bluuebunny/crossref_metadata_2025_split huggingface dataset:
Small RNA sequencing analysis of peptide-affinity isolated plasma extracellular vesicles distinguishes pancreatic cancer patients from non-affected individuals
Authors: Roy Jeremy W. , Wajnberg Gabriel , Ouellette Alexie , Boucher Julie Emilie , Lacroix Jacynthe , Chacko Simi , Ghosh Anirban , Ouellette Rodney J. , Lewis Stephen M. 
Published: June 2023

AbstractPancreatic ductal adenocarcinoma (PDAC) has a high fatality rate, mainly due to its asymptomatic nature until late-stage disease and therefore delayed diagnosis that leads to a lack of timely treatment intervention. Consequently, there is a significant need for better methods to screen populations that are at high risk of developing PDAC. Such advances would result in earlier diagnosis, more treatment options, and ultimately better outcomes for patients. Several recent studies have applied the concept of liquid biopsy, which is the sampling of a biofluid (such as blood plasma) for the presence of disease biomarkers, to develop screening approaches for PDAC; several of these studies have focused on analysis of extracellular vesicles (EVs) and their cargoes. While these studies have identified many potential biomarkers for PDAC that are present within EVs, their application to clinical practice is hindered by the lack of a robust, reproducible method for EV isolation and analysis that is amenable to a clinical setting. Our previous research has shown that the Vn96 synthetic peptide is indeed a robust and reproducible method for EV isolation that has the potential to be used in a clinical setting. We have therefore chosen to investigate the utility of the Vn96 synthetic peptide for this isolation of EVs from human plasma and the subsequent detection of small RNA biomarkers of PDAC by Next-generation sequencing (NGS) analysis. We find that analysis of small RNA from Vn96-isolated EVs permits the discrimination of PDAC patients from non-affected individuals. Moreover, analyses of all small RNA species, miRNAs, and lncRNA fragments are most effective at segregating PDAC patients from non-affected individuals. Several of the identified small RNA biomarkers have been previously associated with and/or characterized in PDAC, indicating the validity of our findings, whereas other identified small RNA biomarkers may have novel roles in PDAC or cancer in general. Overall, our results provide a basis for a clinically-amendable detection and/or screening strategy for PDAC using a liquid biopsy approach that relies on Vn96-mediated isolation of EVs from plasma.
Interplay between diffusion and magnon-drag thermopower in pure iron and dilute iron alloy nanowire networks
Authors: Marchal Nicolas , da Câmara Santa Clara Gomes Tristan , Abreu Araujo Flavio , Piraux Luc 
Published: June 2023

AbstractResults of measurements on the thermoelectric power of 45 nm diameter interconnected nanowire networks consisting of pure Fe, dilute FeCu and FeCr alloys and Fe/Cu multilayers are presented. The thermopower values of Fe nanowires are very close to those found in bulk materials, at all temperatures studied between 70 and 320 K. For pure Fe, the diffusion thermopower at room temperature, estimated to be around − 15 $$\upmu$$
μ
V/K from our data, is largely supplanted by the estimated positive magnon-drag contribution, close to 30 $$\upmu$$
μ
V/K. In dilute FeCu and FeCr alloys, the magnon-drag thermopower is found to decrease with increasing impurity concentration to about 10 $$\upmu$$
μ
V/K at 10$$\%$$
%
impurity content. While the diffusion thermopower is almost unchanged in FeCu nanowire networks compared to pure Fe, it is strongly reduced in FeCr nanowires due to pronounced changes in the density of states of the majority spin electrons. Measurements performed on Fe(7 nm)/Cu(10 nm) multilayer nanowires indicate a dominant contribution of charge carrier diffusion to the thermopower, as previously found in other magnetic multilayers, and a cancellation of the magnon-drag effect. The magneto-resistance and magneto-Seebeck effects measured on Fe/Cu multilayer nanowires allow the estimation of the spin-dependent Seebeck coefficient in Fe, which is about − 7.6 $$\upmu$$
μ
V/K at ambient temperature.
MHD Free convection flows of Jeffrey fluid with Prabhakar-like fractional model subject to generalized thermal transport
Authors: Siddique Imran , Adrees Rubina , Ahmad Hijaz , Askar Sameh 
Published: June 2023

AbstractThis article examines the effects of magnetohydrodynamics and heat absorption on an incompressible Jeffrey fluid’ time-dependent free convection flow over an infinite, vertically heated plate with homogeneous heat flux. The constitutive equation for heat flow utilizes the Prabhakar-like fractional derivative. The Laplace transform technique obtains the precise solution for the momentum and thermal profiles. The typical case and well-known outcomes from the literature are retrieved as restraining cases. The graphical analysis of the impact of the flow and fractionalized parameters on the thermal and momentum profiles is presented. Additionally, a comparison is made between the ordinary model and the Prabhakar-like fractional model, which shows that the latter better captures the retention of the physical features of the problem. It is concluded that the Prabhakar-like fractional model is better suited for describing the memory effect of the thermal and momentum fields.
Corroboration of the Toms effect from a frictional drag reducing self-polishing copolymer
Authors: Park Hyun , Cho Donghyun , Ha Jong-Woon , Hwang Do-Hoon , Park Ra Hui , Seo Hwawon , Lee Inwon 
Published: June 2023

AbstractA novel frictional drag reducing self-polishing copolymer (FDR-SPC) was first developed by the authors. The FDR-SPC is a special derivative of an SPC that was designed to achieve skin frictional drag reduction in turbulent water flow by releasing polyethylene glycol (PEG) into water through a hydrolysis reaction. Thus, the FDR-SPC coating acts as a continuous medium accommodating countless, molecular-level polymer injectors. However, direct evidence of such PEG release has not yet been demonstrated. Here, we report the results of in situ PEG concentration measurement based on the planar laser-induced fluorescence (PLIF) method. Polyethylene glycol methacrylate (PEGMA) was probed by the fluorescent functional material dansyl, and the fluorescence intensity from dansyl-PEG was then measured to quantify the concentration in the flow. The near-wall concentration of dansyl-PEG is observed to range from 1 to 2 ppm depending on the flow speed, which corroborates the existence of a drag reducing function for the FDR-SPC. In the concurrent measurement of skin friction, the present FDR-SPC specimen exhibited a skin friction reduction ratio of 9.49% at the freestream flow speed $$U=5m/s$$

U
=
5
m
/
s

. In the comparative experiment of dansyl-PEGMA solution injection, the skin friction was found to decrease by 11.9%, which is in reasonable accordance with that for the FDR-SPC.
Physiological activation of human and mouse bitter taste receptors by bile acids
Authors: Ziegler Florian , Steuer Alexandra , Di Pizio Antonella , Behrens Maik 
Published: June 2023

AbstractBeside the oral cavity, bitter taste receptors are expressed in several non-gustatory tissues. Whether extra-oral bitter taste receptors function as sensors for endogenous agonists is unknown. To address this question, we devised functional experiments combined with molecular modeling approaches to investigate human and mouse receptors using a variety of bile acids as candidate agonists. We show that five human and six mouse receptors are responsive to an array of bile acids. Moreover, their activation threshold concentrations match published data of bile acid concentrations in human body fluids, suggesting a putative physiological activation of non-gustatory bitter receptors. We conclude that these receptors could serve as sensors for endogenous bile acid levels. These results also indicate that bitter receptor evolution may not be driven solely by foodstuff or xenobiotic stimuli, but also depend on endogenous ligands. The determined bitter receptor activation profiles of bile acids now enable detailed physiological model studies.
Mesenchymal properties of iPSC-derived neural progenitors that generate undesired grafts after transplantation
Authors: Isoda Miho , Sanosaka Tsukasa , Tomooka Ryo , Mabuchi Yo , Shinozaki Munehisa , Andoh-Noda Tomoko , Banno Satoe , Mizota Noriko , Yamaguchi Ryo , Okano Hideyuki , Kohyama Jun 
Published: June 2023

AbstractAlthough neural stem/progenitor cells derived from human induced pluripotent stem cells (hiPSC-NS/PCs) are expected to be a cell source for cell-based therapy, tumorigenesis of hiPSC-NS/PCs is a potential problem for clinical applications. Therefore, to understand the mechanisms of tumorigenicity in NS/PCs, we clarified the cell populations of NS/PCs. We established single cell-derived NS/PC clones (scNS/PCs) from hiPSC-NS/PCs that generated undesired grafts. Additionally, we performed bioassays on scNS/PCs, which classified cell types within parental hiPSC-NS/PCs. Interestingly, we found unique subsets of scNS/PCs, which exhibited the transcriptome signature of mesenchymal lineages. Furthermore, these scNS/PCs expressed both neural (PSA-NCAM) and mesenchymal (CD73 and CD105) markers, and had an osteogenic differentiation capacity. Notably, eliminating CD73+ CD105+ cells from among parental hiPSC-NS/PCs ensured the quality of hiPSC-NS/PCs. Taken together, the existence of unexpected cell populations among NS/PCs may explain their tumorigenicity leading to potential safety issues of hiPSC-NS/PCs for future regenerative medicine.
Structure determination of a low-crystallinity covalent organic framework by three-dimensional electron diffraction
Authors: Zhou Guojun , Yang Taimin , Huang Zhehao 
Published: June 2023

AbstractCovalent organic frameworks (COFs) have been attracting intense research due to their permanent porosity, designable architecture, and high stability. However, COFs are challenging to crystallize and their synthesis often results in tiny crystal sizes and low crystallinities, which hinders an unambiguous structure determination. Herein, we demonstrate that the structure of low-crystallinity COF Py-1P nanocrystals can be solved by coupling three-dimensional electron diffraction (3DED) with simulated annealing (SA). The resulting model is comparable to that obtained from high-crystallinity samples by dual-space method. Moreover, for low-resolution 3DED data, the model obtained by SA shows a better framework than those provided by classic direct method, dual-space method, and charge flipping. We further simulate data with different resolutions to understand the reliability of SA under different crystal quality conditions. The successful determination of Py-1P structure by SA compared to other methods provides new knowledge for using 3DED to analyze low-crystallinity and nanosized materials.
Geology and land use shape nitrogen and sulfur cycling groundwater microbial communities in Pacific Island aquifers
Authors: Watson Sheree J , Arisdakessian Cédric , Petelo Maria , Keliipuleole Kekuʻiapōiula , Tachera Diamond K , Okuhata Brytne K , Dulai Henrietta , Frank Kiana L 
Published: June 2023

Abstract
Resource-constrained island populations have thrived in Hawai’i for over a millennium, but now face aggressive new challenges to fundamental resources, including the security and sustainability of water resources. Characterizing the microbial community in groundwater ecosystems is a powerful approach to infer changes from human impacts due to land management in hydrogeological complex aquifers. In this study, we investigate how geology and land management influence geochemistry, microbial diversity and metabolic functions. We sampled a total of 19 wells over 2-years across the Hualālai watershed of Kona, Hawai’i analyzing geochemistry, and microbial communities by 16S rRNA amplicon sequencing. Geochemical analysis revealed significantly higher sulfate along the northwest volcanic rift zone, and high nitrogen (N) correlated with high on-site sewage disposal systems (OSDS) density. A total of 12,973 Amplicon Sequence Variants (ASV) were identified in 220 samples, including 865 ASVs classified as putative N and sulfur (S) cyclers. The N and S cyclers were dominated by a putative S-oxidizer coupled to complete denitrification (Acinetobacter), significantly enriched up to 4-times comparatively amongst samples grouped by geochemistry. The significant presence of Acinetobacter infers the bioremediation potential of volcanic groundwater for microbial-driven coupled S-oxidation and denitrification providing an ecosystem service for island populations dependent upon groundwater aquifers.
Real-time prediction and adaptive adjustment of continuous casting based on deep learning
Authors: Lu Ziqing , Ren Neng , Xu Xiaowei , Li Jun , Panwisawas Chinnapat , Xia Mingxu , Dong Hongbiao , Tsang Eric , Li Jianguo 
Published: June 2023

AbstractDigitalisation of metallurgical manufacturing, especially technological continuous casting using numerical models of heat and mass transfer and subsequent solidification has been developed to achieve high manufacturing efficiency with minimum defects and hence low scrappage. It is still challenging to perform adaptive closed-loop process adjustment using high-fidelity computation in real-time. To address this challenge, surrogate models are a good option to replace the high-fidelity model, with acceptable accuracy and less computational time and cost. Based on deep learning technology, here we developed a real-time prediction (ReP) model to predict the three-dimensional (3D) temperature field distribution in continuous casting on millisecond timescale, with mean absolute error (MAE) of 4.19 K and mean absolute percent error (MAPE) of 0.49% on test data. Moreover, by combining the ReP model with machine learning technology—Bayesian optimisation, we realised the rapid decision-making intelligent adaptation of the operating parameters for continuous casting with high predictive capability. This innovative and reliable method has a great potential in the intelligent control of the metallurgical manufacturing process.
Two-dimensional metal–organic frameworks as bifunctional electrocatalysts for the oxygen evolution reaction and oxygen reduction reaction (OER/ORR): a theoretical study
Authors: Xu Feifei , Gao Zhixiao , Ge Zhencui , Ma Hao , Ren Hao , Zhu Houyu , Chi Yuhua , Guo Wenyue , Zhao Wen 
Published: June 2023

As bifunctional electrocatalysts for oxygen evolution and reduction reaction (OER/ORR), the two-dimensional MOFs M3(C6Se6)2 show good electrocatalytic performance.
Mixed‐decomposed convolutional network: A lightweight yet efficient convolutional neural network for ocular disease recognition
Authors: Zhang Xiaoqing , Wu Xiao , Xiao Zunjie , Hu Lingxi , Qiu Zhongxi , Sun Qingyang , Higashita Risa , Liu Jiang 
Published: June 2023

AbstractEye health has become a global health concern and attracted broad attention. Over the years, researchers have proposed many state‐of‐the‐art convolutional neural networks (CNNs) to assist ophthalmologists in diagnosing ocular diseases efficiently and precisely. However, most existing methods were dedicated to constructing sophisticated CNNs, inevitably ignoring the trade‐off between performance and model complexity. To alleviate this paradox, this paper proposes a lightweight yet efficient network architecture, mixed‐decomposed convolutional network (MDNet), to recognise ocular diseases. In MDNet, we introduce a novel mixed‐decomposed depthwise convolution method, which takes advantage of depthwise convolution and depthwise dilated convolution operations to capture low‐resolution and high‐resolution patterns by using fewer computations and fewer parameters. We conduct extensive experiments on the clinical anterior segment optical coherence tomography (AS‐OCT), LAG, University of California San Diego, and CIFAR‐100 datasets. The results show our MDNet achieves a better trade‐off between the performance and model complexity than efficient CNNs including MobileNets and MixNets. Specifically, our MDNet outperforms MobileNets by 2.5% of accuracy by using 22% fewer parameters and 30% fewer computations on the AS‐OCT dataset.
Merchant and regulated storage investment in energy and reserve markets: A Stackelberg game
Authors: Guo Peiyao , Hamacher Thomas , Perić Vedran S. 
Published: June 2023

AbstractWith large‐scale integration of renewable generation, energy storage is expected to play an important role in providing flexibility to energy systems. In this paper, the authors construct a trilevel Stackelberg game model to study the co‐investment of merchant and regulated storage in energy and reserve markets. The upper‐level problem is a profit‐maximizing storage investment problem with a desired rate‐of‐return solved by a merchant investor. In the middle‐level problem, the system operator (SO) makes regulated storage investment decisions to minimize system cost. In the lower‐level problem, the SO clears energy and reserve markets. The proposed model captures interactions of regulated and merchant storage investment. Also, it clarifies how different ownership structures of storage influence merchant storage profitability and system cost structures in different capital cost of storage investment and wind penetration level scenarios. The numerical results conducted on a 6‐bus illustrative example and the IEEE 24‐bus Reliability test case validate the proposed model. The results show that both regulated and merchant storage can increase social welfare, and social welfare remains almost the same under different ownership structures of storage.
Effectiveness of specularity removal from hyperspectral images in the colour spectral measurement of wool fibres
Authors: Qiu Kebin , Shen Jiajia , Chen Weiguo , Zhang Jiahui 
Published: June 2023

AbstractMicroscopic hyperspectral imaging technology is a potential non‐destructive and non‐contact method for colour measurement of micrometre‐sized textile fibres. However, specularity on the fibre surface can distort the accurate colour information and affect the accuracy of the colour measurement. This paper proposed a specular‐constrained sparse approximation (SCSA) for specular‐diffuse reflection separation from hyperspectral images of wool fibres. First, a specular prior map is generated based on the lightness dissimilarity. Then the SCSA model is used to decompose the processed hyperspectral image A into low‐rank data L, sparse specularity data S constrained by the specular prior map, sparse noise E, and Gaussian noise N. A non‐linear logistic sigmoid function and a sparse approximation of A – L – N to S are used to improve the performance of specularity removal during iterative optimization. The experimental results show that the proposed method significantly preserves diffuse reflectance and texture details in the specular highlight regions to obtain actual spectral reflectance and chromatic values from hyperspectral images of wool fibres.
A survey on edge and fog nodes' placement methods, techniques, parameters, and constraints
Authors: Al‐Asadi Samraa Adnan , Al‐Mamory Safaa O. 
Published: June 2023

AbstractWithin Edge and Fog computing, edge and fog nodes must be optimally located at the network edge to minimise the network's overall latency. This survey addresses all aspects of these nodes' placement problems. Literature on edge and fog nodes' placement is collected from reputable databases (IEEE Xplore digital library, Scopus, ScienceDirect, and Web of Science) using a search query. Manual search using keywords and the snowball method is also used to get as many related papers as possible. According to defined inclusion criteria, retrieved documents are filtered to 64 articles for eight years (2015–2022). Depending on the optimisation method used, literature is classified into six categories. The first relies on Integer programming, accounting for 20.3% (13/64). The second category depends on heuristic and metaheuristic methods, accounting for 20.3% (13/64). The third category depends on hybrid methods between the two aforementioned categories accounting for 18.7% (12/64). Forth category depends on clustering methods, accounting for 11% (7/64). The fifth category depends on reinforcement learning, accounting for 6.3% (4/64). And the final category depends on the hybrid methods between two or more methods mentioned above, accounting for 23.4% (15/64). Papers have been analysed to get information like the optimisation problem, the method used for solving it, considered parameters, objectives, constraints, implementation tools, and evaluation methods.
Débattre d’une interdisciplinarité en actes : le colloque « Interdisciplinarité(s) » du Réseau national des Maisons des sciences de l’homme
Authors: Casella Philippe 
Published: June 2023

Le Réseau national des Maisons des sciences de l’homme (Rn-MSH) a souhaité engager une réflexion sur les pratiques et les politiques d’interdisciplinarité. À cette fin, le colloque « Interdisciplinarité(s) » s’est attaché à articuler deux approches. En septembre 2021, des ateliers ont examiné les expériences conduites au sein des MSH avec la volonté de débattre de l’interdisciplinarité en actes. Puis, en janvier 2022, la réflexion a été élargie pour examiner la contribution des dynamiques interdisciplinaires à la recomposition du régime de connaissance, à la prise en compte des autres formes de savoir et à l’incorporation des enjeux des sociétés dans la production scientifique. Nous évoquerons notamment ici les agencements qui réduisent la capacité normative de l’organisation disciplinaire tout en préservant les ressources intellectuelles portées par les communautés disciplinaires.
Factors Associated with Need for Intravenous Glucose Infusion for the Treatment of Early Neonatal Hypoglycemia in Late Preterm and Term Neonates
Authors: Brion Luc P. , Scheid Lisa M. , Brown L Steven , Burchfield Patti J. , Rosenfeld Charles R. 
Published: June 2023

Objective The aim of this study was to determine which late-preterm (35–36 weeks' gestational age [GA]) and term neonates with early-onset hypoglycemia in the first 72 hours postnatal required a continuous glucose infusion to achieve and successfully maintain euglycemia.
Study Design This is a retrospective cohort study of late preterm and term neonates born in 2010–2014 and admitted to the Mother-Baby Unit at Parkland Hospital who had laboratory-proven blood glucose concentration < 40 mg/dL (2.2 mmol/L) during the first 72 hours of life. Among the subgroup needing intravenous (IV) glucose infusion, we analyzed which factors predicted a maximum glucose infusion rate (GIR) ≥ 10 mg/kg/min. The entire cohort was randomly divided into a derivation cohort (n = 1,288) and a validation cohort (n = 1,298).
Results In multivariate analysis, the need for IV glucose infusion was associated with small size for GA, low initial glucose concentration, early-onset infection, and other perinatal variables in both cohorts. A GIR ≥ 10 mg/kg/min was required in 14% of neonates with blood glucose value < 20 mg/dL during the first 3 hours of observation. The likelihood of a GIR ≥ 10 mg/kg/min was associated with lower initial blood glucose value and lower umbilical arterial pH.
Conclusion Need for IV glucose infusion was associated with small size for GA, low initial glucose concentration, early-onset infection, and variables associated with perinatal hypoxia–asphyxia. The likelihood of a maximum GIR ≥ 10 mg/kg/min was greater in neonates with lower blood glucose value during the first 3 hours of observation and lower umbilical arterial pH.
Key Points