bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acoustically transparent polybutadiene-based polyurethane encapsulants for deep-sea and transducers
Authors: Li J J , Gao Y , Gu X H , Yang C H , Li J 
Published: January 2024

Abstract
Copolyether polyurethane (PUR), as a typical encapsulation material, is widely used for underwater acoustic transducers. Two novel types of polybutadiene-based PURs were prepared using a one-step method and compared with copolyether PURs. The polybutadiene-based PUR exhibited excellent mechanical properties. Epoxidized hydroxyl-terminated polybutadiene (EHTPB)–based PUR exhibited tensile strength and hardness of up to 17.3 MPa and Shore A95, respectively, which were 76.5% and 13.3% higher than those of copolyether PURs. The molecular chain of hydroxyl-terminated polybutadiene (HTPB)-based PUR exhibited good flexibility, a soft segment glass transition temperature (Tg) (approximately -52 °C), and complete microphase separation. Compared with HTPB-based PUR, EHTPB-based PUR exhibited a higher molecular chain rigidity and a lower degree of microphase separation. The insertion losses of HTPB-based PUR at 350 and 700 kHz were 69.8 dB/m and 204.6 dB/m, respectively, which were 57.4% and 47.1% lower than those of copolymer PUR. The water absorption and water vapor transmission coefficient of HTPB-based PUR were an order of magnitude lower than those of copolymer PUR. EHTPB-based and copolymer PURs exhibited similar insertion losses at 350 kHz. EHTPB-based PUR exhibited the lowest water vapor transmission coefficient of 7.2 × 10−14 g·cm/cm2·s·Pa, which was approximately 1/15th of that of copolyether PUR.
Fabrication process and variation rule of electrical properties of CrSi thin film resistors
Authors: Zhu Jiajia , Zhang Zhili , Gu Lihui , He Nailong , Song Hua , Zhang Sen 
Published: January 2024

Abstract
CrSi film is sputtered on SiO2 by reactive magnetron sputtering method, on which TIW layer is deposited as the resistance end. After lithographic patterns and corrosion, metal layer is deposited and etched as input and output to test the electrical parameters of the film. It is discovered that the target’s component determines the electrical parameters’ adjustable range. It is possible to stabilize the temperature coefficient of resistance of CrSi film in ±10ppm/oC by adjusting the process parameters, resulting in reduction of fluctuations compared with the widely used ±20ppm/oC, and obtainment of high-precision CrSi film resistors. In addition, microscopic factors such as grain size and spacing must be considered. CrSi grains, which transmit electrons, and the SiN groups, which are dispersed along the grain spacing and permit electron tunnelling, dictate the electrical characteristics of the film. The law of process adjustment parameters is clarified through the comparison of different component targets, which has important reference value and guiding significance for the future research of similar targets or high-precision resistors.
Scale inhibition and dispersion performance of epoxy succinic acid copolymer containing sulfonic acid groups
Authors: Yan M F , Liu Z , Li N , Zheng Y X , Li H H , Gao Y H , Liu Z F 
Published: January 2024

Abstract
To improve the dispersion performance of Polyepoxysuccinic acid (PESA), sulfonic acid groups were introduced into the PESA structure, resulting in the synthesis of a phosphorus- and nitrogen-free ternary polymer. The scale inhibition and dispersion performance of the ternary polymer were compared with those of PESA using static experiments, and its dynamic performance was studied. The results showed that the ternary copolymer had outstanding scale inhibition and dispersion properties. At a dosage of 20 mg/L, the scale inhibition rate on calcium carbonate was 100%, while the scale inhibition rate was 100% on calcium sulfate at a dosage of 10 mg/L. The scale inhibition rate on calcium phosphate was 95% at a dosage of 100 mg/L. At 50 mg/L, the transmittance was only 31.9%. Therefore, the copolymer demonstrated good dynamic scale inhibition performance and could inhibit scale precipitation on the surface of the heat exchanger.
Community-scale changes to landfast ice along the coast of Alaska over 2000-2022
Authors: Cooley Sarah W , Ryan Jonathan C 
Published: January 2024

Abstract
Landfast sea ice that forms along the Arctic coastline is of great importance to coastal Alaskan communities. It provides a stable platform for transportation and traditional activities, protects the coastline from erosion, and serves as a critical habitat for marine mammals. Here we present a full assessment of landfast ice conditions across a continuous 7885 km length of the Alaska coastline over 2000–2022 using satellite imagery. We find that the maximum landfast ice extent, usually occurring in March, averaged 67 002 km2 during our study period: equivalent to 4% of the state’s land area. The maximum extent of landfast ice, however, exhibits considerable interannual variability, from a minimum of 29 871 km2 in 2019 to a maximum of 87 571 km2 in 2010. Likewise, the landfast ice edge position averages 22.9 km from the coastline but, at the community-scale, can range from 2.8 km (in Gambell) to 71.1 km (in Deering). Landfast ice breakup date averages 2 June but also varies considerably both between communities (3 May in Quinhagak to 24 July in Nuiqsut) and interannually. We identify a strong control of air temperature on breakup timing and use this relationship to project future losses of ice associated with Paris Climate Agreement targets. Under 2 °C of global air temperature warming, we estimate the average Alaskan coastal community will lose 19 days of ice, with the northernmost communities projected to lose 50 days or more. Overall, our results emphasize the highly localized nature of landfast ice processes and the vulnerability of coastal Arctic communities in a warming climate.
Recognition of grinding surface roughness grade based on adversarial domain adaptation under variable illumination
Authors: Yi Huaian , Huang Jiefeng , Shu Aihua , Song Kun 
Published: January 2024

Abstract
End-to-end roughness measurement can be achieved through the self-extraction of grinding surface features, which can be achieved through deep learning. However, due to the grinding surface texture being random, the features are weak, the self-extracted grinding surface features of the same surface under different lighting environments are different, and the training data and the test data when the lighting environments are inconsistent with the recognition of the measurement of the precision of the lower. To tackle these problems, this paper proposes an adversarial domain self-adaptation (NMDANN) based visual measurement method for grinding surface roughness under variable illumination. An improved residual network is used as a generator to extract more effective metastable features, and multi-head attention is introduced into the domain discriminator to enhance its domain adaptive capability. The experimental results show that the method can achieve an average recognition precision of 96.9112% for different grades of roughness on the grinding surface under the changing light environment, which is 40.1360% higher than the ordinary classification model ResNet50 and 10.1626% higher than the DANN model with migration capability. It lays the foundation for the online visual measurement of roughness on the grinding surface under the variable light environment. This lays the foundation for the online visualization of grinding surface roughness measurement in variable light environments.
Scanning tunneling microscopy study of epitaxial Fe3GeTe2 monolayers on Bi2Te3
Authors: Goff Brad M , Zhou Wenyi , Bishop Alexander J , Bailey-Crandell Ryan , Robinson Katherine , Kawakami Roland K , Gupta Jay A 
Published: January 2024

Abstract
Introducing magnetism to the surface state of topological insulators, such as Bi2Te3, can lead to a variety of interesting phenomena. We use scanning tunneling microscopy (STM) to study a single quintuple layer (QL) of the van der Waals magnet Fe3GeTe2 (FGT) that is grown on Bi2Te3 via molecular beam epitaxy. STM topographic images show that the FGT grows as free-standing islands on Bi2Te3 and outwards from Bi2Te3 steps. Atomic resolution imaging shows triangular lattices of 390 ± 10 pm for FGT and 430 ± 10 pm for Bi2Te3, consistent with the respective bulk crystals. A moiré pattern is observed on FGT regions with a periodicity of 4.3 ± 0.4 nm that can be attributed solely to this lattice mismatch and thus indicates zero rotational misalignment. While most of the surface is covered by a single QL of the FGT, there are small double QL regions, as well as regions with distinct chemical terminations due to an incomplete QL. The most common partial QL surface termination is the FeGe layer, in which the top two atomic layers are missing. This termination has a distinctive electronic structure and a

3

x

3

R

30
∘

reconstruction overlaid on the moiré pattern in STM images. Magnetic circular dichroism measurements confirm these thin FGT films are ferromagnetic with T
C ∼190 K.
Five near-infrared-emissive graphene quantum dots for multiplex bioimaging
Authors: Valimukhametova Alina R , Fannon Olivia , Topkiran Ugur C , Dorsky Abby , Sottile Olivia , Gonzalez-Rodriguez Roberto , Coffer Jeffery , Naumov Anton V 
Published: January 2024

Abstract
Due to high tissue penetration depth and low autofluorescence backgrounds, near-infrared (NIR) fluorescence imaging has recently become an advantageous diagnostic technique used in a variety of fields. However, most of the NIR fluorophores do not have therapeutic delivery capabilities, exhibit low photostabilities, and raise toxicity concerns. To address these issues, we developed and tested five types of biocompatible graphene quantum dots (GQDs) exhibiting spectrally-separated fluorescence in the NIR range of 928–1053 nm with NIR excitation. Their optical properties in the NIR are attributed to either rare-earth metal dopants (Ho-NGQDs, Yb-NGQDs, Nd-NGQDs) or defect-states (nitrogen doped GQDS (NGQDs), reduced graphene oxides) as verified by Hartree-Fock calculations. Moderate up to 1.34% quantum yields of these GQDs are well-compensated by their remarkable >4 h photostability. At the biocompatible concentrations of up to 0.5–2 mg ml−1 GQDs successfully internalize into HEK-293 cells and enable in vitro imaging in the visible and NIR. Tested all together in HEK-293 cells five GQD types enable simultaneous multiplex imaging in the NIR-I and NIR-II shown for the first time in this work for GQD platforms. Substantial photostability, spectrally-separated NIR emission, and high biocompatibility of five GQD types developed here suggest their promising potential in multianalyte testing and multiwavelength bioimaging of combination therapies.
Inkjet-printed transistors with coffee ring aligned carbon nanotubes
Authors: Naderi Paria , Grau Gerd 
Published: January 2024

Abstract
Low-concentration deposition techniques such as inkjet printing for forming carbon nanotube (CNT) transistor channels typically result in higher on–off current ratio, while lowering the field-effect mobility compared to traditional high-concentration techniques. In this paper, we show that inkjet-printed devices can have both high field-effect mobility and on–off current ratio by utilizing coffee ring induced thickness variation in the channel. The coffee ring effect occurs naturally in printed patterns with most solvents and substrates, and it pushes dissolved particles to the edges of printed features. Thickness variation and coffee ring effect are usually avoided in the channel of solution processed thin-film transistors by implementing additional expensive steps in the fabrication process. Instead, here, we control these variations and utilize them to create inkjet-printed CNT channels with printing induced thickness variation that improves transistor properties. Printing properties such as printing speed, and number of layers are studied to manipulate capillary flow and form thicker line edges, which ultimately enhance current transport in the CNT network. A two-pass printing pattern with separate lines improves the field-effect mobility five times compared to a pattern with connected lines that has no defined edges. The field-effect mobility increases from 1.1 to 5.7 cm2 V−1 s−1 at a drain voltage of −2 V.
Grain size and heavy metal assessment in barchan dunes surrounding the Talatan PV power generation area, Qinghai Province
Authors: Wang Lijie , Chen Hao , Xiao Fengjun , Shao Tianjie , Chang Ju , Ma Huirong 
Published: January 2024

Abstract
Heavy metal contamination in sediments near photovoltaic (PV) power generation areas poses potential environmental risks, requiring detailed characterization and source apportionment to facilitate sustainable management. This research explores the characteristics of sediment grains and the concentrations of heavy metals present in surface sediments from barchan dunes proximal to the Talatan Photovoltaic (PV) power generation area, located within Gonghe County, Qinghai Province. The sediments displayed an average grain size within the medium sand range, with marginal differences discernible between the windward and leeward slopes. With the exception of Mn, Cu, Zn, V, Pb, and Ba, concentrations of the remaining metals were found to surpass the baseline levels established by Chinese aeolian soil data, alluding to potential anthropogenic influences. Through employing coefficients of variation in multivariate statistical analysis, it was identified that the concentrations of Cr and Co were significantly elevated, suggesting potential anthropogenic contamination, which may be associated with photovoltaic industrial activities. Specifically, the elevated concentrations of Cr and Co suggested anthropogenic contamination, potentially associated with photovoltaic industrial activities. Utilizing a combination of Correlation Coefficient Analysis, Principal Component Analysis, and Cluster Analysis, three potential sources of heavy metals were identified: (1) industrial origin for elements such as Cu, Cr, Ni, Zn, and As; (2) elements with limited direct application in the photovoltaic industry but associated with materials and energy storage, namely Ba, V, and Mn; (3) anthropogenic inputs related to construction materials and battery storage systems in the photovoltaic park, specifically Co and Pb. The findings offer a significant understanding of the heavy metal characteristics and sources in proximity to the Talatan PV power generation area, emphasizing the impact of human activities on environmental quality. These insights underscore the necessity for enhanced monitoring and management of industrial activities to mitigate potential environmental impacts. Further research is recommended on a broader spatial scale to yield a more comprehensive understanding of this subject.
Sustainability analysis of primary wastewater treatment by willow plantations in Québec
Authors: Fagoaga Noel , Sas Eszter , Jerbi Ahmed , Brereton Nicholas J B , Laplante Robert , Labrecque Michel , Pitre Frederic E 
Published: January 2024

Abstract
Wastewater treatment is a necessary step to avoid environmental impacts of water consumption and usage. Traditional approaches are expensive and are limited to developed countries. Phytofiltration using fast-growing trees and shrubs like willows potentially offer an alternative. This paper aims to determine if wastewater treatment using phytofiltration can provide complementary environmental and economic benefits for rural communities in a Nordic climate such as the province of Québec, Canada. It looks at different perspectives of the wastewater treatment solution in a local and rural context. Based on life cycle analysis (LCA) and life cycle cost analysis (LCC), we found that, for an exemplar Québec municipality, the conventional wastewater treatment scenario impacted more on climate change, ecosystem quality and human health than the two phytofiltration of wastewater scenarios studied, where impact is highly dependant on the biomass valorization. The net present cost of the phytofiltration scenarios were lower than typical conventional treatment in Québec. For a biomass producer, conventional biomass production had the highest environmental impact on ecosystem quality, while biomass production from phytofiltration had the highest environmental impact on climate change, human health, and resources. We demonstrate that the phytofiltration is a viable and multifunctional technology that could provide good incentives for a local biomass value chain. it allows to both alleviate wastewater treatment burden and provide affordable biomass for bioenergy development for rural communities. Mobilizing local stakeholders will be key to make phytofiltration an alternative solution for both environmental burden alleviation and rural economic development.
Sustainable additive manufacturing of polysulfone membranes for liquid separations
Authors: Leonard Brian , Loh Harrison , Lu David , Ogbuoji Ebuka A , Escobar Isabel C , Sierros Konstantinos , Sanyal Oishi 
Published: January 2024

Abstract
Membranes serve as important components for modern manufacturing and purification processes but are conventionally associated with excessive solvent usage. Here, for the first time, a procedure for fabricating large area polysulfone membranes is demonstrated via the combination of direct ink writing (DIW) with non-solvent induced phase inversion (NIPS). The superior control and precision of this process allows for complete utilization of the polymer dope solution during membrane fabrication, thus enabling a significant reduction in material usage. Compared to doctor blade fabrication, a 63% reduction in dope solution volume was achieved using the DIW technique for fabricating similarly sized membranes. Cross flow filtration analysis revealed that, independent of the manufacturing method (DIW vs. doctor blade), the membranes exhibited near identical separation properties. The separation properties were assessed in terms of bovine serum albumin (BSA) rejection and permeances (pressure normalized flux) of pure water and BSA solution. This new manufacturing strategy allows for the reduction of material and solvent usage while providing a large toolkit of tunable parameters which can aid in advancing membrane technology.
Epidemic modelling requires knowledge of the social network
Authors: Johnson Samuel 
Published: January 2024

Abstract
‘Compartmental models’ of epidemics are widely used to forecast the effects of communicable diseases such as COVID-19 and to guide policy. Although it has long been known that such processes take place on social networks, the assumption of ‘random mixing’ is usually made, which ignores network structure. However, ‘super-spreading events’ have been found to be power-law distributed, suggesting that the underlying networks may be scale free or at least highly heterogeneous. The random-mixing assumption would then produce an overestimation of the herd-immunity threshold for given R
0; and a (more significant) overestimation of R
0 itself. These two errors compound each other, and can lead to forecasts greatly overestimating the number of infections. Moreover, if networks are heterogeneous and change in time, multiple waves of infection can occur, which are not predicted by random mixing. A simple SIR model simulated on both Erdős–Rényi and scale-free networks shows that details of the network structure can be more important than the intrinsic transmissibility of a disease. It is therefore crucial to incorporate network information into standard models of epidemics.
On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments
Authors: Alves Caroline L , Ciba Manuel , de O. Toutain Thaise G L , Augusto Moura Porto Joel , Pondé de Sena Eduardo , Thielemann Christiane , Rodrigues Francisco A 
Published: January 2024

Abstract
There is a growing interest in the medical use of psychedelic substances, as preliminary studies using them for psychiatric disorders have shown positive results. In particular, one of these substances is N, N-dimethyltryptamine (DMT), an agonist serotonergic psychedelic that can induce profound alterations in the state of consciousness. In this work, we use an exploratory tool to reveal DMT-induced changes in brain activity using EEG data and provide new insights into the mechanisms of action of this psychedelic substance. We used a two-class classification based on (A) the connectivity matrix or (B) complex network measures derived from it as input to a support vector machine (SVM). We found that both approaches could detect changes in the brain’s automatic activity, with case (B) showing the highest AUC (89%), indicating that complex network measurements best capture the brain changes that occur due to DMT use. In the second step, we ranked the features that contributed the most to this result. For case (A), we found that differences in the high alpha, low beta, and delta frequency bands were most important in distinguishing between the state before and after DMT inhalation, which is consistent with the results described in the literature. Further, the connection between the temporal (TP8) and central cortex (C3) and between the precentral gyrus (FC5) and the lateral occipital cortex (P8) contributed most to the classification result. The connection between regions TP8 and C3 has been found in the literature associated with finger movements that might have occurred during DMT consumption. However, the connection between cortical areas FC5 and P8 has not been found in the literature and is presumably related to the volunteers’ emotional, visual, sensory, perceptual, and mystical experiences during DMT consumption. For case (B), closeness centrality was the most crucial complex network measure. Furthermore, we discovered larger communities and longer average path lengths when DMT was used and the converse when not, showing that the balance between functional segregation and integration had been disrupted. These findings support the idea that cortical brain activity becomes more entropic under psychedelics. Overall, a robust computational workflow has been developed here with interpretability of how DMT (or other psychedelics) modify brain networks and insights into their mechanism of action. Finally, the same methodology applied here may help interpret EEG time series from patients who consumed other psychedelic drugs.