bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retraction: Study of the principal component analysis in air quality databases (IOP Conf. Series: Materials Science and Engineering
872 012030)
Authors: Silva Jesús , Londoño Luz Adriana , Varela Noel , Pineda Lezama Omar Bonerge 
Published: September 2020

Published 15 September 2020
This article, and others within this volume, has been retracted by IOP Publishing following clear evidence of plagiarism and citation manipulation.
This work was originally published in Spanish (1) and has been translated and published without permission or acknowledgement to the original authors. IOP Publishing Limited has discovered other papers within this volume that have been subjected to the same treatment. This is scientific misconduct.
Misconduct investigations are ongoing at the author’s institutions. IOP Publishing Limited will update this notice if required once those investigations have concluded.
IOP Publishing Limited request any citations to this article be redirected to the original work (1).
Anyone with any information regarding these papers is requested to contact conferenceseries@ioppublishing.org.
Retraction: Thermographic imaging for use in artificial intelligence and vision algorithms (IOP Conf. Series: Materials Science and Engineering
872 012035)
Authors: Silva Jesús , Echeverría Ana María , Varela Noel , Pineda Lezama Omar Bonerge 
Published: September 2020

Published 15 September 2020
This article, and others within this volume, has been retracted by IOP Publishing following clear evidence of plagiarism and citation manipulation.
This work was originally published in Spanish (1) and has been translated and published without permission or acknowledgement to the original authors. IOP Publishing Limited has discovered other papers within this volume that have been subjected to the same treatment. This is scientific misconduct.
Misconduct investigations are ongoing at the author’s institutions. IOP Publishing Limited will update this notice if required once those investigations have concluded.
IOP Publishing Limited request any citations to this article be redirected to the original work (1).
Anyone with any information regarding these papers is requested to contact conferenceseries@ioppublishing.org.
Development of a parametric model for calculating cutting forces for external cylindrical turning of steel 20CrMNTi
Authors: Balabanov I P , Balabanova O N , Gilman V N 
Published: September 2020

Abstract
The paper presents a mathematical model for calculating the cutting force when processing 20crmnti steel with the Sandvik CNMG 120408 16P25T tool. The stand based on the 16d25 machine is presented. It allows measuring the actual values of the spindle speed, longitudinal feed, cutting depth, and cutting force. The results are transmitted to the computer via the LTR-EU-8 workstation with galvanically isolated LTE modules and a synchronization interface. According to the test results, the obtained theoretical model has a deviation from the actual measurements of no more than 0.12%. It is shown that the calculation results provided by the leading tool manufacturers are expected to be overstated. The difference in cutting forces can be more than 1.5 times.
Hardening of the working bodies of agricultural machines by electric spark and vibratory arc processing
Authors: Bayniyazova A T , Abzhaev M M , Sharifullin S N 
Published: September 2020

Abstract
The paper presents the results of studies of some physical and mechanical properties of metal samples made of 65G steel, hardened by electric spark and vibratory arc methods. Research is related to solving the problems of increasing the working resource of the working bodies of agricultural machines. The studied elemental composition, phase composition, and microstructure of the surface of the samples.
Features of robotization of agricultural processes
Authors: Kashapov N F , Nafikov M M , Nigmatzyanov A R , Sayfutdinov R F , Mingazov R A 
Published: September 2020

Abstract
The agro-industrial complex, as an industry, currently faces the problems of climate change, limited water resources, soil degradation and biodiversity conservation. It is necessary to significantly increase the production of agricultural products, while it should follow the trend of sustainable development. Resources must be used more efficiently. Intelligent solutions are needed to address conflicts of interest and meet the need for healthy and nutrient-rich foods and feeds. Therefore, it is necessary to assign an increasing role to the digitalization and robotization of agriculture in achieving these goals.
Estimation of precision parameters of milling machines
Authors: Khusainov R M , Ziangirova E R , Davletshina G K 
Published: September 2020

Abstract
The paper considers a mathematical model that allows to evaluate the performance parameters of milling machines during the functioning of the working bodies. An example of the task of selecting equipment is given. The mathematical model is based on the mathematical apparatus of coordinate transformation. Using the proposed methodology, it is possible to solve the direct problem - to evaluate the capabilities of an existing machine for manufacturing parts with a given accuracy, or the inverse problem - to choose a machine for manufacturing parts with a given accuracy.
Influence of nonlinear viscosity of waxy crude oils on the thermohydraulic characterization of their flow in helical channels: theory and experiment
Authors: Khusnutdinova E M , Konakhina I A 
Published: September 2020

Abstract
The authors looked into a matter of how the nonlinear viscosity of waxy crude oils has an effect on the thermohydraulic characterization of their flow in helical symmetry channels. The consideration was given to the energy equation in a helical coordinate system followed by theoretical and experimental values.
Improving the performance of cylinder liners by creating thin-layer coatings in the interface
Authors: Kulakov A T , Baryshnikova E P , Snarsky S V , Gafiatullin A A , Nazarov F L , Malachowski A F 
Published: September 2020

Abstract
The paper presents the technological process of brass plating of the cylinder bore. Application of the coating allows to increase the operational reliability of parts of the cylinder-piston group and the technical life of the entire engine
The use of mathematical models to improve the effective functioning of enterprises
Authors: Kuzmina I A 
Published: September 2020

Abstract
In the process of ensuring the innovative development of machine-building enterprises within the framework of the concept, it is necessary to use mathematical models that correspond to machine vision technologies, robotic technology, automated and intelligent production and control systems at enterprises. Mathematical models of robotic technology allow us to create new equipment, improve technological processes and production organization systems.
Development of cast dispersion-hardening ferrite-carbide steel
Authors: Mukhametzyanova G F , Kolesnikov M S , Astashchenko V I , Mukha-metzyanov I R 
Published: September 2020

Abstract
A method is proposed for producing cast dispersion-hardening ferrite-carbide steel for manufacture of cast molds of hot deformation, molds for die casting under pressure and forging dies for solid-liquid forming, providing production of steel with fine-grain structure and uniform distribution of carbides in a ferrite matrix without formation of casting cracks. In the process of steel production waste carbide ceramic-metal inserts of a cutting tool from alloys are used, they are of the following types: T5K6, T15K6, T5K10, T21K8, TT7K12, TT8K6, TT10K9, TT20K9 and T30K4 containing titanium carbides (TiC), tantalum carbides (TaC), tungsten carbides (WC).
Evaluation of the wear resistance and resource hardened by electrospark machining of the cutting surfaces of the fingers of the headers of combine harvesters
Authors: Velichko S A , Sharifullin S N , Kuznetsov I S , Kolomeichenko A V , Solovyev R Y , Kravchenko I N , Adigamov N R 
Published: September 2020

Abstract
The article presents the technology of hardening the fingers of the reapers of combine harvesters by electrospark processing. To strengthen the cutting surfaces of the fingers, it is recommended to use an amorphous alloy grade 84KXSR. The operational tests presented in the work showed that wear and dulling of both serial products and experimental parts with electric spark coatings is characterized by two stages: running-in and natural wear. The running-in occurs during the running time of the fingers in 1 ha. The results of operational tests showed that the application of a wear-resistant electrospark coating of amorphous alloy grade 84KXSR with a thickness of 30 μm and a track width of 2 mm on the cutting surfaces of the fingers of the headers of grain harvesters makes it possible to increase the resource from 1.4 to 2 times.
Quantum implementation of an artificial feed-forward neural network
Authors: Tacchino Francesco , Barkoutsos Panagiotis , Macchiavello Chiara , Tavernelli Ivano , Gerace Dario , Bajoni Daniele 
Published: September 2020

Abstract
Artificial intelligence algorithms largely build on multi-layered neural networks. Coping with their increasing complexity and memory requirements calls for a paradigmatic change in the way these powerful algorithms are run. Quantum computing promises to solve certain tasks much more efficiently than any classical computing machine, and actual quantum processors are now becoming available through cloud access to perform experiments and testing also outside of research labs. Here we show in practice an experimental realization of an artificial feed-forward neural network implemented on a state-of-art superconducting quantum processor using up to 7 active qubits. The network is made of quantum artificial neurons, which individually display a potential advantage in storage capacity with respect to their classical counterpart, and it is able to carry out an elementary classification task which would be impossible to achieve with a single node. We demonstrate that this network can be equivalently operated either via classical control or in a completely coherent fashion, thus opening the way to hybrid as well as fully quantum solutions for artificial intelligence to be run on near-term intermediate-scale quantum hardware.
Shaping of the flame geometry by non-conventional cold plasma arrangements
Authors: Bardos L , Baránková H 
Published: September 2020

Abstract
Experimental examination of possibility to affect the shapes of flames under combustion of the liquified petroleum gas (LPG) were performed by several non-conventional cold atmospheric plasma arrangements. The lateral fused hollow cathode, the microwave surface wave plasma jet and the combination of these systems confirmed possibility of an efficient control of the flame shapes, increasing stability of flames and broadening of their front parts.
Advances in mechanical characterization of 1D and 2D nanomaterials: progress and prospects
Authors: Pantano Maria F , Kuljanishvili Irma 
Published: September 2020

Abstract
Last several decades have sparked a tremendous interest in mechanical properties of low dimensional systems specifically 1D and 2D nanomaterials, in large, due to their remarkable behavior and potential to possess unique and customizable physical properties, which have encouraged the fabrication of new structures to be tuned and utilized for targeted applications. In this critical review we discuss examples that represent evolution of the mechanical characterization techniques developed for 1D and 2D nanomaterials, with special emphasis on specimen fabrication and manipulation, and the different strategies, tools and metrologies, employed for precise positioning and accurate measurements of materials’ strength, elastic modulus, fracture toughness as well as analysis of failure modes. We focus separately on techniques for the mechanical characterization of 1D and 2D nanomaterials and categorize those methods into top-down and bottom-up approaches. Finally, we discuss advantages and some drawbacks in most common methodologies used for 1D and 2D specimen testing and outline future possibilities and potential paths that could boost the development of more universal approaches for technologically viable solutions which would allow for more streamlined and standardized mechanical testing protocols to be developed and implemented.
Tuning the length/width aspect ratio of epitaxial unidirectional silicide nanowires on Si(110)-16 × 2 surfaces
Authors: Mahato J C , Das Debolina , Das P , Chini T K , Dev B N 
Published: September 2020

Abstract
The reactive deposition epitaxy growth of self-organized cobalt silicide nanowires (NWs) on clean Si(110) surfaces has been investigated by in situ scanning tunneling microscopy (STM) and scanning tunneling spectroscopy (STS) as well as by scanning electron microscopy (SEM). Half a monolayer of cobalt was deposited on the Si(110) surfaces at ∼600 °C substrate temperature. Following cobalt deposition, the substrates have been annealed for different durations. Cobalt forms aligned cobalt disilicide nanowires upon reaction with the silicon substrate, following the twofold substrate symmetry. With increasing duration of annealing, the NWs have been found to grow with larger aspect ratio (length/width), eventually producing narrower NWs. These self-organized unidirectional NWs of sub-hundred nanometer width and ∼4–7 nm height produce a Schottky barrier with the silicon substrate and are expected to find applications in nanoelectronic devices.
Swan: a library for the analysis and visualization of long-read transcriptomes
Authors: Reese Fairlie , Mortazavi Ali 
Published: September 2020

Abstract

Motivation
Long-read RNA-sequencing technologies such as PacBio and Oxford Nanopore have discovered an explosion of new transcript isoforms that are difficult to visually analyze using currently available tools. We introduce the Swan Python library, which is designed to analyze and visualize transcript models.

Results
Swan finds 4909 differentially expressed transcripts between cell lines HepG2 and HFFc6, including 279 that are differentially expressed even though the parent gene is not. Additionally, Swan discovers 285 reproducible exon skipping and 47 intron retention events not recorded in the GENCODE v29 annotation.

Availability and implementation
The Swan library for Python 3 is available on PyPi at https://pypi.org/project/swan-vis/ and on GitHub at https://github.com/mortazavilab/swan_vis.
Geometricus represents protein structures as shape-mers derived from moment invariants
Authors: Durairaj Janani , Akdel Mehmet , de Ridder Dick , van Dijk Aalt D J 
Published: September 2020

Abstract

Motivation
As the number of experimentally solved protein structures rises, it becomes increasingly appealing to use structural information for predictive tasks involving proteins. Due to the large variation in protein sizes, folds and topologies, an attractive approach is to embed protein structures into fixed-length vectors, which can be used in machine learning algorithms aimed at predicting and understanding functional and physical properties. Many existing embedding approaches are alignment based, which is both time-consuming and ineffective for distantly related proteins. On the other hand, library- or model-based approaches depend on a small library of fragments or require the use of a trained model, both of which may not generalize well.

Results
We present Geometricus, a novel and universally applicable approach to embedding proteins in a fixed-dimensional space. The approach is fast, accurate, and interpretable. Geometricus uses a set of 3D moment invariants to discretize fragments of protein structures into shape-mers, which are then counted to describe the full structure as a vector of counts. We demonstrate the applicability of this approach in various tasks, ranging from fast structure similarity search, unsupervised clustering and structure classification across proteins from different superfamilies as well as within the same family.

Availability and implementation
Python code available at https://git.wur.nl/durai001/geometricus.
An assumption-free exact test for fixed-design linear models with exchangeable errors
Authors: Lei Lihua , Bickel Peter J 
Published: September 2020

SummaryWe propose the cyclic permutation test to test general linear hypotheses for linear models. The test is nonrandomized and valid in finite samples with exact Type I error $\alpha$ for an arbitrary fixed design matrix and arbitrary exchangeable errors, whenever $1 / \alpha$ is an integer and $n / p \geqslant 1 / \alpha - 1$, where $n$ is the sample size and $p$ is the number of parameters. The test involves applying the marginal rank test to $1 / \alpha$ linear statistics of the outcome vector, where the coefficient vectors are determined by solving a linear system such that the joint distribution of the linear statistics is invariant with respect to a nonstandard cyclic permutation group under the null hypothesis. The power can be further enhanced by solving a secondary nonlinear travelling salesman problem, for which the genetic algorithm can find a reasonably good solution. Extensive simulation studies show that the cyclic permutation test has comparable power to existing tests. When testing for a single contrast of coefficients, an exact confidence interval can be obtained by inverting the test.
Assessing cure status prediction from survival data using receiver operating characteristic curves
Authors: Amico M , Van Keilegom I , Han B 
Published: September 2020

SummarySurvival analysis relies on the hypothesis that, if the follow-up is long enough, the event of interest will eventually be observed for all observations. This assumption, however, is often not realistic. The survival data then contain a cure fraction. A common approach to modelling and analysing this type of data consists in using cure models. Two types of information can therefore be obtained: the survival at a given time and the cure status, both possibly modelled as a function of the covariates. The cure status is often of interest to medical practitioners, and one is usually interested in predicting it based on markers. Receiver operating characteristic, Roc, curves are one way to evaluate the predicted performance; however, the classical Roc curve method is not appropriate since the cure status is partially unobserved due to the presence of censoring in survival data. We propose a Roc curve estimator that aims to evaluate the cured/noncured status classification performance from cure survival data. This estimator, which handles the presence of censoring, decomposes sensitivity and specificity by means of the definition of conditional probability, and estimates these two quantities by means of weighted empirical distribution functions. The mixture cure model is used to calculate the weights. Based on simulations, we demonstrate good performance of the proposed method, and compare it with the classical Roc curve nonparametric estimator that would be obtained if the cure status was fully observed. We also compare our proposed method with the Roc curves of Heagerty et al. (2000) for classical survival analysis. Finally, we illustrate the methodology on a breast cancer dataset.
Effects of dopamine on reinforcement learning in Parkinson’s disease depend on motor phenotype
Authors: van Nuland Annelies J , Helmich Rick C , Dirkx Michiel F , Zach Heidemarie , Toni Ivan , Cools Roshan , den Ouden Hanneke E M 
Published: September 2020

Abstract
Parkinson’s disease is clinically defined by bradykinesia, along with rigidity and tremor. However, the severity of these motor signs is greatly variable between individuals, particularly the presence or absence of tremor. This variability in tremor relates to variation in cognitive/motivational impairment, as well as the spatial distribution of neurodegeneration in the midbrain and dopamine depletion in the striatum. Here we ask whether interindividual heterogeneity in tremor symptoms could account for the puzzlingly large variability in the effects of dopaminergic medication on reinforcement learning, a fundamental cognitive function known to rely on dopamine. Given that tremor-dominant and non-tremor Parkinson’s disease patients have different dopaminergic phenotypes, we hypothesized that effects of dopaminergic medication on reinforcement learning differ between tremor-dominant and non-tremor patients. Forty-three tremor-dominant and 20 non-tremor patients with Parkinson’s disease were recruited to be tested both OFF and ON dopaminergic medication (200/50 mg levodopa-benserazide), while 22 age-matched control subjects were recruited to be tested twice OFF medication. Participants performed a reinforcement learning task designed to dissociate effects on learning rate from effects on motivational choice (i.e. the tendency to ‘Go/NoGo’ in the face of reward/threat of punishment). In non-tremor patients, dopaminergic medication improved reward-based choice, replicating previous studies. In contrast, in tremor-dominant patients, dopaminergic medication improved learning from punishment. Formal modelling showed divergent computational effects of dopaminergic medication as a function of Parkinson’s disease motor phenotype, with a modulation of motivational choice bias and learning rate in non-tremor and tremor patients, respectively. This finding establishes a novel cognitive/motivational difference between tremor and non-tremor Parkinson’s disease patients, and highlights the importance of considering motor phenotype in future work.
Warp Speed for Coronavirus Disease 2019 (COVID-19) Vaccines: Why Are Children Stuck in Neutral?
Authors: Anderson Evan J , Campbell James D , Creech C Buddy , Frenck Robert , Kamidani Satoshi , Munoz Flor M , Nachman Sharon , Spearman Paul 
Published: September 2020

Abstract
While adult clinical trials of coronavirus disease 2019 (COVID-19) vaccines have moved quickly into phase 3 clinical trials, clinical trials have not started in children in the United States. The direct COVID-19 impact upon children is greater than that observed for a number of other pathogens for which we now have effective pediatric vaccines. Additionally, the role of children in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has clearly been underappreciated. Carefully conducted phase 2 clinical trials can adequately address potential COVID-19 vaccine safety concerns. Delaying phase 2 vaccine clinical trials in children will delay our recovery from COVID-19 and unnecessarily prolong its impact upon children’s education, health, and emotional well-being, and equitable access to opportunities for development and social success. Given the potential direct and indirect benefits of pediatric vaccination, implementation of phase 2 clinical trials for COVID-19 vaccines should begin now.