bluuebunny/crossref_metadata_2025_split huggingface dataset:
Containment control of networked heterogeneous autonomous surface vehicles: A data‐driven control approach
Authors: Weng Yongpeng , Dai Zijie , Qi Wenhai , Hao Liying 
Published: March 2024

AbstractIn this article, by creating a novel distributed full‐form dynamic linearization based model‐free adaptive containment control (FFDL‐MFACC) approach, the containment control problem of networked heterogeneous autonomous surface vehicles (ASVs), suffering from complex external disturbances and unavailable kinetic model‐information, is resolved. In light of the data‐driven strategy, a full‐form dynamic linearization‐based data model is efficiently established. Then, by further deploying the commonly used rotation matrix, a distributed FFDL‐MFACC scheme is thereafter developed such that accurate tracking of a predefined convex hull spanned for all follower vehicles can be achieved. Afterwards, a disturbance observer is further designed to accurately estimate the lumped disturbances and the estimation is served as a compensation within the distributed full‐form dynamic linearization. Rigorously theoretical analysis indicates the devised distributed FFDL‐MFACC method can ensure the asymptotic containment tracking of networked heterogeneous ASVs. Finally, simulation results are illustrated to verify the advantages of the devised approach.
Environmental DNA time series analysis of a temperate stream reveals distinct seasonal community and functional shifts
Authors: Sander Mandy , Beermann Arne J. , Buchner Dominik , Madge Pimentel Iris , Sinclair James S. , Weiss Martina , Haase Peter , Leese Florian 
Published: March 2024

AbstractEnvironmental DNA (eDNA) extracted from water is routinely used in river biodiversity research, and via metabarcoding eDNA can provide comprehensive taxa lists with little effort and cost. However, eDNA‐based species detection in streams and rivers may be influenced by sampling season and other key factors such as water temperature and discharge. Research linking these factors and also informing on the potential of eDNA metabarcoding to detect shifts in ecological signatures, such as species phenology and functional feeding groups across seasons, is missing. To address this gap, we collected water samples every 2 weeks for 15 months at a long‐term ecological research (LTER) site and at three different positions in the river's cross section, specifically the water surface, riverbed, and riverbank. For these 102 samples, we analyzed macroinvertebrate species and molecular operational taxonomic unit (OTU) richness and temporal community turnover across seasons based on cytochrome c oxidase subunit I (COI) metabarcoding data. Using Generalized Additive Models, we found a significant influence of sampling season on species richness. Community turnover followed a cyclic pattern, reflecting the continuous change of the macroinvertebrate community throughout the year (“seasonal clock”). Although water temperature had no influence on the inferred species richness, higher discharge reduced the number of Annelida and Ephemeroptera species detectable with eDNA. Most macroinvertebrate taxa showed the highest species richness in spring, in particular merolimnic species with univoltine life cycles. Further, we detected an increase in the proportion of shredders in winter and parasites in summer. Our results show the usefulness of highly resolved eDNA metabarcoding time series data for ecological research and biodiversity monitoring in streams and rivers.
Online learning for streaming data classification in nonstationary environments
Authors: Gai Yujie , Meng Kang , Wang Xiaodi 
Published: March 2024

AbstractIn this article, we implement the classification of nonstationary streaming data. Due to the inability to obtain full data in the context of streaming data, we adopt a strategy based on clustering structure for data classification. Specifically, this strategy involves dynamically maintaining clustering structures to update the model, thereby updating the objective function for classification. Simultaneously, incoming samples are monitored in real‐time to identify the emergence of new classes or the presence of outliers. Moreover, this strategy can also deal with the concept drift problem, where the distribution of data changes with the inflow of data. Regarding the handling of novel instances, we introduce a buffer analysis mechanism to delay their processing, which in turn improves the prediction performance of the model. In the process of model updating, we also introduce a novel renewable strategy for the covariance matrix. Numerical simulations and experiments on datasets show that our method has significant advantages.
Amine‐ and Polyethylene glycol‐Functionalized Pyrediyne Quantum Dots for Bioimaging Applications
Authors: Arya Jyothibabu Sajila , Vasudha T. K. , Muthuvijayan Vignesh , Prasad Edamana 
Published: March 2024

AbstractPyrediyne, a recent addition to the 2D organic nanomaterials family, is known for its improved electrical conductivity, which can have potential applications in the performance of thin film transistors, field effect transistors, and charge storage devices. It has been shown that similar to carbon quantum dots, pyrediyne quantum dots (PDYQDs) can also be generated from 2D pyrediyne nanosheets and can be utilized for imaging cancer cells. In this context, it is highly desirable to enhance the photoluminescence properties of PDYQDs in order to improve the quality of quantum dots‐based cell imaging techniques. Herein, PDYQDs are effectively functionalized using aqueous functionalization agents such as NH3, PEG200, and PEG20000 via a simple and cost‐effective methodology, which resulted in a significant enhancement in the emission quantum yield (QY) (up to 30.2 %) through effectively reducing the non‐radiative recombination centers. After confirming their cytocompatibility using in vitro studies, the amine‐functionalized PDYQDs were utilized for imaging L929 mouse fibroblast cells. The findings in the present study suggest that it is worth exploring various surface functionalization techniques to enhance the applications of novel carbon‐based nano‐structures in various biological and optoelectronic devices.
Regulating Electron Filling and Orbital Occupancy of Anti‐Bonding States of Transition Metal Nitride Heterojunction for High Areal Capacity Lithium–Sulfur Full Batteries
Authors: Liu Jintao , Yu Lianghao , Ran Qiwen , Chen Xi'an , Wang Xueyu , He Xuedong , Jin Huile , Chen Tao , Chen Jun Song , Guo Daying , Wang Shun 
Published: March 2024

AbstractThe commercialization of lithium–sulfur (Li–S) battery is seriously hindered by the shuttle behavior of lithium (Li) polysulfide, slow conversion kinetics, and Li dendrite growth. Herein, a novel hierarchical p‐type iron nitride and n‐type vanadium nitride (p‐Fe2N/n‐VN) heterostructure with optimal electronic structure, confined in vesicle‐like N‐doped nanofibers (p‐Fe2N/n‐VN⊂PNCF), is meticulously constructed to work as “one stone two birds” dual‐functional hosts for both the sulfur cathode and Li anode. As demonstrated, the d‐band center of high‐spin Fe atom captures more electrons from V atom to realize more π* and moderate σ* bond electron filling and orbital occupation; thus, allowing moderate adsorption intensity for polysulfides and more effective d–p orbital hybridization to improve reaction kinetics. Meanwhile, this unique structure can dynamically balance the deposition and transport of Li on the anode; thereby, more effectively inhibiting Li dendrite growth and promoting the formation of a uniform solid electrolyte interface. The as‐assembled Li–S full batteries exhibit the conspicuous capacities and ultralong cycling lifespan over 2000 cycles at 5.0 C. Even at a higher S loading (20 mg cm−2) and lean electrolyte (2.5 µL mg−1), the full cells can still achieve an ultrahigh areal capacity of 16.1 mAh cm−2 after 500 cycles at 0.1 C.
Hydrogen‐Bonded Metal–Organic Framework Nanosheet as a Proton Conducting Membrane for an H2/O2 Fuel Cell
Authors: Pathak Agamoni , Watanabe Haruki , Manna Biplab , Hatakeyama Kazuto , Ida Shintaro 
Published: March 2024

AbstractProton‐conducting metal–organic frameworks (MOFs) have attracted attention as potential electrolytes for fuel cells. However, research progress in utilizing MOFs as electrolytes for fuel cells has been limited, mainly due to challenges associated with issues such as the fabrication of MOF membranes, and hydrogen crossover through the MOF's pores. Here, proton conductivity and fuel cell performance of a self‐standing membrane prepared from of a bismuth subgallate MOF nanosheets with non‐porous structure are reported. The fabricated MOF nanosheet membrane with no binding agent exhibits structural anisotropy. The proton conductivity in the membrane thickness direction (4.4 × 10−3 S cm−1) at 90 °C and RH 100% is observed to be higher than that in the in‐plane direction of the membrane (3.3 × 10−5 S cm−1). The open circuit voltage (OCV) of a fuel cell with ≈120 µm proton conducting membrane is 1.0 V. The non‐porous nature of the MOF nanosheets contributes to the relatively high OCV. A fuel cell using ≈40 µm membrane as proton conducting electrolyte records a maximum of 25 mW cm−2 power density and a maximum of 109 mA cm−2 current density with 0.91 V OCV at 80 °C in humid conditions.
The Effect of Multi‐Fields Synergy from Electric/Light/Thermal/Force Technologies on Photovoltaic Performance of Ba0.06Bi0.47Na0.47TiO3 Ferroelectric Ceramics via the Mg/Co Substitution at A/B Sites
Authors: Gao Qingyuan , Yang Shanming , Yuan Changlai , Liu Xiao , Zhao Jingtai , Rao Guanghui , Zhou Changrong , Xu Jiwen , Zhu Baohua , Lei Wen 
Published: March 2024

AbstractCurrently, it is widely reported that the photovoltaic effect in ferroelectric materials can be promoted by the application of a piezoelectric force, an external electric field, and intense light illumination. Here, a semiconducting ferroelectric composition is introduced, (1−x) Ba0.06Bi0.47Na0.47TiO3‐xMgCoO3 (abbreviated as xMgCo, where x = 0.02–0.08), synthesized through Mg/Co ions codoping. This process effectively narrows the optical bandgaps to a spectrum of 1.38–3.06 eV. Notably, the system exhibits a substantial increase in short‐circuit photocurrent density (Jsc), by the synergy of the electric, light, and thermal fields. The Jsc can still be further enhanced by the extra introduction of a force field. Additionally, the Jsc also shows an obvious increase after the high field pre‐poling. The generation of a considerable number of oxygen vacancies due to the Co2+/Co3+ mixed valence state (in a 1:3 ratio) contributes to the reduced optimal bandgap. The integration of Mg2+ ion at the A‐site restrains the loss and sustains robust ferroelectricity (Pr = 24.1 µC cm−2), high polarizability under an electric field, and a significant piezoelectric coefficient (d33 = 102 pC N−1). This study provides a novel perspective on the physical phenomena arising from the synergy of multiple fields in ferroelectric photovoltaic materials.
Prediction of potential targets and toxicological insights of Astragalus in liver cancer based on network pharmacology: Integrating systems biology, drug interaction networks, and toxicological perspectives
Authors: Zou Minjun , Zheng Zhiye , Xiahou Zhikai , Cao Jianwei 
Published: March 2024

AbstractThis study investigates Astragalus's efficacy as a novel therapeutic option for primary liver cancer (PLC), capitalizing on its anti‐inflammatory and antiviral effects. We utilized network pharmacology to unveil Astragalus's potential targets against PLC, revealing significant gene expression alterations in treated samples—20 genes were up‐regulated, and 20 were down‐regulated compared to controls. Our analysis extended to single‐cell resolution, where we processed scRNA‐seq data to discern 15 unique cell clusters within the immune, malignant, and stromal compartments through advanced algorithms like UMAP and tSNE. To delve deeper into the functional implications of these gene expression changes, we conducted comprehensive gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, alongside Gene Set Variation Analysis, to elucidate the biological processes and pathways involved. Further, we constructed protein–protein interaction networks to visualize the intricate molecular interplay, highlighting the down‐regulation of MT1E in PLC cells, a finding corroborated by quantitative polymerase chain reaction. Molecular docking studies affirmed the potent interaction between Astragalus's active compounds and MT proteins, underscoring a targeted therapeutic mechanism. Our investigation also encompassed a detailed cellular landscape analysis, identifying nine cell subgroups related to MT1 expression and specifying five cell subsets through the SingleR package. Advanced trajectory and cell–cell interaction analyses offered deeper insights into the dynamics of MT1‐associated cellular subpopulations. This comprehensive methodology not only underpins Astragalus's promising role in PLC treatment but also advances our understanding of its molecular and cellular mechanisms, paving the way for targeted therapeutic strategies.
Navigating colorectal cancer prognosis: A Treg‐related signature discovered through single‐cell and bulk transcriptomic approaches
Authors: Lv Xuening , Ma Wen , Miao Xiaye , Hu Shaohui , Xie Huaibing 
Published: March 2024

AbstractBackgroundThe significance of regulatory T cells (Tregs) in colorectal cancer is unclear.MethodsThe single‐cell sequencing data for colorectal cancer, specifically GSE132465 and GSE188711, were retrieved from the GEO database. Simultaneously, bulk transcriptome data were obtained from the UCSC Xena website. To delve into the heterogeneity of Treg cells and identify key genes at the single‐cell sequencing level, we employed dimensionality reduction techniques alongside clustering and conducted differential expression gene analysis. For the bulk transcriptome data, we utilized weighted co‐expression network analysis to investigate critical gene modules. Additionally, we employed COX regression and Lasso regression methodologies to construct prognostic models, thereby assessing patient outcomes. To facilitate outcome evaluation, nomograms were constructed. The integration of these diverse approaches aims to comprehensively study colorectal cancer, encompassing single‐cell heterogeneity, key gene identification, and prognosis modeling using both single‐cell and bulk transcriptome data. Polymerase chain reaction (PCR) experiments are used to verify mRNA expression levels of key genes. The analysis software was R software (version 4.3.2).ResultsThrough single‐cell sequencing analysis and bulk transcriptome analysis, we constructed a prognostic model composed with Treg‐associated signatures. The high‐risk group demonstrated significantly worse prognosis compared with the low‐risk group, highlighting the clinical relevance of our models. PCR confirmed that the key gene DEAH‐box helicase 15 (DHX15) was significantly overexpressed in colorectal cancer.ConclusionsThe prognostic models developed in this study offer a potential tool for risk assessment, guiding treatment decisions for colorectal cancer patients.
Reducing post‐operative length of stay, is it worth the effort?
Authors: Hashmi Syeda Amrah , Raja Mohummad Hassan Raza , Arif Aiman , Naseem Zehra , Pal Khawaja Muhammad Babar , Pal Khawaja Muhammad Inam 
Published: March 2024

AbstractBackgroundStudies show that reducing the length of hospital stay (LOS) for surgical patients leads to cost savings. We hypothesize that LOS has a nonlinear relationship to cost of care and reduction may not have a meaningful impact on it. We have attempted to define the relationship of LOS to cost of care. We utilized the itemized bill, generated in real time, for hospital services.MaterialsAdult patients admitted under General, Neuro, and Orthopedic surgery over a 3‐month period, with an LOS between 4 and 14 days, were the study population. Itemized bill details were analyzed. Charges in Pakistani rupees were converted to US dollar. Ethical exemption for study was obtained.ResultsOf the 853 patients, 38% were admitted to General Surgery, 27% to Neurosurgery, and 35% to Orthopedics. A total of 64% of the patients had an LOS between 4 and 6 days; 36% had an LOS between 7 and 14 days. Operated and conservatively managed constituted 82% and 18%, respectively. Mean total charge for operated patients was higher $3387 versus $1347 for non‐operated ones. LOS was seen to have a nonlinear relationship to in‐hospital cost of care. The bulk of cost was centered on the day of surgery. This was consistent across all services. The last day of stay contributed 2.4%–3.2% of total charge.ConclusionsFor surgical patients, the cost implications rapidly taper in the postoperative period. The contribution of the last day of stay cost to total cost is small. For meaningful cost containment, focus needs to be on the immediate perioperative period.
Electroosmotic microchannel flow of blood conveying copper and cupric nanoparticles: Ciliary motion experiencing entropy generation using backpropagated networks
Authors: Sharma Parikshit , Sharma Bhupendra K. , Mishra Nidhish K. , Almohsen Bandar , Bhatti Muhammad M. 
Published: March 2024

AbstractA novel mathematical model for a hybrid (Cu–CuO/blood) Jeffrey nanofluid passing a vertical symmetric microchannel along with an electroosmosis pump is presented. The focuses on the advancement of mathematical modeling techniques, its comprehensive analysis of microfluidic system dynamics, and its potential to inform the optimal design of devices using nanofluids with broad applications in various fields. Arrhenius's law is used to analyze endothermic–exothermic reactions and activation energy. The governing partial differential equations of the fixed frame are transformed into ordinary differential equations of the wave frame using self‐similarity transformations. Low Reynolds number and long‐wavelength approximations helped to find solutions of the equations by applying a suitable BVP solver in MATLAB. The fluid's velocity, temperature, concentration, and electroosmosis properties are studied graphically. Two‐dimensional contour plots of fluid velocity and three‐dimensional surface plots of fluid properties are discussed. Physically significant quantities of mass transfer rate, skin friction coefficient, entropy generation, and heat transfer rate are studied using contour plots. Artificial neural network simulation using Bayesian regularization backpropagation algorithms is analyzed for training state, error histogram, fit, performance, and regression plots. Conclusively, the comprehensive analysis of the fluid dynamics, entropy generation, mass and heat transfer, and in the microchannel, coupled with the successful implementation of artificial neural network simulation, contributes to an improved understanding of the system's behavior. Entropy generation was raised for enhanced Brownian motion number and reduced values of thermophoresis, activation energy, and endothermic–exothermic reaction parameters. This study's results can be used to improve the efficiency and effectiveness of microfluidic devices used in fields as diverse as electrical cooling and medicine delivery.
Introduction: Towards a Circular Economy Strategy in the Valencian Region’s Tourism Industry
Authors: Segarra-Oña Marival , Santamarina-Campos Virginia 
Published: March 2024

AbstractAlthough the tourism industry is a cornerstone of the Valencian Region’s economy, it generates a variety of environmental impacts that require robust management and the implementation of measures to mitigate them. To address this issue, an innovative project entitled “Creation of an Innovation Platform for the Promotion and Implementation of a Circular Economy Strategy in the Valencian Region’s Tourism Industry” has been devised.
Impact Culture and the Circular Economy in the Tourism Industry: An Analysis of Challenges and Recommendations for Sustainability
Authors: Santamarina-Campos Virginia , Mas-Gil Miguel Ángel , de-Miguel-Molina María , Catalá-Pérez Daniel 
Published: March 2024

AbstractThis chapter examines the relevance of the circular economy in the tourism industry, highlighting how this model can mitigate environmental and social impacts, promote sustainability and improve competitiveness. Recommendations for the implementation of a circular economy strategy in the Valencian Region’s tourism industry are presented through a Participatory Action Research (PAR) process. The importance of an impact culture in the transition to a circular economy is also highlighted.
The three-pion K-matrix at NLO in ChPT
Authors: Baeza-Ballesteros Jorge , Bijnens Johan , Husek Tomáš , Romero-López Fernando , Sharpe Stephen R. , Sjö Mattias 
Published: March 2024

Abstract
The three-particle K-matrix, $$ \mathcal{K} $$
K
df,3, is a scheme-dependent quantity that parametrizes short-range three-particle interactions in the relativistic-field-theory three-particle finite-volume formalism. In this work, we compute its value for systems of three pions in all isospin channels through next-to-leading order in Chiral Perturbation Theory, generalizing previous work done at maximum isospin. We obtain analytic expressions through quadratic order (or cubic order, in the case of zero isospin) in the expansion about the three-pion threshold.
Eclectic flavor group ∆(27) ⋊ S3 and lepton model building
Authors: Li Cai-Chang , Ding Gui-Jun 
Published: March 2024

Abstract
We have performed a systematical study of the eclectic flavor group ∆(27) ⋊ S3 which is the extension of the traditional flavor symmetry ∆(27) by the finite modular symmetry S3. Consistency between ∆(27) and S3 requires that the eight nontrivial singlet representations of ∆(27) should be arranged into four reducible doublets. The modular transformation matrices are determined for various ∆(27) multiplets, and the CP-like symmetry compatible with ∆(27) ⋊ S3 are discussed. We study the general form of the Kähler potential and superpotential invariant under ∆(27) ⋊ S3, and the corresponding fermion mass matrices are presented. We propose a bottom-up model for lepton masses and mixing based on ∆(27) ⋊ S3, a numerical analysis is performed and the experimental data can be accommodated.
Mutual-Visibility Sets in Cartesian Products of Paths and Cycles
Authors: Korže Danilo , Vesel Aleksander 
Published: March 2024

AbstractFor a given graph G, the mutual-visibility problem asks for the largest set of vertices $$M \subseteq V(G)$$

M
⊆
V
(
G
)

with the property that for any pair of vertices $$u,v \in M$$

u
,
v
∈
M

there exists a shortest u, v-path of G that does not pass through any other vertex in M. The mutual-visibility problem for Cartesian products of a cycle and a path, as well as for Cartesian products of two cycles, is considered. Optimal solutions are provided for the majority of Cartesian products of a cycle and a path, while for the other family of graphs, the problem is completely solved.