bluuebunny/crossref_metadata_2025 huggingface dataset:
What knowledge counts—boundaries of knowledge in cross-institutional curricula in higher education
Authors: Annala Johanna
Published: July 2022

The aim of this study was to explore knowledge in the context of creating a shared curriculum between research-intensive and vocationally oriented universities of applied sciences. Curriculum knowledge was explored from the accounts of 26 teachers from four institutions in Finland. Shared curriculum initiatives created an environment in which teachers were obliged to negotiate and make explicit their approaches to curriculum knowledge and knowledge practices. The phenomenon of blurring boundaries is approached with Bernstein’s sociology of education. The present findings show that institutions have a distinct foundation for curriculum knowledge, but cross-curricular initiatives brought pressure to change towards the knowledge practices of the other institution. Discrepancies were found between knowledge and learning outcomes, and between knowledge as a negotiated artefact and knowledge as enacted in curriculum implementation. Curriculum knowledge emerged with symbolic boundaries and an invisible pedagogic order. This resulted in practices where the official discourse appears to have similar learning outcomes, which are not similar from the perspective of knowledge. Focus on a harmonised degree, as stated in the European qualification framework, obscures the question of knowledge and requires more attention. This is especially the case if the boundaries between degrees and institutions are purposely weakened. If the rationale to weaken the boundaries is on the streamlined educational processes and their efficacy, there is a risk of gaps in knowledge provided for students in the higher education.
On the force field optimisation of $$\beta$$-lactam cores using the force field Toolkit
Authors: Wu Qiyang , Huang Tianyang , Xia Songyan , Otto Frank , Lee Tzong-Yi , Huang Hsien-Da , Chiang Ying-Chih
Published: July 2022

When employing molecular dynamics (MD) simulations for computer-aided drug design, the quality of the used force fields is highly important. Here we present reparametrisations of the force fields for the core molecules from 9 different $$\beta$$
β
-lactam classes, for which we utilized the force field Toolkit and Gaussian calculations. We focus on the parametrisation of the dihedral angles, with the goal of reproducing the optimised quantum geometry in MD simulations. Parameters taken from CGenFF turn out to be a good initial guess for the multiplicity of each dihedral angle, but the key to a successful parametrisation is found to lie in the phase shifts. Based on the optimised quantum geometry, we come up with a strategy for predicting the phase shifts prior to the dihedral potential fitting. This allows us to successfully parameterise 8 out of the 11 molecules studied here, while the remaining 3 molecules can also be parameterised with small adjustments. Our work highlights the importance of predicting the dihedral phase shifts in the ligand parametrisation protocol, and provides a simple yet valuable strategy for improving the process of parameterising force fields of drug-like molecules.
An acrylate-based quasi-solid polymer electrolyte incorporating a novel dinitrile poly(ethylene glycol) plasticizer for lithium-ion batteries
Authors: Leš Kristian , Schönewerk Jens , Glenneberg Jens , Jordan Carmen-Simona
Published: July 2022

The performance of solid polymer electrolytes is characterized by lower ionic conductivity than conventional liquid electrolytes but provides advantages in terms of operational safety. A quasi-solid polymer electrolyte (QSPE) based on a new plasticizer 4,7,10,13-tetraoxahexadecane-1,16-dinitrile (bCN-PEG4) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) incorporated into a polyacrylates matrix was successfully prepared via UV-induced copolymerization. The matrix consists of units of trimethylolpropane ethoxylate triacrylate (ETPTA), poly(ethylene glycol) diacrylate (PEGDA), and the monoacrylate poly(ethylene glycol) methyl ether acrylate (mPEGa). The QSPE containing 55 wt% bCN-PEG4 exhibits highly uniform morphology, thermal stability > 200 °C, ionic conductivity of 1.8 × 10−4 S cm−1 at 30 °C, and 1.3 × 10−3 S cm−1 at 80 °C, coupled with very high electrochemical stability (> 5 V vs. Li/Li+) and a low glass transition temperature (− 55.7 °C). A cycling experiment in a Li/QPSE/Li cell setup demonstrated the compatibility toward lithium metal additionally. The bCN-PEG4 offers an overall satisfying performance as a plasticizer in a poly(ethylene oxide)-based solid polymer electrolyte. The new QSPE is an alternative to dinitrile-based (e.g., succinonitrile) or glycol ether-based (e.g., tetraglyme) plasticizers with application potential in high-voltage lithium-ion batteries.

Graphical abstract
Evaluation of Laboratory and Sonographic Parameters for Detection of Portal Hypertension in Patients with Common Variable Immunodeficiency
Authors: Globig Anna-Maria , Strohmeier Valentina , Surabattula Rambabu , Leeming Diana J. , Karsdal Morten A. , Heeg Maximilian , Kindle Gerhard , Goldacker Sigune , von Spee-Mayer Caroline , Proietti Michele , Bausch Birke , Bettinger Dominik , Schultheiß Michael , Thimme Robert , Schuppan Detlef , Warnatz Klaus
Published: July 2022

Timely detection of portal hypertension as a manifestation in a subgroup of patients with common variable immunodeficiency (CVID) represents a challenge since it is usually not associated with liver cirrhosis. To identify relevant markers for portal hypertension, we evaluated clinical history, laboratory parameters, and abdominal ultrasound including liver elastography and biomarkers of extracellular matrix formation. Twenty seven (6%) of 479 CVID patients presented with clinically significant portal hypertension as defined by either the presence of esophageal varices or ascites. This manifestation occurred late during the course of the disease (11.8 years after first diagnosis of CVID) and was typically part of a multiorgan disease and associated with a high mortality (11/27 patients died during follow up). The strongest association with portal hypertension was found for splenomegaly with a longitudinal diameter of > 16 cm. Similarly, most patients presented with a liver stiffness measurement (LSM) of above 6.5 kPa, and a LSM above 20 kPa was always indicative of manifest portal hypertension. Additionally, many laboratory parameters including Pro-C4 were significantly altered in patients with portal hypertension without clearly increasing the discriminatory power to detect non-cirrhotic portal hypertension in CVID. Our data suggest that a spleen size above 16 cm and an elevated liver stiffness above 6.5 kPa should prompt further evaluation of portal hypertension and its sequelae, but earlier and better liquid biomarkers of this serious secondary complication in CVID are needed.
Machine unlearning: linear filtration for logit-based classifiers
Authors: Baumhauer Thomas , Schöttle Pascal , Zeppelzauer Matthias
Published: July 2022

Recently enacted legislation grants individuals certain rights to decide in what fashion their personal data may be used and in particular a “right to be forgotten”. This poses a challenge to machine learning: how to proceed when an individual retracts permission to use data which has been part of the training process of a model? From this question emerges the field of machine unlearning, which could be broadly described as the investigation of how to “delete training data from models”. Our work complements this direction of research for the specific setting of class-wide deletion requests for classification models (e.g. deep neural networks). As a first step, we propose linear filtration as an intuitive, computationally efficient sanitization method. Our experiments demonstrate benefits in an adversarial setting over naive deletion schemes.
Estimation of tire-road contact forces through a model-based approach employing strain measurements
Authors: Garcia-Pozuelo Daniel , Olatunbosun Oluremi , Palli Gianluca , Strano Salvatore , Terzo Mario , Tordela Ciro
Published: July 2022

The employment of intelligent tires to test the vehicle performances is ever-increasing in the last years. Many research activities have been made to correlate measurements provided by sensors to the tire dynamics. In this paper, a novel tire-road forces estimation technique is presented. The developed estimator is based on an approximation of the well-known Flexible Ring Tire Model (FRTM) and therefore, it is suitable for real-time normal and tangential forces identification. Only the tread band strain measurements are employed in the developed algorithm which can estimate the tire-road forces at every wheel revolution. The tool is validated through both numerical and experimental tests. The results indicate that the developed estimation algorithm, obtained by a mathematical inversion of the FRTM, can be employed as a monitoring tool for tires and vehicles.
Mitigating adversarial evasion attacks by deep active learning for medical image classification
Authors: Ahmed Usman , Lin Jerry Chun-Wei , Srivastava Gautam
Published: July 2022

In the Internet of Medical Things (IoMT), collaboration among institutes can help complex medical and clinical analysis of disease. Deep neural networks (DNN) require training models on large, diverse patients to achieve expert clinician-level performance. Clinical studies do not contain diverse patient populations for analysis due to limited availability and scale. DNN models trained on limited datasets are thereby constraining their clinical performance upon deployment at a new hospital. Therefore, there is significant value in increasing the availability of diverse training data. This research proposes institutional data collaboration alongside an adversarial evasion method to keep the data secure. The model uses a federated learning approach to share model weights and gradients. The local model first studies the unlabeled samples classifying them as adversarial or normal. The method then uses a centroid-based clustering technique to cluster the sample images. After that, the model predicts the output of the selected images, and active learning methods are implemented to choose the sub-sample of the human annotation task. The expert within the domain takes the input and confidence score and validates the samples for the model’s training. The model re-trains on the new samples and sends the updated weights across the network for collaboration purposes. We use the InceptionV3 and VGG16 model under fabricated inputs for simulating Fast Gradient Signed Method (FGSM) attacks. The model was able to evade attacks and achieve a high accuracy rating of 95%.
Do Kernel and Neural Embeddings Help in Training and Generalization?
Authors: Rahbar Arman , Jorge Emilio , Dubhashi Devdatt , Haghir Chehreghani Morteza
Published: July 2022

Recent results on optimization and generalization properties of neural networks showed that in a simple two-layer network, the alignment of the labels to the eigenvectors of the corresponding Gram matrix determines the convergence of the optimization during training. Such analyses also provide upper bounds on the generalization error. We experimentally investigate the implications of these results to deeper networks via embeddings. We regard the layers preceding the final hidden layer as producing different representations of the input data which are then fed to the two-layer model. We show that these representations improve both optimization and generalization. In particular, we investigate three kernel representations when fed to the final hidden layer: the Gaussian kernel and its approximation by random Fourier features, kernels designed to imitate representations produced by neural networks and finally an optimal kernel designed to align the data with target labels. The approximated representations induced by these kernels are fed to the neural network and the optimization and generalization properties of the final model are evaluated and compared.
The Perpetual Trouble with Network Products Why IT Firms Choose Partial Compatibility
Authors: Stadler Manfred , Trexler Céline Tobler , Unsorg Maximiliane
Published: July 2022

Compatibility of network products is an important issue in markets for communication technology as well as hard- and software products. Empirical findings suggest that firms competing in these markets typically choose intermediate degrees of product compatibility. We present a strategic two-stage game of two firms deciding independently or commonly on the degree of product compatibility in the first stage and on prices in the second stage. Indeed, partial compatibility constitutes a subgame perfect Nash equilibrium when coordination costs of standardization are high and the installed bases are low - conditions that typically characterize IT markets.
Five Solar Cycles of Solar Corona Investigations
Authors: Antonucci Ester
Published: July 2022

These are the memoirs of fifty years of research in solar physics, closely related to the history of three of the major solar space missions, from the Solar Maximum Mission, SMM, to Solar Orbiter, at present in navigation toward vantage points closer and closer to the Sun. My interest in solar physics was stimulated by the studies on cosmic rays at the University of Turin, and the research in this field initiated at Stanford University as a postdoctoral fellow in the team of John Wilcox with studies on the large-scale corona and its rotation. Thanks to Alan Gabriel, during my first space mission, SMM, I was involved in the operations and scientific data analysis of the Soft X-ray Polychromator. Together with Giancarlo Noci and Giuseppe Tondello, I participated in the realization of the UltraViolet Coronagraph Spectrometer, NASA/ASI, flown on-board SOHO. After this experience there was the opportunity to participate in the formulation of the proposal of the Solar Orbiter mission, and to guide the team, which for this mission developed the Metis coronagraph, up to the delivery of the instrument to the European Space Agency in 2017.
The metaphysical burden of Millianism
Authors: Mahant Nikhil
Published: July 2022

The Millian semantic view of names relies on a metaphysical view of names—often given the label ‘common currency conception’ (‘CCC’)—on which the names of distinct individuals count as distinct names. While even defenders of the Millian view admit that the CCC ‘does not agree with the most common usage’ (Kripke in Naming & Necessity, Harvard University Press, 1980), I will argue further that the CCC makes names exceptional amongst the class of linguistic expressions: if the CCC is correct, then names must have a sui-generis metaphysical nature, distinct from the metaphysics of every other kind of linguistic expression. Such metaphysical exceptionalism would be justified if the Millian view had a clear, uncontested theoretical advantage over its rivals. However, in the context of a semantic debate about names in which the closest competitors of the Millian view—the Predicate view and Indexicalism—do not result in such exceptionalism, it counts as a strike against the Millian view.
Deploying a robotic positive psychology coach to improve college students’ psychological well-being
Authors: Jeong Sooyeon , Aymerich-Franch Laura , Arias Kika , Alghowinem Sharifa , Lapedriza Agata , Picard Rosalind , Park Hae Won , Breazeal Cynthia
Published: July 2022

Despite the increase in awareness and support for mental health, college students’ mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them only provide one-way passive contents for their users, such as psycho-education, health monitoring, and clinical assessment. We present a robotic coach that not only delivers interactive positive psychology interventions but also provides other useful skills to build rapport with college students. Results from our on-campus housing deployment feasibility study showed that the robotic intervention showed significant association with increases in students’ psychological well-being, mood, and motivation to change. We further found that students’ personality traits were associated with the intervention outcomes as well as their working alliance with the robot and their satisfaction with the interventions. Also, students’ working alliance with the robot was shown to be associated with their pre-to-post change in motivation for better well-being. Analyses on students’ behavioral cues showed that several verbal and nonverbal behaviors were associated with the change in self-reported intervention outcomes. The qualitative analyses on the post-study interview suggest that the robotic coach’s companionship made a positive impression on students, but also revealed areas for improvement in the design of the robotic coach. Results from our feasibility study give insight into how learning users’ traits and recognizing behavioral cues can help an AI agent provide personalized intervention experiences for better mental health outcomes
Surgical Tool Datasets for Machine Learning Research: A Survey
Authors: Rodrigues Mark , Mayo Michael , Patros Panos
Published: July 2022

This paper is a comprehensive survey of datasets for surgical tool detection and related surgical data science and machine learning techniques and algorithms. The survey offers a high level perspective of current research in this area, analyses the taxonomy of approaches adopted by researchers using surgical tool datasets, and addresses key areas of research, such as the datasets used, evaluation metrics applied and deep learning techniques utilised. Our presentation and taxonomy provides a framework that facilitates greater understanding of current work, and highlights the challenges and opportunities for further innovative and useful research.
Tackling Marine Microplastics Pollution: an Overview of Existing Solutions
Authors: Fiore Melania , Fraterrigo Garofalo Silvia , Migliavacca Alessandro , Mansutti Alessandro , Fino Debora , Tommasi Tonia
Published: July 2022

Microplastics pollution is one of the main environmental challenges of our time, even though microplastics were observed for the first time almost 50 years ago. Microplastics—little plastic fragments smaller than 5 mm in size—are released from bigger plastic objects during their use, maintenance, or disposal. As their release is uncontrolled and mostly uncontrollable, microplastics end up in the environment and are easily transported across the world, polluting nearly every ecosystem, especially the aquatic ones. Hence, microplastics represent a huge menace for many living species: they are ingested unintentionally by smaller animals and transferred along the food chain up to human beings, even threatening our health. It is therefore vital to take action against microplastics and many technologies have been designed in recent years with this purpose in mind. This paper provides an overview of the main solutions developed thus far to reduce further microplastic emissions and to collect those already released.
Die Generalisierung, Ausweitung und Rivalität sozialer Perspektiven. Zur Rekonstruktion und Aktualisierung von Meads Theorie der Normativität
Authors: Nungesser Frithjof
Published: July 2022

Der Aufsatz untersucht die normativitätstheoretische Bedeutung von George Herbert Meads Arbeiten. Er konzentriert sich dabei auf zwei zentrale Stränge des Werks. Rekonstruiert werden zum einen Meads am Spielverhalten entwickelte Argumente zur stufenweisen Aneignung normativer Kompetenzen im Laufe der Sozialisation. Im Rückgriff auf aktuelle entwicklungspsychologische Studien wird gezeigt, dass Meads Theorie an Plausibilität gewinnt, wenn man Rollen- („play“) und Regelspiele („game“) nicht als Phasen, sondern als Grundformen des Sozialverhaltens versteht, die parallel zueinander im Zeitverlauf an normativer Bindungskraft und Abstraktheit gewinnen. Rekonstruiert werden zum anderen Meads wenig bekannte gesellschaftstheoretische Überlegungen zu den gegenläufigen Dynamiken generalisierter Perspektiven. In Studien zur Strafjustiz, zu den internationalen Beziehungen oder zu sozialen Konflikten und Reformbewegungen argumentiert Mead, dass die Fähigkeit zur Perspektivenübernahme die Ausweitung des sozialen Dialogs ebenso ermöglicht wie die aggressive Abgrenzung von Anderen. Anhand des Vergleichs mit Luc Boltanskis und Laurent Thévenots Theorie der Rechtfertigungsordnungen wird im Anschluss herausgearbeitet, dass Mead zwar Konflikten zentrale Bedeutung beimisst, insgesamt aber die Pluralität normativer Perspektiven ausblendet, einer Universalisierungsteleologie zuneigt und spezifische Konfliktformen pathologisiert.
Konsensus-Statement der Österreichischen Gesellschaft für Schlafmedizin (ÖGSM/ASRA) zum Management der residualen exzessiven Tagesschläfrigkeit (rETS) bei obstruktiver Schlafapnoe
Authors: Amouzadeh-Ghadikolai O. , Popovic R. , Heidbreder A. , Kugi A. , Saletu M.
Published: July 2022

Hintergrund

Sechs bis zehn Prozent aller Patienten mit einer obstruktiven Schlafapnoe leiden trotz adäquater nächtlicher Überdrucktherapie oder einer effektiven Alternativtherapie an einer residualen exzessiven Tagesschläfrigkeit (rETS). Die Differentialdiagnose der rETS stellt im klinischen Alltag eine interdisziplinäre Herausforderung dar.

Fragestellung

Entwicklung eines übersichtlichen Leitfadens für die Erkennung, die differentialdiagnostischen Abwägungen und die Möglichkeiten der weiterführenden Behandlung der rETS in der klinischen Praxis.

Material und Methode

MeSH-Analyse basierte Recherche und interdisziplinäre Abstimmung von Fachvertreter:innen der Inneren Medizin und Pneumologie, Neurologie sowie Psychiatrie und Psychotherapie.

Ergebnisse

SPAIN-Checkliste zur systematischen differentialdiagnostischen Exploration der rETS mit den Parametern: S chlafverhalten, P sychische Ursachen, A namnese der Medikation, I nternistische Ursachen und N eurologische Ursachen.

Schlussfolgerungen

Die rETS sollte als behandlungswürdiges Symptom erkannt werden. Sie verlangt nach einer interdisziplinären Abklärung und der individuellen Abstimmung der Behandlung auf die Bedürfnisse der Betroffenen.
The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) — development, description and sensitivity analysis
Authors: Hanfland Robert , Pattantyús-Ábrahám Margit , Richter Cornelia , Brunner Dominik , Voigt Christiane
Published: July 2022

Atmospheric dispersion models are applied to describe and predict the dispersion of emitted plumes. Here, we describe the Lagrangian Atmospheric Radionuclide Transport Model (ARTM) 2.8.0 which was developed to simulate the atmospheric dispersion of the emissions of nuclear facilities under routine operation for regulatory purposes over annual time scales. ARTM includes a diagnostic wind field model and a particle dispersion model. It simulates size-dependent wet and dry deposition, plume rise and γ-cloud shine of radioactive exhaust plumes in the simulation domain. This work presents an extensive overview of the different components of the model and of the physical and mathematical concepts of ARTM. We investigate the dependence of the plume dispersion in terms of plume volume, position of maximum concentration and dry deposition rates on key input parameters such as atmospheric stability, surface roughness, zero plane displacement height, source height and the particle size in the case of particulate matter tracers. The results indicate a strong dependence of plume volume and position of the maximum concentration on the stability as well as a minor influence on surface roughness. The source height above ground level has a low impact on the plume volume as the zero plane displacement only slightly affects the position of maximum concentration. Strong turbulence under unstable conditions tends to reduce the impact of sedimentation and decreases deposition in general. This computational model serves to advance the understanding of the dispersion of radioactive plumes in the boundary layer.
Role of Chemokines in the Development and Progression of Alzheimer’s Disease
Authors: Wojcieszak Jakub , Kuczyńska Katarzyna , Zawilska Jolanta B.
Published: July 2022

Alzheimer’s disease (AD) is a progressive neurogenerative disorder manifested by gradual memory loss and cognitive decline due to profound damage of cholinergic neurons. The neuropathological hallmarks of AD are intracellular deposits of neurofibrillary tangles (NFTs) and extracellular aggregates of amyloid β (Aβ). Mounting evidence indicates that intensified neuroinflammatory processes play a pivotal role in the pathogenesis of AD. Chemokines serve as signaling molecules in immune cells but also in nerve cells. Under normal conditions, neuroinflammation plays a neuroprotective role against various harmful factors. However, overexpression of chemokines initiates disruption of the integrity of the blood–brain barrier, facilitating immune cells infiltration into the brain. Then activated adjacent glial cells–astrocytes and microglia, release massive amounts of chemokines. Prolonged inflammation loses its protective role and drives an increase in Aβ production and aggregation, impairment of its clearance, or enhancement of tau hyperphosphorylation, contributing to neuronal loss and exacerbation of AD. Moreover, chemokines can be further released in response to growing deposits of toxic forms of Aβ. On the other hand, chemokines seem to exert multidimensional effects on brain functioning, including regulation of neurogenesis and synaptic plasticity in regions responsible for memory and cognitive abilities. Therefore, underexpression or complete genetic ablation of some chemokines can worsen the course of AD. This review covers the current state of knowledge on the role of particular chemokines and their receptors in the development and progression of AD. Special emphasis is given to their impact on forming Aβ and NFTs in humans and in transgenic murine models of AD.
Unpacking the Addis Ababan Exceptionalism—Living and Making Sense of Violent Protests in Ethiopia’s Capital
Authors: Pellerin Camille Louise , Ashenafi Dalaya
Published: July 2022

Violent protests and ethno-communal violence in Ethiopia have been on the rise since 2015. Whilst the country’s capital has mostly been spared, protests have occurred in areas surrounding the capital, its suburbs and, to a lesser extent, even in its city centre. This article aims to answer how Addis Ababa residents make sense of and (dis)engage from/in violent protests and ethno-communal violence where they occur. The article explores the perceptions and experiences of established middle-class residents in the capital, drawing on ethnographic fieldwork conducted between June 2020 and May 2021. The article finds that, due to the city’s multi-ethnic character and the residents’ strong metropolitan identity, ethnic identity has not constituted a powerful tool for political mobilisation of residents within the capital. Claims based on ethnicity made by non-residents towards the capital’s resources have largely been rejected by Addis Ababans. Instead, residents have collectively defended their right to the city. The federal state’s readiness to intervene in protests in the capital has further discouraged and countered public protests and communal conflicts. The article reveals that, whilst ‘exceptional’ at the first glance, the peaceful normality of Addis Ababa has relied on ignoring conflicts within Ethiopia’s ethnic-based political settlement and has hidden ordinary, everyday forms of structural violence and conflict.
When (deliberate) practice is not enough – the role of intelligence, practice, and knowledge in academic performance
Authors: Bilalić Merim , Đokić Ratko , Koso-Drljević Maida , Đapo Nermin , Pollet Thomas
Published: July 2022

It is well established that academic performance (AP) depends on a number of factors, such as intellectual capacities, practice, and previous knowledge. We know little about how these factors interact as they are rarely measured simultaneously. Here we present mediated-Factors of Academic Performance (m-FAP) model, which simultaneously assesses direct and indirect, mediated, effects on AP. In a semester-long study with 118 first-year college students, we show that intelligence and working memory only indirectly influenced AP on a familiar, less challenging college course (Introduction to Psychology). Their influence was mediated through previous knowledge and self-regulated learning activities akin to deliberate practice. In a novel and more challenging course (Statistics in Psychology), intellectual capacities influenced performance both directly and indirectly through previous knowledge. The influence of deliberate practice, however, was considerably weaker in the novel course. The amount of time and effort that the students spent on the more difficult course could not offset the advantage of their more intelligent and more knowledgeable peers. The m–FAP model explains previous contradictory results by providing a framework for understanding the extent and limitations of individual factors in AP, which depend not only on each other, but also on the learning context.
Diagnosing COVID-19 using artificial intelligence: a comprehensive review
Authors: Khanna Varada Vivek , Chadaga Krishnaraj , Sampathila Niranjana , Prabhu Srikanth , Chadaga Rajagopala , Umakanth Shashikiran
Published: July 2022

In early March 2020, the World Health Organization (WHO) proclaimed the novel COVID-19 as a global pandemic. The coronavirus went on to be a life-threatening infection and is still wreaking havoc all around the globe. Though vaccines have been rolled out, a section of the population (the elderly and people with comorbidities) still succumb to this deadly illness. Hence, it is imperative to diagnose this infection early to prevent a potential severe prognosis. This contagious disease is usually diagnosed using a conventional technique called the Reverse Transcription Polymerase Chain Reaction (RT-PCR). However, this procedure leads to a number of wrong and false-negative results. Moreover, it might also not diagnose the newer variants of this mutating virus. Artificial Intelligence has been one of the most widely discussed topics in recent years. It is widely used to tackle various issues across multiple domains in the modern world. In this extensive review, the applications of Artificial Intelligence in the detection of coronavirus using modalities such as CT-Scans, X-rays, Cough sounds, MRIs, ultrasound and clinical markers are explored in depth. This review also provides data enthusiasts and the broader health community with a complete assessment of the current state-of-the-art approaches in diagnosing COVID-19. The key issues and future directions are also provided for upcoming researchers.
A new sixth-order Jarratt-type iterative method for systems of nonlinear equations
Authors: Yaseen Saima , Zafar Fiza
Published: July 2022

Many real-life problems using mathematical modeling can be reduced to scalar and system of nonlinear equations. In this paper, we develop a family of three-step sixth-order method for solving nonlinear equations by employing weight functions in the second and third step of the scheme. Furthermore, we extend this family to the multidimensional case preserving the same order of convergence. Moreover, we have made numerical comparisons with the efficient methods of this domain to verify the suitability of our method.
On the inter-critical inhomogeneous generalized Hartree equation
Authors: Saanouni Tarek , Alharbi Talal
Published: July 2022

It is the purpose of this work to study the Choquard equation $$\begin{aligned} i\dot{u}-(-\Delta )^s u=\pm |x|^{\gamma }(I_\alpha *|\cdot |^\gamma |u|^p)|u|^{p-2}u \end{aligned}$$

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in the space $$\dot{H}^s\cap \dot{H}^{s_c}$$

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, where $$0<s_c<s$$

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and the second one is the fractional regime $$0<s<1$$

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with radial data. One tries to develop a local theory using a new adapted sharp Gagliardo–Nirenberg estimate. Moreover, one investigates the concentration of non-global solutions in $$L^\infty _{T^*}(\dot{H}^{s_c})$$

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.
Cobalt telluride electrocatalyst for selective electroreduction of CO2 to value-added chemicals
Authors: Saxena Apurv , Singh Harish , Nath Manashi
Published: July 2022

Recent emphasis on carbon dioxide utilization has necessitated the exploration of different catalyst compositions other than copper-based systems that can significantly improve the activity and selectivity towards specific CO2 reduction products at low applied potential. In this study, a binary CoTe has been reported as an efficient electrocatalyst for CO2 reduction in aqueous medium under ambient conditions at neutral pH. CoTe showed high Faradaic efficiency and selectivity of 86.83 and 75%, respectively, for acetic acid at very low potential of − 0.25 V vs RHE. More intriguingly, C1 products like formic acid was formed preferentially at slightly higher applied potential achieving high formation rate of 547.24 μmol cm−2 h−1 at − 1.1 V vs RHE. CoTe showed better CO2RR activity when compared with Co3O4, which can be attributed to the enhanced electrochemical activity of the catalytically active transition metal center as well as improved intermediate adsorption on the catalyst surface. While reduced anion electronegativity and improved lattice covalency in tellurides enhance the electrochemical activity of Co, high d-electron density improves the intermediate CO adsorption on the catalyst site leading to CO2 reduction at lower applied potential and high selectivity for C2 products. CoTe also shows stable CO2RR catalytic activity for 50 h and low Tafel slope (50.3 mV dec–1) indicating faster reaction kinetics and robust functionality. Selective formation of value-added C2 products with low energy expense can make these catalysts potentially viable for integration with other CO2 capture technologies thereby, helping to close the carbon loop.
The minimal Hilbert basis of the Hammond order cone
Authors: Abul Naga Ramses H.
Published: July 2022

We characterize the minimal Hilbert basis of the Hammond order cone, and present several novel applications of the resulting basis. From the basis, we extract an invertible matrix, that provides a numerical representation of the Hammond order relation. The basis also enables the construction of a space—that we call the Hammond order lattice—where order-extensions of the Hammond order (i.e. more complete relations) may be derived. Finally, we introduce a class of maximal linearly independent Hilbert bases, in which the specific results derived in relation to the Hammond order cone, are shown to hold more generally.
Tribological behavior of thermal- and pH-sensitive microgels under steel/CoCrMo alloy contacts
Authors: Sun Kequn , Hu Yuanhua , Dong Yinghui , Yao Lulu , Song Ruhong , Xu Yufu
Published: July 2022

The tribological behavior of 316L stainless steel/CoCrMo alloy contacts under aqueous lubrication was investigated in this work. Three types of microgels including poly(N-isopropylacrylamide) (PNIPAM), polyacrylic acid (PAA), and poly(N-isopropylacrylamide-co-acrylic acid) (PNIPAM-co-PAA) were prepared and used as lubricant additives in aqueous solutions. Tribological tests were conducted using a ball-on-disk reciprocating tribometer, over a range of temperatures, pH, and concentrations of the microgels. The PNIPAM-co-PAA microgels were proven to have excellent anti-friction and anti-wear properties, depending on the temperature and pH values of the solutions. The maximum friction coefficient coincided with the lower critical solution temperature of the PNIPAM-co-PAA microgels at 32 °C. At the same time, the friction coefficient increased with the increase in pH value of the lubricant solution with the PNIPAM-co-PAA microgels. The unique thermal- and pH-sensitive properties of the PNIPAM-co-PAA microgels provided a new strategy for controlling the friction and wear of steel/CoCrMo alloy contacts under aqueous lubrication.
Der Biomarker „eosinophiles kationisches Protein“ (ECP)
Authors: Oremek G. M. , Passek K. , Braun M. , von der Eltz V. , Droege J.
Published: July 2022

Die vorliegende Übersicht zum Biomarker „eosinophiles kationisches Protein“ wird im Rahmen der Serie „Biomarker“ des Zentralblatts für Arbeitsmedizin, Arbeitsschutz und Ergonomie publiziert, die sich mit dem immer häufigeren Gebrauch der Bestimmung von spezifischen Markern bei sog. Manager-Vorsorgen und Check-up-Untersuchungen beschäftigt. Das eosinophile kationische Protein eignet sich grundsätzlich nicht für solche Vorsorgen, sondern ist ein Marker zur Therapieplanung und zum Therapiemonitoring von Asthma. Hier zeigt dieser eine hohe Sensitivität und Spezifität, wobei der Marker aber auf keinen Fall als Screeningparameter zur Frühdiagnostik eingesetzt werden soll.
Mediation roles of pedagogical approaches and personality traits in entrepreneurial curriculum design and entrepreneurial intention nexus
Authors: Nunfam Victor Fannam , Afrifa-Yamoah Ebenezer , Asitik Akanganngang Joseph
Published: July 2022

Planned behaviour theory was used in a path analysis modelling to investigate the serial mediation role of teaching methods and personality traits (locus of control, need for achievement and entrepreneurial attitude) in the relationship between entrepreneurship curriculum and entrepreneurial intention among university students in Ghana. A proposed 40-item instrument was used to measure outcomes for six constructs (3 personality trait constructs, entrepreneurship curriculum, teaching methods and entrepreneurial intention) for 324 participants. Acceptable convergent, divergent and construct validity scores were observed for the instrument. Teaching methods fully mediated the first-order relationships between entrepreneurial curriculum and each personality traits. The three constructs of personality traits parallelly mediated the second-order relationship between teaching methods and entrepreneurial intention. Teaching methods and each personality trait serially mediated the relationship between entrepreneurial curriculum and entrepreneurial intention. This empirical evidence provides insight into the design of pragmatic interventions by major stakeholders including entrepreneurship educators to inspire students into start-up activities
Citizenship Practices of Chinese Students on an Australian Campus: a Case Study
Authors: Fu Jun , Li Meiyi
Published: July 2022

This paper explores the citizenship practices of a group of Chinese international students through their engagement with a language club at a university located in Melbourne, Australia. By considering the practices associated with their mutual engagement in this club, the paper scrutinises how these students creatively carve out space to practise citizenships in ways that are meaningful in their lives. The results show that the club was constructed by its members as an intermediary space for Chinese international students to maintain connection with their own ethnic community and to engage with students from different language and cultural backgrounds. Through their engagement with this club, they practise a form of citizenship which is a hybrid of neoliberal citizenship, Chinese citizenship, and global citizenship. These citizenship practices are illustrative of the efforts made by international students to create conditions for citizenship practice, and they show the students’ capacity to mobilise cultural capital for practising meaningful citizenship and experiencing belonging in the host society. These citizenship practices have implications for higher education institutions and host societies to construct favourable conditions for international students’ citizenship practices and belonging.
Simple efficiency-distribution models of production, with an application to robotics
Authors: DeCanio Stephen J.
Published: July 2022

The “efficiency-distribution” model introduced by Houthakker in 1955 offers a flexible approach to production theory that does not require the measurement of capital and other fixed assets. Thus it avoids the theoretical problems associated with the Cambridge controversies and with Franklin Fisher’s critiques of aggregation. The efficiency distribution model can be empirically implemented using only observed productivity distributions and the share of output received by the non-fixed factors. Applications include estimating, for a variety of potential distributions, the vulnerability of human wages to the introduction of robotic substitutes.
Incidence of complicated appendicitis during the COVID-19 pandemic: A systematic review and meta-analysis
Authors: Kariya Abduljubbar , Krutsri Chonlada , Singhatas Pongsasit , Sumritpradit Preeda , Thampongsa Tharin , Lertsitthichai Panuwat , Phoprom Napaphat
Published: July 2022

ABSTRACT

Introduction:

Measures taken to prevent the spread of coronavirus disease 2019 (COVID-19) slow surgical processes, and patients are avoiding presenting at emergency departments during the outbreak because of fears of contracting the contagious disease. To analyze the rate of complicated appendicitis before and during the COVID-19 pandemic.

Methods:

We systematically reviewed the PubMed and SCOPUS databases for articles published from 2000 to 2021. Including the retrospective review data collected from our hospital of patients aged ≥18 years old who were diagnosed with acute appendicitis. The primary outcome of complicated appendicitis incidence was compared between before and during the COVID-19 pandemic period. We performed a meta-analysis using a random-effects model analysis.

Results:

A total 3559 patients were included for meta-analysis. The overall rate of complicated appendicitis was significantly higher during the pandemic (relative risk, 1.55; 95% confidence interval [CI], 1.26–1.89). The time from onset of symptoms to hospitalisation was 0.41 h longer during the pandemic, which was not significantly different (standardized mean difference, 0.41, 95% CI, −0.03 to 1.11). The operating time during the pandemic was significantly shorter than that before the pandemic (83.45 min and 71.65 min, p = 0.01).

Conclusion:

There are correlation between the pandemic and severity of acute appendicitis. The higher rate of complicated appendicitis in the pandemic indicates that patients require timely medical attention and appropriate treatment despite fears of contracting disease.

Highlights
Translational Science 22 conference proceedings
Authors: Pliakos Elina E. , Tague Laneisha K. , Poblete Roy E.
Published: July 2022

The Translational Science TS22 conference in Chicago in April 2022 was the first time post-pandemic that members of the Association of Clinical and Translational Science were able to meet up in person to share scientific advances. Given the remaining level of risk due to COVID-19, the meeting was designed as hybrid allowing virtual participation to some of the presentations. Prior to the meeting, JCTS Junior Editors were invited to report on the plenary sessions of the meeting. The present perspective constitutes a summary of three plenary sessions.
Combined laparoscopic and open colon surgery rankings fail to accurately rank hospitals by surgical-site infection rate
Authors: Caroff Daniel A. , Chan Christina , Kleinman Ken , Calderwood Michael S. , Wolf Robert , Platt Richard , Huang Susan S.
Published: July 2022

Objective:

To compare strategies for hospital ranking based on colon surgical-site infection (SSI) rate by combining all colon procedures versus stratifying by surgical approach (ie, laparoscopic vs open).

Design:

Retrospective cohort study.

Methods:

We identified SSIs among Medicare beneficiaries undergoing colon surgery from 2009 through 2013 using previously validated methods. We created a risk prediction model for SSI using age, sex, race, comorbidities, surgical approach (laparoscopy vs open), and concomitant colon and noncolon procedures. Adjusted SSI rates were used to rank hospitals. Subanalyses were performed for common colon procedures and procedure types for which there were both open and laparoscopic procedures. We generated ranks using only open and only laparoscopic procedures, overall and for each subanalysis. Rankings were compared using a Spearman correlation coefficient.

Results:

In total, 694,813 colon procedures were identified among 508,135 Medicare beneficiaries. The overall SSI rate was 7.6%. The laparoscopic approach was associated with lower SSI risk (OR, 0.5; 95% CI, 0.4–0.5), and higher SSI risk was associated with concomitant abdominal surgeries (OR, 1.4; 95% CI, 1.4–1.5) and higher Elixhauser score (OR, 1.1; 95% CI, 1.0–1.1). Hospital rankings for laparascopic procedures were poorly correlated with rankings for open procedures (r = 0.23).

Conclusions:

Hospital rankings based on total colon procedures fail to account for differences in SSI risk from laparoscopic vs open procedures. Stratifying rankings by surgical approach yields a more equitable comparison of surgical performance.
Early-Adulthood Economic Experiences and the Formation of Democratic Support
Authors: Krishnarajan Suthan , Doucette Jonathan , Andersen David
Published: July 2022

Do economic experiences early in life affect regime support later in life? Effects of recent economic performance on regime support are extensively studied, but lasting effects of individual-level economic experiences across the lifespan remain unexplored. We argue that in democracies and autocracies alike, economic experiences in early adulthood (that is, age eighteen to twenty-eight) are wired into people's memories and become important cues for their democratic support later in life. Having lived in a well-performing economy in a democracy increases democratic support throughout most of people's lives, whereas having lived in a well-performing economy in an autocracy decreases democratic support throughout most of people's lives. Using extensive survey data on support for democracy covering ninety-seven countries from 1994 to 2015, we find support for these propositions, demonstrating that economic experiences in early adulthood, conditional on the regime in place at the time, have strong, robust and lasting effects on democratic support.
Resilient tracking consensus over dynamic random graphs: A linear system approach
Authors: SHANG Y.
Published: July 2022

Cooperative coordination in multi-agent systems has been a topic of interest in networked control theory in recent years. In contrast to cooperative agents, Byzantine agents in a network are capable to manipulate their data arbitrarily and send bad messages to neighbors, causing serious network security issues. This paper is concerned with resilient tracking consensus over a time-varying random directed graph, which consists of cooperative agents, Byzantine agents and a single leader. The objective of resilient tracking consensus is the convergence of cooperative agents to the leader in the presence of those deleterious Byzantine agents. We assume that the number and identity of the Byzantine agents are not known to cooperative agents, and the communication edges in the graph are dynamically randomly evolving. Based upon linear system analysis and a martingale convergence theorem, we design a linear discrete-time protocol to ensure tracking consensus almost surely in a purely distributed manner. Some numerical examples are provided to verify our theoretical results.