bluuebunny/crossref_metadata_2025_split huggingface dataset:
Esca‐affected grapevine leaf metabolome is clone‐ and vintage‐dependent
Authors: Moret Florian , Delorme Gaël , Clément Gilles , Grosjean Claire , Lemaître‐Guillier Christelle , Trouvelot Sophie , Adrian Marielle , Fontaine Florence 
Published: November 2020

AbstractEsca is a complex grapevine trunk disease caused by wood‐rotting ascomycetes and basidiomycetes and leading to several foliar and wood symptoms. Given that the esca expression can be influenced by several environmental, physiological, and genetic factors, foliar symptoms are inconsistent in incidence and prevalence and may appear 1 year but not the following. We have previously reported a clone‐dependent expression of the disease in cv Chardonnay. Owing to metabolome analysis, we could discriminate the metabolite fingerprint of green leaves collected on diseased vines of clones 76 and 95. These clone‐dependent fingerprints were year‐dependent in intensity and nature. The present work was conducted to determine if the clone‐dependent disease expression observed is specific to Chardonnay or if it also occurs in another cultivar. A plot located in the Jura vineyard (France) and planted with both 1004 and 1026 clones of Trousseau, a cultivar highly susceptible to esca, was thus selected and studied during 2017 and 2018. A year‐dependent variation of the symptoms expression was first observed and a possible relationship with rainfall is hypothesized and discussed. Moreover, a higher percentage of the clone 1026 vines expressed disease, compared to the 1004 ones, suggesting the higher susceptibility of this clone. Finally, metabolomic analyses of the remaining green leaves (i.e, without symptom expression) of partial esca‐apoplectic vines allowed us to confirm a clone‐dependent metabolic response to the disease. The metabolite fingerprints obtained differed in nature and intensity to those previously reported for Chardonnay and also between years.
A Proposal for Integrating Theories of Complexity for Better Understanding Global Systemic Risks
Authors: Haas Armin , Laubichler Manfred , Applegate Joffa , Steudle Gesine , Jaeger Carlo C. 
Published: November 2020

AbstractThe global financial crisis of 2008 has shown that the present financial system involves global systemic risks. The dimension of these risks is hard to grasp with the conceptual tools that have been developed to tackle conventional risks like fire or car accidents. While modern societies know quite well how to deal with conventional risks, we have not yet been equally successful at dealing with global systemic risks. For managing this kind of risks, one needs to understand critical features of specific global systems where many human agents interact in ever changing complex networks. Here we apply two specific dimensions of complexity theory for dealing with global systemic risk in an integrated fashion: normal accidents and extended evolution. Both of them have successfully been applied to the analysis of systemic risks. As a paradigmatic example of global systemic risks, we focus on the global financial crisis that began in 2008, and suggest that the future evolution of the financial system could either see a further increase in complexity, or a reversal to a less complex system. We explore and contrast the implications of normal accident theory and extended evolution perspectives and suggest a four‐point research strategy informed by complexity theory for better understanding global systemic risks in financial systems.
Clearing the clouds: Case‐report and review of the literature
Authors: Relvas Miguel , Beco Ana , Pereira Luciano , Oliveira Ana , Silvano José , Silva Rui , Marques Nídia , Santos Lurdes , Coentrão Luís , Pestana Manuel 
Published: November 2020

AbstractIn peritoneal dialysis (PD), a cloudy dialysate is an alarming finding. Bacterial peritonitis is the most common cause, however, atypical infections and non‐infectious causes must be considered. A 46‐year‐old man presented with asthenia, paraesthesia, foamy urine and hypertension. Laboratory testing revealed severe azotaemia, anaemia, hyperkalaemia and nephrotic‐range proteinuria. Haemodialysis was started through a central venous catheter. Later, due to patient preference, a Tenckhoff catheter was inserted. Conversion to PD occurred 3 weeks later, during hospitalization for a presumed central line infection. A month later, the patient was hospitalized for neutropenic fever. He was diagnosed an acute parvovirus infection and was discharged under isoniazid for latent tuberculosis. Four months later, the patient presented with fever and a cloudy effluent. Peritoneal fluid (PF) cytology was suggestive of infectious peritonitis, but the symptoms persisted despite antibiotic therapy. Bacterial and mycological cultures were negative. No neoplastic cells were detected. Mycobacterium tuberculosis eventually grew in PF cultures, despite previous negative molecular tests. Directed therapy was then initiated with excellent response. Thus, facing a cloudy effluent, one must consider multiple aetiologies. Diagnosis of peritoneal tuberculosis is hampered by the lack of highly sensitive and specific exams. Here, diagnosis was only possible due to positive mycobacterial cultures.
Inter‐observer evaluation of erythema‐directed photography for the assessment of erythema and telangiectasias in rosacea
Authors: Dall'Oglio Federica , Verzi Anna Elisa , Lacarrubba Francesco , Giuffrida Giorgia , Milani Massimo , Micali Giuseppe 
Published: November 2020

AbstractBackgroundPersistent centrofacial erythema associated with telangiectasias is one of the most common phenotypes of rosacea in clinical practice, and the assessment of each component is crucial as each of them may require a different approach. The aim of this study was to evaluate the inter‐observer reliability of standard photography vs erythema‐directed photography for the assessment of erythema and telangiectasias in rosacea.Materials and methodsOne hundred full‐face images of 50 rosacea patients (50 standard photographs and 50 erythema‐directed digital photographs) were evaluated by 8 independent experienced dermatologists using a 5‐item score for erythema and telangiectasias, respectively. Inter‐rater reliability, by comparing erythema and telangiectasias scores and calculating the percentage of agreement between evaluators, was assessed and the strength of agreement using the Cohen's Kappa values (95% CI) was calculated.ResultsPoor and fair strength of agreement for erythema and telangiectasias using standard photography vs moderate and good strength of agreement using erythema‐directed digital photography was found.ConclusionErythema‐directed digital photography may provide a better strength of agreement and higher reliability among independent observers compared to standard photography in the assessment of erythema and telangiectasias in rosacea, thus suggesting new horizons for digital appraisal of skin diseases.
Control ofAilanthus altissimausing cut stump and basal bark herbicide applications in an eighteenth‐century fortress
Authors: Fogliatto Silvia , Milan Marco , Vidotto Francesco 
Published: November 2020

AbstractThe Cittadella di Alessandria (Italy) is a military fortification that was built in the 18th century. The site has recently been abandoned and is now colonised by weeds, including the invasiveAilanthus altissima. The aim of the study was to compare the efficacy of different herbicides (glyphosate, a mixture of aminopyralid + fluroxypyr and triclopyr + fluroxypyr) applied to cut stumps or to the basal bark ofA. altissima. For the cut stump application, plants were first cut at the base and then immediately sprayed and for the basal bark application, the lower 50 cm of the plants was sprayed with the herbicides; untreated cut plants were used as a control, for comparison. Two runs per study were carried out (in summer 2015 and in spring 2016). Efficacy was assessed up to 2018 by counting the resprouts and their height in the cut stump application and, for the basal bark treatment, by measuring the variation in the plant circumference after treatment. The cut stump treatment carried out in summer greatly reduced the number of resprouts, compared to the spring treatment, to less than one sprout per plant when aminopyralid + fluroxypyr was used, and its efficacy lasted for about two years. The basal bark treatment did not control the species, but lower levels of variation in circumference and greater mortality were detected in plants treated with aminopyralid + fluroxypyr. Considering the high level of infestation of the site and the high risk of plant resprouting, repeated cut stump treatments with aminopyralid + fluroxypyr would be preferable to eradicate this invasive species.
Circulating leptin levels in patients with myalgic encephalomyelitis, chronic fatigue syndrome or fibromyalgia: a systematic review protocol
Authors: Musker Michael , McArthur Alexa , Munn Zachary , Wong Ma-Li 
Published: November 2020

ABSTRACT

Objective:
The objective of the review is to evaluate circulating levels of leptin in people diagnosed with myalgic encephalomyelitis chronic fatigue syndrome or fibromyalgia syndrome and to investigate the differences compared with healthy controls.

Introduction:
Myalgic encephalomyelitis chronic fatigue syndrome is a condition that has major symptoms, including self-reported fatigue, post-exertional malaise, and unexplained pain across the body. The widespread pain is measured in a systematic way and is often referred to as fibromyalgia. The two disorders have many similarities, but their association with leptin has indicated that leptin may affect the role of pro-inflammatory cytokines and symptom severity.

Inclusion criteria:
This review will consider observational studies of varying study designs including prospective and retrospective cohort studies, case-control studies, time-series, and analytical cross-sectional studies that include both cases and healthy comparators. Cases will include a diagnosis of myalgic encephalomyelitis, chronic fatigue syndrome, and/or fibromyalgia. Controls are people without this diagnosis, usually healthy participants. Only studies published in English will be included due to limited resources for translation.

Methods:
This protocol will be reported based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist and will follow the JBI methodology for systematic reviews of etiology and risk. A comprehensive search strategy will include PubMed, Embase, Scopus, Science Direct, and PsycINFO. Two reviewers will screen, critically appraise eligible articles, and extract data using a standardized data extraction tool informed by JBI SUMARI. The authors will complete a quantitative analysis that synthesizes findings across studies using pooled effect sizes and confidence intervals of the measures provided.

Systematic review registration number:
PROSPERO CRD42020169903
Housing Profile Design for Improved Apex Seal Lubrication Using a Finite Length Roller Elastohydrodynamic Lubrication Model
Authors: Liu Zhong , Gu Thomas , Pickens David , Nishino Takayuki , Jane Wang Q. 
Published: November 2020

Abstract
Finite-length roller contacts are found in apex seal-housing interfaces in rotary engines, as well as in many other mechanical systems, such as those at the interfaces of meshing gear teeth, cam followers, and roller bearings. Rollers are usually designed with crowns and modified ends to mitigate the negative effects of misalignment, thermal deformation, and edge-induced non-uniform displacement. A crowned-roller elastohydrodynamic lubrication model is enriched and employed to investigate seven housing surface profiles, including a sinusoidal recess, sinusoidal ends, the combination design of a sinusoidal recess and sinusoidal ends, multiple sinusoidal recesses, a concave shape, and a concave shape with sinusoidal ends or round corners, aiming to improve the tribological performance of the interface via increasing the minimum film thickness but reducing the average and maximum film thicknesses, and lowering friction coefficient. The modified discrete convolution and fast Fourier transform method with duplicated padding is utilized to deal with the potential free-end-surface effect. The simulation results suggest that the combinations of a concave shape and sinusoidal ends, or round corners, are the best designs because they can help distribute the lubricant most uniformly without causing a negative edge effect.
Approximation of the Step-to-Step Dynamics Enables Computationally Efficient and Fast Optimal Control of Legged Robots
Authors: Bhounsule Pranav A. , Kim Myunghee , Alaeddini Adel 
Published: November 2020

Abstract
Legged robots with point or small feet are nearly impossible to control instantaneously but are controllable over the time scale of one or more steps, also known as step-to-step control. Previous approaches achieve step-to-step control using optimization by (1) using the exact model obtained by integrating the equations of motion, or (2) using a linear approximation of the step-to-step dynamics. The former provides a large region of stability at the expense of a high computational cost while the latter is computationally cheap but offers limited region of stability. Our method combines the advantages of both. First, we generate input/output data by simulating a single step. Second, the input/output data is curve fitted using a regression model to get a closed-form approximation of the step-to-step dynamics. We do this model identification offline. Next, we use the regression model for online optimal control. Here, using the spring-load inverted pendulum model of hopping, we show that both parametric (polynomial and neural network) and non-parametric (gaussian process regression) approximations can adequately model the step-to-step dynamics. We then show this approach can stabilize a wide range of initial conditions fast enough to enable real-time control. Our results suggest that closed-form approximation of the step-to-step dynamics provides a simple accurate model for fast optimal control of legged robots.
A Practical Safety Factor Method for Reliability-Based Component Design
Authors: Yin Jianhua , Du Xiaoping 
Published: November 2020

Abstract
Reliability-based design (RBD) identifies design variables that maintain reliability at a required level. For many routine component design jobs, RBD may not be practical as it requires nonlinear optimization and specific reliability methods, especially for those design jobs which are performed manually or with a spreadsheet. This work develops a practical approach to reliability-based component design so that the reliability target can be achieved by conducting traditional component design repeatedly using a deterministic safety factor. The new component design is based on the First Order Reliability Method, which iteratively assigns the safety factor during the design process until the reliability requirement is satisfied. In addition to a number of iterations of deterministic component design, the other additional work is the calculation of the derivatives of the design margin with respect to the random input variables. The proposed method can be used for a wide range of component design applications. For example, if a deterministic component design is performed manually or with a spreadsheet, so it the reliability-based component design. Three examples are used to demonstrate the practicality of the new design method.
The Design of Disk Cam Mechanisms With a Translating Follower Having an Added Dual-Roller Intermediate Link
Authors: Hsu Kuan-Lun , Chou Sun-Liang 
Published: November 2020

Abstract
This paper provides a methodology to design a disk cam mechanism that has a translating follower with dual rollers. Dual rollers are joined by an oscillating link and can contact cam profile simultaneously throughout working cycle of cam rotation. The application of this novel follower can offer two engagements in cam-follower pair to spread the induced normal force and reduce the contact stress between cam and follower. Two examples are worked to demonstrate application of design procedures and to illustrate the capability of reducing contact stress of this novel follower. The results show that the contact stress of such a cam mechanism can be reduced by 28.85% in comparison with that of the cam mechanism with a common translating roller follower.
A Convolutional Neural Network-Based Patent Image Retrieval Method for Design Ideation
Authors: Jiang Shuo , Luo Jianxi , Pava Guillermo Ruiz , Hu Jie , Magee Christopher L. 
Published: November 2020

Abstract
The patent database is often used in searches of inspirational stimuli for innovative design opportunities because of its large size, extensive variety and rich design information in patent documents. However, most patent mining research only focuses on textual information and ignores visual information. Herein, we propose a convolutional neural network (CNN)-based patent image retrieval method. The core of this approach is a novel neural network architecture named Dual-VGG that is aimed to accomplish two tasks: visual material type prediction and international patent classification (IPC) class label prediction. In turn, the trained neural network provides the deep features in the image embedding vectors that can be utilized for patent image retrieval and visual mapping. The accuracy of both training tasks and patent image embedding space are evaluated to show the performance of our model. This approach is also illustrated in a case study of robot arm design retrieval. Compared to traditional keyword-based searching and Google image searching, the proposed method discovers more useful visual information for engineering design.
Kinematics, Workspace Optimization, and Performance Evaluation of a 3-Leg 6-DOF Robot in RRRS Configuration
Authors: Jensen Nathan A. , Nelson Carl A. 
Published: November 2020

Abstract
Underactuated parallel manipulators that achieve 6 DOF via multiple controllable degrees of freedom per leg are often pursued and reported due to their large workspaces. This benefit comes at a cost to the manipulator’s performance, however. Such manipulators must then be evaluated in order to characterize their kinematics in terms of position and motion. This paper establishes a pair of inverse kinematic solutions for a previously proposed and prototyped 3-leg, 6-DOF parallel robot. These solutions are then used to define the robot’s workspace with experimental validation and to optimize the robot’s geometry for maximum workspace volume. The linear components of the Jacobian are then defined, allowing for analysis of the manipulability of the robot. The full Jacobian is also defined, and singularities are examined throughout the workspace of the robot.
Efficient Parametric Optimization for Expensive Single Objective Problems
Authors: Weaver-Rosen Jonathan M. , Malak Richard J. 
Published: November 2020

Abstract
Parametric optimization solves optimization problems as a function of uncontrollable or unknown parameters. Such an approach allows an engineer to gather more information than traditional optimization procedures during design. Existing methods for parametric optimization of computationally or monetarily expensive functions can be too time-consuming or impractical to solve. Therefore, new methods for the parametric optimization of expensive functions need to be explored. This work proposes a novel algorithm that leverages the advantages of two existing optimization algorithms. This new algorithm is called the efficient parametric optimization (EPO) algorithm. EPO enables adaptive sampling of a high-fidelity design space using an inexpensive low-fidelity response surface model. Such an approach largely reduces the required number of expensive high-fidelity computations. The proposed method is benchmarked using analytic test problems and used to evaluate a case study requiring finite element analysis. Results show that EPO performs as well as or better than the existing alternative, P3GA, for these problems given an allowable number of function evaluations.
Data Mining From Endmill Tool Catalog Information Based on the Use of a Machine Learning Method
Authors: Asakura Akihito , Hirogaki Toshiki , Aoyama Eiichi , Kodama Hiroyuki 
Published: November 2020

Abstract
In recent years, the needs associated with the development of new technologies in the manufacturing industry that utilize big data typified by the Internet-of-Things (IoT) and artificial intelligence (AI) have been increasing. Recent computer-aided manufacturing (CAM) systems have evolved so that unskilled technicians can create tool paths relatively easily with numerically controlled (NC) programs, but tool-cutting conditions used for machining cannot be automatically determined. Therefore, many unskilled technicians often set the cutting conditions based on the recommended conditions described in the tool catalog. However, given that the catalog contains large-scale data on machining technology, setting the proper conditions becomes a time-consuming and inefficient process. In this study, we aimed to construct a system to support unskilled technicians to determine the optimum machining conditions. To this end, we constructed a prediction model using a random forest machine learning method to predict the cutting conditions. It was confirmed that the prediction with the random forest method can be performed with high accuracy based on the cutting conditions recommended by the tool maker. Thus, the effectiveness of this method was verified.
Large Scale Topology Optimization of 3D Static Mixers
Authors: Sun Sicheng , Ghandhi Jaal , Qian Xiaoping 
Published: November 2020

Abstract
Topology optimization (TO) was conducted for three dimensional static fluid mixers. The problem is optimized using the weakly coupled Navier-Stokes equation at low Reynolds number (Re ≤ 1) and a convection-diffusion equation. The domain was discretized with up to 10 million cells. The optimizations were run with 1024 to 2048 CPUs on a national supercomputer. For a mixer in a square cross-section channel, the mixing was improved by 83% for a modest 2.5 times higher pressure drop compared with the open straight channel. For a cylindrical cross-section tee arrangement, the mixing improved by 91% with a 2.5 times higher pressure drop compared to the straight channel.
A Sequential Calibration and Validation Framework for Model Parameter Updating and Bias Correction
Authors: Jiang Chen , Liu Yixuan , Hu Zhen , Mourelatos Zissimos P. , Gorsich David , Jayakumar Paramsothy 
Published: November 2020

Abstract
Model parameter updating and bias correction plays an essential role in improving the validity of Modeling and Simulation (M&S) in engineering design and analysis. However, it is observed that the existing methods may either be misled by potentially wrong information if the computer model cannot adequately capture the underlying true physics, or be affected by the prior distributions of the unknown model parameters. In this paper, a sequential model calibration and validation (SeCAV) framework is proposed to improve the efficacy of both model parameter updating and model bias correction, where the model validation and Bayesian calibration are implemented in a sequential manner. In each iteration, the model validation assessment is employed as a filter to select the best experimental data for Bayesian calibration, and to update the prior distributions of uncertain model parameters for the next iteration. The calibrated parameters are then integrated with model bias correction to improve the prediction accuracy of the M&S. A mathematical example is employed to demonstrate the advantages of the SeCAV method.