bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atomically Precise Gold Nanoclusters: Towards an Optimal Biocompatible System from a Theoretical–Experimental Strategy
Authors: Matus María Francisca , Häkkinen Hannu 
Published: February 2021

AbstractPotential biomedical applications of gold nanoparticles have increasingly been reported with great promise for diagnosis and therapy of several diseases. However, for such a versatile nanomaterial, the advantages and potential health risks need to be addressed carefully, as the available information about their toxicity is limited and inconsistent. Atomically precise gold nanoclusters (AuNCs) have emerged to overcome this challenge due to their unique features, such as superior stability, excellent biocompatibility, and efficient renal clearance. Remarkably, the elucidation of their structural and physicochemical properties provided by theory–experiment investigations offers exciting opportunities for site‐specific biofunctionalization of the nanoparticle surface, which remains a significant concern for most of the materials in the biomedical field. This concept highlights the advantages conferred by atomically precise AuNCs for biomedical applications and the powerful strategy combining computational and experimental studies towards finding an optimal biocompatible AuNCs‐based nanosystem.
The Role of Dendritic Mesoporous Silica Nanoparticles’ Size for Quantum Dots Enrichment and Lateral Flow Immunoassay Performance
Authors: Gao Fang , Liu Yang , Lei Chang , Liu Chao , Song Hao , Gu Zhengying , Jiang Pei , Jing Sheng , Wan Jingjing , Yu Chengzhong 
Published: February 2021

AbstractUsing dendritic mesoporous silica nanoparticles (DMSNs) for quantum dots (QDs) enrichment and signal amplification is an emerging strategy for improving the detection sensitivity of lateral flow immunoassay (LFIA). In this study, a new and convenient approach is developed to prepare water‐dispersible DMSNs‐QDs. A series of DMSNs with various diameters (138, 251, 368, and 471 nm) are studied for loading QDs and LFIA applications. The resultant water‐dispersible DMSNs‐QDs exhibit a high fluorescence retention of 81.8%. The increase in particle size from 138 to 471 nm results in an increase in loading capacity of QDs and a decrease in binding quantity of the DMSNs‐QDs in the test line of LFIA. This trade‐off leads to an optimal DMSNs‐QDs size of 368 nm with a limit of detection reaching 10 pg mL−1 (equivalent to 9.0 × 10−14 m) for the detection of C‐reactive protein, which is nearly an order of magnitude more sensitive than the literature. To the best of the authors’ knowledge, this study is the first to demonstrate the distinctive role of DMSN's size for QDs enrichment and LFIA. The strategy developed from this work is useful for the rational design of high‐quality QDs‐based nanoparticles for ultrasensitive detection.
Escaping the long arm of the law? Racial disparities in the effect of drivers' license suspensions on offense probabilities
Authors: Mughan Siân , Carroll Joanna 
Published: February 2021

AbstractThis article studies the unintended consequences of failure‐to‐pay (FTP) drivers' license suspensions. Unlike other traffic enforcement papers that focus on the public benefit to increases in enforcement, we focus on the private returns. Drawing on a unique administrative data set and institutional features that result in as‐good‐as random assignment of FTP suspension, we estimate the effect of these suspensions on the probability a driver receives additional tickets. We find that financial penalties and FTP suspensions reduce the probability of reoffense for White drivers. However, among Black drivers, financial penalties have no effect and FTP suspension increases the probability of reoffense by 6‐9 percentage points. A series of additional analyses fail to produce evidence of racial differences in drivers' responses to FTP suspension, leading us to conclude that following suspension drivers make behavioral adjustments to minimize the probability of future tickets. However, these behavioral adjustments are only effective for White drivers.
Nasal compartmentalization in Kogiidae (Cetacea, Physeteroidea): insights from a new late Miocene dwarf sperm whale from the Pisco Formation
Authors: Benites‐Palomino Aldo , Vélez‐Juarbe Jorge , Collareta Alberto , Ochoa Diana , Altamirano Ali , Carré Matthieu , Laime Manuel J. , Urbina Mario , Salas‐Gismondi Rodolfo 
Published: February 2021

AbstractFacial compartmentalization in the skull of extant pygmy whales (Kogiidae) is a unique feature among cetaceans that allows for the housing of a wide array of organs responsible for echolocation. Recent fossil findings indicate a remarkable disparity of the facial bone organization in Miocene kogiids, but the significance of such a rearrangement for the evolution of the clade has been barely explored. Here we describe Kogia danomurai sp. nov., a late Miocene (c. 5.8 Ma) taxon from the Pisco Formation (Peru), based on a partially preserved skull with a new facial bone pattern. Phylogenetic analysis recovers K. danomurai as the most basal representative of the extant genus Kogia, displaying a combination of derived (incipiently developed and excavated sagittal facial crest) and plesiomorphic features (high position of the temporal fossa, and antorbital notch not transformed into a narrow slit). Furthermore, when compared with the extant Kogia, the facial patterning found in K. danomurai indicates differential development among the facial organs, implying different capabilities of sound production relative to extant Kogia spp. Different facial bone patterns are particularly notable within the multi‐species kogiid assemblage of the Pisco Formation, which suggests causal connections between different patterns and feeding ecologies (e.g. nekton piscivory and benthic foraging). At c. 5.8 Ma, K. danomurai was part of a cetacean community composed of clades typical of the late Miocene, and of other early representatives of extant taxa, a mixture probably representing an initial shift of the coastal faunas toward the ecosystem dynamics of the present‐day south‐eastern Pacific.
Thermodynamic Analysis of the Self‐Assembly of Pseudo Isocyanine Chloride in the Presence of Crowding Agents
Authors: Hämisch Benjamin , Pollak Roland , Ebbinghaus Simon , Huber Klaus 
Published: February 2021

AbstractPseudo isocyanine chloride (PIC) is a water‐soluble cationic dyestuff, which self‐assembles to fiber‐like aggregates below a characteristic temperature threshold. The threshold temperature decreases with decreasing PIC concentration. Macromolecular cosolutes affect this self‐assembly of PIC, similar to the impact macromolecular crowding has on the aggregation of proteins in living systems. The present study analyses the impact of triethylene glycol (TEG), polyethylene glycol (PEG), and Ficoll 400 as synthetic macromolecular crowding agents on the self‐assembly of PIC. A drastic change in the absorption behavior of visible light by PIC, which accompanies the transformation of monomeric PIC to the aggregate state of PIC, allows to analyze the temperature‐dependent self‐assembly in detail. Assisted by calorimetric measurements and by an analogy between self‐assembly and chemical polymerization, the thermodynamic analysis allowed to interpret the observed tendency of TEG and PEG to suppress and of Ficoll 400 to promote self‐assembly of PIC. Whereas the suppression by TEG and PEG can be attributed to preferential interactions between TEG or PEG and PIC, the promoting effect induced by Ficoll 400 is caused by excluded volume effects exerted by Ficoll. The results are in support of PIC as a cheap substitute of proteins in test tube studies of self‐assembly and as sensor for crowding effects on self‐assembly processes in cells.
Riparian Timber Harvest Intensity Affects Diets of Appalachian Brook Trout
Authors: Niles Jonathan M. , Hartman Kyle J. 
Published: February 2021

AbstractStream‐dwelling Brook Trout Salvelinus fontinalis rely heavily on terrestrial invertebrates, especially when aquatic prey is limited. We examined the effects of an experimental harvest of riparian timber on the diet and condition of Brook Trout in late summer. We evaluated the effects of two riparian harvest intensities (50% and 90% of the basal area harvest) in each of two streams on the diet, consumption, abundance, and condition of Brook Trout in summer. The diets and consumption patterns of Brook Trout were affected by the percentage of riparian timber harvest. Timber harvest increased the use of aquatic invertebrates—primarily via increased consumption of crayfish. In the 90% treatments, the use of terrestrial invertebrates by Brook Trout declined primarily due to the decreased use of Lepidoptera. Overall, consumption levels in the 50% treatments were nearly double those in the reference or 90% treatments. A common forestry best management practice is to limit riparian harvest to 50% of the basal area. Provided water quality and quantity are not affected, our study suggests that a 50% timber harvest limitation in the riparian area may provide at least a temporary boost in consumption due to an increase in the use of aquatic insects.
Morphogenesis of a bundled tall building: Biomimetic, structural, and wind‐energy design of a multi‐core‐outrigger system combined with diagrid
Authors: Laccone Francesco , Casali Alberto , Sodano Marco , Froli Maurizio 
Published: February 2021

SummarySkyscrapers are among the most distinctive building types of the modern age. Since many resources are attributed to these buildings, their design should consider a proper performance‐based construction economy and environmental sustainable development. This research introduces a new concept for a bundled tall building founded on the use of a multi‐core‐outrigger system, which is additionally enriched with diagrid structures. The concept is inspired by the bamboo plant and follows the biomimetic design principles for the structural organization and performance‐based criteria for optimizing the lateral stiffness and for shaping the cross section. Particularly, the incident wind speed is maximized to exploit Vertical Axis Wind Turbines (VAWTs), which are located along the whole building height at the center of the bundled towers. The building morphogenesis is accomplished by a multistep methodology that is fully developed in a parametric environment and includes structural and computational fluid dynamic analyses. With the aim of validating the proposed concept, a case study of a 320‐m‐tall three‐core building has been designed for the city of Pisa, Italy. The use of VAWTs results in an annual emissions reduction of about 10 kgCO2/m2.
Fluorescence Microscopic Investigations of Molecular Dynamics in Self‐Assembled Nanostructures
Authors: Ito Takashi , Higgins Daniel A. 
Published: February 2021

AbstractMany analytical methods employ self‐assembled nanostructured materials as chemical recognition media. Molecular permeation through these materials exhibits unique selectivity owing to nanoconfinement‐induced enhancement of permeant‐nanostructure interactions. This Personal Account introduces our efforts to investigate the detailed dynamics of single or a small number of molecules in nanostructured materials. We developed new experimental and analysis approaches built upon laser‐based fluorescence microscopy to measure the detailed translational and orientational dynamics of molecules diffusing in horizontally‐oriented, cylindrical nanostructures, including surfactant micelles, silica mesopores, block copolymer microdomains, and bolaamphiphile‐based organic nanotubes. Our studies clarified nanoscale details on the structural/chemical heterogeneity of the nanostructures, and their impacts on molecular mass transport dynamics.
Diagnostic performance of transvaginal ultrasound and magnetic resonance imaging for preoperative evaluation of low‐grade endometrioid endometrial carcinoma: prospective comparative study
Authors: Cubo‐Abert M. , Díaz‐Feijoo B. , Bradbury M. , Rodríguez‐Mías N.‐L. , Vera M. , Pérez‐Hoyos S. , Gómez‐Cabeza J.‐J. , Gil‐Moreno A. 
Published: February 2021

ABSTRACTObjectiveTo compare the diagnostic performance of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) in the prediction of deep myometrial invasion (DMI) and cervical stromal invasion (CSI) in patients with low‐grade (Grade 1 or 2) endometrioid endometrial cancer (EEC).MethodsThis was a prospective study including all patients with low‐grade EEC diagnosed between October 2013 and July 2018 at the Vall d'Hebron Hospital in Barcelona, Spain. Preoperative staging was performed using TVS and MRI, followed by surgical staging. Final histology was considered as the reference standard. Sensitivity, specificity, likelihood ratios and diagnostic accuracy were calculated for both imaging techniques in the prediction of DMI and CSI, and the agreement index was calculated for both techniques. The STARD 2015 guidelines were followed.ResultsA total of 131 patients with low‐grade EEC were included consecutively. Sensitivity was higher for TVS than for MRI both for the prediction of DMI (69% (95% CI, 53–82%) vs 51% (95% CI, 36–66%), respectively) and CSI (43% (95% CI, 27–61%) vs 24% (95% CI, 12–41%), respectively). Specificity was similar for TVS and MRI in the prediction of DMI (87% (95% CI, 78–93%) vs 91% (95% CI, 82–96%)) and equal in the prediction of CSI (97% (95% CI, 91–99%) for both). The agreement index between TVS and MRI was 0.84 (95% CI, 0.76–0.90) for DMI and 0.92 (95% CI, 0.85–0.96) for CSI.ConclusionsThe diagnostic performance of TVS is similar to that of MRI for the prediction of DMI and CSI in low‐grade EEC, and TVS can play a role as a first‐line imaging technique in the preoperative evaluation of low‐grade EEC. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.
Effect of partial replacement of chitosan with halloysite nanotubes on the properties of polylactic acid hybrid biocomposites
Authors: Kamaludin Nor Helya Iman , Ismail Hanafi , Rusli Arjulizan , Sam Sung Ting 
Published: February 2021

AbstractIn this study, hybrid chitosan/halloysite nanotubes (Cs/HNTs) reinforced polylactic acid (PLA) were prepared via melt compounding and compression molding techniques. In the fabrication of PLA/Cs/HNTs hybrid biocomposites, the partial replacement of Cs with HNTs was performed at filler loading of 2.5 parts per hundred parts of polymer (php), proceeding from the highest tensile strength of PLA/Cs obtained in our previous study. Cs was partially replaced with different HNTs loadings (0.5, 1, 1.5, 2, and 2.5) php and its effects on the functional group, thermal, tensile, morphological, and water absorption properties were investigated systematically. The results revealed that the combined loading of 1 php Cs and 1.5 php HNTs hybrid fillers into PLA showed the best performance in all properties. Fourier transform infrared spectroscopy (FTIR) analysis indicated that the siloxane (SiO) group of HNTs had chemically interacted with the amine group of Cs. The thermal analysis demonstrated that partial replacement of Cs with 1.5 php HNTs improved the thermal stability of PLA/2.5Cs/0HNTs biocomposite by ~12%. Yet, the percentage of crystallinity (χc) reduced with HNTs addition due to the phase adhesion improvement. Moreover, PLA/1Cs/1.5HNTs hybrid biocomposites showed the highest tensile strength and elongation at break of 59 MPa and 2.72%, respectively. This correlated with the uniform dispersion and better interfacial adhesion between Cs/HNTs fillers in the PLA matrix, as confirmed by the field emission scanning electron microscopy (FESEM). In addition, partial replacement of Cs with HNTs exhibited a lower water absorption percentage, which suggested the advantage of hybrid fillers to reduce water uptake, and is beneficial in a wide range of applications.
Modeling myths: OnDICEand dynamic realism in integrated assessment models of climate change mitigation
Authors: Grubb Michael , Wieners Claudia , Yang Pu 
Published: February 2021

AbstractWe analyze how stylized Integrated Assessment Models (IAMs), and specifically the widely‐used Dynamic Integrated Climate‐Economy model (DICE), represent the cost of emissions abatement. Many assume temporal independence—that abatement costs in one period are not affected by prior abatement. We contrast this with three dimensions of dynamic realism in emitting systems: (i) inertia, (ii) induced innovation, and (iii) path dependence. We review key evidence from the last quarter century on each of these three components. Studies of stock lifetime, dynamics of diffusion and past transitions suggest typical transition timescales of at least 20–40 years for the bulk emitting systems. The evidence that substantial innovation is induced by both prices and market deployment is unambiguous. Finally, both data and a rapidly growing literature demonstrate substantial path dependence in general, and specifically “carbon lock‐in and lock‐out.” Some stylized models in the past decade have incorporated technology learning, and others have considered inertia, but the combination of these factors is important and not yet evident. More complex hybrid IAMs with technology‐rich energy‐system models incorporate these factors, but their complexity has limited the wider understanding and influence of their underlying insights. Few if any global models fully represent path dependence. We conclude with likely implications drawing upon the empirical and modeling evidence accumulated, including results from extending DICE with a highly stylized representation of such dynamic factors. This suggests that dynamicinterdependencies could multiply several‐fold the optimal level of initial abatement expenditure. This is because early abatement then also directly facilitates subsequent emission savings. The diversity of dynamic linkages across sectors and technologies also implies more nuanced policy than a single global carbon price. Thus, the issues explored in this review can radically change the general policy conclusions drawn from models, which, like DICE, neglect dynamic realism.This article is categorized under:Climate Economics > Aggregation Techniques for Impacts and Mitigation Costs
Fault‐tolerant individual pitch control of floating offshore wind turbines via subspace predictive repetitive control
Authors: Liu Yichao , Frederik Joeri , Ferrari Riccardo M.G. , Wu Ping , Li Sunwei , van Wingerden Jan‐Willem 
Published: February 2021

AbstractIndividual pitch control (IPC) is an effective and widely used strategy to mitigate blade loads in wind turbines. However, conventional IPC fails to cope with blade and actuator faults, and this situation may lead to an emergency shutdown and increased maintenance costs. In this paper, a fault‐tolerant individual pitch control (FTIPC) scheme is developed to accommodate these faults in floating offshore wind turbines (FOWTs), based on a Subspace Predictive Repetitive Control (SPRC) approach. To fulfill this goal, an online subspace identification paradigm is implemented to derive a linear approximation of the FOWT system dynamics. Then, a repetitive control law is formulated to attain load mitigation under operating conditions, both in healthy and faulty conditions. Since the excitation noise used for the online subspace identification may interfere with the nominal power generation of the wind turbine, a novel excitation technique is developed to restrict excitation at specific frequencies. Results show that significant load reductions are achieved by FTIPC, while effectively accommodating blade and actuator faults and while restricting the energy of the persistently exciting control action.
Detecting clusters in multivariate response regression
Authors: Price Bradley S. , Allenbrand Corban , Sherwood Ben 
Published: February 2021

AbstractMultivariate regression, which can also be posed as a multitask machine learning problem, is used to better understand multiple outputs based on a given set of inputs. Many methods have been proposed on how to utilize shared information about responses with applications in fields such as economics, genomics, advanced manufacturing, and precision medicine. Interest in these areas coupled with the rise of large data sets (“big data”) has generated interest in how to make the computations more efficient, but also to develop methods that account for the heterogeneity that may exist between responses. One way to exploit this heterogeneity between responses is to use methods that detect groups, also called clusters, of related responses. These methods provide a framework that can increase computational speed and account for complexity of relationships of a large number of responses. With this flexibility, comes additional challenges such as how to identify these clusters of responses, model selection, and the development of more complex algorithms that combine concepts from both the supervised and unsupervised learning literature. We explore current state of the art methods, present a framework to better understand methods that utilize or detect clusters of responses, and provide insights on the computational challenges associated with this framework. Specifically we present a simulation study that discusses the challenges with model selection when detecting clusters of responses of interest. We also comment on extensions and open problems that are of interest to both the research and practitioner communities.This article is categorized under:Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and ClassificationStatistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data AnalysisStatistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods
Cancer‐associated‐platelet‐inspired nanomedicines for cancer therapy
Authors: Geranpayehvaghei Marzieh , Dabirmanesh Bahareh , Khaledi Mohammad , Atabakhshi‐Kashi Mona , Gao Chao , Taleb Mohammad , Zhang Yinlong , Khajeh Khosro , Nie Guangjun 
Published: February 2021

AbstractPlatelets, with hemostasis and thrombosis activities, are one of the key components in the blood circulation. As a guard, they rapidly respond to any abnormal blood vessel injury signal and release their granules' contents, which induce their adhesion and aggregation on wound site for hemostasis. Recently, increasing evidence has indicated that platelets are critically involved in the growth and metastasis of cancer cells by releasing a variety of cytokines and chemokines to stimulate cancer cell proliferation and various angiogenic regulators to accelerate tumor angiogenesis. Platelets also secrete active transforming growth factor beta (TGF‐β) to promote the epithelial–mesenchymal transition of cancer cells and their extravasation from primary site, and form microthrombus on the surface of cancer cells to protect them from immune attack and high‐speed shear force in the circulation. Therefore, blocking platelet–cancer cell interaction may be an attractive strategy to treat primary tumor and/or prevent cancer metastasis. However, systemic inhibition or depletion of platelets brings risk of severe bleeding complication. Cancer‐associated‐platelets‐targeted nanomedicines and biomimetic nanomedicines coated with platelet membrane can be used for targeted anticancer drug delivery, due to their natural targeting ability to tumor cells and platelets. In the current review, we first summarized the platelet mechanisms of action in physiological condition and their multiple roles in cancer progression and conventional antiplatelet therapeutics. We then highlighted the recent progress on the design and fabrication of cancer‐associated‐platelet‐targeted nanomedicines and platelet membrane coating nanomedicines for cancer therapy. Finally, we discussed opportunities and challenges and offered our thoughts for the future development.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Biology‐Inspired Nanomaterials > Lipid‐Based Structures