bluuebunny/crossref_metadata_2025_split huggingface dataset:
High‐efficient bacterial production of human ApoA‐I amyloidogenic variants
Authors: Del Giudice Rita , Lagerstedt Jens O. 
Published: October 2018

AbstractApolipoprotein A‐I (ApoA‐I)‐related amyloidosis is a rare disease caused by missense mutations in the APOA1 gene. These mutations lead to protein aggregation and abnormal accumulation of ApoA‐I amyloid fibrils in heart, liver, kidneys, skin, nerves, ovaries, or testes. Consequently, the carriers are at risk of single‐ or multi‐organ failure and of need of organ transplantation. Understanding the basic molecular structure and function of ApoA‐I amyloidogenic variants, as well as their biological effects, is, therefore, of great interest. However, the intrinsic low stability of this type of proteins makes their overexpression and purification difficult. To overcome this barrier, we here describe an optimized production and purification procedure for human ApoA‐I amyloidogenic proteins that efficiently provides between 46 mg and 91 mg (depending on the protein variant) of pure protein per liter of Escherichia coli culture. Structural integrity of the amyloidogenic and native ApoA‐I proteins were verified by circular dichroism spectroscopy and intrinsic fluorescence analysis, and preserved functionality was demonstrated by use of a lipid clearance assay as well as by reconstitution of high‐density lipoprotein (HDL) particles. In conclusion, the use of the described high‐yield protein production system to obtain amyloidogenic ApoA‐I proteins, and their native counterpart, will enable molecular and cellular experimental studies aimed to explain the molecular basis for this rare disease.
A Systematic Evaluation of Effect of Adherence Patterns on the Sample Size and Power of a Clinical Study
Authors: Mallayasamy Surulivelrajan , Chaturvedula Ayyappa , Blaschke Terrence , Fossler Michael J. 
Published: October 2018

The objective of our study was to evaluate the effect of adherence patterns on the sample size and power of a clinical trial. Simulations from a population pharmacokinetic/pharmacodynamic (PK/PD) model linked to an adherence model were used. Four types of drug characteristics, such as long (~35 hours) and short (~12 hours) half‐life in combination with earlier or delayed time to reach steady‐state PD end points were studied. Adherence patterns were simulated using Markov chains. Our results clearly demonstrate the significant impact of varying levels and patterns of nonadherence on the sample size and power of a study. For drugs with short half‐lives the evidence to support efficacy could be diluted by various patterns of nonadherence that would make its efficacy indistinguishable from the response to placebo. Prospectively utilizing clinical trial simulations with thorough incorporation of various adherence patterns would provide valuable information when designing a trial.
Reliability analysis of standby systems with multi‐state elements subject to constant transition rates
Authors: Jia Heping , Levitin Gregory , Ding Yi , Song Yonghua 
Published: October 2018

AbstractStandby redundancy has been extensively applied to critical engineering systems to enhance system reliability. Researches on reliability evaluation for standby systems focus more on systems with binary‐state elements. However, multi‐state elements with different performances have played a significant role in engineering systems. This paper presents an approach for reliability analysis of standby systems composed of multi‐state elements with constant state transition rates and absorbing failure states. The approach allows modelling different standby systems beyond cold, warm and hot ones by taking into account differences in possible maintenance of elements in standby and operation modes and dependence of elements' operational behavior on their initial state at the time of activation. An iterative algorithm for reliability evaluation based on element state probabilities is suggested. Illustrating examples of evaluating reliability of different types of homogeneous and heterogeneous standby systems are demonstrated.
Real options economic control chart for binomial and normal processes
Authors: Moltchanova Elena 
Published: October 2018

AbstractIn this paper, we extend the earlier presented real options control chart (ROCC). In the real options framework, at any given moment, we compare the cost of recalibrating the process with the cost of postponing the (optimal) decision for later. The decision is thus based on cost minimization rather than statistically significant deviations from the in‐control process. We explain the general principles of constructing ROCC for both discrete and continuous processes and the describe the numeric algorithms that allow us to apply these principles to the cases of binomial and Gaussian process. Simulation studies demonstrate that, on average, ROCC runs longer than the standard economic control chart (SECC) and outperforms it in terms of average final costs.
Development of a liquid chromatography/tandem mass spectrometry method for monitoring of long‐term exposure to parabens
Authors: Cho Sung‐Hee , Song Han‐Na 
Published: October 2018

RationaleParabens, the alkyl esters of 4‐hydroxybenzoic acid, are a family of compounds widely used as preservatives in cosmetic products, including for children, and some are permitted in foods. Parabens are known to be weak endocrine disruptors because they interfere with the function of endogenous hormones through binding to estrogen receptors. Therefore, the levels of parabens in biological samples indicate endocrine‐disruptive exposure. In particular, hair samples can provide information on accumulated exposure to parabens.MethodsFor monitoring of long‐term exposure to parabens, an improved analytical method for rapid and direct determination in hair sample was developed involving ultra‐performance liquid chromatography–tandem mass spectrometry using on‐line extraction. Five parabens (methyl‐, ethyl‐, propyl‐, butyl‐ and benzylparaben) were separated within 10 min after incubation with 1 N HCl. Parabens were separated using a Waters BEH C18 column (2.1 mm × 100 mm, 1.7 μm) and a mobile phase consisting of 10 mM ammonium acetate in water and acetonitrile with a gradient program at a flow rate of 300 μL/min. The analysis of the separated parabens was monitored with electrospray negative ionization tandem mass spectrometry.ResultsThe linearity of the method was demonstrated by r2 ≥ 0.994. The limits of detection as defined by a signal‐to‐noise ratio of 3 were 1–5 ng/g. The mean concentration of the five parabens in hair of human subjects was measured to be 55.6 ± 24.3 to 136.9 ± 48.5 ng/g.ConclusionsThe levels of parabens in hair samples may play an important role in understanding probable endocrine‐disruptive exposure, and the described method could be used to evaluate and monitor long‐term exposure to parabens as endocrine disruptors.
Bipartite synchronization of Lur'e network under signed digraph
Authors: Liu Fang , Song Qiang , Wen Guanghui , Lu Jianquan , Cao Jinde 
Published: October 2018

SummaryThis paper considers the bipartite leaderless and leader‐following synchronization in a network of coupled Lur'e systems with sector‐condition node dynamics and signed digraph topology, where the interaction digraph consists of both positive and negative communication links. Continuous‐time and sampled‐data control algorithms are, respectively, proposed to solve the bipartite synchronization problems for the signed Lur'e network. Under some assumptions on the network structure and node functions, some bipartite synchronization conditions are established for signed Lur'e network by using coordinate transform, linear matrix inequalities, and algebraic graph theories. For the continuous‐time control algorithms, it is shown that the bipartite synchronization problems of the signed Lur'e network can always be solved if the coupling strength is sufficiently large and the network topology satisfies some suitable conditions. For the sampled‐data control algorithms, an upper bound of the sampling intervals is estimated to ensure that the bipartite synchronization can be reached in the signed Lur'e network. Some simulation results are given to illustrate the effectiveness of the theoretical analysis.
Handling of nonlinear systems using filtered high‐gain output feedback controller
Authors: Ma Tong , Liu Yuqian , Shih Cyuansi , Cao Chengyu 
Published: October 2018

SummaryThis paper develops a filtered high‐gain output feedback controller for a class of nonlinear systems in the presence of unknown state‐dependent and time‐varying nonlinearities. It considers that the nonlinearities satisfy a semiglobal Lipschitz condition. The presence of high‐gain observer in the adaptive law delivers a good property of disturbance rejection at the cost of peaking phenomenon as well as reduced robustness. The addition of filtering mechanism in the control law overcomes the cons of high‐gain observer and makes it robust to uncertainties in modeling the nonlinear functions. In this way, the filtered high‐gain output feedback controller realizes nonlinear time‐varying uncertainty cancelation and good tracking delivering with guaranteed robustness. The simulation results demonstrate the high efficiency of our novel design for handling of a class of nonlinear systems in the presence of time‐varying uncertainty when compared with saturated control signal.
Exploring the impacts of carbon tax on tourism‐related energy consumption in China
Authors: Zhang Jiekuan , Zhang Yan 
Published: October 2018

AbstractA carbon tax policy has been advocated as an effective tool to develop low‐carbon economy in China. As one of the most influential and dynamic industries, Chinese tourism industry will foresee a new challenge under the carbon tax scenario. Given this background, this study explores the impacts of carbon tax on tourism development from the perspective of energy consumption by using computable general equilibrium modeling in China. Our findings clearly indicate that (a) the proportion of tourism energy consumption to national energy consumption in China will increase over time, (b) the impacts of carbon tax on China's tourism fossil energy consumption, electricity consumption, and energy intensity will become increasingly weak, (c) the impacts of a carbon tax on electricity use are greater than the impacts on fossil fuel consumption, and (d) the impacts of different carbon taxes on the levels of energy consumption and energy intensity will vary to a significant degree between the different tourism sectors. Our results are conducive to recognizing the changes of tourism energy consumption levels after levying a carbon tax. Furthermore, this paper also has a certain reference value to guide any relevant, subsequent studies in other destinations or economic sectors, worldwide.
Nitride‐Based Microlight‐Emitting Diodes Using AlN Thin‐Film Electrodes with Nanoscale Indium/Tin Conducting Filaments
Authors: Son Kyung Rock , Lee Tae Ho , Lee Byeong Ryong , Im Hyun Sik , Kim Tae Geun 
Published: October 2018

AbstractMicrolight‐emitting diodes (µLEDs) are emerging solutions for both high‐quality displays and lighting technologies. However, the overall light output power density of these devices is low, as the emission area is shielded by the p‐electrodes required for current injection. In this study, instead of the more conventionally used indium tin oxide (ITO), an AlN thin film with nanoscale conducing filaments (CFs) is used, referred to as CF‐AlN, as a transparent conducting electrode (TCE), to enhance the output power density from the same emission area. As a result of this modification, the electroluminescence intensity is enhanced by 10% at an injection current of 10 mA, and the current density is improved by 13% at a forward voltage of 4.9 V, in comparison to the parameters observed with ITO‐based µLEDs. This improvement is attributed to the higher transmittance of CF‐AlN TCEs, together with efficient hole injection from the p‐electrode into the light‐emitting layer, through the CFs formed in the AlN layer. In addition, using transmission electron microscopy analyses, the origin of the CFs is directly identified as the diffusion of In and Sn ions, which provides critical insight into the conduction mechanism of AlN‐based TCEs.
Emergence of New Density–Strength Scaling Law in 3D Hollow Ceramic Nanoarchitectures
Authors: Na Ye‐eun , Shin Dahye , Kim Kisun , Ahn Changui , Jeon Seokwoo , Jang Dongchan 
Published: October 2018

AbstractDensity–strength tradeoff appears to be an inherent limitation for most materials and therefore design of cell topology that mitigates strength decrease with density reduction has been a long‐lasting engineering pursue for porous materials. Continuum‐mechanics‐based analyses of mechanical responses of conventional porous materials with bending‐dominated structures often give the density–strength scaling law following the power‐law relationship with an exponent of 1.5 or higher, which consequentially determines the upper bound of the specific strength for a material to reach. In this work, a new design criterion capable of significantly abating strength degradation in lightweight materials is presented, by successfully combining the size‐induced strengthening effect in nanomaterials with the architectural design of cellular porous materials. Hollow‐tube‐based 3D ceramic nanoarchitectures satisfying such criterion are fabricated in large area using proximity field nano‐patterning and atomic layer deposition. Experimental data from micropillar compression confirm that the strengths of these nanoarchitectural materials scale with relative densities with a power‐law exponent of 0.93, a hardly observable value in conventional bending‐dominated porous materials. This discovery of a new density–strength scaling law in nanoarchitectured materials will contribute to creating new lightweight structural materials attaining unprecedented specific strengths overcoming the conventional limit.
Radiofrequency‐Triggered Drug Release from Nanoliposomes with Millimeter‐Scale Resolution Using a Superimposed Static Gating Field
Authors: Liu Jessica F. , Neel Nishant , Dang Phillip , Lamb Max , McKenna Jaime , Rodgers Lauren , Litt Brian , Cheng Zhiliang , Tsourkas Andrew , Issadore David 
Published: October 2018

AbstractDrug delivery to a specific site in the body typically relies on the use of targeting agents that recognize a unique biomarker. Unfortunately, it is often difficult to identify unique molecular signatures that exist only at the site of interest. An alternative strategy is to deliver energy (e.g., light) to locally trigger release from a drug carrier; however, the use of this approach is limited because energy delivery to deep tissues is often impractical or invasive. In this work, radiofrequency‐responsive superparamagnetic iron oxide nanoparticles (SPIONs) are used to trigger drug release from nanoscale vesicles. Because the body is inherently nonmagnetic, this approach allows for deep tissue targeting. To overcome the unfavorable meter‐scale diffraction limit of SPION‐compatible radiofrequency (RF) fields, a strong static gating field containing a sharp zero point is superimposed on the RF field. Only drug carriers that are at or near the zero point are susceptible to RF‐triggered drug release, thereby localizing drug delivery with millimeter‐scale resolution. This approach induces >40% drug release from thermally responsive doxorubicin‐loaded liposomes within a 3.2 mm radius of the zero point with <10% release in the surrounding area, leading to a >2.5 therapeutic index in Huh 7 hepatocellular carcinoma cells.
Single or Double: Which Is the Altar of Atomic Catalysts for Nitrogen Reduction Reaction?
Authors: Chen Zhi Wen , Yan Jun‐Min , Jiang Qing 
Published: October 2018

AbstractConverting N2 to NH3 is an extremely valuable process but a long‐standing challenge in chemistry. The crux is the choice of catalysts, where single atomic catalysts (SAC) are always pursued as the altar of atomic catalysts. In this paper, double atomic catalysts (DAC) of TM2‐C2N with SAC of TM‐C2N (TM = Cr, Mn, Fe, Co, and Ni) for nitrogen reduction reaction (NRR) are systematically compared. Unexpectedly, TM2‐C2N are more suitable than TM‐C2N as catalysts for NRR. Moreover, the Mn2‐C2N endows the highest catalytic activity with the lowest potential of −0.23 V versus RHE, which is the best among all reported calculation results for NRR under ambient conditions. As a result, a new way to design catalysts with DAC is provided.
Microvesicles Secreted by Nitric Oxide-Primed Mesenchymal Stromal Cells Boost the Engraftment Potential of Hematopoietic Stem Cells
Authors: Jalnapurkar Sapana , Moirangthem Ranjita Devi , Singh Shweta , Limaye Lalita , Kale Vaijayanti 
Published: October 2018

Abstract
Patients with leukemia, lymphoma, severe aplastic anemia, etc. are frequently the targets of bone marrow transplantation, the success of which critically depends on efficient engraftment by transplanted hematopoietic cells (HSCs). Ex vivo manipulation of HSCs to improve their engraftment ability becomes necessary when the number or quality of donor HSCs is a limiting factor. Due to their hematopoiesis-supportive ability, bone marrow-derived mesenchymal stromal cells (MSCs) have been traditionally used as feeder layers for ex vivo expansion of HSCs. MSCs form a special HSC-niche in vivo, implying that signaling mechanisms operative in them would affect HSC fate. We have recently demonstrated that AKT signaling prevailing in the MSCs affect the HSC functionality. Here we show that MSCs primed with nitric oxide donor, Sodium nitroprusside (SNP), significantly boost the engraftment potential of the HSCs co-cultured with them via intercellular transfer of microvesicles (MVs) harboring mRNAs encoding HSC-supportive genes. Our data suggest that these MVs could be used as HSC-priming agents to improve transplantation efficacy. Since both, nitric oxide donors and MSCs are already in clinical use; their application in clinical settings may be relatively straight forward. This approach could also be applied in regenerative medicine protocols. Stem Cells 2019;37:128–138
An iterative method for detection of the collusive strategy in prisoner's dilemma game of electricity market
Authors: Mohtavipour Seyed Saeid , Zideh Mehdi Jabbari 
Published: October 2018

AbstractThe aim of this article is to present a method, which is called the ‘iterative collusive strategy (CS) search method’, to detect the CS in prisoner's dilemma game in which there is collusive equilibrium. We apply this method to an example of two‐player prisoner's dilemma game and a numerical duopoly example to show its effectiveness. To simulate the electricity market models, we use this method with a local optimization algorithm. Then, we employ a hybrid technique by applying an agent‐based model to the iterative CS search method for improving the results and speeding up their convergence. We simulate an electricity market example with transmission constraint to test the effectiveness of local and hybrid iterative CS search methods. Simulation results show that both local and hybrid iterative CS search methods could successfully identify the CS; however, the hybrid iterative CS search method converges to the final results with less iteration numbers. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems
Authors: Koivisto Matti , Das Kaushik , Guo Feng , Sørensen Poul , Nuño Edgar , Cutululis Nicolaos , Maule Petr 
Published: October 2018

The increasing share of variable renewable energy (VRE) generation poses challenges to power systems. Possible challenges include adequacy of reserves, planning and operation of power systems, and interconnection expansion studies in future power systems with very different generation patterns compared to today. To meet these challenges, there is a need to develop models and tools to analyze the variability and uncertainty in VRE generation. To address the varied needs, the tools should be versatile and applicable to different geographical and temporal scales. Time series simulation tools can be used to model both today and future scenarios with varying VRE installations. Correlations in Renewable Energy Sources (CorRES) is a simulation tool developed at Technical University of Denmark, Department of Wind Energy capable of simulating both wind and solar generation. It uses a unique combination of meteorological time series and stochastic simulations to provide consistent VRE generation and forecast error time series with temporal resolution in the minute scale. Such simulated VRE time series can be used in addressing the challenges posed by the increasing share of VRE generation. These capabilities will be demonstrated through three case studies: one about the use of large‐scale VRE generation simulations in energy system analysis, and two about the use of the simulations in power system operation, planning, and analysis.This article is categorized under:

Wind Power > Systems and Infrastructure
Energy Infrastructure > Systems and Infrastructure
Energy Systems Economics > Systems and Infrastructure
Delusional Beliefs in the Clinical Context
Authors: Upthegrove Rachel , A. S. 
Published: October 2018

AbstractDelusional beliefs are key symptoms of mental illness, and physicians over hundreds of years have attempted to understand and offer treatments for patients with such beliefs. In this chapter, the authors will explore the experience of delusional beliefs within the clinical context: i.e. with people who present to mental health services for help. The authors begin with definition of the descriptive psychopathology, prevalence and context in which delusional beliefs occur and their clinical relevance. Delusional beliefs have a core role in distress, depression and risk within psychosis. Real examples will be used to reflect on both the form delusional beliefs take and their personal content, concluding with treatment options and challenges.
Delusions and Other Beliefs
Authors: Bentall Richard P. 
Published: October 2018

AbstractThe difficulty of distinguishing between delusions and non-pathological beliefs has taxed some of the greatest minds in psychiatry. This chapter argues that this question cannot be resolved without first having an understanding of what is involved in holding an ordinary belief. Although we should not assume that ordinary-language words such as ‘belief’ will correspond with a specific psychological mechanism or process, sufficient evidence is available from diverse areas of psychology to reach some conclusions about what happens when someone ‘believes’ something. Beliefs are propositions about the world that are generated dynamically, often during interactions with other people, and therefore depend on the human capacity for language. Although many beliefs are mundane, it is possible to identify a class of master interpretive systems that includes political ideologies and religious belief systems, which are highly resistant to challenge and capable of generating considerable emotion. These systems seem to depend not only on the ability to generate propositions about the world but also on implicit cognitive processes that are related to fundamental biological and social needs, for example the need to avoid contagion, the need to form close intimate relationships or the need to avoid out-groups. Delusions share many of the properties of master interpretive systems but differ because they are idiosyncratic. They may arise when individuals are very isolated or if they lack the cognitive tools to function effectively in groups. Further progress in understanding delusions is likely to be made if research is informed by findings from political psychology and the psychology of religion.