bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laboratory testing of SARS‐CoV, MERS‐CoV, and SARS‐CoV‐2 (2019‐nCoV): Current status, challenges, and countermeasures
Authors: Yan Ying , Chang Le , Wang Lunan 
Published: April 2020

SummaryEmerging and reemerging infectious diseases are global public concerns. With the outbreak of unknown pneumonia in Wuhan, China in December 2019, a new coronavirus, SARS‐CoV‐2 has been attracting tremendous attention. Rapid and accurate laboratory testing of SARS‐CoV‐2 is essential for early discovery, early reporting, early quarantine, early treatment, and cutting off epidemic transmission. The genome structure, transmission, and pathogenesis of SARS‐CoV‐2 are basically similar to SARS‐CoV and MERS‐CoV, the other two beta‐CoVs of medical importance. During the SARS‐CoV and MERS‐CoV epidemics, a variety of molecular and serological diagnostic assays were established and should be referred to for SARS‐CoV‐2. In this review, by summarizing the articles and guidelines about specimen collection, nucleic acid tests (NAT) and serological tests for SARS‐CoV, MERS‐CoV, and SARS‐CoV‐2, several suggestions are put forward to improve the laboratory testing of SARS‐CoV‐2. In summary, for NAT: collecting stool and blood samples at later periods of illness to improve the positive rate if lower respiratory tract specimens are unavailable; increasing template volume to raise the sensitivity of detection; putting samples in reagents containing guanidine salt to inactivate virus as well as protect RNA; setting proper positive, negative and inhibition controls to ensure high‐quality results; simultaneously amplifying human RNase P gene to avoid false‐negative results. For antibody test, diverse assays targeting different antigens, and collecting paired samples are needed.
Falco: Fast likelihood‐based collision avoidance with extension to human‐guided navigation
Authors: Zhang Ji , Hu Chen , Chadha Rushat Gupta , Singh Sanjiv 
Published: April 2020

AbstractWe propose a planning method to enable fast autonomous flight in cluttered environments. Typically, autonomous navigation through a complex environment requires a continuous search on a graph generated by a k‐connected grid or a probabilistic scheme. As the vehicle travels, updating the graph with data from onboard sensors is expensive as is the search on the graph especially if the paths must be kinodynamically feasible. We propose to avoid the online search to reduce the computational complexity. Our method models the environment differently in two separate regions. Obstacles are considered to be deterministically known within the sensor range and probabilistically known beyond the sensor range. Instead of searching for the path with the lowest cost (typically the shortest path), the method maximizes the likelihood to reach the goal in determining the immediate next step for navigation. With such a problem formulation, the online method realized by a trajectory library can determine a path within 0.2–0.3 ms using a single central processing unit thread on a modem embedded computer. The method supports two configurations working with and without a prior map. Both configurations can be used to plan toward a goal point. Further, the later can allow human guidance for the navigation through a directional input. In experiments, it enables a lightweight unmanned aerial vehicle to fly at 10 m/s in a cluttered forest environment (see Figure 1 as an example).
Study of zinc pollution in river water: Average mass balance based on irrigation schedule
Authors: Andarani Pertiwi , Yokota Kuriko , Saga Makoto , Inoue Takanobu , Matsumoto Yoshitaka 
Published: April 2020

AbstractAichi Prefecture, which has a dense industrial area, is one of the sites in Japan where the levels of zinc are elevated. However, currently, there is no clear evidence of the source of zinc in this prefecture. This study aims to assess zinc concentration and load in a river and identify the main sources of zinc pollution. We conducted a 20‐month survey to identify the temporal and spatial variation of zinc in river water, particularly in the Aizumame River. Using Flame Atomic Absorption Spectrometry, the total fraction of zinc concentrations was determined for nine sampling stations (five points in the mainstream and four points in the tributaries). The results show that the average of zinc concentration was lower during the irrigation period than in the non‐irrigation period. However, the load during the irrigation period was higher. During irrigation, the river discharges were higher resulting in a lower concentration. The highest zinc concentration was 0.139 mg/L in June 2017. Based on this study, the main zinc source was identified from industrial areas which on average contributed about 3,400 g/day into the mainstream. These results became more evident during the non‐irrigation period when only industrial discharges contributed zinc load into the mainstream.
Knot selection in sparse Gaussian processes with a variational objective function
Authors: Garton Nathaniel , Niemi Jarad , Carriquiry Alicia 
Published: April 2020

AbstractSparse, knot‐based Gaussian processes have enjoyed considerable success as scalable approximations of full Gaussian processes. Certain sparse models can be derived through specific variational approximations to the true posterior, and knots can be selected to minimize the Kullback‐Leibler divergence between the approximate and true posterior. While this has been a successful approach, simultaneous optimization of knots can be slow due to the number of parameters being optimized. Furthermore, there have been few proposed methods for selecting the number of knots, and no experimental results exist in the literature. We propose using a one‐at‐a‐time knot selection algorithm based on Bayesian optimization to select the number and locations of knots. We showcase the competitive performance of this method relative to optimization of knots simultaneously on three benchmark datasets, but at a fraction of the computational
cost.
Morphology Control of Doped Spiro‐MeOTAD Films for Air Stable Perovskite Solar Cells
Authors: Wang Sisi , Wei Qi , Wang Kaiyang , Zhang Zhipeng , Zhao Dandan , Liang Chao , Liu Tanghao , Guo Jia , Su Chenliang , Li Ying , Xing Guichuan 
Published: April 2020

AbstractDoped 2,2′,7,7′‐tetrakis(N,N‐di‐p‐methoxyphenylamine)‐9,9′‐spirobifluorene (spiro‐MeOTAD), which acts as a hole‐transporting layer (HTL), endows perovskite solar cells (PSCs) with excellent performance. However, the intrinsically hygroscopic nature of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) dopants also aggravates the moisture instability of PSCs. In this work, the origins of the moisture instability of spiro‐MeOTAD HTLs are explored and strategies to enhance moisture resistance are proposed. After 780 h of aging in air, 52% of the initial power conversion efficiency (PCE) can be sustained by prolonging the mixing time of the precursor solution of spiro‐MeOTAD to reduce accumulated LiTFSI. In contrast, only 7% of the initial PCE remains if the precursor solution is mixed briefly. By thermally annealing an HTL to evaporate residual tBP in spiro‐MeOTAD, pinholes are completely eliminated and 65% of the initial PCE remains after the same aging time. In this study, the significance of the initial morphology of spiro‐MeOTAD HTLs on device stability is analyzed and strategies based on physical morphology for controlling PSC moisture instability induced by HTL dopants are developed.
A Single Molecule Drug Targeting Photosensitizer for Enhanced Breast Cancer Photothermal Therapy
Authors: Zou Yang , Li Mingle , Xiong Tao , Zhao Xueze , Du Jianjun , Fan Jiangli , Peng Xiaojun 
Published: April 2020

AbstractTargeting is one of the most important strategies for enhancing the efficacy of cancer photothermal therapy (PTT) and reducing damage to surrounding normal tissues. Compared with the traditional targeting approaches, the active targeting of breast cancer cells in PTT using chemotherapeutic drugs, such as tamoxifen (TAM), in combination with single‐molecule photothermal photosensitizers has superior selectivity and therapeutic effects. However, single‐molecule drug‐targeting photosensitizers for improved PTT efficacy are not widely reported. Accordingly, herein, a near‐infrared induced small‐molecule photothermal photosensitizer (CyT) is developed that actively targets the estrogen receptors (ERs) of breast cancer cells as well as targets mitochondria by structure‐inherent targeting. Cell uptake and cytotoxicity studies using different types of cells show that CyT enhances the efficiency of TAM‐based PTT by targeting ER‐overexpressing breast cancer cells and selectively killing them. In vivo experiments demonstrate that CyT can be used as a photothermal agent for fluorescence imaging‐guided PTT. More importantly, the intravenous injection of CyT results in better targeting and efficiency of tumor inhibition compared with that achieved with the TAM‐free control molecule Cy. Thus, the study presents an excellent small‐molecule photothermal agent for breast cancer therapy with potential clinical application prospects.
Target‐Triggered Assembly of Nanogap Antennas to Enhance the Fluorescence of Single Molecules and Their Application in MicroRNA Detection
Authors: Peng Manshu , Sun Feifei , Na Na , Ouyang Jin 
Published: April 2020

AbstractNanogap antennas are plasmonic nanostructures with a strong electromagnetic field generated at the gap region of two neighboring particles owing to the coupling of the collective surface plasmon resonance. They have great potential for improving the optical properties of fluorophores. Herein, nanogap antennas are constructed using an aqueous solution‐based method to overcome the defects of weak fluorescence and photobleaching associated with traditional organic dyes, and a highly sensitive nanogap antenna‐based sensing strategy is presented for the detection of low‐abundance nucleic acid biomarkers via a target‐triggered strand displacement amplification (SDA) reaction between two DNA hairpins that are tagged to the tips of gold nanorods (Au NRs). In the presence of targets, end‐to‐end Au NR dimers gradually form, and the fluorophores quenched by the Au NRs exhibit a dramatic fluorescence enhancement due to the plasmon‐enhanced fluorescence effect of nanogap antennas. Meanwhile, the SDA reaction results in secondary amplification of fluorescence signals. Combined with single‐molecule counting, this method applied in miRNA‐21 detection can achieve a low detection limit of 97.2 × 10−18 m. Moreover, accurate discrimination between different cells through miRNA‐21 imaging demonstrates the potential of this method in monitoring the expression level of low‐abundance nucleic acid biomarkers.
Lanthanide‐Doped Core@Multishell Nanoarchitectures: Multimodal Excitable Upconverting/Downshifting Luminescence and High‐Level Anti‐Counterfeiting
Authors: Huang Hai , Chen Jiangkun , Liu Yutong , Lin Jidong , Wang Shaoxiong , Huang Feng , Chen Daqin 
Published: April 2020

AbstractThe development of luminescent materials with concurrent multimodal emissions is a great challenge to improve security and data storage density. Lanthanide‐doped nanocrystals are particularly appropriate for such applications for their abundant intermediate energy states and distinguishable spectroscopic profiles. However, traditional lanthanide luminescent nanoparticles have a limited capacity for information storage or complexity to shield against counterfeiting. Herein, it is demonstrated that the combination of upconverting and downshifting emissions in a particulate designed lanthanide‐doped core@multishell nanoarchitecture allows the generation of multicolor dual‐modal luminescence over a wide spectral range for complex information storage. Precise control of lanthanide dopants distribution in the core and distinct shells enables simultaneous excitation of 980/808 nm focusing/defocusing laser and 254 nm light and produces complex upconverting emissions from Er, Tm, Eu, and Tb via multiphoton energy transfer processes and downshifting emissions from Eu and Tb via efficient energy transfer from Ce to Eu/Tb in Gd‐assisted lattices. It is experimentally proven that multiple visualized anti‐counterfeit and information encryption with facile decryption and authentication using screen‐printing inks containing the present core@multishell nanocrystals are practically applicable by selecting different excitation modes.
A precision medicine framework using artificial intelligence for the identification and confirmation of genomic biomarkers of response to an Alzheimer's disease therapy: Analysis of the blarcamesine (ANAVEX2‐73) Phase 2a clinical study
Authors: Hampel Harald , Williams Coralie , Etcheto Adrien , Goodsaid Federico , Parmentier Frédéric , Sallantin Jean , Kaufmann Walter E. , Missling Christopher U. , Afshar Mohammad 
Published: April 2020

AbstractIntroductionThe search for drugs to treat Alzheimer's disease (AD) has failed to yield effective therapies. Here we report the first genome‐wide search for biomarkers associated with therapeutic response in AD. Blarcamesine (ANAVEX2‐73), a selective sigma‐1 receptor (SIGMAR1) agonist, was studied in a 57‐week Phase 2a trial (NCT02244541). The study was extended for a further 208 weeks (NCT02756858) after meeting its primary safety endpoint.MethodsSafety, clinical features, pharmacokinetic, and efficacy, measured by changes in the Mini‐Mental State Examination (MMSE) and the Alzheimer's Disease Cooperative Study‐Activities of Daily Living scale (ADCS‐ADL), were recorded. Whole exome and transcriptome sequences were obtained for 21 patients. The relationship between all available patient data and efficacy outcome measures was analyzed with unsupervised formal concept analysis (FCA), integrated in the Knowledge Extraction and Management (KEM) environment.ResultsBiomarkers with a significant impact on clinical outcomes were identified at week 57: mean plasma concentration of blarcamesine (slope MMSE:P < .041), genomic variants SIGMAR1 p.Gln2Pro (ΔMMSE:P < .039; ΔADCS‐ADL:P < .063) and COMT p.Leu146fs (ΔMMSE:P < .039; ΔADCS‐ADL:P < .063), and baseline MMSE score (slope MMSE:P < .015). Their combined impact on drug response was confirmed at week 148 with linear mixed effect models.DiscussionConfirmatory Phase 2b/3 clinical studies of these patient selection markers are ongoing. This FCA/KEM analysis is a template for the identification of patient selection markers in early therapeutic development for neurologic disorders.
An enhanced analytical model for airfoil‐based shrouded wind turbines
Authors: Werle Michael J. 
Published: April 2020

AbstractThis paper provides a simple yet accurate lower order model for predicting the performance of shrouded wind turbines for a range of shroud airfoil shapes varying in length, camber, and thickness. The model employs classic thin airfoil aerodynamic principals and is an enhancement of a previous related model developed for shrouded propellers. The new method's accuracy is assessed using inviscid and viscous computational studies employing an actuator‐disc representation for the turbine rotor. Detailed comparisons are made for three shrouds over a full range of rotor loadings. For the range of configurations assessed, it was found that the algebraic solutions from the new method provided very good engineering approximations at all operating conditions considered, thereby enabling rapid preliminary design of shrouded power systems. Additionally, the new model is used to establish a Betz‐like power performance limit for airfoil‐based shrouded turbines.
Role of thermal decomposition process in the photocatalytic or photoluminescence properties of BiPO4 polymorphs
Authors: Bouddouch Abdessalam , Amaterz Elhassan , Bakiz Bahcine , Taoufyq Aziz , Guinneton Frédéric , Villain Sylvie , Gavarri Jean‐Raymond , Ezahri Mohmad , Valmalette Jean‐Christophe , Benlhachemi Abdeljalil 
Published: April 2020

AbstractThermal decomposition process was used to obtain modified photocatalytic and/or photoluminescence properties of bismuth phosphate polymorphs. The precursor BiPO4, 0.7H2O was synthesized by a coprecipitation route. The observed polymorphs were the hexagonal P3121 hydrate phase BiPO4, 0.7H2O at 25°C, a mix system of hexagonal and monoclinic P21/n phases at 200°C and 400°C, a mix system of monoclinic phases P21/n and P21/m at 600°C, and a unique monoclinic phase P21/m at 900°C. The X‐ray diffraction analyses allowed evidencing lattice deformations due to structural defects. The photocatalytic activities in the presence of rhodamine B in aqueous solution were determined using UV light irradiation. The best photocatalytic efficiencies were observed with the mix systems resulting from thermal decomposition at 400 and 600°C. Photoluminescence experiments performed under UV‐laser light irradiation revealed unexpected emissions in the green‐orange range, with optimal intensities for the mix systems observed at 400°C. The role of structural defects resulting from decomposition process is discussed.Practitioner points

Thermal decomposition is used to introduce structural defects in BiPO4 polymorphs

The BiPO4 intermediate systems are used to photodegrade rhodamine B

Active species trapping experiments are performed

Photoluminescence experiments highlight green‐orange emissions

Structural defects are at the origin of this photoluminescence
Naturally occurring modified ribonucleosides
Authors: McCown Phillip J. , Ruszkowska Agnieszka , Kunkler Charlotte N. , Breger Kurtis , Hulewicz Jacob P. , Wang Matthew C. , Springer Noah A. , Brown Jessica A. 
Published: April 2020

AbstractThe chemical identity of RNA molecules beyond the four standard ribonucleosides has fascinated scientists since pseudouridine was characterized as the “fifth” ribonucleotide in 1951. Since then, the ever‐increasing number and complexity of modified ribonucleosides have been found in viruses and throughout all three domains of life. Such modifications can be as simple as methylations, hydroxylations, or thiolations, complex as ring closures, glycosylations, acylations, or aminoacylations, or unusual as the incorporation of selenium. While initially found in transfer and ribosomal RNAs, modifications also exist in messenger RNAs and noncoding RNAs. Modifications have profound cellular outcomes at various levels, such as altering RNA structure or being essential for cell survival or organism viability. The aberrant presence or absence of RNA modifications can lead to human disease, ranging from cancer to various metabolic and developmental illnesses such as Hoyeraal–Hreidarsson syndrome, Bowen–Conradi syndrome, or Williams–Beuren syndrome. In this review article, we summarize the characterization of all 143 currently known modified ribonucleosides by describing their taxonomic distributions, the enzymes that generate the modifications, and any implications in cellular processes, RNA structure, and disease. We also highlight areas of active research, such as specific RNAs that contain a particular type of modification as well as methodologies used to identify novel RNA modifications.This article is categorized under:RNA Processing > RNA Editing and Modification
Molecular networks in Network Medicine: Development and applications
Authors: Silverman Edwin K. , Schmidt Harald H. H. W. , Anastasiadou Eleni , Altucci Lucia , Angelini Marco , Badimon Lina , Balligand Jean‐Luc , Benincasa Giuditta , Capasso Giovambattista , Conte Federica , Di Costanzo Antonella , Farina Lorenzo , Fiscon Giulia , Gatto Laurent , Gentili Michele , Loscalzo Joseph , Marchese Cinzia , Napoli Claudio , Paci Paola , Petti Manuela , Quackenbush John , Tieri Paolo , Viggiano Davide , Vilahur Gemma , Glass Kimberly , Baumbach Jan 
Published: April 2020

AbstractNetwork Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein–protein interaction networks, correlation‐based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases.This article is categorized under:
Models of Systems Properties and Processes > Mechanistic Models
Translational, Genomic, and Systems Medicine > Translational Medicine
Analytical and Computational Methods > Analytical Methods
Analytical and Computational Methods > Computational Methods
Modular Inference of Linear Types for Multiplicity-Annotated Arrows
Authors: Matsuda Kazutaka 
Published: April 2020

AbstractBernardy et al. [2018] proposed a linear type system $$\lambda ^q_\rightarrow $$

λ
→
q

as a core type system of Linear Haskell. In the system, linearity is represented by annotated arrow types $$A \rightarrow _m B$$

A

→
m

B

, where m denotes the multiplicity of the argument. Thanks to this representation, existing non-linear code typechecks as it is, and newly written linear code can be used with existing non-linear code in many cases. However, little is known about the type inference of $$\lambda ^q_\rightarrow $$

λ
→
q

. Although the Linear Haskell implementation is equipped with type inference, its algorithm has not been formalized, and the implementation often fails to infer principal types, especially for higher-order functions. In this paper, based on OutsideIn(X) [Vytiniotis et al., 2011], we propose an inference system for a rank 1 qualified-typed variant of $$\lambda ^q_\rightarrow $$

λ
→
q

, which infers principal types. A technical challenge in this new setting is to deal with ambiguous types inferred by naive qualified typing. We address this ambiguity issue through quantifier elimination and demonstrate the effectiveness of the approach with examples.
Proving the Safety of Highly-Available Distributed Objects
Authors: Nair Sreeja S. , Petri Gustavo , Shapiro Marc 
Published: April 2020

AbstractTo provide high availability in distributed systems, object replicas allow concurrent updates. Although replicas eventually converge, they may diverge temporarily, for instance when the network fails. This makes it difficult for the developer to reason about the object’s properties, and in particular, to prove invariants over its state. For the subclass of state-based distributed systems, we propose a proof methodology for establishing that a given object maintains a given invariant, taking into account any concurrency control. Our approach allows reasoning about individual operations separately. We demonstrate that our rules are sound, and we illustrate their use with some representative examples. We automate the rule using Boogie, an SMT-based tool.
Graded Algebraic Theories
Authors: Kura Satoshi 
Published: April 2020

AbstractWe provide graded extensions of algebraic theories and Lawvere theories that correspond to graded monads. We prove that graded algebraic theories, graded Lawvere theories, and finitary graded monads are equivalent via equivalence of categories, which extends the equivalence for monads. We also give sums and tensor products of graded algebraic theories to combine computational effects as an example of importing techniques based on algebraic theories to graded monads.