bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isotope Engineered Fluorinated Single and Bilayer Graphene: Insights into Fluorination Selectivity, Stability, and Defect Passivation
Authors: Thakur Mukesh Kumar , Haider Golam , Sonia Farjana J. , Plšek Jan , Rodriguez Alvaro , Mishra Vipin , Panda Jaganandha , Gedeon Ondrej , Mergl Martin , Volochanskyi Oleksandr , Valeš Václav , Frank Otakar , Vejpravova Jana , Kalbáč Martin 
Published: January 2023

AbstractTailoring the physicochemical properties of graphene through functionalization remains a major interest for next‐generation technological applications. However, defect formation due to functionalization greatly endangers the intrinsic properties of graphene, which remains a serious concern. Despite numerous attempts to address this issue, a comprehensive analysis has not been conducted. This work reports a two‐step fluorination process to stabilize the fluorinated graphene and obtain control over the fluorination‐induced defects in graphene layers. The structural, electronic and isotope‐mass‐sensitive spectroscopic characterization unveils several not‐yet‐resolved facts, such as fluorination sites and CF bond stability in partially‐fluorinated graphene (F‐SLG). The stability of fluorine has been correlated to fluorine co‐shared between two graphene layers in fluorinated‐bilayer‐graphene (F‐BLG). The desorption energy of co‐shared fluorine is an order of magnitude higher than the CF bond energy in F‐SLG due to the electrostatic interaction and the inhibition of defluorination in the F‐BLG. Additionally, F‐BLG exhibits enhanced light–matter interaction, which has been utilized to design a proof‐of‐concept field‐effect phototransistor that produces high photocurrent response at a time <200 µs. Thus, the study paves a new avenue for the in‐depth understanding and practical utilization of fluorinated graphenic carbon.
A Multilayered Mesoporous Gold Nanoarchitecture for Ultraeffective Near‐Infrared Light‐Controlled Chemo/Photothermal Therapy for Cancer Guided by SERS Imaging
Authors: Yin Bohan , Ho Willis Kwun Hei , Xia Xinyue , Chan Cecilia Ka Wing , Zhang Qin , Ng Yip Ming , Lam Ching Ying Katherine , Cheung James Chung Wai , Wang Jianfang , Yang Mo , Wong Siu Hong Dexter 
Published: January 2023

AbstractSurface‐enhanced Raman scattering (SERS) imaging has emerged as a promising tool for guided cancer diagnosis and synergistic therapies, such as combined chemotherapy and photothermal therapy (chemo‐PTT). Yet, existing therapeutic agents often suffer from low SERS sensitivity, insufficient photothermal conversion, or/and limited drug loading capacity. Herein, a multifunctional theragnostic nanoplatform consisting of mesoporous silica‐coated gold nanostar with a cyclic Arg‐Gly‐Asp (RGD)‐coated gold nanocluster shell (named RGD–pAS@AuNC) is reported that exhibits multiple “hot spots” for pronouncedly enhanced SERS signals and improved near‐infrared (NIR)‐induced photothermal conversion efficiency (85.5%), with a large capacity for high doxorubicin (DOX) loading efficiency (34.1%, named RGD/DOX–pAS@AuNC) and effective NIR‐triggered DOX release. This nanoplatform shows excellent performance in xenograft tumor model of HeLa cell targeting, negligible cytotoxicity, and good stability both in vitro and in vivo. By SERS imaging, the optimal temporal distribution of injected RGD/DOX–pAS@AuNCs at the tumor site is identified for NIR‐triggered local chemo‐PTT toward the tumor, achieving ultraeffective therapy in tumor cells and tumor‐bearing mouse model with 5 min of NIR irradiation (0.5 W cm−2). This work offers a promising approach to employing SERS imaging for effective noninvasive tumor treatment by on‐site triggered chemo‐PTT.
Dual‐strategy modification on P2‐Na0.67Ni0.33Mn0.67O2 realizes stable high‐voltage cathode and high energy density full cell for sodium‐ion batteries
Authors: Wan Guanglin , Peng Bo , Zhao Liping , Wang Feng , Yu Lai , Liu Rong , Zhang Genqiang 
Published: January 2023

AbstractP2‐type Na0.67Ni0.33Mn0.67O2 is considered as a potential cathode material for sodium‐ion batteries due to the merits of high voltage, low cost, and air stability. However, the unsatisfied cycling stability and rate performance caused by the destructive phase transition and side reactions hinder its practical application. Herein, we present a feasible dual strategy of Mg2+ doping integrated with ZrO2 surface modification for P2‐Na0.67Ni0.33Mn0.67O2, which can well address the issues of phase transition and side reactions benefitting from the enhanced structural and interfacial stabilities. Specifically, it exhibits a decent cycling stability with a capacity retention of 81.5% at 1 C and promising rate performance with a discharge capacity of 76.6 mA h g−1 at 5 C. The in situ X‐ray diffraction measurement confirms that the damaged P2–O2 phase transition is suppressed with better reversibility in high‐voltage region, whereas the side reactions are inhibited due to the protective ZrO2 surface modification. Commendably, the full cell achieves an outstanding operating voltage of 3.57 V and a fabulous energy density of 238.91 W h kg−1 at 36.73 W kg−1, demonstrating great practicability. This work is expected to provide a new insight for designing stable high‐voltage cathode materials and high energy density full cells for sodium ion batteries.
Analysis of an elastic–rigid obstacle problem described by a variational–hemivariational inequality
Authors: Wang Xilu , Ran Qinghua , Xiao Qichang 
Published: January 2023

AbstractIn this paper, we consider a new obstacle problem for the elastic membrane lying above an elastic–rigid obstacle. The elastic–rigid obstacle allows limited penetration and offers a nonmonotone reactive force. We introduce the mathematical model and prove that its weak form, which is a variational–hemivariational inequality, has a unique solution. Then, we consider a discrete scheme to solve the problem. The optimal‐order error estimate under appropriate regularity assumptions is derived. Finally, numerical examples are reported, from which the theoretical predicted optimal‐order error estimate can be clearly observed.
Compiler-Assisted Instrumentation Selection for Large-Scale C++ Codes
Authors: Kreutzer Sebastian , Iwainsky Christian , Lehr Jan-Patrick , Bischof Christian 
Published: January 2023

AbstractCode instrumentation is the primary method for collecting fine-grained performance data. As instrumentation introduces an inherent runtime overhead, it is essential to measure only those regions of the code which are most relevant to the analysis. In practice, the typical approach is to define filter lists manually. Prior projects aim to automate this process using static analysis. Specifically, InstRO enables tailored instrumentation via sophisticated user-defined selection of code regions. However, due to the need for whole-program call-graph analysis, its application on large-scale scientific codes is currently impractical. In this work, we present the new instrumentation tool CaPI (short for “Compiler-assisted Performance Instrumentation”), which is targeted towards such large-scale applications. We demonstrate its application on the CFD framework OpenFOAM. Our evaluation shows that a hybrid approach of CaPI and existing profile-guided filtering outperforms profile-guided filtering alone. Furthermore, we identify correctness and usability issues and propose possible avenues to improve CaPI, as well as compiler-assisted instrumentation tools in general.
Multistage s–t Path: Confronting Similarity with Dissimilarity
Authors: Fluschnik Till , Niedermeier Rolf , Schubert Carsten , Zschoche Philipp 
Published: January 2023

AbstractAddressing a quest by Gupta et al. (in: Proceedings of the 41st international colloquium on automata, languages, and programming (ICALP 2014), vol 8572 of LNCS. Springer, pp 563–575, 2014), we provide a first, comprehensive study of finding a short s–t path in the multistage graph model, referred to as the Multistages–tPath problem. Herein, given a sequence of graphs over the same vertex set but changing edge sets, the task is to find short s–t paths in each graph (“snapshot”) such that in the found path sequence the consecutive s–t paths are “similar”. We measure similarity by the size of the symmetric difference of either the vertex set (vertex-similarity) or the edge set (edge-similarity) of any two consecutive paths. We prove that these two variants of Multistages–tPath are already $${\text {NP}}$$
NP
-hard for an input sequence of only two snapshots and maximum vertex degree four. Motivated by this fact and natural applications of this scenario e.g. in traffic route planning, we perform a parameterized complexity analysis. Among other results, for both variants, vertex- and edge-similarity, we prove parameterized hardness ($${\text {W[1]}}$$
W[1]
-hardness) regarding the parameter path length (solution size). As a further conceptual investigation, we then modify the multistage model by asking for dissimilar consecutive paths. As one of the main technical results (employing so-called representative sets known from non-temporal settings), we prove that dissimilarity allows for fixed-parameter tractability for the parameter solution size, contrasting with our W[1]-hardness proof of the corresponding similarity case. We also provide partially positive results concerning efficient and effective data reduction (kernelization).
Predation risk and landscape properties shape reproductive output of an endangered sea duck from two subpopulations with contrasting predation risk
Authors: Hermansson Ida , von Numers Mikael , Jaatinen Kim , Öst Markus 
Published: January 2023

AbstractPredation is the leading cause of avian reproductive failure and theory predicts clutch size reduction under high nest predation risk. However, the impact of nest predation on population dynamics is debated, and spatiotemporal variation in reproductive output is poorly understood due to the predominance of short-term, single-site studies. To this end, we investigated how island geography (size, forest cover, isolation), predation risk (White-tailed EagleHaliaeetus albicillaabundance), climate (migration phenology, winter severity) and time trends affected early breeding success (inverse of early predation rate) and clutch size of endangered Baltic Common Eiders (Somateria mollissima). The study was conducted at two close sites (Tvärminne, Velkua) during 1991–2020. Local breeding numbers showed a similar annual decline. Interestingly, fecundity components were negatively correlated across sites: early breeding success was higher in Velkua and clutch size in Tvärminne. Island forest cover and exposure were the best determinants of early breeding success and clutch size (with only weak explanatory power for clutch size), but their effects were mediated by differential susceptibility to eagle predation risk. Clutch size increased in Tvärminne but decreased in Velkua. The former finding likely reflects increased breeder phenotypic quality due to selective disappearance at this high-predation site, whereas the latter finding may indicate increasingly compromised food intake. Only at the high-risk site did clutch size show the expected decline with increasing eagle predation risk, and the expected increase with increasing overhead protection (forest cover). We identify the least exposed forested islands, associated with the highest productivity, as prime targets of conservation.
Computational Performance of Deep Reinforcement Learning to Find Nash Equilibria
Authors: Graf Christoph , Zobernig Viktor , Schmidt Johannes , Klöckl Claude 
Published: January 2023

AbstractWe test the performance of deep deterministic policy gradient—a deep reinforcement learning algorithm, able to handle continuous state and action spaces—to find Nash equilibria in a setting where firms compete in offer prices through a uniform price auction. These algorithms are typically considered “model-free” although a large set of parameters is utilized by the algorithm. These parameters may include learning rates, memory buffers, state space dimensioning, normalizations, or noise decay rates, and the purpose of this work is to systematically test the effect of these parameter configurations on convergence to the analytically derived Bertrand equilibrium. We find parameter choices that can reach convergence rates of up to 99%. We show that the algorithm also converges in more complex settings with multiple players and different cost structures. Its reliable convergence may make the method a useful tool to studying strategic behavior of firms even in more complex settings.
CenterLoc3D: monocular 3D vehicle localization network for roadside surveillance cameras
Authors: Tang Xinyao , Wang Wei , Song Huansheng , Zhao Chunhui 
Published: January 2023

AbstractMonocular 3D vehicle localization is an important task for vehicle behaviour analysis, traffic flow parameter estimation and autonomous driving in Intelligent Transportation System (ITS) and Cooperative Vehicle Infrastructure System (CVIS), which is usually achieved by monocular 3D vehicle detection. However, monocular cameras cannot obtain depth information directly due to the inherent imaging mechanism, resulting in more challenging monocular 3D tasks. Currently, most of the monocular 3D vehicle detection methods still rely on 2D detectors and additional geometric constraint modules to recover 3D vehicle information, which reduces the efficiency. At the same time, most of the research is based on datasets of onboard scenes, instead of roadside perspective, which is limited in large-scale 3D perception. Therefore, we focus on 3D vehicle detection without 2D detectors in roadside scenes. We propose a 3D vehicle localization network CenterLoc3D for roadside monocular cameras, which directly predicts centroid and eight vertexes in image space, and the dimension of 3D bounding boxes without 2D detectors. To improve the precision of 3D vehicle localization, we propose a multi-scale weighted-fusion module and a loss with spatial constraints embedded in CenterLoc3D. Firstly, the transformation matrix between 2D image space and 3D world space is solved by camera calibration. Secondly, vehicle type, centroid, eight vertexes, and the dimension of 3D vehicle bounding boxes are obtained by CenterLoc3D. Finally, centroid in 3D world space can be obtained by camera calibration and CenterLoc3D for 3D vehicle localization. To the best of our knowledge, this is the first application of 3D vehicle localization for roadside monocular cameras. Hence, we also propose a benchmark for this application including a dataset (SVLD-3D), an annotation tool (LabelImg-3D), and evaluation metrics. Through experimental validation, the proposed method achieves high accuracy with $$A{P_{3D}}$$

A

P

3
D

of 51.30%, average 3D localization precision of 98%, average 3D dimension precision of 85% and real-time performance with FPS of 41.18.
A combined synchronization index for evaluating collective action social media
Authors: Ng Lynnette Hui Xian , Carley Kathleen M. 
Published: January 2023

AbstractSocial media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided by inorganic synchronization, which arise from bot actors. It is thus important to identify the synchronicity of emerging discourse on social media and the indications of organic/inorganic activity within the conversations. This provides a way of profiling an event for possibility of offline protests and violence. In this study, we build on past definitions of synchronous activity on social media— simultaneous user action–and develop a Combined Synchronization Index (CSI) which adopts a hierarchical approach in measuring user synchronicity. We apply this index on six political and social activism events on Twitter and analyzed three action types: synchronicity by hashtag, URL and @mentions.The CSI provides an overall quantification of synchronization across all action types within an event, which allows ranking of a spectrum of synchronicity across the six events. Human users have higher synchronous scores than bot users in most events; and bots and humans exhibits the most synchronized activities across all events as compared to other pairs (i.e., bot-bot and human-human). We further rely on the harmony and dissonance of CSI-Network scores with network centrality metrics to observe the presence of organic/inorganic synchronization. We hope this work aids in investigating synchronized action within social media in a collective manner.
A perspective on biodiversity data and applications for spatio-temporally robust spatial planning for area-based conservation
Authors: Takashina Nao , Kusumoto Buntarou 
Published: January 2023

AbstractThe growing availability of high-resolution biodiversity data is enhancing our ability to implement biodiversity conservation more effectively. Spatial planning has widely utilized such fine-scale biodiversity data, and proposals of finely-organized protected area networks have been increasing. However, a naive adoption of such fine-scale data for conservation may not only degrade the utility of the data, but may even risk reduction of long-term efficacy of conservation efforts. This is due to inherent tradeoffs between the efficacy of conservation actions over short-term and its persistence over long-term that is characterized by the management scale of spatial planning associated with the resolution of the data used. To demonstrate this argument, the spatiotemporal ecosystem dynamics must be described, but such discussions are limited in the literature. Here, we discuss the potential issues associated with naive uses of fine-scale biodiversity data to establish fine-tuned spatial planning. We then emphasize the importance of matching the data resolution with an appropriate scale of spatial planning that is realized by transforming the data resolution. This method is readily applicable for widely used decision-support tools for spatial planning. A simple worked example is provided to demonstrate its utility with a long-term conservation efficacy in spatial planning. Guided by the recent explosion of biological data, our discussion provides new insights into the ways to maximize the utility of these data, and further improve biodiversity conservation.
Experimental study on supercritical carbon dioxide gasification of biomass
Authors: Zhou Chenchen , Ge Zhiwei , Wang Yu , Shang Fei , Guo Liejin 
Published: January 2023

AbstractWith the excessive use of fossil energy and concern for environmental protection, biomass gasification as an effective means of biomass energy utilization has received widespread attention worldwide. Supercritical carbon dioxide (SCCO2) (T ≥ 31.26 °C, P ≥ 72.9 atm) has the advantages of near liquid density and high solubility, and the supercritical carbon dioxide gasification of biomass will be a promising technology. However, there has been no research on the technology at present. In this work, experimental study on supercritical carbon dioxide gasification of biomass were carried out in a batch reactor. The influences of temperature, residence time, the amount of carbon dioxide and catalyst on gas yield and fraction were investigated. Experimental results showed that the gas yield and carbon gasification efficiency (CE) of biomass gasification increased with increasing temperature, reaction time or the amount of carbon dioxide. As the gasification temperature increased from 700 °C to 900 °C, the gas yield increased from 23.53 to 50.24 mol/kg biomass and CE increased from 47.26% to 94.53% in CO2 atmosphere at 30 min. The gasification efficiency of biomass was greatly improved with catalyst, and the effect of impregnated catalyst was better than that of mechanical mixing. The gas yield increased from 23.72 to 50.24 mol/kg biomass with the increasing of the equivalent ratio from 0 to 1 at 900 °C and 30 min. Finally, a detailed supercritical carbon dioxide gasification mechanism of biomass was proposed.
Exploring the activities and outcomes of digital teaching and learning of practical skills in higher education for the social and health care professions: a scoping review
Authors: Söderlund Anne , Blazeviciene Aurelija , Elvén Maria , Vaskelyte Alina , Strods Raimonds , Blese Inguna , Paakkonen Heikki , Fernandes Antonio , Cardoso Daniela , Kav Sultan , Baskici Cigdem , Wiktsröm-Grotell Camilla 
Published: January 2023

AbstractHigher education for health care professionals faces numerous challenges. It is important to develop and apply methods supporting education, especially the practical skills. This scoping review aimed to explore the activities and learning outcomes of digital technology in practical skills teaching and learning in higher education for the social and health professions. Scoping review recommendations and the PRISMA-ScR checklist were applied. Randomized controlled trials published between 2016 and 2021 involving students in higher education who were taking courses in the social sciences and health care and reported interventions with digital technology activities and practices in practical teaching and learning were included. The CINAHL Plus, PubMed, Scopus, ERIC, and Sociological Abstracts/Social Services Abstracts databases were searched. Teaching methods were blended, e-learning or other online-based, and digital simulation-based activities. Teaching and learning environments, methods, resources, and activity characteristics varied, making a summary difficult. Interventions were developed in a face-to-face format prior to digitalization. The outcomes were measured at the knowledge level, not at the performance level. One-third of the studies showed a significant improvement in practical skills in the intervention group in comparison to the control conditions. The use of digital technology in the learning and teaching process have potential to develop of students' skills, knowledge, motivation, and attitudes. The pedagogy of technology use is decisive. The development of new digital methods for teaching and learning practical skills requires the engagement of students and teachers, in addition the researchers.
Granular flows in drums of non-uniform widths
Authors: Hung Chi-Yao , Chen Tzu-Yin Kasha , Wang I-Hsuan , Hill Kimberly M. 
Published: January 2023

We study how channel width variations influence the dynamics of free-surface granular flows. For this purpose, we extend a continuum model framework to granular flows passing through channels that narrow or widen. Our theory uses a linearized approximation to an established dense granular flow rheology and a Coulomb friction law to model interaction between flow and sidewalls. We test the theoretical predictions using two novel 40 cm-diameter drums (convex and concave) filled halfway with 2 mm diameter particles rotated at rates in which the shear layer remains shallow and dense. We apply particle tracking velocimetry to enable quantitative comparisons between experimental data and theoretical predictions. We find that our experimental kinematics and energy profiles largely agree with the theoretical predictions. In general, flows through narrowing channels are faster and deeper than flows through widening channels. The influence of width variations grows with increasing flow speed, and the form of the rate dependence changes fundamentally as the regime changes from one in which kinetic energy is dissipated locally to one in which it is advected downstream. For both regimes, theoretical scaling analysis leads us to experimentally validated power laws, in which the exponent depends on the flow regime, and the multiplicative coefficient depends on channel geometry alone. Finally, we discuss how the differences between theoretical predictions and experimental data may be useful for improving our understanding of flows through non-uniform channels.