistance for RS 1250 rpm & TS 40 mm min−1 due to the grain strengthening mechanism and microstructure modification. Formation of oxide layer played a crucial role on the wear resistance of the FSPed AA6082 and its significance has been discussed elaborately using the Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS).
Effect of centrifugal casting temperature on the microstructure and properties of ZTAP/HCCI matrix composites
Authors: Niu Ge , Sui Yudong , Zeng Hongbin , He Han , Jiang Yehua , Zhou Mojin 
Published: January 2021

Abstract
In the centrifugal casting process, the casting temperature parameters affected the microstructure characteristics, and the performance of the materials was greatly significant. ZTA (ZrO2 reinforced Al2O3) particles reinforced HCCI (High chromium cast iron) matrix composites with honeycomb structure were obtained by centrifugal casting. With the increased casting temperature (1450 °C, 1500 °C, 1550 °C, and 1600 °C), the austenite equivalent diameter size was 43.5 μm, 34.8 μm, 33.1 μm, 22.3 μm respective in the compound area and 58.3 μm, 63.1 μm, 65.2 μm, 71.5 μm respective in substrate area. The average size of eutectic carbides in the compound area decreased from 5.7 μm to 2.5 μm with the casting temperature increased. Meanwhile, the lattice constants of austenite and carbide increased with the increased temperature. The hardness of the composites increased by 4 ∼ 6HRC with a change in casting temperature. The results of three-body abrasive wear under high-stress static load conditions showed that the wear volume loss of the composites reduced with the temperature increased and the wear resistance was 1.4 times at 1600 °C than that at 1450 °C.
High ionic conductivity of Lu2O3–TiO2 co-doped Bi2O3 ceramics
Authors: Luo Zeyang , Wang Huan , Ma Yuxin , Zhang Guodong , Yan Duanting , Bai Xinyu , Wang Dejun , Liu Runru 
Published: January 2021

Abstract
In this study, a promising electrolyte material Bi0.76Lu0.16Ti0.08O1.5+δ
(abbreviated as ‘8T16LSB’) with high oxygen ion conductivity was obtained by co-doping with Lu2O3 and TiO2 into Bi2O3. The phase composition, microstructure, and conductivity of TLSB ceramics were respectively investigated by x-ray diffraction, scanning electron microscopy (SEM), and electrochemical impedance spectroscopy (EIS). XRD results exhibited that the sintered TLSB ceramics with an unchanged total doping concentration of 24 mol.% existed as a cubic fluorite structure. SEM results showed that the TLSB pellets were relatively dense. The relationship between temperature and conductivity showed that the 8T16LSB ceramic exhibited the highest conductivity of 0.56 S cm−1 at 700 °C, which was higher than the value of 0.37 S cm−1 for the representative single-doping Er0.4Bi1.6O3 (abbreviated as ‘20ESB’). The results certified that the electrochemical performance of Bi2O3 was promoted by the co-dopant of Lu3+and Ti4+.
Influence of drying methods on the physical properties of bacterial nanocellulose
Authors: Andree Verena , Niopek Daniel , Müller Christine , Eiselt Jan-Philipp , Foh Nina , Rzany Alexander , Hensel Bernhard 
Published: January 2021

Abstract
Bacterial nanocellulose (BNC) is a promising material for the use in medical implants. BNC does not induce unwanted reactions in vivo, is long term stable and possesses unique mechanical properties. However, to make the most of these features, BNC must be carefully processed. Details of the cultivation and post-synthetic methods offer various ways to control the properties of BNC. The focus of this work is put on drying of the BNC. Different unconstrained drying methods (climate chamber at 23°C, oven at 100°C, freeze-drying) and constrained drying under excertion of uniaxial pressure at various temperatures have been investigated. The reduction of the high water content of native BNC (≈98%) causes a thickness reduction of the samples. For oven or climate chamber drying a thickness reduction of 98% is observed, while freeze-drying widely preserves the nano- or micro-structure of the fibrous material and leads to a thickness reduction of only ≈13%. During drying or pressing at high temperature (100°C), i.e. by evaporation of the water, intermolecular hydrogen bonds are formed and interconnect the individual fibres and strands. Consequently mechanical stiffening is observed in tensile tests at small strains. After drying, a densified cellulose nano-fibre network is observed by scanning electron microscopy. Due to the irreversibility of drying by evaporation, the water content and water retention capacity of BNC are not recovered by rehydration. Applying uniaxial pressure before drying further enhances the irreversible reinforcement of the fibre network, while this is not the case when pressing the samples after drying. The presented results show that the properties of BNC can be widely controlled by post-processing steps. Thus, taylor-made BNC can be produced for biomedical applications.
The white light caused by defects and complex cation distribution in ZnAl2-xFexO4 magnetic nanocrystals
Authors: Zhang Dong , Zhu Bingjun , Ren Shiqi , Wang Qingru , Wang Qinglin , Li Shuhong , Zhang Bingyuan , Wang Wenjun 
Published: January 2021

Abstract
ZnAl2O4 with spinel structure has attracted more attentions due to its robust dielectric and luminescence properties. Complex cation distribution in spinel structure influences the optical and magnetic properties. Herein, we report white emission related to the defects and the magnetism assigned to Fe impurity in ZnAl2-xFexO4 (

0
≤
x
≤
0.6

) nanocrystals fabricated by using common sol-gel method at a relatively lower temperature (700 °C) than that reported earlier. ZnAl2-xFexO4 phosphors reveal single spinel phase without impure phase. Complex cation distribution is observed in all samples, for instance, Fe and Zn in antisites, cation vacancies, and with Fe content increasing, cation distribution reveals obvious change. The band gap energy of ZnAl2-xFexO4 phosphors is reduced from 3.84 eV to 3.33 eV when the content of Fe ions (x value) increases from 0 to 0.6. Two wide band emissions assigned to the various types of shallow and deep donor/acceptor defects are observed, monitoring with the excitation wavelength of 280 nm. The Commission International de I’Eclairage (CIE) colour coordinate (x, y) of the ZnAl2-xFexO4 phosphors is found to shift from (0.3218, 0.2957) to (0.3422, 0.3122) with Fe doping in spinel lattices owing to rearrangement of defects, indicating the potential application in white-light illumination. ZnAl2-xFexO4 reveals a room ferromagnetism resulting from Fe3 + ions in spinel lattices.
Characterization of carbonate apatite derived from chicken bone and its in-vitro evaluation using MC3T3-E1 cells
Authors: Xuan Thanh Tram Nguyen , Ishikawa Kunio , Minh Tran Hoang , Benson David , Tsuru Kanji 
Published: January 2021

Abstract
Chicken bone by-product has the potential to be utilized as a source of carbonate apatite (CO3Ap) for the preparation of bone grafts. In this study, the raw bones were cleaned with NaCl and then immersed in NaOH solution at 80 °C. After chemical treatment, the as-prepared powder was calcined in a range of 300 °C–900 °C. The results showed that calcination was useful for the complete elimination of organic residues; but, it led to increasing of crystal size, coarsening of particles, and the loss of the carbonate groups in the apatite structure. In vitro evaluation showed that CO3Ap prepared at the optimum temperature, 500 °C, exhibited a great biological response; such as good cell attachment, cell viability, and cell morphology. This research suggests a promising biomaterial for the fabrication of bone substitutes and could offer a solution for recycling and adding value to food waste.
Effect of matrix hardness on the impact abrasive wear performance of ZTAp/steel architecture composite
Authors: Ma Wei , Lu Dehong , Tang Lu , Gong Wenhao , Yan Qinghua 
Published: January 2021

Abstract
The effect of the hardness of a steel matrix by heat treatment on the impact abrasive wear of ZTAp/40Cr steel architecture composites is investigated. Of these composites, the ZTA particles-reinforced 40Cr steel matrix composite and pure 40Cr steel formed a 3D network interpenetrating structure. The results show that the architecture composites with the martensite matrix demonstrate the best wear resistance, which is 32.76% higher than that with the troostite matrix and 163.60% higher than that with the pearlite matrix. Under the same Under the same quenching + 460 °C tempering conditions, the wear resistance of the architecture composites is 79.0% higher than that of the homogeneous composites. The wear mechanism analysis shows that the wear performance of composites depends on the interaction between the matrix and the reinforced particles. As the hardness of the composites matrix increases, the reinforcement particles are more strongly supported by the matrix. Conversely, the matrix is preferentially worn, and the ZTA particles are shed due to the lack of protection. The main wear mechanisms include micro-cutting, plastic fatigue wear, and particle crushing and spalling.
Bacterial cellulose growth on 3D acrylate-based microstructures fabricated by two-photon polymerization
Authors: Otuka Adriano J G , Domeneguetti Rafael R , Moraes Jonathas Q R , Balogh Debora T , Ribeiro Sidney J L , Mendonça Cleber R 
Published: January 2021

Abstract
Miniaturized environments have emerged as an excellent alternative to evaluate and understand biological mechanisms. These systems are able to simulate macroenvironments with high reproducibility, achieving many results in a short time of analysis. However, microenvironments require specific architectures that can be reached using laser micromachining techniques, such as two-photon polymerization (TPP). This technique has many advantages, allowing the production of environments without shape limitation and with special features. In this work, aided by the TPP technique, we produce different arrays of microstructures, fabricated using acrylate-based materials, in order to evaluate the growth and development of the Komagataeibacter xylinus bacteria, the micro-organism responsible for producing bacterial cellulose (BC), a natural polymer with several biological applications. BC grown in microenvironments presents similar features to those of biofilm formed in macroenvironments, maintaining their attractive properties. In addition, due to the high optical quality and mechanical resistance of the BC matrices, we use these films as flexible substrates in TPP experiments, obtaining promising results for tissue engineering studies.
A Pilot Study Evaluation of 3-Dimensional Imaging in Cosmetic Breast Augmentation: Results of a Single Surgeon 3.5-Year Retrospective Study Using the BREAST-Q Questionnaire
Authors: Hutchinson Lauren E , Castaldo Andrea D , Malone Cedar H , Sommer Nicole Z , Amalfi Ashley N 
Published: January 2021

Abstract

Background
Traditional methods of breast implant size selection provide limited ability to demonstrate postoperative outcomes. Three-dimensional (3D) imaging provides an opportunity for improved patient evaluation, surgical planning, and evaluation of postoperative breast appearance.

Objectives
The authors hypothesized that preoperative 3D imaging for patients undergoing breast augmentation would improve patient satisfaction and understanding of expected surgical outcomes.

Methods
A retrospective review of patients undergoing breast augmentation by a single surgeon over a 3.5-year period was performed. Patients presenting after the VECTRA was purchased had preoperative 3D imaging, while patients presenting before this did not. Eligible patients received a BREAST-Q questionnaire designed for postoperative evaluation of breast augmentation. They also received a second survey that evaluated expected vs actual breast outcomes.

Results
In total, 120 surveys were mailed and 61 patients (50.8%) returned the survey. The 3D imaged group had improved BREAST-Q scores regarding satisfaction with outcome, surgeon, and physical well-being compared with the group that did not. The imaged group also had higher size, shape, and overall breast correlation scores, confidence in implant size selection scores, and communication with surgeon scores. The differences between the 2 groups were not statistically significant.

Conclusions
Three-dimensional imaging is a valuable tool in breast surgery. Although this study showed improvement in patient satisfaction and predicted outcome scores in the 3D imaged group, the results were not statistically significant. With the majority of patients reporting that they would choose 3D imaging, it appears to instill confidence in patients regarding both surgeon and implant selection.

Level of Evidence: 4
Unsupervised and self-supervised deep learning approaches for biomedical text mining
Authors: Nadif Mohamed , Role François 
Published: January 2021

Abstract
Biomedical scientific literature is growing at a very rapid pace, which makes increasingly difficult for human experts to spot the most relevant results hidden in the papers. Automatized information extraction tools based on text mining techniques are therefore needed to assist them in this task. In the last few years, deep neural networks-based techniques have significantly contributed to advance the state-of-the-art in this research area. Although the contribution to this progress made by supervised methods is relatively well-known, this is less so for other kinds of learning, namely unsupervised and self-supervised learning. Unsupervised learning is a kind of learning that does not require the cost of creating labels, which is very useful in the exploratory stages of a biomedical study where agile techniques are needed to rapidly explore many paths. In particular, clustering techniques applied to biomedical text mining allow to gather large sets of documents into more manageable groups. Deep learning techniques have allowed to produce new clustering-friendly representations of the data. On the other hand, self-supervised learning is a kind of supervised learning where the labels do not have to be manually created by humans, but are automatically derived from relations found in the input texts. In combination with innovative network architectures (e.g. transformer-based architectures), self-supervised techniques have allowed to design increasingly effective vector-based word representations (word embeddings). We show in this survey how word representations obtained in this way have proven to successfully interact with common supervised modules (e.g. classification networks) to whose performance they greatly contribute.
Fur: Find unique genomic regions for diagnostic PCR
Authors: Haubold Bernhard , Klötzl Fabian , Hellberg Lars , Thompson Daniel , Cavalar Markus 
Published: January 2021

Abstract

Motivation
Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions.

Results
Fur takes as input a sample of target sequences and a sample of closely related neighbors. It returns the regions present in all targets and absent from all neighbors. The recently published program genmap can also be used for this purpose and we compared it to fur. When analyzing a sample of 33 genomes representing the major phylogroups of E.coli, fur was 40 times faster than genmap but used three times more memory. On the other hand, genmap yielded three times more markers, but they were less accurate when tested in silico on a sample of 237 E.coli genomes. We also designed phylogroup-specific PCR primers based on the markers proposed by genmap and fur, and tested them by analyzing their virtual amplicons in GenBank. Finally, we used fur to design primers specific to a Lactobacillus species, and found excellent sensitivity and specificity in vitro.

Availability and implementation
Fur sources and documentation are available from https://github.com/evolbioinf/fur. The compiled software is posted as a docker container at https://hub.docker.com/r/haubold/fox.

Supplementary information
Supplementary data are available at Bioinformatics online.
Epidemiological modeling in StochSS Live!
Authors: Jiang Richard , Jacob Bruno , Geiger Matthew , Matthew Sean , Rumsey Bryan , Singh Prashant , Wrede Fredrik , Yi Tau-Mu , Drawert Brian , Hellander Andreas , Petzold Linda 
Published: January 2021

Abstract

Summary
We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results.

Availability and implementation
StochSS Live! is freely available at https://live.stochss.org/

Supplementary information
Supplementary data are available at Bioinformatics online.
Can plastid genome sequencing be used for species identification in Lauraceae?
Authors: Liu Zhi-Fang , Ma Hui , Ci Xiu-Qin , Li Lang , Song Yu , Liu Bing , Li Hsi-Wen , Wang Shu-Li , Qu Xiao-Jian , Hu Jian-Lin , Zhang Xiao-Yan , Conran John G , Twyford Alex D , Yang Jun-Bo , Hollingsworth Peter M , Li Jie 
Published: January 2021

AbstractUsing DNA barcoding for species identification remains challenging for many plant groups. New sequencing approaches such as complete plastid genome sequencing may provide some increased power and practical benefits for species identification beyond standard plant DNA barcodes. We undertook a case study comparing standard DNA barcoding to plastid genome sequencing for species discrimination in the ecologically and economically important family Lauraceae, using 191 plastid genomes for 131 species from 25 genera, representing the largest plastome data set for Lauraceae to date. We found that the plastome sequences were useful in correcting some identification errors and for finding new and cryptic species. However, plastome data overall were only able to discriminate c. 60% of the species in our sample, with this representing a modest improvement from 40 to 50% discrimination success with the standard plant DNA barcodes. Beyond species discrimination, the plastid genome sequences revealed complex relationships in the family, with 12/25 genera being non-monophyletic and with extensive incongruence relative to nuclear ribosomal DNA. These results highlight that although useful for improving phylogenetic resolution in the family and providing some species-level insights, plastome sequences only partially improve species discrimination, and this reinforces the need for large-scale nuclear data to improve discrimination among closely related species.