bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrahigh concentration and stable dispersion of graphite nanosheet paste as composite nanofillers for thermal management and electromagnetic shielding
Authors: Su Liying , Wang Jie , Zhou Jiale , Wang Jianfeng , Teng Chao 
Published: May 2021

AbstractGraphene provides thermal and electrical conductivity to polymer composites, which significantly improves the properties of heat dissipation and electromagnetic interference (EMI) shielding. However, due to the low concentration and stability of graphene dispersion, its industrial application is greatly hindered. In this work, graphite nanosheet (GNS) paste was successfully fabricated from the expanded graphite through wet ball‐milling technology in a one pot process. The ultrahigh GNS concentration is up to 59.4 mg mL−1, and exhibits high stability for 6 months. Furthermore, the average thickness of GNS is less than 10 layers. The GNS paste could mix uniformly with polymer dispersion to obtain large‐area and flexible films by the doctor‐blading process. The composites containing 80 wt% GNS exhibit layered structure, leading to high thermal conductivities with an in‐plane value of 71.18 W m−1 K, far surpassing the pristine polymer material (0.19 W m−1 K), and reveal an efficient total electromagnetic shielding (SEtot≈ 45 dB in the range of 8.2 to 12.4 GHz). This work provides a direct route to prepare composites with high thermal conductivity and EMI shielding from ultrahigh concentration GNS paste.
Enhanced fuzzy state estimation of discrete‐time nonlinear systems via a multi‐instant united switch‐type observer
Authors: Lu Hongyu , Xie Xiangpeng , Liu Wei 
Published: May 2021

AbstractThe performance of state estimation of discrete‐time Takagi–Sugeno systems is enhanced by proposing a featured multiinstant united switch‐type observer. The novelty of the proposed observer lies in both the definition and application of a set of switching modes. Since different time‐variant free matrices can be for the first time introduced in accordance with each switching mode, both the current time and the past time normalized fuzzy weighting functions are together considered for designing the corresponding observer gain matrices with much less conservatism than those recent methods reported in the literature. Furthermore, there are only two tuning parameters which are both located in a limited candidate set and thus this fact does benefit for giving the optimal solution of our developed multiinstant united switch‐type candidates. Finally, numerical comparisons are provided in order to verify the technical superiority of the results developed in this article.
A new double EWMA‐t chart with auxiliary information for the process mean
Authors: Haq Abdul , Ejaz Sana , Lee Ming Ha , Khan Manzoor 
Published: May 2021

AbstractIn this paper, we propose an auxiliary‐information‐based (AIB) double EWMA‐ (AIB‐DEWMA‐) chart for monitoring the process mean. The DEWMA‐ chart encompasses the EWMA‐ and AIB‐EWMA‐ charts. The Monte Carlo simulations are used to compute the run length characteristics of the AIB‐DEWMA‐ chart. Based on detailed run length comparisons, it is found that the AIB‐DEWMA‐ chart may uniformly and substantially outperform the AIB‐EWMA‐ chart when detecting different shifts in the process mean. In addition, the AIB‐DEWMA‐ chart is uniformly more sensitive than the DEWMA‐ chart. Similar trends are observed when comparing these control charts with the variable sampling interval feature. A real dataset is also considered to demonstrate the implementation of the proposed chart.
An extended nonparametric homogeneously weighted moving average sign control chart
Authors: Alevizakos Vasileios , Chatterjee Kashinath , Koukouvinos Christos 
Published: May 2021

AbstractParametric (or traditional) control charts are based on the assumption that the quality characteristic of interest follows a specific distribution. However, in many applications, there is a lack of knowledge about the underlying distribution. To this end, nonparametric (or distribution‐free) control charts have been developed in recent years. In this article, a nonparametric double homogeneously weighted moving average (DHWMA) control chart based on the sign statistic is proposed for monitoring the location parameter of an unknown and continuous distribution. The performance of the proposed chart is measured through the run‐length distribution and its associated characteristics by performing Monte Carlo simulations. The DHWMA sign chart is compared with other nonparametric sign charts, such as the homogeneously weighted moving average, generally weighted moving average (GWMA), double GWMA, and triple exponentially weighted moving average sign charts, as well as the traditional DHWMA chart. The results indicate that the proposed chart performs just as well as and in some cases better than its competitors, especially for small shifts. Finally, two examples are provided to show the application and implementation of the proposed chart.
INFERYS rescoring: Boosting peptide identifications and scoring confidence of database search results
Authors: Zolg Daniel P. , Gessulat Siegfried , Paschke Carmen , Graber Michael , Rathke‐Kuhnert Magnus , Seefried Florian , Fitzemeier Kai , Berg Frank , Lopez‐Ferrer Daniel , Horn David , Henrich Christoph , Huhmer Andreas , Delanghe Bernard , Frejno Martin 
Published: May 2021

Database search engines for bottom‐up proteomics largely ignore peptide fragment ion intensities during the automated scoring of tandem mass spectra against protein databases. Recent advances in deep learning allow the accurate prediction of peptide fragment ion intensities. Using these predictions to calculate additional intensity‐based scores helps to overcome this drawback.Here, we describe a processing workflow termed INFERYS™ rescoring for the intensity‐based rescoring of Sequest HT search engine results in Thermo Scientific™ Proteome Discoverer™ 2.5 software. The workflow is based on the deep learning platform INFERYS capable of predicting fragment ion intensities, which runs on personal computers without the need for graphics processing units. This workflow calculates intensity‐based scores comparing peptide spectrum matches from Sequest HT and predicted spectra. Resulting scores are combined with classical search engine scores for input to the false discovery rate estimation tool Percolator.We demonstrate the merits of this approach by analyzing a classical HeLa standard sample and exemplify how this workflow leads to a better separation of target and decoy identifications, in turn resulting in increased peptide spectrum match, peptide and protein identification numbers. On an immunopeptidome dataset, this workflow leads to a 50% increase in identified peptides, emphasizing the advantage of intensity‐based scores when analyzing low‐intensity spectra or analytes with very similar physicochemical properties that require vast search spaces.Overall, the end‐to‐end integration of INFERYS rescoring enables simple and easy access to a powerful enhancement to classical database search engines, promising a deeper, more confident and more comprehensive analysis of proteomic data from any organism by unlocking the intensity dimension of tandem mass spectra for identification and more confident scoring.
Cas9‐Cleavage Sequences in Size‐Reduced Plasmids Enhance Nonviral Genome Targeting of CARs in Primary Human T Cells
Authors: Jing Ruirui , Jiao Peng , Chen Jiangqing , Meng Xianhui , Wu Xiaoyan , Duan Yanting , Shang Kai , Qian Liling , Huang Yanjie , Liu Junwei , Huang Tao , Jin Jin , Chen Wei , Zeng Xun , Yin Weiwei , Gao Xiaofei , Zhou Chun , Sadelain Michel , Sun Jie 
Published: May 2021

AbstractT cell genome editing holds great promise to advance a range of immunotherapies but is encumbered by the dependence on difficult‐to‐produce and expensive viral vectors. Here, small double‐stranded plasmid DNA modified to mediate high‐efficiency homologous recombination is designed. The resulting chimeric antigen receptor (CAR)‐T cells display a similar phenotype, transcriptional profile, and in vivo potency to CAR‐T cells generated using adeno‐associated viral vector. This method should simplify and accelerate the use of precision engineering to produce edited T cells for research and clinical purposes.
Synthesis of a complex prototype filter including no inductors and its Realization Using CCII's
Authors: Fujii Tatsuya , Shouno Kazuhiro 
Published: May 2021

AbstractIn this paper, synthesis of a complex prototype filter including no inductors and its realization using Second Generation Current Conveyors (CCII's) are proposed. The proposed complex prototype filter is obtained through the frequency shifting method and an equivalent transformation. The proposed complex prototype filter includes no inductors and has fewer nodes connected to imaginary resistors than the conventional one. The proposed filter is compared with the conventional one from the viewpoints of the sensitivity characteristics and the number of the required elements. The frequency response is improved by compensating the parasitic resistors included in CCII's. The validity of the proposed method is confirmed through experiment. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
MiR‐17‐5p downregulation alleviates apoptosis and fibrosis in high glucose‐induced human mesangial cells through inactivation of Wnt/β‐catenin signaling by targeting KIF23
Authors: Chen Xiaoli , Gu Liyan , Cheng Xia , Xing Jianping , Zhang Minxia 
Published: May 2021

AbstractDiabetic nephropathy (DN) remains the major cause of end‐stage renal disease. MicroRNAs (miRNAs) have been reported to perform biological functions in many diseases. This investigation elucidated the biological role of miR‐17‐5p in DN. In this study, high glucose‐cultured human mesangial cells (HMCs) were used as a cell model of DN. The miR‐17‐5p and KIF23 expression was measured by RT‐qPCR. Cell apoptosis was detected by flow cytometry. The protein levels of apoptosis markers, fibrosis markers, and Wnt/β‐catenin signaling‐related genes were assessed using western blotting. The interaction of miR‐17‐5p with KIF23 was tested by a luciferase reporter assay. We found that miR‐17‐5p was upregulated in both DN patients and high glucose‐treated HMCs. Silencing miR‐17‐5p attenuated the apoptosis and fibrosis in high glucose‐treated HMCs. MiR‐17‐5p binds to KIF23 3′UTR and negatively regulates KIF23 expression. KIF23 knockdown could suppress the role of miR‐17‐5p inhibition in high glucose‐treated HMCs. Additionally, inhibition of miR‐17‐5p activated Wnt/β‐catenin signaling in HMCs through upregulating KIF23 expression. Suppression of Wnt/β‐catenin signaling antagonized the effect of miR‐17‐5p in HMCs. In conclusion, miR‐17‐5p inhibition alleviates the apoptosis and fibrosis in high glucose‐treated HMCs by targeting KIF23 activating Wnt/β‐catenin signaling.
Molecular characterization of dissolved organic nitrogen during anoxic/oxic and anammox processes using ESI FT–ICR MS
Authors: Zhang Li , Zheng Kexin , Wang Yueping , Peng Yongzhen 
Published: May 2021

AbstractDissolved organic nitrogen (DON) is a component of wastewater with a negative influence on the environment. The removal of DON is conducted through the anoxic/oxic (A/O) and anammox processes. However, the mechanisms and chemical preferences in the removal of DON compounds have not been understood and compared so far. This study, for the first time, comparatively investigated the molecular‐level characteristics of DON during both processes by using FT–ICR MS (Fourier transform ion cyclotron resonance mass spectrometry). The results indicated that the number of DON formulas increased from 1844 to 1935 during A/O process, and from 2784 to 3242 during anammox process, highlighting the increase in complexity of DON after undergoing both processes. DON with high saturation and aliphatic structures was removed by A/O process, whereas highly unsaturated and aromatic structures were removed by anammox process. For DON without S atom, Lignin‐like and tannin‐like ones were resistant to both processes and protein‐like and condensed aromatic structures were resistant to anammox process. The complementarity of these two processes provided a sequential combination with sufficient theoretical support to improve DON removal efficiency.Practitioner points

Molecular components of dissolved organic nitrogen characterized by ESI FT–ICR MS.
DON removal preferences of A/O and anammox processes evaluated.
A/O and anammox processes are effective to remove aliphatic and aromatic DON, respectively.
Complementarity in removal preferences of A/O and anammox processes can remove recalcitrant DON of each other.
Sequential A/O and anammox processes can improve DON removal.
“Conservation Agriculture,” Possible Climate Change Adaptation Option in Taita Hills, Kenya
Authors: Motaroki Lilian , Ouma Gilbert , Kalele Dorcas 
Published: May 2021

AbstractThe vicious cycle of food insecurity in Kenya and Africa at large is partly attributed to the high reliance on rainfed agriculture, which makes production systems vulnerable to the adverse impacts of climate change and variability. Conservation agriculture (CA) has been disseminated as a climate-smart practice that operates on three main principles to realize the multiple benefits of making crop production systems more resilient to climate change impacts, enhancing food security, and providing environmental services, such as carbon sequestration. As a major source of livelihood in the Taita Hills, agriculture is constrained by climate change owing to its rainfed nature. The yield and environmental and economic benefits of CA make it a suitable alternative approach to sustainable agricultural intensification, which is fundamentally different from conventional approaches based on intensive tillage and often disrupts ecosystem functions. This chapter provides the rationale for enhancing the adoption of CA in the Taita Hills by evaluating the current challenges affecting crop production, the role of CA in addressing the challenges and its potential benefits, and the barriers that must be overcome in order to promote its wide-scale adoption. A number of constraints appear to hinder the wide-scale adoption of CA in the Taita Hills, including lack of awareness, tenure-related issues, and weak policy and institutional support. Addressing these constraints will help catalyze investments for upscaling CA in the Taita Hills, with potential for replication in other parts of the country.
Digital Platforms in Climate Information Service Delivery for Farming in Ghana
Authors: Sarku Rebecca , Appiah Divine Odame , Adiku Prosper , Alare Rahinatu Sidiki , Dotsey Senyo 
Published: May 2021

AbstractPhone-based applications, Internet connectivity, and big data are enabling climate change adaptations. From ICT for development and agriculture perspectives, great interest exists in how digital platforms support climate information provision for smallholder farmers in Africa. The vast majority of these platforms both private and public are for delivering climate information services and for data collection. The sheer number of digital platforms in the climate information sector has created a complex information landscape for potential information users, with platforms differing in information type, technology, geographic coverage, and financing structures and infrastructure. This chapter mapped the existing climate information services and examined their impact on policy and practices in smallholder farming development in Africa, with a focus on Ghana. Specifically, the chapter provides highlights of digital platforms available to smallholder farmers and agricultural extension agents, analyzes the public and/or private governance arrangements that underpin the implementation of digital climate information delivery, and assesses the potential of these platforms in scaling up the use of climate information. The chapter contributes to understanding the dynamics of climate information delivery with digital tools in Africa, and suggests a future research agenda.
Use and Impact of Artificial Intelligence on Climate Change Adaptation in Africa
Authors: Rutenberg Isaac , Gwagwa Arthur , Omino Melissa 
Published: May 2021

AbstractAlthough Climate Change is a global phenomenon, the impact in Africa is anticipated to be greater than in many other parts of the world. This expectation is supported by many factors, including the relatively low shock tolerance of many African countries and the relatively high percentage of African workers engaged in the agricultural sector. High-income countries are increasingly turning their focus to climate change adaptation, and Artificial Intelligence (AI) is a critical tool in those efforts. Algorithms using AI are making better predictions on the short- and long-term effects of climate change, including predictions related to weather patterns, floods and droughts, and human migration patterns. It is not clear, however, that Africa is (or will be) maximally benefitting from those AI tools, particularly since they are largely developed by highly developed countries using data sets that are specific to those same countries. It is therefore important to characterize the efforts underway to use AI in a way that specifically benefits Africa in climate change adaptation. These efforts include projects undertaken physically in Africa as well as those that have Africa as their focus. In exploring AI projects in or about Africa, this chapter also looks at the sufficiency of such efforts and the variety of approaches taken by researchers working with AI to address climate change in Africa.
Bridging the Metabolic Parallels Between Neurological Diseases and Cancer
Authors: Guo Shenghao , Gu Yanni , Qu Jiayin , Le Anne 
Published: May 2021

AbstractDespite the many recent breakthroughs in cancer research, oncology has traditionally been seen as a distinct field from other diseases. Recently, more attention has been paid to repurposing established therapeutic strategies and targets of other diseases towards cancer treatment, with some of these attempts generating promising outcomes [1, 2]. Recent studies using advanced metabolomics technologies [3] have shown evidence of close metabolic similarities between cancer and neurological diseases. These studies have unveiled several metabolic characteristics shared by these two categories of diseases, including metabolism of glutamine, gamma-aminobutyric acid (GABA), and N-acetyl-aspartyl-glutamate (NAAG) [4–6]. The striking metabolic overlap between cancer and neurological diseases sheds light on novel therapeutic strategies for cancer treatment. For example, 2-(phosphonomethyl) pentanedioic acid (2-PMPA), one of the glutamate carboxypeptidase II (GCP II) inhibitors that prevent the conversion of NAAG to glutamate, has been shown to suppress cancer growth [6, 7]. These promising results have led to an increased interest in integrating this metabolic overlap between cancer and neurological diseases into the study of cancer metabolism. The advantages of studying this metabolic overlap include not only drug repurposing but also translating existing knowledge from neurological diseases to the field of cancer research. This chapter discusses the specific overlapping metabolic features between cancer and neurological diseases, focusing on glutamine, GABA, and NAAG metabolisms. Understanding the interconnections between cancer and neurological diseases will guide researchers and clinicians to find more effective cancer treatments.
Intersecting surface defects and 3d superconformal indices
Authors: Liu Junfeng , Pan Yiwen , Zhang Hong-Hao 
Published: May 2021

Abstract
We compute the 3d $$ \mathcal{N} $$
N
= 2 superconformal indices for 3d/1d coupled systems, which arise as the worldvolume theories of intersecting surface defects engineered by Higgsing 5d $$ \mathcal{N} $$
N
= 1 gauge theories. We generalize some known 3d dualities, including non-Abelian 3d mirror symmetry and 3d/3d correspondence, to some of the simple 3d/1d coupled systems. Finally we propose a q-Virasoro construction for the superconformal indices.
Global fits of axion-like particles to XENON1T and astrophysical data
Authors: Athron Peter , Balázs Csaba , Beniwal Ankit , Camargo-Molina J. Eliel , Fowlie Andrew , Gonzalo Tomás E. , Hoof Sebastian , Kahlhoefer Felix , Marsh David J. E. , Prim Markus Tobias , Scaffidi Andre , Scott Pat , Su Wei , White Martin , Wu Lei , Zhang Yang 
Published: May 2021

Abstract
The excess of electron recoil events seen by the XENON1T experiment has been interpreted as a potential signal of axion-like particles (ALPs), either produced in the Sun, or constituting part of the dark matter halo of the Milky Way. It has also been explained as a consequence of trace amounts of tritium in the experiment. We consider the evidence for the solar and dark-matter ALP hypotheses from the combination of XENON1T data and multiple astrophysical probes, including horizontal branch stars, red giants, and white dwarfs. We briefly address the influence of ALP decays and supernova cooling. While the different datasets are in clear tension for the case of solar ALPs, all measurements can be simultaneously accommodated for the case of a sub-dominant fraction of dark-matter ALPs. Nevertheless, this solution requires the tuning of several a priori unknown parameters, such that for our choices of priors a Bayesian analysis shows no strong preference for the ALP interpretation of the XENON1T excess over the background hypothesis.
Determinant form of correlators in high rank integrable spin chains via separation of variables
Authors: Gromov Nikolay , Levkovich-Maslyuk Fedor , Ryan Paul 
Published: May 2021

Abstract
In this paper we take further steps towards developing the separation of variables program for integrable spin chains with $$ \mathfrak{gl}(N) $$
gl

N

symmetry. By finding, for the first time, the matrix elements of the SoV measure explicitly we were able to compute correlation functions and wave function overlaps in a simple determinant form. In particular, we show how an overlap between on-shell and off-shell algebraic Bethe states can be written as a determinant. Another result, particularly useful for AdS/CFT applications, is an overlap between two Bethe states with different twists, which also takes a determinant form in our approach. Our results also extend our previous works in collaboration with A. Cavaglia and D. Volin to general values of the spin, including the SoV construction in the higher-rank non-compact case for the first time.
The rationality of M&A targets in the choice of payment methods
Authors: Klitzka Michael , He Jianan , Schiereck Dirk 
Published: May 2021

AbstractThis study analyzes mergers and acquisitions (M&A) payment methods in large transactions of public U.S. acquirers between 2009 and 2016. While we find consistent with previous evidence that asymmetric information between acquirers and targets significantly influences the choice of M&A payment methods, we show that contrary to prevailing findings in the literature, acquirers cannot exploit their overvaluation through stock-financed M&A at targets’ disadvantage. In addition, when facing larger uncertainty in the counterparty’s valuation, a higher ratio of cash is applied in M&A payment. Our results document that both acquirers and targets are rational in choosing M&A payment methods.