bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiscale Catalysis Under Magnetic Fields: Methodologies, Advances, and Trends
Authors: Liu Dong , Huang Yanjie , Hu Jiawang , Wang Bin , Lu Yuan 
Published: November 2022

AbstractMagnetic field‐enhanced catalysis is an advanced strategy for enhancing catalytic reactions that have emerged in recent years, presenting great potential for alleviating the energy crisis and environmental pollution. Under favorable non‐contact magnetic field conditions, the external magnetic field that produces the enhancement effect can provide additional energy to the catalytic system as an additional driving force for the catalytic reaction and thus positively improve the overall catalytic efficiency. Exploring the effects of magnetic fields on multiscale catalytic reactions can broaden the practical applications of various catalytic reactions. This review begins with a brief introduction and analysis of possible mechanisms for magnetic field‐enhanced catalytic reactions (including spin polarization theory and electromagnetic theory), a description of the forces generated by magnetic fields, nano‐ and microscale magnetic materials, and various commonly used magnetic manipulation systems, and an overview of the application of magnetic fields to enhanced photocatalytic, electrocatalytic and biocatalytic reactions. Finally, the challenges and future prospects for advancing magnetic field‐enhanced catalytic reactions are presented. It is hoped that this review will provide a reference for the development and in‐depth study of magnetic field‐assisted enhanced catalytic reactions to improve catalytic efficiency.
Exploring school counselors’ and interns’ socioeconomic construct understanding and awareness
Authors: Brookover Dana L. , Johnson Kaprea F. , Crane Erin 
Published: November 2022

AbstractNine professional school counselors (PSCs) and eight school counseling interns in training (SCIT) participated in semi‐structured interviews to explore their understanding and awareness of socioeconomic constructs that influence a range of social, emotional, and academic outcomes for youth. Findings suggest that participants in both groups displayed advanced cognitive complexity of constructs, more SCIT focused on the micro‐level of economic stability, and more PSCs described the constructs through their experience with examples. The authors recommend that counselor educators and supervisors develop competencies to support advanced training and continuing education to increase clarity, awareness, and understanding of socioeconomic constructs that are impacting youth clients. The authors include future research directions.
A Comparative Numerical Investigation of the Behavior of Two‐Phase Hydrocarbon Flow Phenomena in Horizontal Flowline with Different Turbulence Models Using OpenFOAM
Authors: Sunday Nsidibe , Settar Abdelhakim , Chetehouna Khaled , Gascoin Nicolas 
Published: November 2022

AbstractTwo‐phase flow in pipes finds application in many industrial activities, mostly in the energy sector, necessitating model systems that correctly predict flow behaviors like flow pattern, pressure drop, and liquid holdup during the design and planning of a fluid transport system. This study aims to analyze three‐dimensional two‐phase liquid‐gas flows in a horizontal flowline. InterFoam, a transient two‐phase solver, was first modified to implement the low‐Reynolds number (LRN) k‐ε model in the OpenFOAM source code. This LRN k‐ε turbulence model is utilized to resolve the turbulence phenomena within the two‐phase mixtures. The two‐phase flow is calculated by using the developed solver based on the volume‐of‐fluid approach. Flow pattern results at different superficial gas and liquid velocities are validated by experimental data from the literature. Then, three Reynolds‐averaged Navier‐Stokes models were used for computations: LRN k‐ε, standard k‐ε, and the shear stress transport k‐ω model.
Controlled Formation of Porous 2D Lattices from C3‐symmetric Ph6−Me‐Tribenzotriquinacene‐OAc3
Authors: Toksabay Sinem , Leisegang Markus , Christ Andreas , Härtl Patrick , Krebs Johannes , Marder Todd B. , Haldar Soumyajyoti , Heinze Stefan , Bode Matthias , Krueger Anke 
Published: November 2022

AbstractThe on‐surface self‐assembly of molecules to form holey nanographenes is a promising approach to control the properties of the resulting 2D lattice. Usually, planar molecules are utilized to prepare flat, structurally confined molecular layers, with only a few recent examples of warped precursors. However, control of the superstructures is limited thus far. Herein, we report the temperature‐controlled self‐assembly of a bowl‐shaped, acetylated C3‐symmetric hexaphenyltribenzotriquinacene derivative on Cu(111). Combining scanning tunneling microscopy (STM) and density functional theory (DFT) confirms the formation of highly differing arrangements starting with π‐stacked bowl‐to‐bowl dimers at low coverage at room temperature via chiral honeycomb structures, an intermediate trigonal superstructure, followed by a fully carbon‐based, flattened hexagonal superstructure formed by on‐surface deacetylation, which is proposed as a precursor for holey graphene networks with unique defect structures.
Copper‐Catalyzed Stereoselective Borylation and Palladium‐Catalyzed Stereospecific Cross‐Coupling to Give Aryl C‐Glycosides
Authors: Kurahayashi Kazuki , Hanaya Kengo , Sugai Takeshi , Hirai Go , Higashibayashi Shuhei 
Published: November 2022

AbstractMetabolically stable C‐glycosides are an essential family of compounds in bioactive natural products, therapeutic agents, and biological probes. For their application, development of synthetic methods by connecting glycosides and aglycons with strict stereocontrol at the anomeric carbon, as well as with high functional‐group compatibility and environmental compatibility is a pivotal issue. Although Suzuki–Miyaura‐type C(sp3)−C(sp2) cross‐coupling using glycosyl boronates is a potential candidate for the construction of C‐glycosides, neither the cross‐coupling itself nor the facile synthesis of the coupling precursor, glycosyl boronates, have been achieved to date. Herein, it was succeeded to develop a copper‐catalyzed stereoselective one‐step borylation of glycosyl bromides to glycosyl boronates and palladium‐catalyzed stereospecific cross‐coupling of β‐glycosyl borates with aryl bromides to give aryl β‐C‐glycosides, in which the β‐configuration of the anomeric carbon of the glycosyl trifluoroborates is stereoretentively transferred to that of the resulting aryl C‐glycosides.
Betriebliche Qualifizierung 4.0
Authors: Voges Susanna 
Published: November 2022

AbstractIn Zeiten hoher Fluktuation haben sich die Anforderungen an Systeme betrieblicher Qualifizierung für Anlagenbediener grundlegend verändert. Die nachwachsende Generation erweist sich insbesondere post covid als wechselfreudiger als bisher gewohnt. Wie kann betriebliche Qualifizierung mit dieser Entwicklung Schritt halten, welcher Methoden bedarf es?
Einfach, sicher und vernetzt
Authors: Bracht Dagmar , Freudenberger Martin , Kraftschik Florian , Möller Einar 
Published: November 2022

AbstractDie Memosens‐Technologie zur Flüssigkeitsanalyse von Endress+Hauser ist vielen Prozessindustrien nicht mehr wegzudenken. Spätestens seit der Patenterteilung im Jahr 2008 wurde der Hersteller mit der Technologie zum Vorreiter für digitale Lösungen in der Flüssigkeitsanalyse. Mit Memosens 2.0 geht er jetzt einen weiteren großen Schritt in Richtung Idustrie 4.0.
Vorteile einer durchgehenden Ethernet‐Kommunikation
Authors: Ungermann Manuel 
Published: November 2022

AbstractMit der Verfügbarkeit von Safety over OPC UA werden Ethernet‐basierte sichere Kommunikationsprotokolle eine immer wichtigere Rolle in der Prozessindustrie einnehmen. Kommt das gerade entstehenden Advanced Physical Layer (APL) hinzu, kann in allen Bereichen einer Prozessanlage erstmals eine Datenübertragung via Ethernet umgesetzt werden. Die erheblichen Vorteile sowie die bereits erfolgte Adaption des Ethernet‐basierten Datenaustausches sind nun ebenfalls im Feld nutzbar.
Sicherer Transport von Lithiumionen‐Batteriespeichersystemen
Authors: Rasche David 
Published: November 2022

AbstractLithiumionen‐Batteriezellen finden Verwendung in Energiegroßspeichern, Traktionsbatterien und Solar‐Heimspeichern aber auch in einer Vielzahl kleinerer Geräte dienen sie als sehr effizienter Ladungsträger. Doch von den Batteriezellen können Risiken ausgehen können, wenn Temperaturgrenzen überschritten werden oder die Zellen mechanisch beschädigt werden.
Pretest and shrinkage estimators in generalized partially linear models with application to real data
Authors: Hossain Shakhawat , Mandal Saumen , Lac Le An 
Published: November 2022

AbstractSemiparametric models hold promise to address many challenges to statistical inference that arise from real‐world applications, but their novelty and theoretical complexity create challenges for estimation. Taking advantage of the broad applicability of semiparametric models, we propose some novel and improved methods to estimate the regression coefficients of generalized partially linear models (GPLM). This model extends the generalized linear model by adding a nonparametric component. Like in parametric models, variable selection is important in the GPLM to single out the inactive covariates for the response. Instead of deleting inactive covariates, our approach uses them as auxiliary information in the estimation procedure. We then define two models, one that includes all the covariates and another that includes the active covariates only. We then combine these two model estimators optimally to form the pretest and shrinkage estimators. Asymptotic properties are studied to derive the asymptotic biases and risks of the proposed estimators. We show that if the shrinkage dimension exceeds two, the asymptotic risks of the shrinkage estimators are strictly less than those of the full model estimators. Extensive Monte Carlo simulation studies are conducted to examine the finite‐sample performance of the proposed estimation methods. We then apply our proposed methods to two real data sets. Our simulation and real data results show that the proposed estimators perform with higher accuracy and lower variability in the estimation of regression parameters for GPLM compared with competing estimation methods.
Bilateral anisotropic Gabor wavelet transformation based deep stacked auto encoding for lossesless image compression
Authors: Suresh Kumar S. , Sarankumar R. , Vignesh O. , Prakash A. 
Published: November 2022

SummaryA highly challenging aspect of the data compression technique is maintaining the quality of data that reconstructs in high compression rates. To overcome these limitations, a bilateral anisotropic Gabor wavelet transformation with deep stacked auto encoding (BAGWT‐DSAE) technique based lossesless image compression is proposed in this article to save the storage space and processing time during transferring the images. The proposed method contains three main processes namely preprocessing, compression and decompression. Initially input aerial image and digital image are taken and these images are given bilateral filter based preprocessing for eliminates the different types of noises and also multiple artifacts. Then the preprocessed images are given to anisotropic Gabor wavelet transformation based deep stacked auto encoding to compress and decompress the wavelet transform's sensitive sub‐bands effectually. In DSAE, the decoder of the auto encoder achieves a better quality decompressed image. The proposed method is implemented in MATLAB simulations run in PC through Intel Core, 8 GB of RAM, 2.50 GHz CPU and Windows 8. Then, the simulation performance of proposed BAGWT‐DSAE‐LIC method provides 20.23%, 24.85%, and 38.56% low compression ratio and 26.48%, 21.23%, and 12.53% lower computational time, 4.56%, 7.68%, and 8.34% high space saving than the existing methods.
Graphics processing unit‐accelerated high‐quality watercolor painting image generation
Authors: Huang Jiamian , Ito Yasuaki , Nakano Koji 
Published: November 2022

AbstractStroke‐based rendering is a rendering method that mimics the actual painting technique by drawing a stroke by stroke on a blank canvas image. In this paper, we propose a watercolor image generation method using stroke‐based rendering. The proposed method generates an image that is a good approximation of the input image as well as having the characteristics of a watercolor painting by repeatedly painting strokes while referring to the input image. To generate a high‐quality image, that is, an image that closely resembles an actual watercolor painting, various techniques are employed: modeling of watercolor paper, detailed physical simulation of the movement of water and pigment, strokes using a brush model, among others. The proposed method generates a large number of strokes and performs computationally intensive watercolor simulations for each stroke. Therefore, this paper also presents its parallel algorithm using a Graphics Processing Unit (GPU). We implemented this parallel algorithm on an NVIDIA A100 GPU. The experimental results show that the CPU implementations with sequential and parallel executions take 34,651 and 867 s to generate a 4K‐watercolor image of size , respectively. In contrast, the GPU implementation with parallel execution succeeded in reducing the time to 44 s.
Inorganic Bergman Cyclization: An Appeal From Theory
Authors: Kashyap Chayanika , Purkayastha Siddhartha K. , Rohman Shahnaz S. , Guha Ankur K. 
Published: November 2022

AbstractThe scope of Bergman cyclization is expanded computationally by exploring the cyclization in inorganic B, N substituted derivative. This substitution has introduced polarity into the transition state, which resulted in dramatic lowering of the activation barrier. Natural charge distribution throughout the reaction profile has ascertained this hypothesis. Single B and N atom substitution at 1 and 6 terminal positions lowers the activation barrier by almost half of the original value which becomes even lower in the complete B, N analogue. The parent Bergman and single B, N substituted products were characterized by significant biradical character while the complete B, N substituted analogue was characterized by significant zwitterionic character. Reduction in electron delocalization is also observed in the complete B, N substituted analogue.
Silane‐Bearing Borasilsesquioxanes: Synthetic Protocol and Unsuspected Redistribution Reactions
Authors: Frydrych Miłosz , Sztorch Bogna , Brząkalski Dariusz , Pakuła Daria , Przekop Robert E. , Srishailam Kanugula , Reddy Byru Venkatram , Marciniec Bogdan 
Published: November 2022

AbstractThe presented work is a continuation of research on the reactivity of unsaturated borasilsesquioxanes under the conditions of common organometallic transformations. The catalytic hydrosilylation reaction with silanes, siloxanes and silsesquioxanes in presence of platinum catalyst was explored. The majority of the products were obtained in high yields (>90 %) and their structures were confirmed and characterized by spectroscopy and spectrometry, i. e. NMR and MALDI‐TOF‐MS. The most significant segment of the work is research on the spontaneous redistribution reaction of the alkoxy group from silane to borane moiety occurring in the obtained products, not being limited to the heterosilsesquioxane chemistry, however. The products were confirmed using GC‐MS, ESI‐MS methods and B3LYP exchange‐correlation, in order to ascertain formation of the silicon‐boron hybrid molecule.
Implementing High Dimensional Reduction Analysis on Histocytometric Data
Authors: Munoz‐Erazo Luis , Shinko Diana , Schmidt Alfonso J. , Price Kylie M. 
Published: November 2022

AbstractIn a previous protocol article, we demonstrated construction of a histocytometry pipeline that is capable of both segmenting highly aggregated cell populations and retaining the original intensity data range of the input microscopy images. In the protocol presented here, using the output from the aforementioned article, we demonstrate how to phenotype the data using the high dimensional reduction analysis technique optimized t‐distributed stochastic neighbor embedding (opt‐t‐SNE) and compare it to traditional manual gating. Additionally, we present a protocol illustrating the advantage of the inclusion of cell junction/membrane markers for accurately segmenting highly aggregated cell populations in ilastik. © 2022 Wiley Periodicals LLC.Basic Protocol 1: Phenotyping lymph node populations using manual gatingBasic Protocol 2: Phenotyping lymph node populations using t‐SNE dimensional reductionSupport Protocol: ilastik segmentation using a pan marker
A regression approach to identify discriminating locations
Authors: Vemireddy Hanisha , Olafsson Sigurdur 
Published: November 2022

AbstractSelection of planting locations is an important issue in plant breeding and may significantly impact the probability of correctly identifying the desired genotype based on noisy data. This is especially true for early‐stage experimentation where a set of experimental genotypes is observed in very few locations. This study aims to identify locations that are most helpful for discriminating the main effects of two or more genotypes. A regression‐based model is proposed that characterizes the sensitivity of location to the genotype main effect, and locations with significant positive sensitivity are termed discriminative. Comparing or ranking genotypes using these locations results in exaggerated expected differences between genotype main effects, allowing for more accurate comparisons in the presence of noise. Based on the proposed model, an expression for the probability of making correct genotype selection is derived given a set of locations with known location sensitivities. The probability of correct selection is then used to characterize an optimal set of location that maximizes the probability of selecting the genotype with better main effect. These locations are independent of the genotypes being compared and only depend on the number of locations being considered and the sensitivities of these locations to genotype effects. The theoretical implications of the model are validated using data obtained from a commercial soybean breeding program. The results show that by using discriminating locations correct selection is made 76% of the time, versus 67% for all locations and only 63% of the time for non‐discriminating locations.
High Current Density Oxygen Evolution in Carbonate Buffered Solution Achieved by Active Site Densification and Electrolyte Engineering
Authors: Nishimoto Takeshi , Shinagawa Tatsuya , Naito Takahiro , Harada Kazuki , Yoshida Masaaki , Takanabe Kazuhiro 
Published: November 2022

AbstractHigh current density reaching 1 A cm−2for efficient oxygen evolution reaction (OER) was demonstrated by interactively optimizing electrolyte and electrode at non‐extreme pH levels. Careful electrolyte assessment revealed that the state‐of‐the‐art nickel‐iron oxide electrocatalyst in alkaline solution maintained its high OER performance with a small Tafel slope in K‐carbonate solution at pH 10.5 at 353 K. The OER performance was improved when Cu or Au was introduced into the FeOx‐modified nanostructured Ni electrode as the third element during the preparation of electrode by electrodeposition. The resultant OER achieved 1 A cm−2at 1.53 V vs. reversible hydrogen electrode (RHE) stably for 90 h, comparable to those in extreme alkaline conditions. Constant Tafel slopes, apparent activation energy, and the same signatures from operando X‐ray absorption spectroscopy among these samples suggested that this improvement seems solely correlated with enhanced electrochemical surface area caused by adding the third element.
Electrophoretic detection of black market myostatin propeptide
Authors: Reichel Christian , Gmeiner Günter , Thevis Mario 
Published: November 2022

AbstractMyostatin propeptide is prohibited according to chapter S4 of the “WADA 2022 List of Prohibited Substances and Methods.” So far, no approved myostatin‐propeptide pharmaceuticals are available. Nevertheless, myostatin‐propeptides can be bought on the black market for “research purposes.” A study on black market myostatin propeptide products is presented as well as electrophoretic detection methods for serum and urine. Out of the 12 tested products, only nine actually contained the protein. Separation by SDS‐PAGE revealed that the nine products were relatively impure and that the main compound had a much higher mass (approximately 54–55 kDa) than expected (approximately 33 kDa). Further analyses by mass spectrometry showed that the elevated molecular mass was due to the presence of a full length GST‐tag on the propeptide. The developed detection method for serum is based on immunoprecipitation (IP) followed by SDS‐PAGE and Western blotting. In total, three anti‐myostatin propeptide antibodies were tested. All of them were well suited for either IP or immunoblotting. The final protocol applies a biotinylated polyclonal antibody, streptavidin‐coated magnetic beads, and a monoclonal detection antibody. For a sample volume of 500 μL serum, the detection limit of the method is approximately 2.5 ng/mL. The urine method applies a commercial ELISA for IP and performs with a limit of detection (LOD) of approximately 0.4 ng/mL. Furthermore, practically all currently available myostatin propeptide standards were also investigated. Due to the significant molecular mass difference of the black market products, an unambiguous differentiation from endogenous myostatin propeptide is possible.
Declining temperature and increasing moisture sensitivity of shrub growth in the Low‐Arctic erect dwarf‐shrub tundra of western Greenland
Authors: Weijers Stef 
Published: November 2022

AbstractEvergreen dwarf shrubs respond swiftly to warming in the cool and dry High Arctic, but their response in the warmer Low Arctic, where they are expected to be outcompeted by taller species under future warming, remains to be clarified.Here, 12,528 annual growth increments, covering 122 years (1893–2014), were measured of 764 branches from 25 individuals of the evergreen dwarf shrub Cassiope tetragona from a Low‐Arctic erect dwarf‐shrub tundra site in western Greenland. In addition, branch initiation and mortality frequency time series were developed. The influence of seasonal climate and correspondence with fluctuations in regional normalized difference vegetation index (NDVI), a satellite‐proxy for vegetation productivity, were studied.Summer temperatures were the main driver of growth, while winter temperatures were the main non‐summer‐climate driver. During past and recent warm episodes, shrub growth diverged from summer temperatures. In recent decades, early summer precipitation has become the main growth‐limiting factor for some individuals, likely through micro‐topography‐determined soil moisture availability, and more than half of the shrubs studied became irresponsive to summer temperatures. There was correspondence between climatic drivers, C. tetragona growth and branch initiation frequency, and satellite‐observed vegetation productivity, suggesting the area's shrub‐dominated tundra vegetation is limited by similar climatic factors. Winter warming events were likely the predominant cause of branch mortality, while branching increased after years with poor growth and cooler‐than‐average summers.These findings show that the erect dwarf‐shrub tundra in the Low Arctic has already and will likely become decreasingly temperature‐ and increasingly moisture‐limited and that winter warming supports shrub growth, but increased extreme winter warming event frequency may increase branch mortality and vegetation damage. Such counter‐acting mechanisms could offer an explanation for the vegetation stability observed over large parts of the Arctic.