bluuebunny/crossref_metadata_2025 huggingface dataset:
Acridin-9(10H)-one based thermally activated delayed fluorescence material: simultaneous optimization of RISC and radiation processes to boost luminescence efficiency
Authors: Mei Yongqiang , Liu Di , Li Jiuyan , Li Huiting , Wei Wenkui
Published: March 2021

The high radiation and RISC rate constants were achieved simultaneously for a TADF emitter with acridin-9(10H)-one as acceptor due to high molecular rigidity and multichannel RISC processes, OLED with this TADF emitter exhibits a high EQE of 30.6%.
Oxygen vacancies modulating the photodetector performances in ε-Ga2O3 thin films
Authors: Li Shan , Yue Jianying , Ji Xueqiang , Lu Chao , Yan Zuyong , Li Peigang , Guo Daoyou , Wu Zhenping , Tang Weihua
Published: March 2021

The oxygen vacancies regulated via the lattice O atom formation/desorption process under oxidizing/reducing annealing reveal an effective modulating effect on the ε-Ga2O3 photodetector performances.
Barium-based scintillating MOFs for X-ray dosage detection with intrinsic energy resolution via luminescent multidentate naphthalene disulfonate moieties
Authors: Lu Jian , Gao Juan , Wang Wen-Fei , Li Bao-Yi , Li Pei-Xin , Zheng Fa-Kun , Guo Guo-Cong
Published: March 2021

Non-toxic Ba-SMOFs assembled by luminescent multidentate naphthalene-sulfonate moieties exhibit merited intrinsic energy resolution for X-ray dosage detection.
EB2 promotes hepatocellular carcinoma proliferation and metastasis via MAPK/ERK pathway by modulating microtubule dynamics
Authors: Zhong Fang-Jing , Li Yi-Ming , Xu Cong , Sun Bo , Wang Ji-Long , Yang Lian-Yue
Published: March 2021

Metastasis is the main cause of poor postoperative survival of hepatocellular carcinoma (HCC) patients. Cytoskeleton rearrangement is a key event in cancer metastasis. However, the significance of microtubule (MT), one of the core components of cytoskeleton, in this process is only beginning to be revealed. Here, we find that the MT dynamics regulator end-binding protein 2 (EB2) is highly expressed in HCC and predicts poor prognosis of HCC patients. Functional studies show that EB2 overexpression promotes HCC proliferation, invasion and metastasis in vitro and in vivo, while EB2 knockdown has opposite results. Mechanistically, EB2 mediates MTs destabilization, increases Src (Src proto-oncogene non-receptor tyrosine kinase) activity, and thus facilitates extracellular signal-regulated kinase (ERK) signaling activation, which could in turn promote EB2 expression in HCC, eventually resulting in enhanced HCC proliferation, invasion and metastasis. Furthermore, U0126, a specific ERK inhibitor, could effectively inhibit EB2-mediated HCC proliferation and metastasis in vitro and in vivo. In conclusion, EB2 coordinates MT cytoskeleton and intracellular signal transduction, forming an EB2–MT–ERK positive feedback loop, to facilitate HCC proliferation, invasion and metastasis. EB2 could serve as a promising prognostic biomarker and potential therapeutic target for HCC; HCC patients with high EB2 expression may benefit from treatment with ERK inhibitors.
Technologies enabling rapid crop improvements for sustainable agriculture: example pennycress (Thlaspi arvense L.)
Authors: Marks M. David , Chopra Ratan , Sedbrook John C.
Published: March 2021

Growing concerns over food insecurity and ecosystems health related to population growth and climate change have challenged scientists to develop new crops, employing revolutionary technologies in combination with traditional methods. In this review, we discuss the domestication of the oilseed-producing cover crop pennycress, which along with the development of other new crops and improvements to farming practices can provide sustainable solutions to address malnutrition and environmental impacts of production agriculture. We highlight some of the new technologies such as bioinformatics-enabled next-generation sequencing and CRISPR genome editing in combination with traditional mutation breeding that has accelerated pennycress development as a new crop and a potential model system. Furthermore, we provide a brief overview of the technologies that can be integrated for improving pennycress and other crops and the status of pennycress development using these technologies.
Continuous improvement and adaptation of predictive models in smart manufacturing and model management
Authors: Bachinger Florian , Kronberger Gabriel , Affenzeller Michael
Published: March 2021

Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for long‐term monitoring of model performance and adaptation of models if surrounding conditions change and the desired prediction accuracy is no longer met. The heterogeneous landscape of application scenarios, machine learning frameworks, hardware‐restricted IIoT platforms, and the diversity of enterprise systems require flexible, yet stable and error resilient solutions that allow the automated adaptation of prediction models. Recommendations are provided for the application and management of predictive models in smart manufacturing. Typical causes for concept drift in real‐world smart manufacturing applications are analysed, and essential steps in data and prediction model management are highlighted, to ensure reliability and efficiency in such applications. For this purpose, recommendations and a reference architecture for model management are provided. In addition, experimental results of two model adaptation strategies on an artificial dataset are shown.
Machine learning discovery of distinguishing laboratory features for severity classification of COVID‐19 patients
Authors: Xiao Yang , Yan Li , Zhang Mingyang , Pinkerton Kent E. , Cao Haosen , Xiao Ying , Li Wei , Li Shuai , Wang Yancheng , Li Shusheng , Cao Zhiguo , Wong Gary Wing‐Kin , Xu Hui , Zhang Hai‐Tao
Published: March 2021

The exponential spread of COVID‐19 worldwide is evident, with devastating outbreaks primarily in the United States, Spain, Italy, the United Kingdom, France, Germany, Turkey and Russia. As of 1 May 2020, a total of 3,308,386 confirmed cases have been reported worldwide, with an accumulative mortality of 233,093. Due to the complexity and uncertainty of the pathology of COVID‐19, it is not easy for front‐line doctors to categorise severity levels of clinical COVID‐19 that are general and severe/critical cases, with consistency. The more than 300 laboratory features, coupled with underlying disease, all combine to complicate proper and rapid patient diagnosis. However, such screening is necessary for early triage, diagnosis, assignment of appropriate level of care facility, and institution of timely intervention. A machine learning analysis was carried out with confirmed COVID‐19 patient data from 10 January to 18 February 2020, who were admitted to Tongji Hospital, in Wuhan, China. A softmax neural network‐based machine learning model was established to categorise patient severity levels. According to the analysis of 2662 cases using clinical and laboratory data, the present model can be used to reveal the top 30 of more than 300 laboratory features, yielding 86.30% blind test accuracy, 0.8195 F1‐score, and 100% consistency using a two‐way patient classification of severe/critical to general. For severe/critical cases, F1‐score is 0.9081 (i.e. recall is 0.9050, and precision is 0.9113). This model for classification can be accomplished at a mini‐second‐level computational cost (in contrast to minute‐level manual). Based on available COVID‐19 patient diagnosis and therapy, an artificial intelligence model paradigm can help doctors quickly classify patients with a high degree of accuracy and 100% consistency to significantly improve diagnostic and classification efficiency. The discovered top 30 laboratory features can be used for greater differentiation to serve as an essential supplement to current guidelines, thus creating a more comprehensive assessment of COVID‐19 cases during the early stages of infection. Such early differentiation will help the assignment of the appropriate level of care for individual patients.
Rhythm motion control in bio‐inspired fishtail based on central pattern generator
Authors: Chen Song , Liu Yubiao , Chen Tehuan , Lou Junqiang
Published: March 2021

The elastic oscillation structure based on central pattern generators (CPGs), which can produce rhythmic motions, is discussed. First, Hopf CPG, the typical CPG model, being a signal generator for the elastic oscillation structure, is analysed via the theory of differential equations. Next, the well‐posedness results of a coupling system composed by the CPG and an elastic beam are proved by means of the linear operator semi‐group theory. Then, the numerical results using the finite difference method indicate that the coupled system can obtain a variety of periodic motion behaviours by choosing the internal parameters of the CPG network. Finally, the dynamic simulation of complex system motion is investigated using COMSOL Multiphysics.
Real‐time multi‐window stereo matching algorithm with fuzzy logic
Authors: Vázquez‐Delgado Héctor‐Daniel , Pérez‐Patricio Madaín , Aguilar‐González Abiel , Arias‐Estrada Miguel‐Octavio , Palacios‐Ramos Marco‐Antonio , Camas‐Anzueto Jorge Luis , Pérez‐Cruz Antonio , Velázquez‐Trujillo Sabino
Published: March 2021

Stereo matching obtains a depth map called a disparity map that indicates or shows the positions of the objects in a scene. To estimate a disparity map, the most popular trend consists of comparing two images (left‐right) from two different points from the same scene. Unfortunately, small window sizes are suitable to preserve the edges, while large window sizes are required in homogeneous areas. To solve this problem, in this article, a novel real‐time stereo matching algorithm embedded in an FPGA is proposed. The approach consists of estimating disparity maps with different window sizes by using the sum of absolute differences (SAD) as a local correlation metric. Once the disparity maps are obtained, the left‐right consistency for each window size is computed. At the end of this stage, the centre pixel deviation is estimated through a 5 × 5 window and the Sobel gradient is extracted from the left image. Finally, both parameters are processed by a Fuzzy Inference System (FIS), which combines the calculated disparities and generates a final disparity map. An architecture embedded in FPGA is established and hardware acceleration strategies are discussed. Experimental results demonstrated that this algorithmic formulation provides promising results compared with the current state of the art.
Point cloud classification by dynamic graph CNN with adaptive feature fusion
Authors: Guo Rui , Zhou Yong , Zhao Jiaqi , Man Yiyun , Liu Minjie , Yao Rui , Liu Bing
Published: March 2021

The deep neural network has made the most advanced breakthrough in almost all 2D image tasks, so we consider the application of deep learning in 3D images. Point cloud data, as the most basic and important form of representation of 3D images, can accurately and intuitively show the real world. The authors propose a new network based on feature fusion to improve the point cloud classification and segmentation tasks. Our network mainly consists of three parts: global feature extractor, local feature extractor and adaptive feature fusion module. A multi‐scale transformation network is devised to guarantee the invariance of the transformation of the global feature, and a residual block is introduced to alleviate the problem of gradient disappearance to enhance the global feature extractor. Based on the edge convolution and multi‐layer perceptron, a local feature extractor is constructed. Finally, an adaptive feature‐fusion module is proposed to complete the fusion of global features and local features. Extensive experiments on point cloud classification and segmentation tasks are carried out to verify the effectiveness of the proposed method. The classification accuracy of the ModelNet40 is 93.6%, which is 4.4% higher than that of the PointNet. Similarly, the segmentation accuracy on the ShapeNet is 85.6%, which is higher than other methods.
An automatic feature selection and classification framework for analyzing ultrasound kidney images using dragonfly algorithm and random forest classifier
Authors: Narasimhulu C Venkata
Published: March 2021

In medical imaging, the automatic diagnosis of kidney carcinoma has become more difficult because it is not easy to detect by physicians. Pre‐processing is the first identification method to enhance image quality, remove noise and unwanted components from the backdrop of the kidneys image. The pre‐processing method is essential and significant for the proposed algorithm. The objective of this analysis is to recognize and classify kidney disturbances with an ultrasound scan by providing a number of substantial content description parameters. The ultrasound pictures are prepared to protect the interest pixels before extracting the feature. A series of quantitative features were synthesized of each images, the principal component analysis was conducted for minimizing the number of features to produce set of wavelet‐based multi‐scale features. Dragonfly algorithm (DFA) was executed in this method. In the proposed work, the design and training of a random decision forest classifier and selected features are implemented. The classification of e‐health information using ideal characteristics is used by the RF classifier. The proposed technique is activated in MATLAB/simulink work site and the experimental results show that the peak accuracy of the proposed technique is 95.6% using GWO‐FFBN techniques compared to other existing techniques.
Optimisation‐based design of transversal signal‐interference microwave bandpass and lowpass filters with extended stopband
Authors: Gómez‐García Roberto , Yang Li , Muñoz‐Ferreras José‐María
Published: March 2021

Generalised bi‐path stepped‐impedance‐line signal‐interference bandpass and lowpass transversal filtering sections (TFSs) with increased stopband bandwidth above the main transmission band are presented. They are realised by partitioning the two in‐parallel transmission‐line paths in their related classic spectrally periodic TFS approach into a plurality of line sub‐segments, whose characteristic‐impedance and electrical‐length values are derived through optimisation. It is demonstrated that the stopband range above the transmission band in these generalised non‐frequency‐periodic TFSs can be remarkably broadened with regard to those intrinsic to their conventional bandpass and lowpass TFS counterparts. Furthermore, as added benefits, this is achieved for shorter transmission‐line paths and a sharper cut‐off slope between the transmission band and the extended stopband. For experimental‐validation purposes, three proof‐of‐concept microstrip prototypes are manufactured and characterised. They correspond to a 1‐GHz bandpass TFS, a 1‐GHz two‐TFS‐in‐series‐cascade‐based bandpass filter (BPF) with augmented selectivity and out‐of‐band power‐rejection levels, and one lowpass TFS with a designed 3‐dB cut‐off frequency of 1.25 GHz.
Proposal for metal–insulator–metal plasmonic power splitter and demultiplexer suitable for implementation in optical switches
Authors: Ghasemi Mohammad Reza , Bayati Mohammad Sajjad
Published: March 2021

The authors propose a nanoplasmonic structure based on metal–insulator–metal (MIM) waveguides which consists of a 3 db power splitter and a side‐coupled nanocavity placed between its two output ports. The proposed structure is analysed by the resonant theory and dispersion relation. Transmission spectra of the presented device are also extracted using the finite difference time domain method. Numerical simulations demonstrate that the structure operates as a band‐stop filter in each output channel. Moreover, the resonance wavelengths can be tuned by adjusting the geometrical parameters of the nanocavity. Meanwhile, the authors developed the cavity and added an extra stub to it to append a new stopband to the output spectrum. Each resonance wavelength can be easily manipulated by changing the widths of the nanocavity and the added stub. In the end, by choosing two different lengths for the side‐coupled cavities, the authors convert the power splitter into a wavelength division multiplexer. These introduced MIM, the authors proposed here, may have various meaningful applications in nanoscale high‐density photonic circuits such as optical switches, logic plasmonic circuits and slow‐light devices.
Adaptative vital signs monitoring system based on the early warning score approach in smart hospital context
Authors: Ben Ida Imen , Balti Moez , Chaabane Sondes , Jemai Abderrazak
Published: March 2021

Changes in vital signs are an important indicator of physiological decline and provide opportunities for early recognition and intervention. The collected vital signs data can be evaluated using several approaches such as the Early warning score (EWS) approach to predict the risk level of patients. By exploring the Internet of things (IoT), vital signs monitoring solutions are automated based on various medical devices and sensors. However, there is a lack of efficient tools that enable an adaptative monitoring depending on the patient situations. This article explores the IoT technologies to provide an EWS system in smart hospital situation. The proposed solution presents an adaptative configuration of the vital signs monitoring process depending on the patient’s health status variation and the medical staff decisions. Also, an intelligent notification mechanism that reduces the delay of the medical staff intervention in the case of risk detection is proposed.
A novel communication‐free charge controller for electric vehicles using machine learning
Authors: Shafiq Saifullah , Khan Bilal , Raussi Petra , Al‐Awami Ali Taleb
Published: March 2021

Despite many advantages, wide‐spread integration of electric vehicles (EVs) in the power systems is challenging. Large‐scale uncontrolled EV charging load may lead to under‐voltage violations, higher power losses, overloading of transformers and transmission lines. In this research work, a machine learning‐based communication‐free EV charge control strategy is developed to mitigate the issues caused by the uncontrolled EV charging. Another notable feature of the proposed controller is to ensure the fairness among the EVs available at different locations in the distribution system. Moreover, two indices are proposed, that is system utilisation index (SUI) and system average voltage violation duration index (SAVVDI), to assess the performance of any EV charge controller. In the proposed control structure, a nodal voltage and the voltage‐to‐load sensitivity are measured at each load node which are fed to the EV charge controller. In fact, an upstream node is generally less sensitive to the changes in load, since it is closer to the feeding point, as compared to a downstream node. The output of the charge controller is the charging rate of an EV. In order to validate the robustness of the proposed controller, light and heavy loading conditions are considered which mimic the daily, monthly, yearly and seasonal load variations. Simulation results prove that the proposed controller effectively improves the voltage profiles and ensures fairness among the EVs connected at various charging points in the distribution system. Moreover, it effectively utilises the power system resources.
Mixture models for photometric redshifts
Authors: Ansari Zoe , Agnello Adriano , Gall Christa
Published: March 2021

Context.Determining photometric redshifts (photo-zs) of extragalactic sources to a high accuracy is paramount to measure distances in wide-field cosmological experiments. With only photometric information at hand, photo-zs are prone to systematic uncertainties in the intervening extinction and the unknown underlying spectral-energy distribution of different astrophysical sources, leading to degeneracies in the modern machine learning algorithm that impacts the level of accuracy for photo-zestimates.

Aims.Here, we aim to resolve these model degeneracies and obtain a clear separation between intrinsic physical properties of astrophysical sources and extrinsic systematics. Furthermore, we aim to have meaningful estimates of the full photo-zprobability distribution, and their uncertainties.

Methods.We performed a probabilistic photo-zdetermination using mixture density networks (MDN). The training data set is composed of optical (grizphotometric bands) point-spread-function and model magnitudes and extinction measurements from the SDSS-DR15 and WISE mid-infrared (3.4 μm and 4.6 μm) model magnitudes. We used infinite Gaussian mixture models to classify the objects in our data set as stars, galaxies, or quasars, and to determine the number of MDN components to achieve optimal performance.

Results.The fraction of objects that are correctly split into the main classes of stars, galaxies, and quasars is 94%. Furthermore, our method improves the bias of photometric redshift estimation (i.e., the mean Δz = (zp − zs)/(1 + zs)) by one order of magnitude compared to the SDSS photo-z, and it decreases the fraction of 3σoutliers (i.e., 3 × rms(Δz) < Δz). The relative, root-mean-square systematic uncertainty in our resulting photo-zs is down to 1.7% for benchmark samples of low-redshift galaxies (zs < 0.5).

Conclusions.We have demonstrated the feasibility of machine-learning-based methods that produce full probability distributions for photo-zestimates with a performance that is competitive with state-of-the art techniques. Our method can be applied to wide-field surveys where extinction can vary significantly across the sky and with sparse spectroscopic calibration samples. The code is publicly available.
Large-scale vertical movements in Cenomanian to Santonian carbonate platform in Iberia: indicators of a Coniacian pre-orogenic compressive stress
Authors: Andrieu Simon , Saspiturry Nicolas , Lartigau Marine , Issautier Benoit , Angrand Paul , Lasseur Eric
Published: March 2021

The Cenomanian to early Santonian interval is usually considered a time of postrifting tectonic quiescence around the northern margins of Iberia that preceded the onset of the Pyrenean convergence by crustal thrusting in the latest Santonian. However, plate kinematic models of the Mesozoic evolution of Iberia poorly constrain the Turonian-Santonian position of Iberia relative to Eurasia. This study reconstructs changes in the sedimentary facies and architecture of the Iberian carbonate platform throughout the Late Cretaceous and sheds new light on the geodynamic evolution of the Iberia-Eurasia relationship at that time. Sixteen outcrop sections were described and 24 sedimentary facies identified that define 5 depositional environments ranging from the deep marine basin to the continental setting. From these and previously published field data we reconstruct the evolution of the Pyrenean carbonate platform, on an east-west transect nearly 400 km long, on the basis of 11 short-term depositional sequences and 5 long-term hemicycles. In our interpretation, the Cenomanian and Turonian correspond to a postrift stage during which the European and Iberian margins, together with the deep basin between them, subside gently, as shown by accommodation rates varying from ∼15 to 30 m/My in the margins and ∼100 to 150 m/My in the basin. The Coniacian and early Santonian are characterized by a large-scale flexural response consisting of (1) uplift of the southern Iberian margin, with negative accommodation rates, karstified surfaces and paleosols, and (2) increasing subsidence rates in the basin and its edges (the northern Iberian margin and eastern Aquitaine platform), with accommodation rates several times greater than during the Turonian. We propose that far-field stress possibly related to the northeastward motion of Africa, and/or onset of shortening at the Iberia-Europe boundary in the central and eastern Pyrenees led to the incipient large-scale flexural deformation in the Pyrenean domain. The late Santonian and Campanian are an early orogenic stage marked by rapid subsidence throughout the Pyrenean domain, except at its western end. We evidence for the first time a pre-orogenic flexure at the Iberia-Europe plate boundary induced by regional plate reorganisation between Africa and Europe during the Coniacian and the early Santonian.
The role of voucher sale in advance for a capital-constrained supply chain
Authors: Wang Haijun , Liu Guanmei
Published: March 2021

This paper studies voucher sale as an operational method to raise working capital for a supply chain, which consists of a supplier and a capital-constrained retailer. The retailer takes advantage of an online platform to sell vouchers and to get access to borrowing from a bank. By formulating a Stackelberg game model, we show the retailer’s possible order quantities in the cases without and with bank loan and analyze the impact of voucher sale on the retailer’s optimal choice of order quantity and the supplier’s optimal wholesale price. We find that a smaller voucher’s price induces the retailer to be more likely to order with loan from a bank while a larger voucher’s value induces an order quantity with the loan more difficult to be repaid. In addition, if voucher’s price is large, the supplier decides a wholesale price which leads the retailer not to borrow from a bank; and if voucher’s price is small, the supplier’s optimal decision is obtained by anticipating the retailer to borrow from a bank. We also analyze the impact of voucher sale in the presence of trade credit financing on the firms’ decisions. The results show that the voucher’s price should be small so that the large; otherwise, the retailer either does not borrow from the supplier or may not repay the supplier. Besides, the supplier decides a wholesale price so that the retailer does not borrow or can repay the supplier, except that the voucher’s value is large and the voucher’s price is medium.
Evaluating the relationship between strong geomagnetic storms and electric grid failures in Poland using the geoelectric field as a GIC proxy
Authors: Gil Agnieszka , Berendt-Marchel Monika , Modzelewska Renata , Moskwa Szczepan , Siluszyk Agnieszka , Siluszyk Marek , Tomasik Lukasz , Wawrzaszek Anna , Wawrzynczak Anna
Published: March 2021

We study intense geomagnetic storms (Dst < −100nT) during the first half of the solar cycle 24. This type of storm appeared only a few times, mostly associated with southwardly directed heliospheric magnetic fieldBz. Using various methods such as self-organizing maps, statistical and superposed epoch analysis, we show that during and right after intense geomagnetic storms, there is growth in the number of transmission line failures. We also examine the temporal changes in the number of failures during 2010-2014 and find that the growing linear tendency of electrical grid failure occurrence is possibly connected with solar activity. We compare these results with the geoelectric field calculated for the region of Poland using a 1-D layered conductivity Earth model.
Preoperative Assessment of Cervical Involvement in Endometrial Cancer by Transvaginal Ultrasound and Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
Authors: Alcazar Juan Luis , Carazo Patricia , Pegenaute Leyre , Gurrea Elena , Campos Irene , Neri Manuela , Pascual Maria Angela , Guerriero Stefano
Published: March 2021

Objective To compare the diagnostic accuracy of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) for detecting cervical infiltration by endometrial carcinoma using meta-analysis assessment.

Methods An extensive search of papers comparing TVS and MRI for assessing cervical infiltration in endometrial cancer in the same set of patients was performed in Medline (Pubmed), Web of Science, and the Cochrane Database. Quality was assessed using QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies-2). Quantitative meta-analysis was performed.

Results Our extended search identified 12 articles that used both techniques in the same set of patients and were included in the meta-analysis. The risk of bias for most studies was high for patient selection and index tests in QUADAS-2. Overall, the pooled estimated sensitivity and specificity for diagnosing cervical infiltration in women with endometrial cancer were identical for both techniques [69 % (95 % CI, 51 %–82 %) and 93 % (95 % CI, 90 %–95 %) for TVS, and 69 % (95 % CI, 57 %–79 %) and 91 % (95 % CI, 90 %–95 %) for MRI, respectively]. No statistical differences were found when comparing both methods. Heterogeneity was high for sensitivity and moderate for specificity when analyzing TVS and moderate for both sensitivity and specificity in the case of MRI.

Conclusion TVS and MRI showed very similar diagnostic performance for diagnosing cervical involvement in women with endometrial cancer.
Molecular Editing of Flavins for Catalysis
Authors: Rehpenn Andreas , Walter Alexandra , Storch Golo
Published: March 2021

The diverse activity of flavoenzymes in organic transformations has fascinated researchers for a long time. However, when applied outside an enzyme environment, the isolated flavin cofactor only shows largely reduced activity. This highlights the importance of embedding the reactive isoalloxazine core of flavins in defined surroundings. The latter include crucial non-covalent interactions with amino acid side chains or backbone as well as controlled access to reactants such as molecular oxygen. Nevertheless, molecular flavins are increasingly applied in the organic laboratory as valuable organocatalysts. Chemical modification of the parent isoalloxazine structure is of particular interest in this context in order to achieve reactivity and selectivity in transformations, which are so far only known with flavoenzymes or even unprecedented. This review aims to give a systematic overview of the reported designed flavin catalysts and highlights the impact of each structural alteration. It is intended to serve as a source of information when comparing the performance of known catalysts, but also when designing new flavins. Over the last few decades, molecular flavin catalysis has emerged from proof-of-concept reactions to increasingly sophisticated transformations. This stimulates anticipating new flavin catalyst designs for solving contemporary challenges in organic synthesis.

1 Introduction

2 N1-Modification

3 N3-Modification

4 N5-Modification

5 C6–C9-Modification

6 N10-Modification

7 Conclusion
CuI-Catalyzed Ullmann-Type Coupling of Phenols and Thiophenols with 5-Substituted 1,2,3-Triiodobenzenes: Facile Synthesis of Mammary Carcinoma Inhibitor BTO-956 in One Step
Authors: Al-Zoubi Raed M. , Altamimi Reem M. , Al-Jammal Walid K. , Shawakfeh Khaled Q. , Al-Zoubi Mazhar S. , Ferguson Michael J. , Zarour Ahmad , Yassin Aksam , Al-Ansari Abdulla
Published: March 2021

A facile and unprecedented synthesis of 2,3-diiodinated or 2,6-diiodinated diaryl ether/thioether derivatives through regioselective Ullmann-type cross couplings of 5-substituted 1,2,3-triiodobenzenes and phenols/thiophenols is described. Remarkably, the coupling reactions are simply controlled by the type of nucleophiles and the nature of C5 substituent at 1,2,3-triiodoarenes providing the internal or terminal coupling products in high regioselectivity and good isolated yields. Noticeable steric and electronic effects were clearly observed on both 1,2,3-triiodoarenes and nucleophiles. The highest yields were isolated from a combination between either electron-poor 1,2,3-triiodoarenes and phenols or electron-rich 1,2,3-triiodoarenes and thiophenols. The optimized conditions were found to be suitable for several functional groups. Using this methodology, mammary carcinoma inhibitor BTO-956 is prepared in only one step with excellent regioselectivity and good isolated yield. This report discloses the first method to prepare 2,3-diiodinated and 2,6-diiodinated diaryl ethers/thioethers in one step that is efficient, regioselective, and general in scope. The products are truly remarkable precursors for other transformations.
Integrated MicroRNA–mRNA Analyses of Distinct Expression Profiles in Hyperoxia-Induced Bronchopulmonary Dysplasia in Neonatal Mice
Authors: Wang Chengqiang , Zhang Sheng , Zhu Lina , Duan Jun , Huang Bo , Zhang Xiaoying
Published: March 2021

Objective Bronchopulmonary dysplasia (BPD) is a common chronic lung disease of preterm neonates; the underlying pathogenesis is not fully understood. Recent studies suggested microRNAs (miRNAs) may be involved in BPD.

Study Design miRNA and mRNA microarrays were performed to analyze the expression profiles of miRNA and mRNA in BPD and control lung tissues after oxygen and air exposure on day 21. Bioinformatics methods, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed to predict the potential functions of differentially expressed genes. Then, miRNA–mRNA regulatory network was constructed by protein–protein interaction (PPI) data and TarBase data.

Results Our results showed that a total of 192 differentially expressed miRNAs (74 downregulated and 118 upregulated) and 1,225 differentially expressed mRNAs (479 downregulated and 746 upregulated) were identified between BPD mice and normoxia-control mice. GO and KEGG analysis showed that for downregulated genes, the top significant enriched GO terms and KEGG pathways were both mainly related to immune and inflammation processes; for upregulated genes, the top significant enriched GO terms and KEGG pathways were both mainly related to extracellular matrix (ECM) remodeling. PPI network and miRNA–mRNA regulatory network construction revealed that the key genes and pathways associated with inflammation and immune regulation.

Conclusion Our findings revealed the integrated miRNA–mRNA data of distinct expression profiles in hyperoxia-induced BPD mice, and may provide some clues of the potential biomarkers for BPD, and provide novel insights into the development of new promising biomarkers for the treatment of BPD.

Key Points
How shades of truth and age affect responses to COVID-19 (Mis)information: randomized survey experiment among WhatsApp users in UK and Brazil
Authors: Vijaykumar Santosh , Jin Yan , Rogerson Daniel , Lu Xuerong , Sharma Swati , Maughan Anna , Fadel Bianca , de Oliveira Costa Mariella Silva , Pagliari Claudia , Morris Daniel
Published: March 2021

We examined how age and exposure to different types of COVID-19 (mis)information affect misinformation beliefs, perceived credibility of the message and intention-to-share it on WhatsApp. Through two mixed-design online experiments in the UK and Brazil (total N = 1454) we first randomly exposed adult WhatsApp users to full misinformation, partial misinformation, or full truth about the therapeutic powers of garlic to cure COVID-19. We then exposed all participants to corrective information from the World Health Organisation debunking this claim. We found stronger misinformation beliefs among younger adults (18–54) in both the UK and Brazil and possible backfire effects of corrective information among older adults (55+) in the UK. Corrective information from the WHO was effective in enhancing perceived credibility and intention-to-share of accurate information across all groups in both countries. Our findings call for evidence-based infodemic interventions by health agencies, with greater engagement of younger adults in pandemic misinformation management efforts.
Prediction of COVID-19 Social Distancing Adherence (SoDA) on the United States county-level
Authors: Ingram Myles , Zahabian Ashley , Hur Chin
Published: March 2021

Social distancing policies are currently the best method of mitigating the spread of the COVID-19 pandemic. However, adherence to these policies vary greatly on a county-by-county level. We used social distancing adherence (SoDA) estimated from mobile phone data and population-based demographics/statistics of 3054 counties in the United States to determine which demographics features correlate to adherence on a countywide level. SoDA scores per day were extracted from mobile phone data and aggregated from March 16, 2020 to April 14, 2020. 45 predictor features were evaluated using univariable regression to determine their level of correlation with SoDA. These 45 features were then used to form a SoDA prediction model. Persons who work from home prior to the COVID-19 pandemic (β = 0.259, p < 0.00001) and owner-occupied housing unit rate (β = −0.322, p < 0.00001) were the most positively correlated and negatively correlated features to SoDA, respectively. Counties with higher per capita income, older persons, and more suburban areas were positively associated with adherence while counties with higher African American population, high obesity rate, earlier first COVID-19 case/death, and more Republican-leaning residents were negatively correlated with adherence. The base model predicted county SoDA with 90.8% accuracy. The model using only COVID-19-related features predicted with 64% accuracy and the model using the top 25 most substantial features predicted with 89% accuracy. Our results indicate that economic features, health features, and a few other features, such as political affiliation, race, and the time since the first case/death, impact SoDA on a countywide level. These features, combined, can predict adherence with a high level of confidence. Our prediction model could be utilized to inform health policy planning and potential interventions in areas with lower adherence.
Continuous and discrete phasor analysis of binned or time-gated periodic decays
Authors: Michalet Xavier
Published: March 2021

The time-resolved analysis of periodically excited luminescence decays by the phasor method in the presence of time-gating or binning is revisited. Analytical expressions for discrete configurations of square gates are derived, and the locus of the phasors of such modified periodic single-exponential decays is compared to the canonical universal semicircle. The effects of instrument response function offset, decay truncation, and gate shape are also discussed. Finally, modified expressions for the phase and modulus lifetimes are provided for some simple cases. A discussion of a modified phasor calibration approach is presented, and an illustration of the new concepts with examples from the literature concludes this work.
Isothermal furnace for long-term in situ and real-time X-radiography solidification experiments
Authors: Wegener M. , Dreißigacker C. , Becker M. , Kargl F.
Published: March 2021

A new x-ray isothermal furnace has been developed, suitable for in situ observations of semi-solid processes including the transition from dendritic to globulitic grain morphology and grain coarsening in metallic samples. A homogeneous, isothermal temperature field is achieved using a novel heater concept. The furnace structure is sandwich-like with heating elements positioned in the beam line and parallel to the sample. Planar heat transfer to the sample enables measurements with low cooling rates and a minimized temperature gradient. Cooling rates from 0.1 to 15 K min−1 can be controlled in the temperature range 1170–670 K. The furnace setup is integrable in the existing rotatable laboratory x-ray facility (X-RISE) at the German Aerospace Center (DLR). In this setup, an effective pixel size of 3 μm and a field of view of 8 mm in diameter can be achieved. Preliminary solidification and semi-solid experiments in the hypo-eutectic alloy systems Al–Ge and Al–Cu, inoculated with Al–5Ti–1B grain refiner, are presented. They indicate a very uniform temperature distribution in the sample.
Phase behavior of polymer–nanorod composites: A comparative study using PRISM theory and molecular dynamics simulations
Authors: Erigi Umashankar , Dhumal Umesh , Tripathy Mukta
Published: March 2021

Well-dispersed composites of polymer and nanorods have many emerging applications and, therefore, are an important area of research. Polymer reference interaction site model (PRISM) theory and molecular dynamics simulations have become powerful tools in the study of the structure and phase behavior of polymer nanocomposites. In this work, we employ both PRISM theory and molecular dynamics simulations to determine the structure and spinodal phase diagram of 1% volume fraction of nanorods in a polymer melt. We make quantitative comparisons between the phase diagrams, which are reported as a function of nanorod aspect ratio and polymer–nanorod interactions. We find that both PRISM theory and molecular dynamics simulations predict the formation of contact aggregates at low polymer–nanorod attraction strength (γ) and bridged aggregates at high polymer–nanorod attraction strength. They predict an entropic depletion-driven phase separation at low γ and a bridging-driven spinodal phase separation at high γ. The polymer and nanorods are found to form stable composites at intermediate values of the polymer–nanorod attraction strength. The fall of the bridging boundary and the gradual rise of the depletion boundary with the nanorod aspect ratio are predicted by both PRISM theory and molecular dynamics simulations. Hence, the miscible region narrows with increasing aspect ratio. The depletion boundaries predicted by theory and simulation are quite close. However, the respective bridging boundaries present a significant quantitative difference. Therefore, we find that theory and simulations qualitatively complement each other and display quantitative differences.
Effect of tab parameters on the near-field mixing characteristics of a Mach 1.5 elliptic jet
Authors: Akram Saif , Perumal Arun Kumar , Rathakrishnan Ethirajan
Published: March 2021

The effect of delta-tabs with its apex leaning downstream on the jet mixing characteristics of a Mach 1.5 elliptic jet of aspect ratio (AR) 3.37 is reported in this paper. The delta-tabs were placed along the minor and major axes of the elliptic nozzle, referred to as tab configuration C1 and C2, respectively. For each tab configuration, four different orientation angles varying from θ= 90∘ to 150∘ were studied, where θ= 90∘ is the tab positioned normal to the nozzle exit and θ= 150∘ is the tab oriented in the downstream direction at the nozzle exit. The tab effects on jet manipulation were investigated via shadowgraph visualization, and the mean Pitot pressure was measured along the jet centerline and along the orthogonal planes of the jet. The non-dimensonalized supersonic core length Lc*, average shock-cell spacing Ls¯*, and the axis-switching location xas* were examined in detail to understand the jet characteristics of the natural and manipulated jets. The mixing capability of the manipulated jets quantified based on the reduction in supersonic core length ΔLc* depends strongly on the ideally expanded jet Mach number Mj, tab configuration (C1 and C2), and θ. As such, the ΔLc* for the manipulated jet at θ= 135∘ is the largest, revealing the optimal tab orientation for jet mixing enhancement, as also observed for the circular jet [Zaman et al., “Control of an axisymmetric jet using vortex generators,” Phys. Fluids 6(2), 778–793 (1994)]. The relationship between ΔLc* and ΔLs* is presented to understand the correlation between the jet mixing and noise characteristics of the manipulated jet. Discussion is conducted based on the dependence of ΔLc* and ΔLs* with θ, which provides useful insight into the jet flow physics. With suitable placement of tabs C1 and C2, the axis switching could be either stopped or augmented. The superior mixing characteristics of an elliptic jet relative to a circular jet, which were found in previous works on the supersonic over-expanded jet [Kumar and Rathakrishnan, “Characteristics of a supersonic elliptic jet,” Aeronaut. J. 120(1225), 495 (2016)] prevail in the supersonic jet under-expanded jet as well.
Nano-thermoelectric infrared bolometers
Authors: Varpula Aapo , Tappura Kirsi , Tiira Jonna , Grigoras Kestutis , Kilpi Olli-Pekka , Sovanto Kuura , Ahopelto Jouni , Prunnila Mika
Published: March 2021

Infrared (IR) radiation detectors are used in numerous applications from thermal imaging to spectroscopic gas sensing. Obtaining high speed and sensitivity, low-power operation, and cost-effectiveness with a single technology remains to be a challenge in the field of IR sensors. By combining nano-thermoelectric transduction and nanomembrane photonic absorbers, we demonstrate uncooled IR bolometer technology that is material-compatible with large-scale CMOS fabrication and provides fast and high sensitivity response to long-wavelength IR (LWIR) around 10 µm. The fast operation speed stems from the low heat capacity metal layer grid absorber connecting the sub-100 nm-thick n- and p-type Si nano-thermoelectric support beams, which convert the radiation induced temperature rise into voltage. The nano-thermoelectric transducer-support approach benefits from enhanced phonon surface scattering in the beams, leading to reduction in thermal conductivity, which enhances the sensitivity. We demonstrate different size nano-thermoelectric bolometric photodetector pixels with LWIR responsitivities, specific detectivities, and time constants in the ranges 179 V/W–2930 V/W, 1.5 × 107 cm Hz1/2/W–3.1 × 108 cm Hz1/2/W, and 66 µs–3600 µs, respectively. We benchmark the technology against different LWIR detector solutions and show how nano-thermoelectric detector technology can reach the fundamental sensitivity limits posed by phonon and photon thermal fluctuation noise.
Collective optical Thomson scattering in pulsed-power driven high energy density physics experiments (invited)
Authors: Suttle L. G. , Hare J. D. , Halliday J. W. D. , Merlini S. , Russell D. R. , Tubman E. R. , Valenzuela-Villaseca V. , Rozmus W. , Bruulsema C. , Lebedev S. V.
Published: March 2021

Optical collective Thomson scattering (TS) is used to diagnose magnetized high energy density physics experiments at the Magpie pulsed-power generator at Imperial College London. The system uses an amplified pulse from the second harmonic of a Nd:YAG laser (3 J, 8 ns, 532 nm) to probe a wide diversity of high-temperature plasma objects, with densities in the range of 1017–1019 cm−3 and temperatures between 10 eV and a few keV. The scattered light is collected from 100 μm-scale volumes within the plasmas, which are imaged onto optical fiber arrays. Multiple collection systems observe these volumes from different directions, providing simultaneous probing with different scattering K-vectors (and different associated α-parameters, typically in the range of 0.5–3), allowing independent measurements of separate velocity components of the bulk plasma flow. The fiber arrays are coupled to an imaging spectrometer with a gated intensified charge coupled device. The spectrometer is configured to view the ion-acoustic waves of the collective Thomson scattered spectrum. Fits to the spectra with the theoretical spectral density function S(K, ω) yield measurements of the local plasma temperatures and velocities. Fitting is constrained by independent measurements of the electron density from laser interferometry and the corresponding spectra for different scattering vectors. This TS diagnostic has been successfully implemented on a wide range of experiments, revealing temperature and flow velocity transitions across magnetized shocks, inside rotating plasma jets and imploding wire arrays, as well as providing direct measurements of drift velocities inside a magnetic reconnection current sheet.
Second order accurate boundary conditions for the general propagation lattice Boltzmann method
Authors: Ilyin Oleg
Published: March 2021

In the present work, the problem of the development of the second order accurate boundary conditions for the lattice Boltzmann models with the general streaming step is addressed. The proposed boundary conditions are applicable to the flows in domains with solid and curved boundaries. The presented boundary scheme can be considered as the generalization of the Mei-Luo-Shyy conditions, in the case of the standard lattice Boltzmann models both approaches coincide. Several benchmark problems are considered: the Poiseuille flow, the oscillating Womersley flow, the Taylor-Couette flow, and the flow past a circular cylinder. These problems are studied for different spatial grid resolutions, and the convergence rates to the solutions from literature are presented.