bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Satisficing Framework for Environmental Policy Under Model Uncertainty
Authors: Athanasoglou Stergios , Bosetti Valentina , Drouet Laurent 
Published: March 2021

AbstractWe propose a novel framework for the economic assessment of environmental policy. Our main point of departure from existing work is the adoption of a satisficing, as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different policies meet a set of goals at a specific future date instead of their performance vis-a-vis some intertemporal objective function. Consistent to the nature of environmental policymaking, our model takes explicit account of model uncertainty. To this end, the decision criterion we propose is an analog of the well-known success-probability criterion adapted to settings characterized by model uncertainty. We apply our criterion to the climate-change context and the probability distributions constructed by Drouet et al. (2015) linking carbon budgets to future consumption. Insights from computational geometry facilitate computations considerably and allow for the efficient application of the model in high-dimensional settings.
Optimistic Fiction as a Tool for Ethical Reflection in STEM
Authors: Hansen Kathryn Strong 
Published: March 2021

AbstractGreater emphasis on ethical issues is needed in science, technology, engineering, and mathematics (STEM) education. The fiction for specific purposes (FSP) approach, using optimistic science fiction texts, offers a way to focus on ethical reflection that capitalizes on role models rather than negative examples. This article discusses the benefits of using FSP in STEM education more broadly, and then explains how using optimistic fictions in particular encourages students to think in ethically constructive ways. Using examples of science fiction texts with hopeful perspectives, example discussion questions are given to model how to help keep students focused on the ethical issues in a text. Sample writing prompts to elicit ethical reflection are also provided as models of how to guide students to contemplate and analyze ethical issues that are important in their field of study. The article concludes that the use of optimistic fictions, framed through the lens of professional ethics guidelines and reinforced through ethical reflection, can help students to have beneficial ethical models.
Estimate of theoretical shear strength of C60 single crystal by nanoindentation
Authors: Dub Sergey N. , Haftaoglu Cetin , Kindrachuk Vitaliy M. 
Published: March 2021

AbstractThe onset of plasticity in a single crystal C60 fullerite was investigated by nanoindentation on the (111) crystallographic plane. The transition from elastic to plastic deformation in a contact was observed as pop-in events on loading curves. The respective resolved shear stresses were computed for the octahedral slip systems $$\langle{01}\overline{1}\rangle\left\{ {{111}} \right\}$$

⟨
01

1
¯

⟩

111

, supposing that their activation resulted in the onset of plasticity. A finite element analysis was applied, which reproduced the elastic loading until the first pop-in, using a realistic geometry of the Berkovich indenter blunt tip. The obtained estimate of the C60 theoretical shear strength was about $${1}/{11}$$

1
/
11

of the shear modulus on {111} planes.
Graphical abstract
Effect of melatonin/BMP-2 co-delivery scaffolds on the osteoclast activity
Authors: Jarrar Hala , Çetin Altındal Damla , Gümüşderelioğlu Menemşe 
Published: March 2021

AbstractBone morphogenetic protein two (BMP-2) has been widely used as an osteoinductive agent in the treatment of bone diseases. However, some side effects, such as osteoclast activation have emerged when it was used at high doses. In this study, by considering the osteoclast-suppressing capability of melatonin (MEL), its effect on osteoclast differentiation induced by BMP-2 was investigated. These two factors, MEL and BMP-2, were embedded into chitosan/hydroxyapatite (HAp) scaffolds that were characterized morphologically by scanning electron microscopy (SEM) and micro-computed tomography (μ-CT). Release profiles of MEL and BMP-2 from scaffolds were determined in vitro and then, the differentiation of RAW 264.7 cells to osteoclasts was investigated on the scaffolds. Results of tartrate-resistant acid phosphatase (TRAP) staining, SEM imaging and expression of cathepsin K gene showed that, in the presence of BMP-2, osteoclast differentiation increased, whereas it decreased in MEL and MEL/BMP-2 embedded scaffolds suggesting that melatonin successfully attenuated osteoclast differentiation induced by BMP-2. Thus, the MEL/BMP-2 loaded chitosan/HAp scaffolds that have dual function in enhancing bone formation and inhibiting osteoclast activity are recommended biomaterials in the field of bone regeneration.
Cystatin-like protein of sweet orange (CsinCPI-2) modulates pre-osteoblast differentiation via β-Catenin involvement
Authors: da Costa Fernandes Célio , Rodríguez Victor Manuel Ochoa , Soares-Costa Andrea , Cirelli Joni Augusto , Justino Daniela Morilha Neo , Roma Bárbara , Zambuzzi Willian Fernando , Faria Gisele 
Published: March 2021

AbstractPhytocystatins are endogenous cysteine-protease inhibitors present in plants. They are involved in initial germination rates and in plant defense mechanisms against phytopathogens. Recently, a new phytocystatin derived from sweet orange, CsinCPI-2, has been shown to inhibit the enzymatic activity of human cathepsins, presenting anti-inflammatory potential and pro-osteogenic effect in human dental pulp cells. The osteogenic potential of the CsinCPI-2 protein represents a new insight into plants cysteine proteases inhibitors and this effect needs to be better addressed. The aim of this study was to investigate the performance of pre-osteoblasts in response to CsinCPI-2, mainly focusing on cell adhesion, proliferation and differentiation mechanisms. Together our data show that in the first hours of treatment, protein in CsinCPI-2 promotes an increase in the expression of adhesion markers, which decrease after 24 h, leading to the activation of Kinase-dependent cyclines (CDKs) modulating the transition from G1 to S phases cell cycle. In addition, we saw that the increase in ERK may be associated with activation of the differentiation profile, also observed with an increase in the B-Catenin pathway and an increase in the expression of Runx2 in the group that received the treatment with CsinCPI-2.
Interactions between cover crops and soil microorganisms increase phosphorus availability in conservation agriculture
Authors: Hallama Moritz , Pekrun Carola , Pilz Stefan , Jarosch Klaus A. , Frąc Magdalena , Uksa Marie , Marhan Sven , Kandeler Ellen 
Published: March 2021

AbstractAimsAn essential task of agricultural systems is to improve internal phosphorus (P) recycling. Cover crops and tillage reduction can increase sustainability, but it is not known whether stimulation of the soil microbial community can increase the availability of soil organic P pools.MethodsIn a field experiment in southwest Germany, the effects of a winter cover crop mixture (vs. bare fallow) and no-till (vs. non-inversion tillage) on microbial P-cycling were assessed with soybean as the main crop. Microbial biomass, phospholipid fatty acids (PLFAs), P cycling enzymes, and carbon-substrate use capacity were linked for the first time with the lability of organic P pools measured by enzyme addition assays (using phosphodiesterase, non-phytase-phosphomonoesterase and fungal phytase).ResultsMicrobial phosphorus, phosphatase, and fatty acids increased under cover crops, indicating an enhanced potential for organic P cycling. Enzyme-stable organic P shifted towards enzyme-labile organic P pools. Effects of no-till were weaker, and a synergy with cover crops was not evident.ConclusionsIn this experiment, cover crops were able to increase the microbially mediated internal P cycling in a non-P-limited, temperate agroecosystems.
Simple method of selecting totalistic rules for pseudorandom number generator based on nonuniform cellular automaton
Authors: Szaban Miroslaw 
Published: March 2021

AbstractThis paper is devoted to selecting rules for one-dimensional (1D) totalistic cellular automaton (TCA). These rules are used for the generation of pseudorandom sequences, which could be useful in cryptography. The power of pseudorandom number generator (PRNG) based on nonuniform TCA can be improved using not only one rule but a large set of rules. For this purpose, each subset of rules should be analyzed with its assignation to cellular automaton (CA) cells should be analyzed. We examine each of the subsets of totalistic rules, consisting of rules with neighborhood radius equal to 1 and 2. The entropy of bitstreams generated by the nonuniform TCA points out the best set of rules appropriate for the TCA-based generator. The paper also presents the method of simple selection of CA rules based on a cryptographic criterion known as a balance. The proposed method selects a maximal size of the set of available CA rules for a given neighborhood radius and suitable for PRNG. The method guarantees to avoid conflicting assignments of rules resulting in the creation of unwanted stable bit sequences, and provides high-quality pseudorandom sequences. This technique is used to verify the subsets of rules selected experimentally. Verified rules are proposed for 1D TCA-based PRNG as a new subset of best nonuniform TCA rules. New picked, examined, and verified subset of rules could be used in TCA-based PRNG and provide cryptographically strong bit sequences and huge keyspace.
Frequency of flower visitors and achene production increase with rising population size in the self-incompatible herb Centaurea scabiosa (Asteraceae)
Authors: Abrahamczyk Stefan , Thielen Mirjam , Weigend Maximilian 
Published: March 2021

AbstractSelf-incompatible, non-clonal plant species are especially dependent on the activity of flower visitors for seed production. Therefore, populations of these plants are vulnerable to a reduced flower visitation rates, but also to increased isolation by extinction of local populations. To study how local populations ofCentaurea scabiosa, a self-incompatible, bee-pollinated herb species changed over time in the region of Bonn, we collected historical population records in the area and investigated their current status. We found that more than half of the subpopulations mentioned in the literature between 1950 and 2012 (38 of 65) have since disappeared. Small populations were most vulnerable, whereas medium to large populations increased in size. In a second step, we studied visitation frequencies and achene production and weight across 14 extant populations. We found that both flower visitation frequency and achene production were positively related to population size. Achene weight was neither related to the frequency of flower visitors nor to achene production. These results clearly indicate that reduced pollen transfer and lower pollination rates may contribute to local extinction in small populations ofCentaurea scabiosa. Overall our results call for an intensified monitoring of the populations of self-incompatible plant species.
Design and Implementation of Low-Cost Real-Time Energy Logger for Industrial and Home Applications
Authors: Khanna Pooja R. , Howells Gareth , Lazaridis Pavlos I. 
Published: March 2021

AbstractWith the significant increase in energy demands in the last decade, the issues of unnecessary energy usage have increased rapidly. Therefore, there is an immediate need to provide a cheap and easily accessible monitoring tool for the energy consumed by an appliance used in homes and industries. Instead of monitoring the total power consumption of the houses and/or industries, it is useful to monitor the power consumption of the individual appliance, which in turn, helps in saving the overall energy usage and thereby makes it cost-effective. This paper presents a cost-efficient design and implementation of a monitoring system that can precisely measure the current and voltage of each appliance. The design provides tracking of device activity in a real-time environment for the industries and helps in adopting to the green initiative. The design comprises of Arduino based micro-controller and Raspberry Pi, that performs precise measurements of current and voltage of the device, followed by measuring the power consumed by the device. This paper presents two different system designs, one for the single-phase measurements and the other for the DC measurements. The single-phase measurement device comprises of 10-bit ADC whereas, the 24 V DC measurement device comprises of a 12-bit ADC, which provides higher measurement accuracy compared to other systems available in the market. The implemented design uses the EmonCMS web application to accumulate and envision the monitored data. It provides a flexible and user-friendly solution to monitor the measured data easily on any android or iOS devices.
Inferring the Number of Attributes for the Exploratory DINA Model
Authors: Chen Yinghan , Liu Ying , Culpepper Steven Andrew , Chen Yuguo 
Published: March 2021

Diagnostic classification models (DCMs) are widely used for providing fine-grained classification of a multidimensional collection of discrete attributes. The application of DCMs requires the specification of the latent structure in what is known as the Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document} matrix. Expert-specified Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document} matrices might be biased and result in incorrect diagnostic classifications, so a critical issue is developing methods to estimate Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document} in order to infer the relationship between latent attributes and items. Existing exploratory methods for estimating Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document} must pre-specify the number of attributes, K. We present a Bayesian framework to jointly infer the number of attributes K and the elements of Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document}. We propose the crimp sampling algorithm to transit between different dimensions of K and estimate the underlying Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document} and model parameters while enforcing model identifiability constraints. We also adapt the Indian buffet process and reversible-jump Markov chain Monte Carlo methods to estimate Q\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$${\varvec{Q}}$$\end{document}. We report evidence that the crimp sampler performs the best among the three methods. We apply the developed methodology to two data sets and discuss the implications of the findings for future research.
Pupil Mental Health, Concerns and Expectations About Secondary School as Predictors of Adjustment Across the Transition to Secondary School: A Longitudinal Multi-informant Study
Authors: Rice Frances , Ng-Knight Terry , Riglin Lucy , Powell Victoria , Moore Graham F. , McManus I. Chris , Shelton Katherine H. , Frederickson Norah 
Published: March 2021

AbstractThe transition from primary to secondary schooling is challenging and involves a degree of apprehension. The extent to which pre-existing mental health difficulties, as well as pupil, parent, and teacher concerns and expectations about secondary school predict adaptation to secondary school, is unclear. In a three-wave, prospective longitudinal study, we examined associations between pre-transition concerns and expectations about moving to secondary school with mental health difficulties and demographic factors. We then evaluated whether these constructs predicted multiple indicators of adaptive pupil functioning at the end of the first year of secondary school (academic attainment, classmate behaviour rating, school liking and loneliness at school). We found children’s concerns reduced across the transition period. Concurrent associations were identified between both concerns about secondary school and lower parent and teacher expectations that children would settle in well at secondary school, with mental health difficulties and special educational needs. Investigating associations with multiple indicators of adaptive functioning at secondary school, multivariable regression analyses controlling for a range of baseline factors (e.g. special educational needs), found children’s concerns about secondary school to be specifically associated with loneliness. In contrast, children’s mental health difficulties and both parent and teacher expectations of how well children would settle into secondary school were associated with a wider range of indicators of adaptive functioning at secondary school. When examining all predictors simultaneously, primary school teacher expectations showed longitudinal association with a wide range of indicators of successful transition. These findings suggest that assessing primary school teacher expectations may be useful for monitoring and supporting pupils through this transition period and could usefully inform school-based interventions to support transition and mental health.
Three Responses to Anthropomorphism in Social Robotics: Towards a Critical, Relational, and Hermeneutic Approach
Authors: Coeckelbergh Mark 
Published: March 2021

AbstractBoth designers and users of social robots tend to anthropomorphize robots. Focusing on the question how to conceptualize the relation between robots and humans, this paper first outlines two opposite philosophical views regarding this relation, which are connected to various normative responses to anthropomorphism and anthropomorphization. Then it argues for a third view: navigating between what it calls “naïve instrumentalism” and “uncritical posthumanism”, it develops a hermeneutic, relational, and critical approach. Paradoxically, by unpacking the human dimension of robotics in its use and development, this view enables a critical discussion of anthropomorphizing robots. At the same time, and again somewhat paradoxically, it avoids a naïve instrumentalist position by taking robots’ role as an instrument in a larger con-technology seriously. As such, the third view questions the dualism assumed in the debate. The paper then explores what this means for the field of social robotics and the education of computer scientists and engineers. It proposes a reform based on a relational understanding of the field itself and offers suggestions for the role of users-citizens.
Expanding the etiologic spectrum of spastic ataxia syndrome: chronic infection with human T lymphotropic virus type 1
Authors: Edhom Karolina af , Lidman Christer , Granberg Tobias , Taylor Graham P. , Paucar Martin 
Published: March 2021

Abstract

Human T-lymphotropic virus type-1 (HTLV-1) is a neglected infection most often associated with an indolent process. However, a subset of HTLV-1 seropositive patients face the risk to develop life-threatening T-cell lymphoma/leukemia, or the highly disabling and incurable HTLV1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Over the years, other complications to HTLV-1 have been proposed and debated intensely. One of these, although rare, associations include cerebellar ataxia occurring most often in Japanese patients with manifest HAM/TSP. Here we present a HTLV-1 seropositive patient from the Middle East featuring a slowly progressive cerebellar syndrome with cerebellar atrophy but not evidence of spastic paraparesis. In addition, this patient suffered from autoimmune conditions such as Sjögren’s syndrome and vitiligo which are putatively associated with HTLV-1.
Performance Evaluation of Independent Component Analysis-Based Fault Detection Using Measurements Corrupted with Noise
Authors: Kini K. Ramakrishna , Madakyaru Muddu 
Published: March 2021

AbstractThe detection of sensor faults has proven to be easier through data-driven methods which rely on historical data collected from sensors that are placed at various locations in a process plant. Since the distribution of industrial process variables is random and non-Gaussian, the independent component analysis (ICA) method has been better suited for fault detection (FD) problems. Whenever data comes with any level of noise, there is difficulty in separating useful information, which hence degrades the monitoring quality of an FD strategy. In this paper, the robustness of FD strategies is assessed for different noise realizations of sensor data using stochastic simulations. The main objective of this work is to demonstrate that ICA-based FD strategies are more robust for different noise levels in comparison with principal component analysis (PCA). The ICA modeling algorithm is improved to avoid random initialization of a de-mixing orthogonal matrix during computation of independent components. Two case studies are considered for evaluating the robustness of FD strategies: a simulated quadruple tank process and a simulated distillation column process. Comparisons have been carried out between ICA, dynamic ICA, modified ICA and PCA strategies for different sensor noise levels. The simulation results reveal that ICA-based FD strategies over-perform PCA FD strategy in monitoring sensor faults for different levels of noise.