bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nitride‐Oxide‐Metal Heterostructure with Self‐Assembled Core–Shell Nanopillar Arrays: Effect of Ordering on Magneto‐Optical Properties
Authors: Wang Xuejing , Jian Jie , Wang Haohan , Liu Juncheng , Pachaury Yash , Lu Ping , Rutherford Bethany X. , Gao Xingyao , Xu Xiaoshan , El‐Azab Anter , Zhang Xinghang , Wang Haiyan 
Published: January 2021

AbstractMagneto‐optical (MO) coupling incorporates photon‐induced change of magnetic polarization that can be adopted in ultrafast switching, optical isolators, mode convertors, and optical data storage components for advanced optical integrated circuits. However, integrating plasmonic, magnetic, and dielectric properties in one single material system poses challenges since one natural material can hardly possess all these functionalities. Here, co‐deposition of a three‐phase heterostructure composed of a durable conductive nitride matrix with embedded core–shell vertically aligned nanopillars, is demonstrated. The unique coupling between ferromagnetic NiO core and atomically sharp plasmonic Au shell enables strong MO activity out‐of‐plane at room temperature. Further, a template growth process is applied, which significantly enhances the ordering of the nanopillar array. The ordered nanostructure offers two schemes of spin polarization which result in stronger antisymmetry of Kerr rotation. The presented complex hybrid metamaterial platform with strong magnetic and optical anisotropies is promising for tunable and modulated all‐optical‐based nanodevices.
Prussian Blue Analogs and Their Derived Nanomaterials for Electrochemical Energy Storage and Electrocatalysis
Authors: Song Xuezhi , Song Shuyan , Wang Dan , Zhang Hongjie 
Published: January 2021

AbstractPrussian blue analogs (PBAs), the oldest artificial cyanide‐based coordination polymers, possess open framework structures, large specific surface areas, uniform metal active sites, and tunable composition, showing significant perspective in electrochemical energy storage. These electrochemically active materials have also been converted to various functional metal containing nanomaterials, including carbon encapsulated metals/metal alloys, metal oxides, metal sulfides, metal phosphides, etc. originating from the multi‐element compositions as well as elaborate structure design. In this paper, a comprehensive review will be presented on the recent progresses in the development of PBA frameworks and their derivatives based electrode materials and electrocatalysts for electrochemical energy storage and conversion. In particular, it will focus on the synthesis of representative nanostructures, the structure design, and figure out the correlation between nanomaterials structure and electrochemical performance. Lastly, critical scientific challenges in this research area are also discussed and perspective directions for the future research in this field are provided, in order to provide a brand new vision into the further development of novel active materials for the next‐generation advanced electrochemical devices.
A design science research approach to closing the gap between the research and practice of project scheduling
Authors: Scales Jeff 
Published: January 2021

AbstractThis paper illustrates one researcher's experience of applying design science research (DSR) to the nexus between systems thinking and project scheduling. Project management has become increasingly popular in the decades since its advent but has changed little in that time. This is especially true because of its signature technique, project scheduling. Scheduling research however is vibrant and modern and even includes dynamic concepts such as learning curves in schedule construction. However, justifications for acquiring this level of systems literacy have not yet convinced the practice community. A similar gap is identified in management science, and a literature review yields two potential solutions: dissolving the subjective‐objective divide by adopting Critical Realism and using DSR as a framework for producing artefacts. This paper outlines how these concepts were applied to project scheduling, resulting in a new method for schedule construction that allows an expanded range of concepts to be included.
Brucellosis: Prevalence with reference to East African community countries – A rapid review
Authors: Djangwani Juvenal , Ooko Abong’ George , Gicuku Njue Lucy , Kaindi Dasel W. M. 
Published: January 2021

AbstractBrucellosis is a zoonotic disease which is endemic to certain regions of the world including Sub‐Saharan Africa. The aim of this article is to provide a recent and rapid review on brucellosis prevalence in East African Community (EAC) countries. Literature was obtained using Google Scholar search engine and screened for relevancy and fulfilment of criteria to 1, 17, 4, 4, 30 and 29 articles retained for brucellosis prevalence in Burundi, Kenya, Rwanda, South Sudan, Tanzania and Uganda. Recent literature (published in the last decade 2010 to 2019) was considered for prevalence results in this review. In EAC, livestock had an animal‐level prevalence of 0.2% to 43.8%, 0.0% to 20.0% and 0.0% to 13.8% for cattle, goats and sheep respectively. In humans, the prevalence varied mostly between 0.0% and 35.8%. In conclusion, brucellosis is quite prevalent in the region. The reported prevalence calls for plans or more efforts from individual member countries and from EAC, as a region, to control brucellosis.
Floods and the COVID‐19 pandemic—A new double hazard problem
Authors: Simonovic Slobodan P. , Kundzewicz Zbigniew W. , Wright Nigel 
Published: January 2021

AbstractThe coincidence of floods and coronavirus disease 2019 (COVID‐19) is a genuine multihazard problem. Since the beginning of 2020, many regions around the World have been experiencing this double hazard of serious flooding and the pandemic. There have been 70 countries with flood events occurring after detection of the country's first COVID‐19 case and hundreds of thousands of people have been evacuated. The main objective of this article is to assess challenges that arise from complex intersections between the threat multipliers and to provide guidance on how to address them effectively. We consider the limitations of our knowledge including “unknown unknowns.” During emergency evacuation, practicing social distancing can be very difficult. However, people are going to take action to respond to rising waters, even if it means breaking quarantine. This is an emergency manager's nightmare scenario: two potentially serious emergencies happening at once. During this unprecedented year (2020), we are experiencing one of the most challenging flood seasons we have seen in a while. Practical examples of issues and guides for managing floods and COVID‐19 are presented. We feel that a new approach is needed in dealing with multiple hazards. Our main messages are: a resilience approach is needed whether in response to floods or a pandemic; preparation is vital, in addition to defense; the responsible actors must be prepared with actions plans and command structure, while the general population must be involved in the discussions so that they are aware of the risk and the reasons for the actions they must take.This article is categorized under:
Engineering Water > Methods
Adaptive sliding mode control of floating offshore wind turbine equipped by permanent magnet synchronous generator
Authors: Zhang Cheng , Plestan Franck 
Published: January 2021

AbstractHigh‐order sliding mode control laws with gain adaptation algorithms are applied, in Region III, on a floating offshore wind turbine equipped by permanent magnet synchronous generator (PMSG). These adaptive control methods are especially efficient for systems with uncertainties and external perturbations and are well adapted to wind turbines systems. Such controllers can be implemented with very reduced knowledge of system model (only the relative degree is necessary) and strongly reduce the controller gains tuning effort. Simulations are made on Fatigue, Aerodynamics, Structures and Turbulence (FAST) software and compared with standard gain‐scheduled proportional–integral (PI) controllers.
Optimization of chromium(VI) removal by indigenous microalga (Chlamydomonas sp.)‐based biosorbent using response surface methodology
Authors: Ayele Abate , Suresh Arumuganainar , Benor Solomon , Konwarh Rocktotpal 
Published: January 2021

AbstractPhycoremediation of heavy metals has garnered considerable recent research interest. In this study, an indigenous microalga (Chlamydomonas sp.)‐based biosorbent was employed for biosorption of Cr(VI) dissolved solids (Cr(VI)‐DS), optimized using response surface methodology (RSM). The effects of microalga concentration, pH, and contact time were studied with 250 mg Cr(VI)‐DS L−1. The biosorption of Cr(VI)‐DS was higher at acidic pH (94.17% at pH 4) than at alkaline conditions (68.53% at pH 10). The interaction of pH and microalga concentration exerted significant (p < 0.05) influence on the biosorption. Under the optimized parameters of 1.5 g microalga L−1, pH 4, and contact time of 30 min, a predicted biosorption of 91.31% and biosorption capacity of 152 mg Cr(VI)‐DS g−1 biomass were documented. FTIR analysis attested the electronegative surface functional groups of the microalgae biomass, bracketed together with its high biosorption potency. The study evinced the potential of the indigenous microalga for remediation of hexavalent chromium.Practitioner points

Indigenous Ethiopian microalga (Chlamydomonas sp.) exhibited 94% Cr(VI) abatement with biosorption capacity of 152 mg Cr(VI) g−1.
FTIR analysis of the biosorbent divulged the presence of electronegative functional groups (amino, carboxyl, hydroxyl, and carbonyl groups).
Higher biosorption of Cr(VI)‐DS under acidic pH (94.17% at pH 4) than alkaline pH (68.53% at pH 10).
Significant (p < 0.05) interaction effect of pH and biomass concentration on the biosorption, evinced in RSM optimization
91% Cr(VI) removal achieved under optimal conditions of 1.5 g biosorbent L−1, 30 min of contact time, and pH 4.
Dynamic transcriptomic m5C and its regulatory role in RNA processing
Authors: Chen Yu‐Sheng , Yang Wen‐Lan , Zhao Yong‐Liang , Yang Yun‐Gui 
Published: January 2021

AbstractRNA 5‐methylcytosine (m5C) is a prevalent RNA modification in multiple RNA species, including messenger RNAs (mRNAs), transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), and noncoding RNAs (ncRNAs), and broadly distributed from archaea, prokaryotes to eukaryotes. The multiple detecting techniques of m5C have been developed, such as m5C‐RIP‐seq, miCLIP‐seq, AZA‐IP‐seq, RNA‐BisSeq, TAWO‐seq, and Nanopore sequencing. These high‐throughput techniques, combined with corresponding analysis pipeline, provide a precise m5C landscape contributing to the deciphering of its biological functions. The m5C modification is distributed along with mRNA and enriched around 5′UTR and 3′UTR, and conserved in tRNAs and rRNAs. It is dynamically regulated by its related enzymes, including methyltransferases (NSUN, DNMT, and TRDMT family members), demethylases (TET families and ALKBH1), and binding proteins (ALYREF and YBX1). So far, accumulative studies have revealed that m5C participates in a variety of RNA metabolism, including mRNA export, RNA stability, and translation. Depletion of m5C modification in the organism could cause dysfunction of mitochondria, drawback of stress response, frustration of gametogenesis and embryogenesis, abnormality of neuro and brain development, and has been implicated in cell migration and tumorigenesis. In this review, we provide a comprehensive summary of dynamic regulatory elements of RNA m5C, including methyltransferases (writers), demethylases (erasers), and binding proteins (readers). We also summarized the related detecting technologies and biological functions of the RNA 5‐methylcytosine, and provided future perspectives in m5C research.This article is categorized under:
RNA Processing > RNA Editing and Modification
Application of an immobilized ionic liquid for the preparation of hydroxylamine via hydrolysis of cyclohexanone oxime
Authors: Wang Shuangyu , Liu Jiaqi , Cheng Peng , Li Zhihui , Zhang Dongsheng , Yang Qiusheng , Zhao Xinqiang , Wang Yanji 
Published: January 2021

AbstractPreparation of hydroxylamine via hydrolysis of cyclohexanone oxime was studied over porous SiO2 supported acid ionic liquid catalyst. The catalyst [SPIPTES]CF3SO3@SiO2 was prepared through sol‐gel method and characterized by elemental analysis, IR and TG, etc. Various parameters such as reaction temperature and time, catalyst amount were investigated systematically. The optimized reaction conditions investigated were catalyst:cyclohexanone oxime (mass ratio) 4 : 1, conducted at 60 °C for 1 h. Since the present hydrolysis reaction is controlled by thermodynamics, the conversion of cyclohexanone oxime could not be very high. However, reasonable result was achieved under the optimized reaction conditions. Cyclohexanone oxime conversion was 38.41 % and NH2OH yield was 37.65 %. Additionally, combining experiments with density functional theory calculations, a possible catalyst structure and reaction pathway involved protonated cyclohexanone oxime mechanism was proposed for the present hydrolysis in this study.
Mixed boundary value problems for Rayleigh wave in a half‐plane with cubic anisotropy
Authors: Şahin Onur 
Published: January 2021

AbstractThe paper deals with mixed boundary value problems in an elastic half‐plane with cubic symmetry. The formulation of the problem depends on an asymptotic model derived for anisotropic materials. It is demonstrated that defining the displacements in terms of a pair of plane harmonic functions reduces the problem to a classical isotropic form, which can be formulated within the framework of the asymptotic hyperbolic–elliptic model developed for isotropic materials. As an example, a semi‐infinite rigid stamp moving at a constant speed along the surface is considered.
Liouville quantum gravity — holography, JT and matrices
Authors: Mertens Thomas G. , Turiaci Gustavo J. 
Published: January 2021

Abstract
We study two-dimensional Liouville gravity and minimal string theory on spaces with fixed length boundaries. We find explicit formulas describing the gravitational dressing of bulk and boundary correlators in the disk. Their structure has a striking resemblance with observables in 2d BF (plus a boundary term), associated to a quantum deformation of SL(2, ℝ), a connection we develop in some detail. For the case of the (2, p) minimal string theory, we compare and match the results from the continuum approach with a matrix model calculation, and verify that in the large p limit the correlators match with Jackiw-Teitelboim gravity. We consider multi-boundary amplitudes that we write in terms of gluing bulk one-point functions using a quantum deformation of the Weil-Petersson volumes and gluing measures. Generating functions for genus zero Weil-Petersson volumes are derived, taking the large p limit. Finally, we present preliminary evidence that the bulk theory can be interpreted as a 2d dilaton gravity model with a sinh Φ dilaton potential.
Exploding operators for Majorana neutrino masses and beyond
Authors: Gargalionis John , Volkas Raymond R. 
Published: January 2021

Abstract
Building UV completions of lepton-number-violating effective operators has proved to be a useful way of studying and classifying models of Majorana neutrino mass. In this paper we describe and implement an algorithm that systematises this model-building procedure. We use the algorithm to generate computational representations of all of the tree-level completions of the operators up to and including mass-dimension 11. Almost all of these correspond to models of radiative neutrino mass. Our work includes operators involving derivatives, updated estimates for the bounds on the new-physics scale associated with each operator, an analysis of various features of the models, and a look at some examples. We find that a number of operators do not admit any completions not also generating lower-dimensional operators or larger contributions to the neutrino mass, ruling them out as playing a dominant role in the neutrino-mass generation. Additionally, we show that there are at most five models containing three or fewer exotic multiplets that predict new physics that must lie below 100 TeV. Accompanying this work we also make available a searchable database containing all of our results and the code used to find the completions. We emphasise that our methods extend beyond the study of neutrino-mass models, and may be useful for generating completions of high-dimensional operators in other effective field theories. Example code: ref. [37].
Quiver origami: discrete gauging and folding
Authors: Bourget Antoine , Hanany Amihay , Miketa Dominik 
Published: January 2021

Abstract
We study two types of discrete operations on Coulomb branches of 3d$$ \mathcal{N} $$
N
= 4 quiver gauge theories using both abelianisation and the monopole formula. We generalise previous work on discrete quotients of Coulomb branches and introduce novel wreathed quiver theories. We further study quiver folding which produces Coulomb branches of non-simply laced quivers. Our methods explicitly describe Coulomb branches in terms of generators and relations including mass deformations.
An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview
Authors: Zahoor Insha , Rui Bin , Khan Junaid , Datta Indrani , Giri Shailendra 
Published: January 2021

AbstractMultiple sclerosis (MS) is an inflammatory demyelinating disease of the nervous system that primarily affects young adults. Although the exact etiology of the disease remains obscure, it is clear that alterations in the metabolome contribute to this process. As such, defining a reliable and disease-specific metabolome has tremendous potential as a diagnostic and therapeutic strategy for MS. Here, we provide an overview of studies aimed at identifying the role of metabolomics in MS. These offer new insights into disease pathophysiology and the contributions of metabolic pathways to this process, identify unique markers indicative of treatment responses, and demonstrate the therapeutic effects of drug-like metabolites in cellular and animal models of MS. By and large, the commonly perturbed pathways in MS and its preclinical model include lipid metabolism involving alpha-linoleic acid pathway, nucleotide metabolism, amino acid metabolism, tricarboxylic acid cycle,d-ornithine andd-arginine pathways with collective role in signaling and energy supply. The metabolomics studies suggest that metabolic profiling of MS patient samples may uncover biomarkers that will advance our understanding of disease pathogenesis and progression, reduce delays and mistakes in diagnosis, monitor the course of disease, and detect better drug targets, all of which will improve early therapeutic interventions and improve evaluation of response to these treatments.
Machine-learning algorithm that can improve the diagnostic accuracy of septic arthritis of the knee
Authors: Choi Eun-Seok , Sim Jae Ang , Na Young Gon , Seon Jong- Keun , Shin Hyun Dae 
Published: January 2021

Abstract
Purpose
Prompt diagnosis and treatment of septic arthritis of the knee is crucial. Nevertheless, the quality of evidence for the diagnosis of septic arthritis is low. In this study, the authors developed a machine learning-based diagnostic algorithm for septic arthritis of the native knee using clinical data in an emergency department and validated its diagnostic accuracy.

Methods
Patients (n = 326) who underwent synovial fluid analysis at the emergency department for suspected septic arthritis of the knee were enrolled. Septic arthritis was diagnosed in 164 of the patients (50.3%) using modified Newman criteria. Clinical characteristics of septic and inflammatory arthritis were compared. Area under the receiver-operating characteristic (ROC) curve (AUC) statistics was applied to evaluate the efficacy of each variable for the diagnosis of septic arthritis. The dataset was divided into independent training and test sets (comprising 80% and 20%, respectively, of the data). Supervised machine-learning techniques (random forest and eXtreme Gradient Boosting: XGBoost) were applied to develop a diagnostic model using the training dataset. The test dataset was subsequently used to validate the developed model. The ROC curves of the machine-learning model and each variable were compared.

Results
Synovial white blood cell (WBC) count was significantly higher in septic arthritis than in inflammatory arthritis in the multivariate analysis (P = 0.001). In the ROC comparison analysis, synovial WBC count yielded a significantly higher AUC than all other single variables (P = 0.002). The diagnostic model using the XGBoost algorithm yielded a higher AUC (0.831, 95% confidence interval 0.751–0.923) than synovial WBC count (0.740, 95% confidence interval 0.684–0.791; P = 0.033). The developed algorithm was deployed as a free access web-based application (www.septicknee.com).

Conclusion
The diagnosis of septic arthritis of the knee might be improved using a machine learning-based prediction model.

Level of evidence
Diagnostic study Level III (Case–control study).
Hydrolytic secretome engineering in Yarrowia lipolytica for consolidated bioprocessing on polysaccharide resources: review on starch, cellulose, xylan, and inulin
Authors: Celińska Ewelina , Nicaud Jean-Marc , Białas Wojciech 
Published: January 2021

Abstract
Consolidated bioprocessing (CBP) featuring concomitant hydrolysis of renewable substrates and microbial conversion into value-added biomolecules is considered to bring substantial benefits to the overall process efficiency. The biggest challenge in developing an economically feasible CBP process is identification of bifunctional biocatalyst merging the ability to utilize the substrate and convert it to value-added product with high efficiency. Yarrowia lipolytica is known for its exceptional performance in hydrophobic substrates assimilation and storage. On the other hand, its capacity to grow on plant-derived biomass is strongly limited. Still, its high potential to simultaneously overproduce several secretory proteins makes Y. lipolytica a platform of choice for expanding its substrate range to complex polysaccharides by engineering its hydrolytic secretome. This review provides an overview of different genetic engineering strategies advancing development of Y. lipolytica strains able to grow on the following four complex polysaccharides: starch, cellulose, xylan, and inulin. Much attention has been paid to genome mining studies uncovering native potential of this species to assimilate untypical sugars, as in many cases it turns out that dormant pathways are present in Y. lipolytica’s genome. In addition, the magnitude of the economic gain by CBP processing is here discussed and supported with adequate calculations based on simulated process models.

Key points
• The mini-review updates the knowledge on polysaccharide-utilizing Yarrowia lipolytica.
• Insight into molecular bases founding new biochemical qualities is provided.
• Model industrial processes were simulated and the associated costs were calculated.