bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-throughput reprogramming of an NRPS condensation domain
Authors: Folger Ines B. , Frota Natália F. , Pistofidis Angelos , Niquille David L. , Hansen Douglas A. , Schmeing T. Martin , Hilvert Donald 
Published: February 2024

AbstractEngineered biosynthetic assembly lines could revolutionize the sustainable production of bioactive natural product analogs. Although yeast display is a proven, powerful tool for altering the substrate specificity of gatekeeper adenylation domains in nonribosomal peptide synthetases (NRPSs), comparable strategies for other components of these megaenzymes have not been described. Here we report a high-throughput approach for engineering condensation (C) domains responsible for peptide elongation. We show that a 120-kDa NRPS module, displayed in functional form on yeast, can productively interact with an upstream module, provided in solution, to produce amide products tethered to the yeast surface. Using this system to screen a large C-domain library, we reprogrammed a surfactin synthetase module to accept a fatty acid donor, increasing catalytic efficiency for this noncanonical substrate >40-fold. Because C domains can function as selectivity filters in NRPSs, this methodology should facilitate the precision engineering of these molecular assembly lines.
Synergistic effect of nitrate exposure and heatwaves on the growth, and metabolic activity of microalgae, Chlamydomonas reinhardtii, and Pseudokirchneriella subcapitata
Authors: Akter Sabiha , AbdElgawad Hamada , Beemster Gerrit T. S. , De Boeck Gudrun , Schoelynck Jonas 
Published: February 2024

AbstractAquatic biota are threatened by climate warming as well as other anthropogenic stressors such as eutrophication by phosphates and nitrate. However, it remains unclear how nitrate exposure can alter the resilience of microalgae to climate warming, particularly heatwaves. To get a better understanding of these processes, we investigated the effect of elevated temperature and nitrate pollution on growth, metabolites (sugar and protein), oxidative damage (lipid peroxidation), and antioxidant accumulation (polyphenols, proline) in Chlamydomonas reinhardtii and Pseudokirchneriella subcapitata. The experiment involved a 3 × 3 factorial design, where microalgae were exposed to one of three nitrate levels (5, 50, or 200 mg L−1 NO3−l) at 20 °C for 2 weeks. Subsequently, two heatwave scenarios were imposed: a short and moderate heatwave at 24 °C for 2 weeks, and a long and intense heatwave with an additional 2 weeks at 26 °C. A positive synergistic effect of heatwaves and nitrate on growth and metabolites was observed, but this also led to increased oxidative stress. In the short and moderate heatwave, oxidative damage was controlled by increased antioxidant levels. The high growth, metabolites, and antioxidants combined with low oxidative stress during the short and moderate heatwaves in moderate nitrate (50 mg L−1) led to a sustainable increased food availability to grazers. On the other hand, long and intense heatwaves in high nitrate conditions caused unsustainable growth due to increased oxidative stress and relatively low antioxidant (proline) levels, increasing the risk for massive algal die-offs.
Horizontal metaproteomics and CAZymes analysis of lignocellulolytic microbial consortia selectively enriched from cow rumen and termite gut
Authors: Auer Emeline , Lazuka Adèle , Huguenin-Bizot Bertrand , Jehmlich Nico , Déjean Sébastien , Lombard Vincent , Henrissat Bernard , O’Donohue Michael , Hernandez-Raquet Guillermina 
Published: February 2024

Abstract
Selectively enriched microbial consortia are potentially useful for the conversion of lignocellulose (LC) into biofuels and commodity chemicals. Consortia are also of interest to elucidate the roles of individual microorganisms and the dynamics of enzymes involved in LC deconstruction. Using metaproteomics, 16 S rRNA gene amplicon sequencing and multivariate discriminant analysis, we revealed the temporal dynamics of microbial species and their proteins during anaerobic conversion of LC by microbial consortia derived from cow rumen (RWS) and termite gut (TWS) microbiomes. Bacteroidetes (Bacteroidota), Firmicutes (Bacillota) and Proteobacteria (Pseudomonadota) phyla were dominant, irrespective the inoculum origin, displaying functional complementarities. We identified a large variety of carbohydrate-active enzymes, distributed in 94 CAZy families, involved in biomass deconstruction. Additionally, proteins involved in short chain fatty acids biosynthesis were detected. Multivariate analysis clearly differentiates RWS and TWS metaproteomes, with differences originating in the initial inoculates. Further supervised discriminant analysis of the temporal succession of CAZymes revealed that both consortia consume easily accessible oligosaccharides during the early stage of incubation, degrading more complex hemicellulose and cellulose fractions at later stages, an action that pursues throughout the incubation period. Our results provide new insights regarding the functional roles and complementarities existing in lignocellulolytic consortia and highlight their potential for biorefinery applications.
Reassembling digital archives—strategies for counter-archiving
Authors: Blanke Tobias 
Published: February 2024

AbstractArchives have long been a key concern of academic debates about truth, memory, recording and power and are important sites for social sciences and humanities research. This has been the case for traditional archives, but these debates have accelerated with the digital transformation of archives. The proliferation of digital tools and the fast-growing increase in digital materials have created very large digitised and born-digital archives. This article investigates how new digital archives continue existing archival practices while at the same time discontinuing them. We present novel methodologies and tools for changing memory and power relations in digital archives through new ways of reassembling marginalised, non-canonical entities in digital archives. Reassembling digital archives can take advantage of the materiality and the algorithmic processuality of digital collections and reshape them to inscribe lost voices and previously ignored differences. Digital archives are not fixed and are changed with new research and political questions and are only identified through new questions. The article presents six distinct techniques and strategies to reassemble digital archives and renders these according to three different types of new digital archives. We consider both the extension of archives towards evidence that is otherwise thrown away as well as the provision of new intensive, non-discriminatory viewpoints on existing collections.
Understanding the self-perceived customer experience and repurchase intention in live streaming shopping: evidence from China
Authors: Yi Minqin , Chen Ming , Yang Jilang 
Published: February 2024

AbstractAs an increasingly mature way of shopping in China, live streaming shopping still faces the problems of high return rates and low repurchase rates. Based on the expectation confirmation theory, this study uses structural equation modeling (SEM) to explore the repurchase intention of live streaming shopping(LSS)users. The results show that perceived interactivity, perceived quality and perceived value have a direct and significant effect on confirmation and customer satisfaction. Perceived discounts do not directly improve user satisfaction; they must pass through a complete intermediary variable of confirmation. In addition, we also verified that the degree of confirmation affects satisfaction, and satisfaction has an impact on repurchase intention. Finally, our model tested gender factors as a control variable and found that gender differences significantly impact consumers’ repurchase intentions. Considering these findings, we provide practical suggestions for retaining users and hopefully promoting the long-term development of live streaming shopping.
A scoping review of the literature on content and language integrated learning assessment
Authors: Liang Weijun , Wu Yanjun 
Published: February 2024

Abstract
Despite being an essential element of Content and Language Integrated Learning (CLIL), CLIL assessment has received scarce
research attention and remains a relatively underexplored area. Since few review studies have been conducted in the field of CLIL
assessment, this article constitutes the first attempt to synthesise both theoretical and empirical studies on CLIL assessment around the
globe with a view to yielding implications for the understanding, design, and improvement of assessment in CLIL and providing suggestions
for future research agendas. Based on a thematic analysis of 77 pertinent publications selected among 763 search results, this scoping
review first identified three prominent research themes in CLIL assessment including assessment issues, assessment practices, and assessment
frameworks. Subsequently, the review elaborated each theme and discussed some interesting patterns of the literature in great depth. The
review concluded with suggestions on future research directions with a view to advancing the uncharted area of CLIL assessment.
The scattering map on collapsing charged spherically symmetric spacetimes
Authors: Alford Fred 
Published: February 2024

Abstract
In this paper we generalise our previous results (Alford 2020 Ann. Inst. Henri Poincare
21 2031–92) concerning scattering on the exterior of collapsing dust clouds to the charged case, including in particular the extremal case. We analyse the energy boundedness of solutions φ to the wave equation on the exterior of collapsing spherically symmetric charged matter clouds. We then proceed to define the scattering map on this spacetime, and look at the implications of our boundedness results on this map. More specifically, we first construct a class of spherically symmetric charged collapsing matter cloud exteriors, and then consider solutions to the wave equation with Dirichlet (reflective) boundary conditions on the surface of these clouds. We then show that the energy of φ remains uniformly bounded going forwards or backwards in time, and that the scattering map is bounded going forwards but not backwards. Therefore, the scattering map is not surjective onto the space of finite energy on

I

+

∪

H

+

. Thus there does not exist a backwards scattering map from finite energy radiation fields on

I

+

∪

H

+

to finite energy radiation fields on

I

−

for these models. These results will be used to give a treatment of Hawking radiation in a companion paper (Alford 2023 arXiv:2309.03022).
Atomic-scale insight into arc plasma radiation-induced gassing materials ablation: photothermal decomposition behavior
Authors: Cao Weidong , Li Xingwen , Zhang Yanfeng , Wang Qian , Yu Renjie , Chen Zhenyi , Zhuang Tao 
Published: February 2024

Abstract
In this study, we present a novel computational atomistic study of the photothermal decomposition behavior of arc plasma on radiation-induced gassing materials ablation, studying a polyamide 66 (PA66) system using reactive force field (ReaxFF) molecular dynamics (MD). We determine the infrared (IR) vibrational frequency of the PA66 permanent molecular dipole using MD and then computationally impose an electric field at the same frequency to simulate photothermal decomposition by IR, verifying our observations with gas chromatography-mass spectrometry (GCMS) of experimental decomposition. MD indicates that photothermal decomposition reaction is dominated by either cleavage at low temperature or cyclization at high temperature. At low temperature, initial chain scission takes place at the two amide C–N, and the remaining chains break down into a variety of molecular fragments and free radicals. Further increasing the temperature stabilizes a variety of branched chain structures via cyclization, debranching and polymerization, with further cleavage forming hydrocarbons and volatile small molecule gases. Overall, H2, CO, H2O, alkanes and alkenes are the main gaseous products and cyclic structures (especially nitrogen-containing three-membered ring) are the main solid products during the photothermal decomposition of PA66, and their formation results from a variety of complex chemical reactions. The results of MD cover the experimental observations of GCMS, demonstrating that this computational methodology helps us understand the molecular breakdown mechanisms of arc plasma radiation-induced gassing materials. We also discuss the physical mechanism by which the main gas can accelerate arc quenching, and the importance and necessity of using electric fields to simulate IR photothermal decomposition of arc-induced ablation.
Thermal evolution of low-temperature magnetic texture modulation in fept thin films by direct visualization
Authors: Quinteros Cynthia P , Goijman Dafne , Damerio Silvia , Milano Julián 
Published: February 2024

Abstract
Patterns of ferroic domains and domain walls are being intensively studied to implement new logic schemes. Any technological application of such objects depends on a detailed understanding of them. Using low-temperature magnetic force measurements (10–300 K), the evolution of ferromagnetic stripes on equiatomic FePt thin films is thoroughly analyzed. Since FePt is known to develop a transition from in-plane homogeneous magnetization to stripe domains upon varying its thickness, multiple samples are studied demonstrating the well-established reduction upon thickness decrease and a non-trivial dependence on temperature. Moreover, the room-temperature uniform distribution of the pattern evolves into a distorted one upon temperature cycling. Finally, dissimilar stripe patterns are obtained upon reducing and increasing temperature indicating the states are dependent on the history of applied stimuli rather than the parametric conditions.
An effective approach for aerosol dynamics modeling in dusty plasma
Authors: Tetard G , Michau A , Prasanna S , Hassouni K 
Published: February 2024

Abstract
In this paper, we demonstrate the application of the Dirac-lognormal bimodal moment approach to investigate aerosol dynamics in dusty plasmas. This approach was evaluated by comparison with the detailed and computationally expensive sectional approach for two dusty plasma systems. The first one is a sputtering Argon DC discharge and the second is a capacitively coupled Ar/C2H2 radio-frequency (CCRF) discharge. The results obtained by the bimodal and the sectional approaches are in good agreement for the sputtering DC discharge where the aerosol dynamics is dominated by nucleation and surface deposition growth processes. This agreement is obtained not only on the averaged characteristics of the particle cloud, but also on the detailed particle size distributions. In the case of the CCRF discharge a satisfactory agreement between the two approaches is obtained on the averaged characteristics and on the core distributions of the particle cloud even if a significant difference is observed at low and intermediate particle size. Nevertheless, the bimodal moment approach is accurate enough for the simulation of the dusty plasmas of interest. Its low-computational cost makes it a very effective method as far as dusty plasma simulation is concerned.
Predicting materials properties with generative models: applying generative adversarial networks for heat flux generation
Authors: Kong Qi , Shibuta Yasushi 
Published: February 2024

Abstract
In the realm of materials science, the integration of machine learning techniques has ushered in a transformative era. This study delves into the innovative application of generative adversarial networks (GANs) for generating heat flux data, a pivotal step in predicting lattice thermal conductivity within metallic materials. Leveraging GANs, this research explores the generation of meaningful heat flux data, which has a high degree of similarity with that calculated by molecular dynamics simulations. This study demonstrates the potential of artificial intelligence (AI) in understanding the complex physical meaning of data in materials science. By harnessing the power of such AI to generate data that is previously attainable only through experiments or simulations, new opportunities arise for exploring and predicting properties of materials.
Study on the detection technology for inner-wall outer surface defects of the automotive ABS brake master cylinder based on BM-YOLOv8
Authors: Liu Guixiong , Yan Yipu , Meng Joe 
Published: February 2024

Abstract
A defect detection approach based on the BiFormer + MPDIoU’s YOLOv8 (BM-YOLOv8) model is proposed which addresses the challenges of low accuracy and low efficiency in detecting tiny defects on the inner-wall outer surface of automotive Anti-lock Brake Systems (ABS) brake master cylinder. This method constructs an imaging model based on process parameters such as speed and inspection accuracy required during the production of automotive ABS brake master cylinder. On this basis, it employs the dynamic sparse self-attention mechanism of the BiFormer to build a network for self-attention feature extraction and fusion. It also utilizes the Minimum Point Distance Intersection over Union (MPDIoU) to optimize the bounding box regression loss function, allowing for precise detection of defects on the inner-wall outer surface of automotive ABS brake master cylinder. Both qualitative and quantitative studies demonstrated that the BM-YOLOv8 method achieves a defect identification rate of 98.8% for the inner-wall outer surface defects of automotive ABS brake master cylinder. More than 25 images per second can be detected in this process. The performance of this method meets the accuracy and real-time requirements for defect detection on the inner-wall outer surface of automotive ABS brake master cylinder.
Control of the robotic arm system with an SSVEP-based BCI
Authors: Fu Rongrong , Feng Xiaolei , Wang Shiwei , Shi Ye , Jia Chengcheng , Zhao Jing 
Published: February 2024

Abstract
Recent studies on brain–computer interfaces (BCIs) implemented in robotic systems have shown that the system’s effectiveness in assisting individuals with movement disorders to enhance their human–computer interaction skills. However, achieving precise and rapid online completion of tasks remains a challenge for manipulators with multiple degrees of freedom (DOFs). In this paper, we explore a time-sharing control strategy for studying motion control of a robotic arm based on steady-state visual evoked potentials. The signals are generated by the joint frequency-phase modulation method, analyzed with the filter-bank canonical correlation analysis algorithm, and identified to control the six-DOF robotic arm for task execution. The shared control strategy not only reduces user’s cognitive fatigue but also enhances system in practical environments. The use of high-frequency stimuli significantly improves user comfort, and hybrid coding increases the universality of the BCI system. Additionally, by setting multiple locations and actions randomly, the robotic arm can adaptively program the optimal path. The online results showed that BCI instructions of the proposed system could be accurately chosen from six options within 6.45 s. Subjects used an average of 12 commands for the robotic arm to achieve the proposed task with an average accuracy of 98.21%. These findings validate the feasibility and effectiveness of applying the system to robotic control. The control strategy proposed in this study exhibits versatility in controlling robots to perform various complex tasks across different domains.
Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging
Authors: Richtsmeier Devon , Rodesch Pierre-Antoine , Iniewski Kris , Bazalova-Carter Magdalena 
Published: February 2024

Abstract

Objective. Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourque et al (2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material. Approach. The method decomposes materials into their effective atomic number (Z
eff) and electron density relative to water (ρ

e
). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with known ρ

e
values and elemental compositions. Theoretical Z
eff values were found for the appropriate energy ranges using the elemental composition of the materials. Z
eff varied slightly with energy but was considered a systematic error. An ex vivo bovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent. Main results. The mean root mean squared percent errors on the extracted Z
eff and ρ

e
for PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in the ex vivo bovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from the ex vivo tissue sample with K-edge imaging. Significance. PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.
Analysis of electrode arrangements for brain stroke diagnosis via electrical impedance tomography through numerical computational models
Authors: Lee Hannah , Culpepper Jared , Porter Emily 
Published: February 2024

Abstract

Objective. Rapid stroke-type classification is crucial for improved prognosis. However, current methods for classification are time-consuming, require expensive equipment, and can only be used in the hospital. One method that has demonstrated promise in a rapid, low-cost, non-invasive approach to stroke diagnosis is electrical impedance tomography (EIT). While EIT for stroke diagnosis has been the topic of several studies in recent years, to date, the impact of electrode placements and arrangements has rarely been analyzed or tested and only in limited scenarios. Optimizing the location and choice of electrodes can have the potential to improve performance and reduce hardware cost and complexity and, most importantly, diagnosis time. Approach. In this study, we analyzed the impact of electrodes in realistic numerical models by (1) investigating the effect of individual electrodes on the resulting simulated EIT boundary measurements and (2) testing the performance of different electrode arrangements using a machine learning classification model. Main results. We found that, as expected, the electrodes deemed most significant in detecting stroke depend on the location of the electrode relative to the stroke lesion, as well as the role of the electrode. Despite this dependence, there are notable electrodes used in the models that are consistently considered to be the most significant across the various stroke lesion locations and various head models. Moreover, we demonstrate that a reduction in the number of electrodes used for the EIT measurements is possible, given that the electrodes are approximately evenly distributed. Significance. In this way, electrode arrangement and location are important variables to consider when improving stroke diagnosis methods using EIT.