bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Support Effect in the Catalytic Application of Ligand‐Protect Gold Clusters
Authors: Li Shuohao , Fu Shenguang , Gong Yuqing , Wu Nuojie , Wang Lei , Wang Liang 
Published: August 2023

Comprehensive SummaryLigand‐protected gold (Aun) clusters sometimes need the removal of organic ligands to expose more active sites and reduce steric hindrance in catalytic reactions, and large amount of organic and inorganic materials usually need to be employed as supports to anchor Aun clusters through different interaction mechanisms. Whereas, less comprehensive summaries have been provided about the crucial contribution of various supports to the catalytic performance of the supported Aun clusters. Herein, this review firstly summarizes synthesis methods (e.g., impregnation and encapsulation processes) for the supported Aun cluster catalysts, and then mainly points out specific contributions of support effect in a great diversity of catalytic reactions, as well as deep interaction mechanisms. Besides, opportunities and challenging issues will be stated towards supported Aun clusters, in terms of improving catalytic performance and structural stability of Aun clusters in the demand of catalysis.
Modeling isovolumetric phases in cardiac flows by an Augmented Resistive Immersed Implicit Surface method
Authors: Zingaro Alberto , Bucelli Michele , Fumagalli Ivan , Dede' Luca , Quarteroni Alfio 
Published: August 2023

AbstractA major challenge in the computational fluid dynamics modeling of the heart function is the simulation of isovolumetric phases when the hemodynamics problem is driven by a prescribed boundary displacement. During such phases, both atrioventricular and semilunar valves are closed: consequently, the ventricular pressure may not be uniquely defined, and spurious oscillations may arise in numerical simulations. These oscillations can strongly affect valve dynamics models driven by the blood flow, making unlikely to recovering physiological dynamics. Hence, prescribed opening and closing times are usually employed, or the isovolumetric phases are neglected altogether. In this article, we propose a suitable modification of the Resistive Immersed Implicit Surface (RIIS) method (Fedele et al., Biomech Model Mechanobiol 2017, 16, 1779–1803) by introducing a reaction term to correctly capture the pressure transients during isovolumetric phases. The method, that we call Augmented RIIS (ARIIS) method, extends the previously proposed ARIS method (This et al., Int J Numer Methods Biomed Eng 2020, 36, e3223) to the case of a mesh which is not body‐fitted to the valves. We test the proposed method on two different benchmark problems, including a new simplified problem that retains all the characteristics of a heart cycle. We apply the ARIIS method to a fluid dynamics simulation of a realistic left heart geometry, and we show that ARIIS allows to correctly simulate isovolumetric phases, differently from standard RIIS method. Finally, we demonstrate that by the new method the cardiac valves can open and close without prescribing any opening/closing times.
FD‐DBN: Flow directed deep belief network for accurate anomaly detection in cloud computing
Authors: Rajarao Banavathu , Sreenivasulu Meruva 
Published: August 2023

SummarySecurity becomes the key concern in a cloud environment, as the servers are distributed throughout the globe and involve the circulation of highly sensitive data. Intrusions in the cloud are common because of the huge network traffic that paves the way for intruders to breach traditional security systems with sophisticated software. To avoid such problems, intrusion detection systems (IDSs) have been introduced by various researchers. Each IDS was developed to achieve a particular objective, that is, providing security by detecting intrusions. Most of the available IDS are inefficient and are unable to provide accurate classification. Also, some of them are computationally expensive to be implemented in practical scenarios. This article proposes a new and efficient IDS framework that can accurately classify the intrusion type through effective training to address the existing drawbacks. The proposed framework, named flow directed deep belief network (FD‐DBN), involves three main phases: pre‐processing, clustering, and classification. In pre‐processing, certain data mining operations are carried out to clean the data. The clustering phase is carried out using the game‐based k‐means (GBKM) clustering algorithm. The clustered data is then provided as input to the FD‐DBN classification framework, where the training process is carried out. The deep belief network (DBN) training is performed with dataset features, and the flow direction algorithm is adopted for tuning the weight parameters of DBN. Through tuning, the model yielded accurate classification outcomes. The simulations are done in Python 3.6, and the results proved that the proposed framework is much more effective than the existing IDS frameworks.
Improving coral cover using an integrated pest management framework
Authors: Rogers Jacob G. D. , Plagányi Éva E. , Babcock Russell C. , Fletcher Cameron S. , Westcott David A. 
Published: August 2023

AbstractIntegrated pest management (IPM) leverages our understanding of ecological interactions to mitigate the impact of pest species on economically and/or ecologically important assets. It has primarily been applied in terrestrial settings (e.g., agriculture), but has rarely been attempted for marine ecosystems. The crown‐of‐thorns starfish (CoTS), Acanthaster spp., is a voracious coral predator throughout the Indo‐Pacific where it undergoes large population increases (irruptions), termed outbreaks. During outbreaks CoTS act as a pest species and can result in substantial coral loss. Contemporary management of CoTS on the Great Barrier Reef (GBR) adopts facets of the IPM paradigm to manage these outbreaks through strategic use of direct manual control (culling) of individuals in response to ecologically based target thresholds. There has, however, been limited quantitative analysis of how to optimize the implementation of such thresholds. Here we use a multispecies modeling approach to assess the performance of alternative CoTS management scenarios for improving coral cover trajectories. The scenarios examined varied in terms of their ecological threshold target, the sensitivity of the threshold, and the level of management resourcing. Our approach illustrates how to quantify multidimensional trade‐offs in resourcing constraints, concurrent CoTS and coral population dynamics, the stringency of target thresholds, and the geographical scale of management outcomes (number of sites). We found strategies with low target density thresholds for CoTS (≤0.03 CoTS min−1) could act as “Effort Sinks” and limit the number of sites that could be effectively controlled, particularly under CoTS population outbreaks. This was because a handful of sites took longer to control, which meant other sites were not controlled. Higher density thresholds (e.g., 0.04–0.08 CoTS min−1), tuned to levels of coral cover, diluted resources among sites but were more robust to resourcing constraints and pest population dynamics. Our study highlights trade‐off decisions when using an IPM framework and informs the implementation of threshold‐based strategies on the GBR.
Object judgment with an event‐driven MEMS‐LSI integrated tactile sensor array system
Authors: Muroyama Masanori , Tanaka Shuji 
Published: August 2023

AbstractWe have developed tactile sensor systems for next‐generation robots. To install a large number of tactile sensors, we have proposed micro electro mechanical systems‐large‐scale integration (MEMS‐LSI) integrated tactile sensors. The integrated device has the following features: capacitive type three‐axis force sensing, embedded diode‐based temperature sensing, signal processing for sensing data digitalization, and event‐driven response for efficient serial bus communication. This paper demonstrates a sensor array system as up‐to 40 integrated tactile sensors which are connected on one bus line. After acquiring the sensing data from the sensor array system, we applied a machine learning technique for target object judgment. The objective of the judgment is to classify the targets into normal object and abnormal object. With the sensor array system, data preprocessing and tuned Recurrent Neural network (RNN)/Long Short‐Term Memory (LSTM) neural network models, we achieved high‐accuracy, high‐precision, and high‐recall scores for the experiment of the judgment.
Antinociceptive effects of nefopam activating descending serotonergic modulation via 5‐HT2 receptors in the nucleus raphe magnus
Authors: Li Yaqun , Kim Woong Mo , Lee Yu Jun , Kang Dong Ho , Lee Hyung Gon , Choi Jeong Il , Yoon Myung Ha 
Published: August 2023

AbstractBackgroundNefopam is a centrally acting antinociceptive drug; however, the underlying mechanisms are not fully understood. This study investigated the supraspinal mechanisms of nefopam.MethodsThe effects of intraperitoneally administered nefopam were assessed in rats using the formalin test, and the mechanisms were investigated by intrathecal or intra‐nucleus raphe magnus (NRM) pre‐treatment with the serotonin (5‐HT) receptor antagonist or 5‐HT2 receptor antagonist. The change in extracellular 5‐HT levels was measured by spinal cord microdialysis.ResultsIntraperitoneally administered nefopam showed antinociceptive effects in the rat formalin test, which were reversed by intrathecal pre‐treatment with 5‐HT receptor antagonist dihydroergocristine. Microdialysis study revealed that systemic nefopam significantly increased 5‐HT level in the spinal dorsal horn. Pretreatment of cinanserin, a 5‐HT2 receptor antagonist, into the NRM blocked the antinociceptive effects of intraperitoneally delivered nefopam. Direct injection of nefopam into the NRM mimicked the effects of systemic nefopam, and this effect was reversed by intra‐NRM cinanserin pre‐treatment. The increase in spinal level of 5‐HT by systemic nefopam was attenuated by intra‐NRM cinanserin pre‐treatment.ConclusionThe antinociceptive effects of systemically administered nefopam are mediated by 5‐HT2 receptors in the NRM, which recruit the descending serotonergic fibres to increase the release of 5‐HT into the spinal dorsal horn.SignificanceThis study revealed supraspinal mechanisms of nefopam‐produced analgesia mediated by 5‐HT2 receptors in the NRM recruiting the descending serotonergic fibres to increase the release of 5‐HT into the spinal dorsal horn. These observations support a potential role for nefopam in multimodal analgesia based on its distinct mechanisms of action that are not shared by the other analgesics.
ASCE/SEI 7‐compliant site‐specific evaluation of the seismic demand posed to reinforced concrete buildings with real and simulated ground motions
Authors: Matinrad Pezhman , Petrone Floriana 
Published: August 2023

AbstractState‐of‐the‐art seismic design and assessment methodologies rely on the utilization of ground‐motion records scaled to site‐specific risk‐targeted spectra to perform nonlinear time‐history analyses and estimate mean structural demands. Motivated by the discrepancies in structural response estimates resulting from different selection and scaling methods, this study assesses the implications of utilizing site‐specific simulated ground motions from 3‐D physics‐based wave‐propagation models as opposed to historical records from worldwide catalogs in ASCE/SEI7‐compliant procedures for seismic performance evaluations. A suite of validated realizations of an M7 Hayward Fault earthquake in the San Francisco Bay Area and two modern reinforced concrete moment‐resisting frame buildings are utilized as a case study. The 2014 USGS earthquake hazard and probability maps are employed for the hazard calculations, and the PEER NGA‐West2 database is used for the selection of the real ground motions. The building models are coupled with the simulated and real ground motions to perform a total of 30,552 nonlinear time‐history analyses. Structural demands obtained from real and simulated motions are examined and compared at the regional‐scale in terms of peak interstory drift ratio median and dispersion, and localization along the building height. The correlations between observed structural responses and ground‐motion features are discussed to potentially inform current code‐compliant methodologies for ground‐motion selection. Results show that utilizing site‐specific simulated ground motions that incorporate path, fault geometry, and site‐condition effects as opposed to historical ground‐motion records may lead to differences in the structural demands above 50%. Such differences are highly spatially variable throughout the region and difficult to predict.
Defining the length parameter in river bifurcation models: a theoretical approach
Authors: Redolfi Marco 
Published: August 2023

SummaryOne‐dimensional models for river bifurcations rely on a nodal point relation that determines the distribution of sediments between the downstream branches. The most widely‐adopted nodal point relation describes the two‐dimensional topographic effects exerted by the bifurcation by introducing two computational cells, located just upstream the bifurcation node, that laterally exchange water and sediments. The results of this approach strongly depend on a dimensionless parameter that represents the ratio between the cell length and the main channel width, whose value needs to be empirically estimated. Previous works proposed calibrating this parameter on the basis of more complete two‐dimensional linear models, which directly solve the momentum and mass conservation equations. This study demonstrates that a full consistency between the one‐dimensional approach and the two‐dimensional models can be directly achieved by adopting different scaling for the bifurcation cell length, which results in a theoretically‐defined and constant dimensionless length parameter. Comparison with experimental observations reveals that this physically‐based scaling yields more accurate predictions of bifurcation stability and discharge asymmetry. This indicates that the proposed method may provide a more reliable and precise estimation of the cell length, potentially improving the performance of one‐dimensional models for bifurcation processes in rivers.
Interpretation and Use of a Workplace English Language Proficiency Test Score Report: Perspectives of TOEIC® Test Takers and Score Users in Taiwan
Authors: Hsieh Ching‐Ni 
Published: August 2023

AbstractResearch in validity suggests that stakeholders' interpretation and use of test results should be an aspect of validity. Claims about the meaningfulness of test score interpretations and consequences of test use should be backed by evidence that stakeholders understand the definition of the construct assessed and the score report information. The current study explored stakeholders' uses and interpretations of the score report of a workplace English language proficiency test, the TOEIC® Listening and Reading (TOEIC L&R) test. Online surveys were administered to TOEIC L&R test takers and institutional and corporate score users in Taiwan to collect data about their uses and interpretations of the test score report. Eleven survey respondents participated in follow‐up interviews to further elaborate on their uses of the different score reporting information within the stakeholders' respective contexts. Results indicated that the participants used the TOEIC L&R test scores largely as intended by the test developer although some elements of the score report appeared to be less useful and could be confusing for stakeholders. Findings from this study highlight the importance of providing score reporting information with clarity and ease to enhance appropriate use and interpretation.
An Outlook on Harnessing Technological Innovative Competence in Sustainably Transforming African Agriculture
Authors: Asem ‐ Hiablie Senorpe , Uyeh Daniel Dooyum , Adelaja Adesoji , Gebremedhin Kifle , Srivastava Ajit , Ileleji Klein , Gitau Margaret , Ha Yushin , Park Tusan 
Published: August 2023

AbstractAgricultural value chains worldwide provide essential support to livelihoods, ecosystem services, and the growing bioeconomy. The coronavirus disease 2019 (COVID‐19) pandemic slowed down or reversed decades of agricultural growth and exposed the vulnerabilities of farmers and the food insecure in Africa, thus reiterating the need to build resilience, agility, and adaptability for a sustainable agriculture. Existing social, political, environmental, and economic challenges demonstrate that a path to faster sustainable growth is increased productivity through improved input quality, of which technical inputs are a part. This work presents a perspective calling for African innovative competence in technological and methodological applications and solutions as part of the most critical area of a holistic organization for social progress. It finds that while performances of previous agricultural transformation efforts offer insights for future directions, novel pathways fitting to the diversity of situations and contexts on the continent are needed. These may include vertical agriculture in land‐constrained regions to grow high‐value products, ocean or sea farming in coastal regions, development of multiple‐harvesting crops, and self‐replicating plants. Developing standards that integrate current scientific methodologies and technologies with indigenous knowledge for agricultural growth and disaster management will bring the complementary benefits of both worlds into optimal development.
Envisioning Solidarity
Authors: Pacia Danielle 
Published: August 2023

AbstractAn underdiscussed dilemma in bioethics concerns individuals who are arguably owed health care resources yet actively refuse such essential goods. In twelve states—my home state among them—many people have refused to support the expansion of the Affordable Care Act, negatively affecting health outcomes for millions of people—including those that oppose the ACA. In the midst of strong political polarization, the value of solidarity may help guide America toward finding consensus, teaching us to acknowledge one another's needs so that we can live and build healthier lives together.
Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI
Authors: Karat Bradley G. , DeKraker Jordan , Hussain Uzair , Köhler Stefan , Khan Ali R. 
Published: August 2023

AbstractThe hippocampus is classically divided into mesoscopic subfields which contain varying microstructure that contribute to their unique functional roles. It has been challenging to characterize this microstructure with current magnetic resonance based neuroimaging techniques. In this work, we used diffusion magnetic resonance imaging (dMRI) and a novel surface‐based approach in the hippocampus which revealed distinct microstructural distributions of neurite density and dispersion, T1w/T2w ratio as a proxy for myelin content, fractional anisotropy, and mean diffusivity. We used the neurite orientation dispersion and density imaging (NODDI) model optimized for grey matter diffusivity to characterize neurite density and dispersion. We found that neurite dispersion was highest in the cornu ammonis (CA) 1 and subiculum subfields which likely captures the large heterogeneity of tangential and radial fibres, such as the Schaffer collaterals, perforant path, and pyramidal neurons. Neurite density and T1w/T2w were highest in the subiculum and CA3 and lowest in CA1, which may reflect known myeloarchitectonic differences between these subfields. Using a simple logistic regression model, we showed that neurite density, dispersion, and T1w/T2w measures were separable across the subfields, suggesting that they may be sensitive to the known variability in subfield cyto‐ and myeloarchitecture. We report macrostructural measures of gyrification, thickness, and curvature that were in line with ex vivo descriptions of hippocampal anatomy. We employed a multivariate orthogonal projective non‐negative matrix factorization (OPNNMF) approach to capture co‐varying regions of macro‐ and microstructure across the hippocampus. The clusters were highly variable along the medial–lateral (proximal–distal) direction, likely reflecting known differences in morphology, cytoarchitectonic profiles, and connectivity. Finally, we show that by examining the main direction of diffusion relative to canonical hippocampal axes, we could identify regions with stereotyped microstructural orientations that may map onto specific fibre pathways, such as the Schaffer collaterals, perforant path, fimbria, and alveus. These results highlight the value of combining in vivo dMRI with computational approaches for capturing hippocampal microstructure, which may provide useful features for understanding cognition and for diagnosis of disease states.
Distributed attribute representation in the superior parietal lobe during probabilistic decision‐making
Authors: Wang Pinchun , Chen Shuning , Deng Kun , Zhang Bin , Im Hohjin , Feng Junjiao , Liu Liqing , Yang Qinghao , Zhao Guang , He Qinghua , Chen Chunhui , Wang He , Wang Qiang 
Published: August 2023

AbstractSeveral studies have examined the neural substrates of probabilistic decision‐making, but few have systematically investigated the neural representations of the two objective attributes of probabilistic rewards, that is, the reward amount and the probability. Specifically, whether there are common or distinct neural activity patterns to represent the objective attributes and their association with the neural representation of the subjective valuation remains largely underexplored. We conducted two studies (nStudy1 = 34, nStudy2 = 41) to uncover distributed neural representations of the objective attributes and subjective value as well as their association with individual probability discounting rates. The amount and probability were independently manipulated to better capture brain signals sensitive to these two attributes and were presented simultaneously in Study 1 and successively in Study 2. Both univariate and multivariate pattern analyses showed that the brain activities in the superior parietal lobule (SPL), including the postcentral gyrus, were modulated by the amount of rewards and probability in both studies. Further, representational similarity analysis revealed a similar neural representation between these two objective attributes and between the attribute and valuation. Moreover, the SPL tracked the subjective value integrated by the hyperbolic function. Probability‐related brain activations in the inferior parietal lobule were associated with the variability in individual discounting rates. These findings provide novel insights into a similar neural representation of the two attributes during probabilistic decision‐making and perhaps support the common neural coding of stimulus objective properties and subjective value in the field of probabilistic discounting.