bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic learning‐based event‐triggered control of strict‐feedback systems with finite‐time prescribed performance
Authors: Wang Lixue , Wang Min , Yang Chenguang
Published: January 2022

This paper is concerned with the event‐triggered neural learning control for strict‐feedback nonlinear systems (SFNSs) subject to predefined tracking performance. A system transformation approach is utilized to transform the original SFNSs into the normal form, which makes it easily to verify the convergence of neural weights since only one neural network (NN) approximator is employed. Then, a novel finite‐time performance function is first proposed to characterize the performance constraints of tracking error, thus guaranteeing the prescribed tracking performance. On this basis, a new lemma is given, which is crucial to ensure the stability of the closed‐loop system. By using the error transformation technique, the constrained tracking control problem is converted into the stabilization problem of unconstrained error system. Subsequently, by introducing the first‐order sliding mode differentiator into the backstepping procedure and with the help of the high‐gain observer, a novel adaptive neural tracking control scheme is presented to ensure that the prescribed tracking performance is satisfied and all closed‐loop signals are ultimately bounded. After ensuring the satisfaction of the partial persistent excitation condition for radial basis function NN, the neural weight estimates are verified to converge to the ideal values, and then the convergent weights are stored as the constant values. By utilizing the stored knowledge, an event‐triggered neural learning controller is constructed to accomplish the same or similar control tasks, which can effectively improve the transient control performance, save the communication resource, and relieve the online computation at the same time. Finally, the effectiveness of the presented scheme is testified by numerical and practical examples.
Quaternary Organic Solar Cells Enable Suppressed Energy Loss
Authors: Kang Hui , Zheng Bing , Li Yanxun , Li Shilin , Zhou Huiqiong , Huo Lijun , Zhang Yuan
Published: January 2022

Multi‐component organic solar cells (OSCs) composing of more than two donor and acceptor materials have attracted increasing attention, due to the possibilities to further mitigate voltage loss (ΔVoc) for the gain of open‐circuit voltage (Voc). However, the control of phase morphology in multi‐component blend systems that critically impacts ΔVoc and the ultimate power conversion efficiency (PCE) is still a challenge. Here, we report a quaternary blend‐based strategy for non‐fullerene OSCs by using two polymer donors (PM6 and L20) along with acceptors of a non‐fullerene (Y6) and PC71BM, leading to concurrent improvements of the Voc, device fill factor and eventual PCE. The quaternary OSC exhibits the advantages of a higher charge collection efficiency, expedited charge carrier sweep‐out, and reduced charge recombination losses. The suppression on ΔVoc is attributed to the reduced radiative recombination loss below the bandgap (0.143 V) and non‐radiative voltage loss (0.216 V). These properties are linked to synergies of modified energetics and film morphology of the quaternary blends. This work demonstrates that incorporating suitable donor and acceptor guest molecules to organic binary blend systems is a highly viable approach for lowering the energy loss in organic bulk heterojunctions towards the boost of photovoltaic performance for realistic energy conversion applications.
K‐fold cross‐validation for complex sample surveys
Authors: Wieczorek Jerzy , Guerin Cole , McMahon Thomas
Published: January 2022

Although K‐fold cross‐validation (CV) is widely used for model evaluation and selection, there has been limited understanding of how to perform CV for non‐iid data, including those from sampling designs with unequal selection probabilities. We introduce CV methodology that is appropriate for design‐based inference from complex survey sampling designs. For such data, we claim that we will tend to make better inferences when we choose the folds and compute the test errors in ways that account for the survey design features such as stratification and clustering. Our mathematical arguments are supported with simulations, and our methods are illustrated on real survey data.
Improving image classification robustness using self‐supervision
Authors: Wittscher Ladyna , Diers Jan , Pigorsch Christian
Published: January 2022

Self‐supervised learning allows training of neural networks without immense, high‐quality or labelled data sets. We demonstrate that self‐supervision furthermore improves robustness of models using small, imbalanced or incomplete data sets which pose severe difficulties to supervised models. For small data sets, the accuracy of our approach is up to 12.5% higher using MNIST and 15.2% using Fashion‐MNIST compared to random initialization. Moreover, self‐supervision influences the way of learning itself, which means that in case of small or strongly imbalanced data sets, it can be prevented that classes are not or insufficiently learned. Even if input data are corrupted and large image regions are missing from the training set, self‐supervision significantly improves classification accuracy (up to 7.3% for MNIST and 2.2% for Fashion‐MNIST). In addition, we analyse combinations of data manipulations and seek to generate a better understanding of how pretext accuracy and downstream accuracy are related. This is not only important to ensure optimal pretraining but also for training with unlabelled data in order to find an appropriate evaluation measure. As such, we make an important contribution to learning with realistic data sets and making machine learning accessible to application areas that require expensive and difficult data collection.
Wake expansion continuation: Multi‐modality reduction in the wind farm layout optimization problem
Authors: Thomas Jared J. , McOmber Spencer , Ning Andrew
Published: January 2022

In this paper we present a continuation optimization method for reducing multi‐modality in the wind farm layout optimization problem that we call wake expansion continuation (WEC). We achieve the reduction in multi‐modality by starting with an increased wake diameter while maintaining normal velocity deficits at the center of the wakes, and then reducing the wake diameter for each of a series of optimization runs until the accurate wake diameter is used. We applied and demonstrated the effectiveness of WEC with two different wake models. We tested WEC on four optimization case studies and compared the results with a gradient‐based optimization method and a gradient‐free optimization method. We found a significant improvement in the mean, standard deviation, and minimum wake loss for optimization with WEC compared to optimization without WEC for all test cases. We found the gradient‐free optimization algorithm resulted in less optimal layouts on average for all cases than the gradient‐based algorithm with WEC. We also applied WEC to the gradient‐free algorithm for one case study with significantly improved results, but there was more improvement when we applied WEC to a gradient‐based algorithm. WEC enables gradient‐based algorithms to search the wind farm layout optimization space more globally and provides more optimal results more consistently than optimization without WEC.
Blade planform design optimization to enhance turbine wake control
Authors: Allen Jeffery , Young Ethan , Bortolotti Pietro , King Ryan , Barter Garrett
Published: January 2022

This study considers optimizing the planform of wind turbine blades to ultimately enhance wind plant controls, namely, wake steering strategies. Adjoint‐enabled unsteady actuator line simulations are carried out to obtain gradients for optimization of several different performance objectives with respect to blade chord length at 10 locations along blade span. We demonstrate different blade design optimizations that can maximize time‐averaged lateral wake deflection, entrainment of kinetic energy, or total power of multiple turbines. Our optimized designs can produce a 4+% increase in wake deflection, a 4× increase in vertical kinetic energy entrainment, or a 3.6% increase in power when compared with the baseline case. While lateral wake deflection is only modestly sensitive to chord changes, we find that increasing the outboard chord length can dramatically increase kinetic energy entrainment, resulting in faster wake recovery and gains in net power. While this work develops only a few case studies emphasizing relative performance improvements and general trends, these results show the promise of a framework that combines mid‐fidelity computation with adjoint‐based optimization for control and design problems.
General Elements of Genomic Selection and Statistical Learning
Authors: Montesinos López Osval Antonio , Montesinos López Abelardo , Crossa Jose
Published: January 2022

Nowadays, huge data quantities are collected and analyzed for delivering deep insights into biological processes and human behavior. This chapter assesses the use of big data for prediction and estimation through statistical machine learning and its applications in agriculture and genetics in general, and specifically, for genome-based prediction and selection. First, we point out the importance of data and how the use of data is reshaping our way of living. We also provide the key elements of genomic selection and its potential for plant improvement. In addition, we analyze elements of modeling with machine learning methods applied to genomic selection and stress their importance as a predictive methodology. Two cultures of model building are analyzed and discussed: prediction and inference; by understanding modeling building, researchers will be able to select the best model/method for each circumstance. Within this context, we explain the differences between nonparametric models (predictors are constructed according to information derived from data) and parametric models (all the predictors take predetermined forms with the response) as well their type of effects: fixed, random, and mixed. Basic elements of linear algebra are provided to facilitate understanding the contents of the book. This chapter also contains examples of the different types of data using supervised, unsupervised, and semi-supervised learning methods.
Bayesian Genomic Linear Regression
Authors: Montesinos López Osval Antonio , Montesinos López Abelardo , Crossa Jose
Published: January 2022

The Bayesian paradigm for parameter estimation is introduced and linked to the main problem of genomic-enabled prediction to predict the trait of interest of the non-phenotyped individuals from genotypic information, environment variables, or other information (covariates). In this situation, a convenient practice is to include the individuals to be predicted in the posterior distribution to be sampled. We explained how the Bayesian Ridge regression method is derived and exemplified with data from plant breeding genomic selection. Other Bayesian methods (Bayes A, Bayes B, Bayes C, and Bayesian Lasso) were also described and exemplified for genome-based prediction. The chapter presented several examples that were implemented in the Bayesian generalized linear regression (BGLR) library for continuous response variables. The predictor under all these Bayesian methods includes main effects (of environments and genotypes) as well as interaction terms related to genotype × environment interaction.
Digitale Daten und Big Data
Authors: Lünich Marco
Published: January 2022

Um die Bedeutung digitaler Daten im sozialen Kontext der Digitalisierung nachvollziehen zu können, muss nun zunächst ein grundlegendes Verständnis dafür hergestellt werden, was Daten und insbesondere digitale Daten ausmacht sowie warum im Kontext digitaler Daten oft von Big Data die Rede ist. Dabei steht zunächst erst einmal die eher technische Definition von Daten im Vordergrund. Doch bereits bei Betrachtung dessen, was gemeinhin unter Big Data verstanden wird, wird in der Literatur die rein technische Abgrenzung aufgeweicht und auch um sozio-technologische Aspekte der großen digitalen Datenbestände erweitert.
Das Big-Data-Glaubenssystem (BDGS)
Authors: Lünich Marco
Published: January 2022

In diesem Abschnitt wird nun mit Bezug auf die vorhergehenden Ausführungen zu Big Data argumentiert, dass sich das soeben beschriebene Wahrnehmungsmuster als ein Glaubenssystem beschreiben lässt: das Big-Data-Glaubenssystem (BDGS), das sich in seinen Glaubensüberzeugen insbesondere auf den Erkenntnis- und Nutzengewinn durch Big Data bezieht. Denn an dieser Stelle kommen die zuvor in den einzelnen Kapiteln gespannten konzeptuellen Fäden sozio-technischer Betrachtung des Phänomens Big Data zusammen und bereiten gleichzeitig ein genaueres Verständnis durch kognitions-psychologische Messung vor. Es muss daher zunächst die Bedeutung der zuvor beleuchteten Überlegungen für eine nachfolgende Analyse verdeutlicht werden.
Das Korpus
Authors: Ackermann Ulrike
Published: January 2022

Das Ziel dieses Kapitels ist es, die Leser/innen mit der materialen Grundlage bekannt zu machen, damit ihnen die später folgenden theoretischen und methodischen Ausführungen plausibel sind. Angewandte qualitative Aufbereitungs- und Auswertungstechniken – also die Methode der Datenanalyse – um narrative Praktiken von Unternehmen im Zusammenspiel mit ihrer (S)D im Internet nachzuverfolgen, habe ich in direkter Nähe der Analysekapitel platziert. Mag die Trennung der Korpusbeschreibung von der Analysemethode ungewöhnlich wirken, erachte ich sie in Anbetracht der heterogenen Datenlage jedoch als zielführend.
Linguistische Spezifizierung des Untersuchungsgegenstandes
Authors: Ackermann Ulrike
Published: January 2022

Da ich für die vorliegende Arbeit eine interdisziplinäre Betrachtung der Daten aufgrund ihres Entstehungskontextes als zentral erachte und aus diesem Grund neben den linguistischen Beschreibungsebenen insbesondere wirtschaftswissenschaftliche Hintergründe einbringe – und literaturwissenschaftliche Konzepte einbeziehe –, stelle ich den Analyseergebnissen ein Kapitel zur linguistischen Verortung des Untersuchungsgegenstandes voran. Dieses Kapitel umfasst maßgebende linguistische Merkmale der erhobenen Daten sowie die Zuordnung der Daten in den textlinguistischen Fachbereich. In dem daran anschließenden dritten Kapitel werden in Folge erzähltheoretische Ansätze in den Blick genommen.
Erzähltheoretische Grundlagen für uRE
Authors: Ackermann Ulrike
Published: January 2022

Nachdem im vorausgegangenen Kapitel der Untersuchungsgegenstand im Fachbereich der Textlinguistik verortet und anhand dessen beschrieben wurde, führe ich die Bestimmung der erhobenen uRE nun im erzähltheoretischen Bereich fort. In diesem Kapitel geht es also darum, (1) die uRE unter einer narratologischen Perspektive zu betrachten und (2) den narratologischen Rahmen vorzustellen, in dem sich die uRE bewegen. Einleitend greife ich Termini auf (Abschn. 5.1), die aufgrund ihrer vielfältigen Anwendung im Rahmen dieser Arbeit genauer gefasst werden müssen.
Situativer Kontext: „text“-externe und „text“-interne Einflussfaktoren
Authors: Ackermann Ulrike
Published: January 2022

URE zur imagefördernden (S)D sind funktional angelegt, um ein Ziel zu erreichen. Sie entstehen daher unter bestimmten Einflussfaktoren. Diese bilden den spezifischen situativen Kontext, in dem sich die erhobenen uRE erst entwickeln. Die Einflussfaktoren sind darin verschieden, dass sie entweder „text“-extern oder „text“-intern wirksam werden. Gülich/Raible (1977: 46 f.) verwenden die beiden Termini für unterschiedliche Perspektiven, die man auf einen Text einnehmen kann. Auf diesen Kontext angewendet, bezieht sich eine „text“-externe Perspektive auf konzeptionelle Einflüsse auf die uRE (= „text“-externe Einflussfaktoren).
Narrativ gestützte Typen zur imagefördernden (Selbst)Darstellung
Authors: Ackermann Ulrike
Published: January 2022

Im Mittelpunkt dieses Kapitels stehen vier Grundtypen imagefördernder (S)D von Unternehmen, die empirisch aus den erhobenen Erzähltexten methodisch (Abschn. 6.2.1) hervorgehen. Diese Grundtypen bilden immaterielle Werte der Unternehmen ab, die aus einem Selbstverständnis in ein gewünschtes Selbstbild geleitet werden, wie es aus Prozessen der Corporate Identity (Abschn. 1.1) hervorgeht.
General gauge-Yukawa-quartic β-functions at 4-3-2-loop order
Authors: Davies Joshua , Herren Florian , Thomsen Anders Eller
Published: January 2022

Abstract

We determine the full set of coefficients for the completely general 4-loop gauge and 3-loop Yukawa β-functions for the most general renormalizable four-dimensional theories. Using a complete parametrization of the β-functions, we compare the general form to the specific β-functions of known theories to constrain the unknown coefficients. The Weyl consistency conditions provide additional constraints, completing the determination.
Fiducial cross sections for the lepton-pair-plus-photon decay mode in Higgs production up to NNLO QCD
Authors: Chen X. , Gehrmann T. , Glover E. W. N. , Huss A.
Published: January 2022

Abstract

The rare three-body decay of a Higgs boson to a lepton-antilepton pair and a photon is starting to become experimentally accessible at the LHC. We investigate how higher-order QCD corrections to the dominant gluon-fusion production process impact on the fiducial cross sections in this specific Higgs decay mode for electrons and muons. Corrections up to NNLO QCD are found to be sizeable. They are generally uniform in kinematical variables related to the Higgs boson, but display several distinctive features in the kinematics of its individual decay products.
Lessons learned from terror attacks: thematic priorities and development since 2001—results from a systematic review
Authors: Schorscher Nora , Kippnich Maximilian , Meybohm Patrick , Wurmb Thomas
Published: January 2022

Purpose

The threat of national and international terrorism remains high. Preparation is the key requirement for the resilience of hospitals and out-of-hospital rescue forces. The scientific evidence for defining medical and tactical strategies often feeds on the analysis of real incidents and the lessons learned derived from them. This systematic review of the literature aims to identify and systematically report lessons learned from terrorist attacks since 2001.

Methods

PubMed was used as a database using predefined search strategies and eligibility criteria. All countries that are part of the Organization for Economic Cooperation and Development (OECD) were included. The time frame was set between 2001 and 2018.

Results

Finally 68 articles were included in the review. From these, 616 lessons learned were extracted and summarized into 15 categories. The data shows that despite the difference in attacks, countries, and casualties involved, many of the lessons learned are similar. We also found that the pattern of lessons learned is repeated continuously over the time period studied.

Conclusions

The lessons from terrorist attacks since 2001 follow a certain pattern and remained constant over time. Therefore, it seems to be more accurate to talk about lessons identified rather than lessons learned. To save as many victims as possible, protect rescue forces from harm, and to prepare hospitals at the best possible level it is important to implement the lessons identified in training and preparation.
Sooner or later? The impact of child education on household consumption
Authors: Aina Carmen , Sonedda Daniela
Published: January 2022

We study the impact of one more year of child’s education on household (non-durable) consumption. We exploit an exogenous shock generated by a university reform in Italy in the early 2000s. We find that families responded in a way that is consistent with education as a production good. The higher child’s education produced household positive, permanent income innovations. Hence, family non-durable consumption increased. Our findings suggest that education can be an insurance device against adverse permanent income shocks. The 2001 reform not only positively affected offspring’s years of schooling, but it also had a positive effect to boost household consumption.
A model-based approach to designing developmental toxicology experiments using sea urchin embryos
Authors: Collins Michael D. , Cui Elvis Han , Hyun Seung Won , Wong Weng Kee
Published: January 2022

The key aim of this paper is to suggest a more quantitative approach to designing a dose–response experiment, and more specifically, a concentration–response experiment. The work proposes a departure from the traditional experimental design to determine a dose–response relationship in a developmental toxicology study. It is proposed that a model-based approach to determine a dose–response relationship can provide the most accurate statistical inference for the underlying parameters of interest, which may be estimating one or more model parameters or pre-specified functions of the model parameters, such as lethal dose, at maximal efficiency. When the design criterion or criteria can be determined at the onset, there are demonstrated efficiency gains using a more carefully selected model-based optimal design as opposed to an ad-hoc empirical design. As an illustration, a model-based approach was theoretically used to construct efficient designs for inference in a developmental toxicity study of sea urchin embryos exposed to trimethoprim. This study compares and contrasts the results obtained using model-based optimal designs versus an ad-hoc empirical design.
Spatial and Seasonal Structure of Bacterial Communities Within Alpine Vineyards: Trentino as a Case Study
Authors: Guzzon Raffaele , Bertoldi Daniela , Roman Tomas , Zanzotti Roberto , Franciosi Elena
Published: January 2022

Bacteria have a fundamental role in determining the fitness of grapevine, the composition of grapes and the features of wines but at present, little information is available. In this work, the bacteria colonizing the different portions of grapevine (bark, leaves and grapes) were explored in the vineyards of the Alpine region of Trentino, considering the impact of different environmental and agronomical variables. The vineyards included in the work were selected based on their different geographical positions (altitude) and grapevine training systems in order to explore the whole variability of the grapevine ecosystem. Moreover, the surface amount of copper was measured on grapes and leaves during the vegetative growth. Bacterial analysis, performed using plate counts and Illumina MiSeq, revealed an increase in the concentration of grape bacteria proportional to the progress of the ripening stage. Conversely, the peak of bacterial concentration onto leaf and bark samples occurred in August, probably due to the more favourable environmental conditions. In bark samples, the bacterial microbiota reached the 7 log CFU/cm2, while 6 log UFC/g were measured in grape samples. A remarkable biodiversity was observed, with 13 phyla, 35 classes, 55 orders, 78 families and 95 genera of bacteria present. The presence of some taxa (Alphaproteobacteria, Desulfovibrionaceae, Clostriadiales, Oscillospira, Lachnospiraceae and Bacteroidales) was ubiquitous in all vineyards, but differences in terms of relative abundance were observed according to the vegetative stage, altitude of the vineyard and training system. Bacteria having oenological implication (Lactobacillus, Pediococcus and Oenococcus) were detected in grape samples collected in August, in low abundance. The data revealed a complex bacterial ecosystem inside the vineyard that, while maintaining common traits, evolves according to environmental and agronomical inputs. This study contributes to define the role of bacteria in the complex balance established in each vineyard between human actions and agricultural environment, known as terroir.
An eco-friendly facile approach for imparting multifunctional protection properties to cellulose/wool blends
Authors: Ibrahim Nabil A. , Eid Basma M. , Emam El-Amir M.
Published: January 2022

A green facile nano-finishing route was developed to impart high antibacterial efficacy, UV-protection, self-cleaning and anti-wrinkle functions to cotton/wool and viscose/wool blends using TiO2, and/or Ag-NPs, as active ingredients, along with citric acid and/or succinic acid/ SHP as ester-crosslinking/fixing systems. The data so obtained demonstrated that outstanding durable functional properties can be achieved using the following formulation: TiO2/Ag-NPs (20 g/L each), citric acid/SHP (50 g/L/30 g/L) and the pad- dry microwave fixation at 1300 W for 5 min. SEM and EDX analysis for selected samples as well mode of interactions among the nominated finishing ingredients and the treated substrates were also investigated.
Zertifizierung von Cardiac-Arrest-Zentren
Authors: Grübl T. , Nauheimer D. , Wolff H. , Gehret G. , Rott N. , Schmidbauer W. , Schieffer B. , Gliwitzky B.
Published: January 2022

Die Versorgung von Patienten mit bzw. nach einem Kreislaufstillstand ist besonders komplex und sollte in einem Cardiac Arrest Center (CAC) erfolgen. Zur Etablierung der CAC finden Zertifizierungen mit regelmäßigen Reaudits statt. Dieser Artikel beschreibt den Zertifizierungsprozess. Die Zertifizierung zum CAC ist ein mehrstufiger Prozess und nimmt insgesamt etwa ein Jahr Zeit in Anspruch. Ein CAC vereint multidisziplinär alle relevanten prä- und innerklinischen Akteure. Die vorgegebene Infrastruktur, evidenzbasierte Behandlungsalgorithmen und eine systematische Ausbildung sind zu organisieren. Im Rahmen regelmäßiger Konferenzen sind die Abläufe anhand statistischer Auswertungen zu evaluieren und Ansätze zur Prozessoptimierung zu etablieren. Entscheidend ist die fokussierte Organisation dieses Zentrums, sodass Patienten mit ähnlichen Gegebenheiten und Voraussetzungen den annähernd gleichen Behandlungspfad erfahren, ohne dass dies von einzelnen Akteuren abhängig wäre. Multidisziplinäre Zusammenarbeit, präzise Vorgehensweisen unter hoher Patientensicherheit und exakter Dokumentation sichern das Zertifizierungsziel. Das Ergebnis dieser Maßnahmen führt zur Behandlungsoptimierung und Outcomeverbesserung von Patienten mit bzw. nach Kreislaufstillstand. In den aktualisierten internationalen Reanimationsleitlinien von 2020/21 führte dies zu einer stärkeren Empfehlung für die Etablierung von CAC.
Altered DNA methylation in kidney disease: useful markers and therapeutic targets
Authors: Hayashi Kaori
Published: January 2022

Recent studies have demonstrated the association of altered epigenomes with lifestyle-related diseases. Epigenetic regulation promotes biological plasticity in response to environmental changes, and such plasticity may cause a ‘memory effect’, a sustained effect of transient treatment or an insult in the course of lifestyle-related diseases. We investigated the significance of epigenetic changes in several genes required for renal integrity, including the nephrin gene in podocytes, and the sustained anti-proteinuric effect, focusing on the transcription factor Krüppel-like factor 4 (KLF4). We further reported the role of the DNA repair factor lysine-acetyl transferase 5 (KAT5), which acts coordinately with KLF4, in podocyte injury caused by a hyperglycemic state through the acceleration of DNA damage and epigenetic alteration. In contrast, KAT5 in proximal tubular cells prevents acute kidney injury via glomerular filtration regulation by an epigenetic mechanism as well as promotion of DNA repair, indicating the cell type-specific action and roles of DNA repair factors. This review summarizes epigenetic alterations in kidney diseases, especially DNA methylation, and their utility as markers and potential therapeutic targets. Focusing on transcription factors or DNA damage repair factors associated with epigenetic changes may be meaningful due to their cell-specific expression or action. We believe that a better understanding of epigenetic alterations in the kidney will lead to the development of a novel strategy for chronic kidney disease (CKD) treatment.
Fluid-structure interaction simulation of tissue degradation and its effects on intra-aneurysm hemodynamics
Authors: Wang Haifeng , Uhlmann Klemens , Vedula Vijay , Balzani Daniel , Varnik Fathollah
Published: January 2022

Tissue degradation plays a crucial role in vascular diseases such as atherosclerosis and aneurysms. Computational modeling of vascular hemodynamics incorporating both arterial wall mechanics and tissue degradation has been a challenging task. In this study, we propose a novel finite element method-based approach to model the microscopic degradation of arterial walls and its interaction with blood flow. The model is applied to study the combined effects of pulsatile flow and tissue degradation on the deformation and intra-aneurysm hemodynamics. Our computational analysis reveals that tissue degradation leads to a weakening of the aneurysmal wall, which manifests itself in a larger deformation and a smaller von Mises stress. Moreover, simulation results for different heart rates, blood pressures and aneurysm geometries indicate consistently that, upon tissue degradation, wall shear stress increases near the flow-impingement region and decreases away from it. These findings are discussed in the context of recent reports regarding the role of both high and low wall shear stress for the progression and rupture of aneurysms.
The role of channel height and actuation method on particle manipulation in surface acoustic wave (SAW)-driven microfluidic devices
Authors: Devendran Citsabehsan , Collins David J. , Neild Adrian
Published: January 2022

Surface acoustic wave (SAW) micromanipulation offers modularity, easy integration into microfluidic devices and a high degree of flexibility. A major challenge for acoustic manipulation, however, is the existence of a lower limit on the minimum particle size that can be manipulated. As particle size reduces, the drag force resulting from acoustic streaming dominates over acoustic radiation forces; reducing this threshold is key to manipulating smaller specimens. To address this, we investigate a novel excitation configuration based on diffractive-acoustic SAW (DASAW) actuation and demonstrate a reduction in the critical minimum particle size which can be manipulated. DASAW exploits the inherent diffractive effects arising from a limited transducer area in a microchannel, requiring only a travelling SAW (TSAW) to generate time-averaged pressure gradients. We show that these acoustic fields focus particles at the channel walls, and further compare this excitation mode with more typical standing SAW (SSAW) actuation. Compared to SSAW, DASAW reduces acoustic streaming effects whilst generating a comparable pressure field. The result of these factors is a critical particle size with DASAW (1 $$\upmu$$
μ
m) that is significantly smaller than that for SSAW actuation (1.85 $$\upmu$$
μ
m), for polystyrene particles and a given $$\lambda _{\text {SAW}}$$

λ
SAW

= 200 $$\upmu$$
μ
m. We further find that streaming magnitude can be tuned in a DASAW system by changing the channel height, noting optimum channel heights for particle collection as a function of the fluid wavelength at which streaming velocities are minimised in both DASAW and SSAW devices.
Risk Factors for COVID-19 Mortality Among People Living with HIV: A Scoping Review
Authors: Varshney Karan , Ghosh Prerana , Stiles Helena , Iriowen Rosemary
Published: January 2022

People living with HIV (PLWH) are particularly vulnerable to worsened outcomes of COVID-19. Therefore, the purpose of this work was to provide a scoping review of the literature to assess the risk factors for COVID-19 mortality among PLWH. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), searches were conducted in PubMed, Scopus, Global Health, and WHO Coronavirus Database. Articles were eligible for inclusion if they were in English, included PLWH who died after COVID-19 infection, and described risk factors for mortality. Results were descriptively synthesized and pooled thereafter. Study quality was assessed using the Joanna Brigg Institute’s critical appraisal tools. 20 studies were eligible for inclusion, with the pooled death rate being 11.7%. Age was a major risk factor, especially after 50 (23.2%) and after 70 (41.8%), and males had a death rate nearly double that of females. As total comorbidities increased, the death rate also greatly increased; among those with comorbidities, the highest fatality rates were those with cardiovascular disease (30.2%), chronic kidney disease (23.5%), obesity (22.4%), and diabetes (18.4%). Other risk factors for mortality among PLWH included having a Black racial background, being an injection drug user, being a smoker, and having a CD4 cell count below 200. There is a need to better study confounding factors, and to understand how vaccination influences mortality risk. Overall, the findings highlight a need to ensure that focus is placed on the varying demographics of PLWH amidst COVID-19 control efforts.
Ki-67 and breast cancer prognosis: does it matter if Ki-67 level is examined using preoperative biopsy or postoperative specimen?
Authors: Choi Soon Bo , Park Jung Min , Ahn Jee Hyun , Go Jieon , Kim Jeeye , Park Hyung Seok , Kim Seung Il , Park Byeong-Woo , Park Seho
Published: January 2022

Purpose

This study aimed to identify the association between Ki-67 level and the prognosis of patients with breast cancer, regardless of the timing of Ki-67 testing (using preoperative biopsy vs. postoperative specimen).

Methods

A total of 4177 patients underwent surgery between January 2008 and December 2016. Immunohistochemical Ki-67 levels, using either preoperative (1673) or postoperative (2831) specimens, were divided into four groups using cutoff points of 10%, 15%, and 20%.

Results

Groups with higher-Ki-67 levels, in both the pre- and postoperative periods, showed significantly larger tumor size, higher grade, more frequent hormone receptor-negativity and human epidermal growth factor receptor 2 overexpression, and active adjuvant treatments than groups with lower-Ki-67 levels. High-Ki-67 levels were also significantly associated with poor survival, irrespective of the timing of specimen examination.

Conclusion

Despite the problems associated with Ki-67, Ki-67 level is an important independent prognostic factor, regardless of the timing of Ki-67 testing, i.e., preoperative or postoperative testing.
Are born global firms really a “new breed” of exporters? Empirical evidence from an emerging market
Authors: Moen Øystein , Falahat Mohammad , Lee Yan-Yin
Published: January 2022

This study investigates and compares born global (BG) firms and non-BG firms in Malaysia. We employed the multigroup analysis technique with structural equation models to test six hypotheses to determine the differences and similarities between two proposed models of BG and non-BG firms across a wide range of industries. The study reveals differences between the antecedents of marketing capabilities for BGs versus non-BGs, indicating that the performance enabling mechanisms differ between the groups. More precisely, the ability of BG firms to convert digital and entrepreneurial orientations into marketing capabilities is found to be a distinguishing characteristic of these firms. Moreover, non-BGs utilize government support to build marketing capabilities and obtain superior performance in the international market. This result suggests that governmental export promotion initiatives in Malaysia should be adjusted to increase relevance for BGs. The findings indicate that marketing capabilities play an essential role in the international market performance of both BGs and non-BGs. An important implication is that managerial focus and actions need to be adjusted depending on the type of firm. The two types of firms are not equal; if they are managed similarly, misjudgment will arise.
Shape binary patterns: an efficient local descriptor and keypoint detector for point clouds
Authors: Romero-González Cristina , García-Varea Ismael , Martínez-Gómez Jesus
Published: January 2022

Many of the research problems in robot vision involve the detection of keypoints, areas with salient information in the input images and the generation of local descriptors, that encode relevant information for such keypoints. Computer vision solutions have recently relied on Deep Learning techniques, which make extensive use of the computational capabilities available. In autonomous robots, these capabilities are usually limited and, consequently, images cannot be processed adequately. For this reason, some robot vision tasks still benefit from a more classic approach based on keypoint detectors and local descriptors. In 2D images, the use of binary representations for visual tasks has shown that, with lower computational requirements, they can obtain a performance comparable to classic real-value techniques. However, these achievements have not been fully translated to 3D images, where research is mainly focused on real-value approaches. Thus, in this paper, we propose a keypoint detector and local descriptor based on 3D binary patterns. The experimentation demonstrates that our proposal is competitive against state-of-the-art techniques, while its processing can be performed more efficiently.
Multi Clustering Recommendation System for Fashion Retail
Authors: Bellini Pierfrancesco , Palesi Luciano Alessandro Ipsaro , Nesi Paolo , Pantaleo Gianni
Published: January 2022

Fashion retail has a large and ever-increasing popularity and relevance, allowing customers to buy anytime finding the best offers and providing satisfactory experiences in the shops. Consequently, Customer Relationship Management solutions have been enhanced by means of several technologies to better understand the behaviour and requirements of customers, engaging and influencing them to improve their shopping experience, as well as increasing the retailers’ profitability. Current solutions on marketing provide a too general approach, pushing and suggesting on most cases, the popular or most purchased items, losing the focus on the customer centricity and personality. In this paper, a recommendation system for fashion retail shops is proposed, based on a multi clustering approach of items and users’ profiles in online and on physical stores. The proposed solution relies on mining techniques, allowing to predict the purchase behaviour of newly acquired customers, thus solving the cold start problems which is typical of the systems at the state of the art. The presented work has been developed in the context of Feedback project partially founded by Regione Toscana, and it has been conducted on real retail company Tessilform, Patrizia Pepe mark. The recommendation system has been validated in store, as well as online.
Hybrid Electron Beam Powder Bed Fusion Additive Manufacturing of Ti–6Al–4V: Processing, Microstructure, and Mechanical Properties
Authors: Tosi R. , Muzangaza E. , Tan X. P. , Wimpenny D. , Attallah M. M.
Published: January 2022

Processing, microstructure, and mechanical properties of the hybrid electron beam powder bed fusion (E-PBF) additive manufacturing of Ti–6Al–4V have been investigated. We explore the possibility of integrating the substrate as a part of the final component as a repair, integrated, or consolidated part. Various starting plate surface conditions are used to understand the joining behavior and their microstructural properties in the bonding region between the plate and initial deposited layers. It is found that mechanical failures mainly occur within the substrate region due to the dominant plastic strains localized in the weaker Ti–6Al–4V substrate. The hybrid concept is successfully proven with satisfactory bonding performance between the E-PBF build and substrate. This investigation improves the practice of using the hybrid E-PBF additive manufacturing technique and provides basic understanding to this approach.
Effect of Holding Time on Populations of Microparticles in Spheroidal Graphite Irons
Authors: Michels L. , Pires A. J. F. , Ribeiro C. A. S. , Kroka B. , Hoel E. G. , Ott E. , Hartung C.
Published: January 2022

Non-metallic microparticles in spheroidal graphite irons are a product of the inoculation and the Mg-treatment of the liquid melt. Besides the influence on the mechanical properties of these iron–carbon–silicon alloys, they are also responsible for the nucleation and the morphology of the graphite phase. The present investigation is undertaken to study holding time effects of a (Ba, Ca, Al)–ferrosilicon (called Ba-inoculant) and (Ca, Al)–ferrosilicon (called Ca-inoculant) inoculants on the overall distribution of microparticles. Using the 2D to 3D conversions method, which is typically used for graphite nodules, the non-metallic microparticles’ statistical parameters, such as size distributions and number densities, are quantified. The total number of particles is similar after Mg-treatment and inoculation for Ca-inoculant but not for Ba-inoculated samples, which lose approximately 25 pct of microparticles after 1 minute of holding time. Iron treated with the Ca-inoculant loses about 37 pct of its nodules after 5 minutes, while the Ba-inoculated melts maintain their performance even after 10 minutes. Based on extrapolating the trend of the undercooling, Ba-inoculated samples would reach the uninoculated undercooling values in 48 minutes, while Ca-inoculated samples in only 11 minutes. By evaluating the size distributions of the non-metallic microparticles, the Ostwald ripening hypothesis or particle aggregation can be verified. The results suggest that sulfides are more critical for graphite nucleation since they can be correlated with the graphite number densities. However, due to the small difference in the microparticle population of the uninoculated sample with Ca-inoculated samples, other aspects of the fading mechanism need to be considered, such as transient metastable states, since the central hypothesis of loss of inclusions cannot alone explain the decrease in the nucleation frequency of graphite.
Emerging Internet of Things driven carbon nanotubes-based devices
Authors: Zhang Shu , Pang Jinbo , Li Yufen , Yang Feng , Gemming Thomas , Wang Kai , Wang Xiao , Peng Songang , Liu Xiaoyan , Chang Bin , Liu Hong , Zhou Weijia , Cuniberti Gianaurelio , Rümmeli Mark H.
Published: January 2022

Carbon nanotubes (CNTs) have attracted great attentions in the field of electronics, sensors, healthcare, and energy conversion. Such emerging applications have driven the carbon nanotube research in a rapid fashion. Indeed, the structure control over CNTs has inspired an intensive research vortex due to the high promises in electronic and optical device applications. Here, this in-depth review is anticipated to provide insights into the controllable synthesis and applications of high-quality CNTs. First, the general synthesis and post-purification of CNTs are briefly discussed. Then, the state-of-the-art electronic device applications are discussed, including field-effect transistors, gas sensors, DNA biosensors, and pressure gauges. Besides, the optical sensors are delivered based on the photoluminescence. In addition, energy applications of CNTs are discussed such as thermoelectric energy generators. Eventually, future opportunities are proposed for the Internet of Things (IoT) oriented sensors, data processing, and artificial intelligence.
A novel alkali-surfactant for optimization of filtercake removal in oil–gas well
Authors: Lichinga Kevin Nsolloh , Luanda Amos , Sahini Mtabazi Geofrey
Published: January 2022

The main objective of this study is to improve the oil-based filtercake removal at the wellbore second interface through chemical method. The reductions in near-well permeability, bonding strength at wellbore second interface and acidizing treatment are the critical problems in oilfield upstream operations. One of the major causes has been identified as drilling fluid filtrate invasion during the drilling operations. This as result leads to near-well reduction in-flow capacity due to high drawdown pressure and wellbore instability. A number of chemical methods such as enzymes, acids, oxidizers, or their hybrids, have been used, however, due to the presence of a number of factors prior to its removal, there are still many challenges in cleaning oil-based filtercake from the wellbore surface. There is a need for development an effective method for improving oil-based filtercake removal. This study presents a novel Alkali-Surfactant (KV-MA) solution developed in the laboratory to optimize the filtercake removal of oil–gas wellbore. The Reynold number for KV-MA solution was found to be 9,068 indicating that turbulent flow regime will dominate in the annulus which enhances the cleaning efficiency. The wettability test established that, contact angle of 14° was a proper wetting agent. The calculated cleaning efficiency was 86.9%, indicating that it can effectively remove the oil-based filtercake. NaOH reacts with the polar components in the oil phase of the oil-based filtercake to produce ionized surface-active species; hence reducing the Interfacial Tension. Surfactant quickens the diffusion of ionized species from the interface to the bulk phase.
Genomic Perspectives on the Emerging SARS-CoV-2 Omicron Variant
Authors: Ma Wentai , Yang Jing , Fu Haoyi , Su Chao , Yu Caixia , Wang Qihui , de Vasconcelos Ana Tereza Ribeiro , Bazykin Georgii A. , Bao Yiming , Li Mingkun
Published: January 2022

A new variant of concern for SARS-CoV-2, Omicron (B.1.1.529), was designated by the World Health Organization on November 26, 2021. This study analyzed the viral genome sequencing data of 108 samples collected from patients infected with Omicron. First, we found that the enrichment efficiency of viral nucleic acids was reduced due to mutations in the region where the primers anneal to. Second, the Omicron variant possesses an excessive number of mutations compared to other variants circulating at the same time (median: 62 vs. 45), especially in the Spike gene. Mutations in the Spike gene confer alterations in 32 amino acid residues, more than those observed in other SARS-CoV-2 variants. Moreover, a large number of nonsynonymous mutations occur in the codons for the amino acid residues located on the surface of the Spike protein, which could potentially affect the replication, infectivity, and antigenicity of SARS-CoV-2. Third, there are 53 mutations between the Omicron variant and its closest sequences available in public databases. Many of these mutations were rarely observed in public databases and had a low mutation rate. In addition, the linkage disequilibrium between these mutations was low, with a limited number of mutations concurrently observed in the same genome, suggesting that the Omicron variant would be in a different evolutionary branch from the currently prevalent variants. To improve our ability to detect and track the source of new variants rapidly, it is imperative to further strengthen genomic surveillance and data sharing globally in a timely manner.
The Consumer Revolution, 1650–1800
Authors: Kwass Michael
Published: January 2022

The production, acquisition, and use of consumer goods defines our daily lives, and yet consumerism is seen as increasingly controversial. Movements for sustainable and ethical consumerism are gaining momentum alongside an awareness of how our choices in the marketplace can affect public issues. How did we get here? This volume advances a bold new interpretation of the 'consumer revolution' of the eighteenth century, when European elites, middling classes, and even certain labourers purchased unprecedented quantities of clothing, household goods, and colonial products. Michael Kwass adopts a global perspective that incorporates the expansion of European empires, the development of world trade, and the rise of plantation slavery in the Americas. Kwass analyses the emergence of Enlightenment material cultures, contentious philosophical debates on the morality of consumption, and new forms of consumer activism to offer a fresh interpretation of the politics of consumption in the age of abolitionism and the Atlantic Revolutions.