bluuebunny/crossref_metadata_2025 huggingface dataset:
Changing the Subject ofSati
Authors: Das Acevedo Deepa
Published: June 2020

Charan Shah's 1999 death was widely considered to be the first sati, or widow immolation, to have occurred in India in over twenty years. Media coverage of the event focused on procedural minutiae—her sari, her demeanor—and ultimately, several progressive commentators came to the counterintuitive conclusion that the ritually anomalous nature of Charan's death confirmed its voluntary, secular, and noncriminal nature. This article argues that the “unlabeling” of Charan's death, like those of other women between 1999 and 2006, reflects a tension between the nonindividuated, impervious model of personhood exemplified by sati and the particularized citizen‐subject of liberal‐democratic politics in India.
High temperatures modify plant responses to abiotic stress conditions
Authors: Balfagón Damián , Zandalinas Sara I. , Mittler Ron , Gómez‐Cadenas Aurelio
Published: June 2020

Climate change is altering environments in which plants and different crops grow and survive. We already experienced an increase in worldwide average earth surface temperatures, as well as frequency and extent of damaging heat waves. These conditions collide in the field with other abiotic stresses such as water deficit, high salinity, increased light irradiation, and so on, generating complex harmful conditions that destabilize agricultural systems. The conditions generated during these episodes of stress combination greatly differ from those occurring in the field when different stress factors occur individually; conditions that have been the focus of study for decades. Fortunately, knowledge of physiological and molecular responses to stress combinations and the cost they inflict on plant growth and yield has been exponentially increasing in the past several years. Understanding plant performance under multiple stress combinations will allow breeding crops capable of maintaining yield production under the new climatic conditions. Here, after reviewing recent data on physiological, hormonal and transcriptional responses to different stress combinations, we highlight the importance of photodamage avoidance, abscisic and jasmonic acid signaling, and the upregulation of genes involved in oxidation–reduction processes, photosynthesis and protein metabolism, for plant acclimation to conditions of high temperatures, in combination with other common abiotic stress factors such as drought or salinity. Finally, we propose new approaches to investigate the response of plants to stress combinations and discuss strategies for improving crop resilience to stress combination.
A Unified Data-Adaptive Framework for High Dimensional Change Point Detection
Authors: Liu Bin , Zhou Cheng , Zhang Xinsheng , Liu Yufeng
Published: June 2020

In recent years, change point detection for a high dimensional data sequence has become increasingly important in many scientific fields such as biology and finance. The existing literature develops a variety of methods designed for either a specified parameter (e.g. the mean or covariance) or a particular alternative pattern (sparse or dense), but not for both scenarios simultaneously. To overcome this limitation, we provide a general framework for developing tests that are suitable for a large class of parameters, and also adaptive to various alternative scenarios. In particular, by generalizing the classical cumulative sum statistic, we construct the U-statistic-based cumulative sum matrix C. Two cases corresponding to common or different change point locations across the components are considered. We then propose two types of individual test statistics by aggregating C on the basis of the adjusted Lp-norm with p ∈ {1, …, ∞}. Combining the corresponding individual tests, we construct two types of data-adaptive tests for the two cases, which are both powerful under various alternative patterns. A multiplier bootstrap method is introduced for approximating the proposed test statistics’ limiting distributions. With flexible dependence structure across co-ordinates and mild moment conditions, we show the optimality of our methods theoretically in terms of size and power by allowing the dimension d and the number of parameters q to be much larger than the sample size n. An R package called AdaptiveCpt is developed to implement our algorithms. Extensive simulation studies provide further support for our theory. An application to a comparative genomic hybridization data set also demonstrates the usefulness of our proposed methods.
Irradiated and CCl4‐treated bone marrow‐derived liver macrophages exhibit different gene expression patterns and phenotypes
Authors: Fan Xu , Shan Shan , Wu Peng , Lin Weiran , Jia Jidong , He Fuchu
Published: June 2020

Myeloid cells infiltrate into the liver and differentiate into macrophages in different liver injury mouse models. However, the heterogeneity of bone marrow (BM)‐derived LMs populations remains to be understood. To investigate this and understand the impact of the macrophage niche on the properties of recruited BM‐derived macrophages, we used a non‐myeloablation BM transplantation model to label and trace BM‐derived LMs. Subsequently, we quantified the number of embryonic‐derived liver‐resident macrophages, BM‐derived LMs and total LMs in CCl4 and irradiated acute liver injury mouse models, respectively. Finally, we compared the cell fate, gene expression patterns, chemokine signals, and surface markers of irradiated and CCl4‐treated BM‐derived LMs. We observed that, as compared to CCl4, radiation generated a macrophage niche by depleting embryonic‐derived liver‐resident macrophages and induced the recruitment of BM‐derived LMs that further settled in the liver. Irradiated and CCl4‐treated BM‐derived LMs are different with respect to their cell fates, gene expression patterns, and chemokine expression and recruitment. They also have different surface markers shortly after differentiating from their progenitors. Our findings suggest that irradiated and CCl4‐treated LM populations derived from the bone marrow display different patterns of gene expression and phenotypes; these differences may be due to the availability of macrophage niche.
Survival of Formula One Drivers
Authors: Celik Onur Burak
Published: June 2020

Objectives

To examine the determinants of the duration time of drivers in the Formula One (F1) competition, which is an industry with high physical capital investment and requires labor with very high human capital.

Methods

Since estimates may be biased when the whole F1 history, starting with the 1950 season, is considered, unlike prior studies in the literature, this article limits its data set to racing seasons from 1981 to 2017. In addition, since the failure times are correlated within the drivers with multiple spells, single‐spell methods used in prior studies underestimate true standard errors and produce inflated test statistics. Hence, the most appropriate approach for the duration analysis of F1 drivers would be the survival analysis for recurrent events, which is employed in this study.

Results

Once a driver exits F1, he survives for a shorter period of time if he returns. In order to survive longer, a driver has to perform better than his teammate. Each year of age decreases the probability of exit while drivers can increase their duration time in F1 by switching teams. Completing a race does not make any difference to survival but finishing a race on the podium lowers the probability of exit.

Conclusion

Team owners and managers should be cautious when they consider hiring a driver who exited F1 before. A driver should be at least better than his teammate in order to survive in F1. Drivers can also increase their chances of survival substantially by changing teams.
The African Growth and Opportunity Act and growth in sub‐Saharan Africa: A local projection approach
Authors: Cook Nathaniel P. S. , Jones Jason C.
Published: June 2020

The African Growth and Opportunity Act (AGOA) is intended to increase exports and economic growth in sub‐Saharan Africa by providing trade preferences to eligible countries. While previous research has generally found a positive relationship between AGOA and exports, no previous research has investigated the relationship between AGOA and economic growth. We explore the dynamic relationship between AGOA and economic growth in sub‐Saharan Africa by applying the local projection method (American Economic Review, 95, 2005 and 161) to estimate impulse responses. We find that a country's becoming eligible for AGOA preferences is associated with higher growth rates in the future, but that this effect may not be immediate, highlighting the importance of exploring the dynamic relationship between AGOA and growth.
Computing a categorical Gromov–Witten invariant
Authors: Căldăraru Andrei , Tu Junwu
Published: June 2020

We compute the $g=1$, $n=1$ B-model Gromov–Witten invariant of an elliptic curve $E$ directly from the derived category $\mathsf{D}_{\mathsf{coh}}^{b}(E)$. More precisely, we carry out the computation of the categorical Gromov–Witten invariant defined by Costello using as target a cyclic $\mathscr{A}_{\infty }$ model of $\mathsf{D}_{\mathsf{coh}}^{b}(E)$ described by Polishchuk. This is the first non-trivial computation of a positive-genus categorical Gromov–Witten invariant, and the result agrees with the prediction of mirror symmetry: it matches the classical (non-categorical) Gromov–Witten invariants of a symplectic 2-torus computed by Dijkgraaf.
Technique for comprehensive fetal hepatic blood flow assessment in sheep using 4D flow MRI
Authors: Schrauben Eric M. , Darby Jack R.T. , Saini Brahmdeep S. , Holman Stacey L. , Lock Mitchell C. , Perumal Sunthara R. , Seed Mike , Morrison Janna L. , Macgowan Christopher K.
Published: June 2020

Key points

The comprehensive visualization and quantification of in vivo fetal hepatic haemodynamics, particularly the shunting of ductus venosus blood, has been elusive and is not yet fully understood.

We introduce the combination of chronically instrumented fetal sheep and 4D flow MRI of the whole fetal liver, which allows retrospective blood flow measurement in all visible vessels as well as qualitative assessment.

The applicability and usefulness of this technique is exhibited in normally grown fetal Merino sheep in mid‐ and late‐gestation with detailed dynamic distribution of hepatic blood flow presented. The feasibility of this approach in clinical pathology is demonstrated in two growth‐restricted fetuses at mid‐gestation.

Further exemplification of blood flow quantification is performed over major hepatic vessels.

Although the fetal vasculature has been demarcated and well understood for several decades, the corresponding haemodynamics permitting oxygen‐ and nutrient‐rich blood delivery to the fetal organs has been comparatively difficult to study. We married two well‐established methods: 4D flow MRI, a volumetric and dynamic blood‐flow measurement technique, and chronically instrumented sheep to broadly assess fetal hepatic circulation. We performed this technique in mid‐ and late‐gestation fetal Merino sheep under normoxemic conditions and major hepatic vasculature was segmented to quantify blood flow and related parameters. Dynamic blood flow was visualized, exhibiting an acceleration of umbilical vein blood through the ductus venosus as well as spiralling into the inferior vena cava where its stream remained separate from that of the hepatic veins and lower body. Ductus venosus changes from mid‐ to late‐gestation included larger diameter (mid: 5.8 ± 0.9 vs. late: 7.1 ± 1.1 mm; P = 0.003) and cross‐sectional area (mid: 27.1 ± 8.6 vs. late: 40.4 ± 11.8 mm2; P = 0.003), and lower velocity averaged over the cardiac cycle (mid: 15.7 ± 5.4 vs. late: 9.8 ± 7.0 cm s‐1; P = 0.020). This resulted in higher magnitude blood flow (indexed to umbilical vein input) at mid‐gestation in the ductus venosus (mid: 0.73 ± 0.21; late: 0.46 ± 0.21; P = 0.008). The visualization and quantification results support the further use of this technique to better understand regional blood flow changes during normal or abnormal fetal growth, as well as to observe acute haemodynamic responses to physiological challenges or drug interventions.
Energy Harvesting for System of Coupled Oscillators Under External Excitation in the Vicinity of Resonance 1:1
Authors: Zuppa Leonardo Acho , Awrejcewicz Jan , Losyeva Nataliya , Puzyrov Volodymyr , Savchenko Nina
Published: June 2020

Vibration energy is abundantly present in many natural and artificial systems and can be assembled by various devices, mainly employing the benefits of the piezo-electric and electromagnetic phenomena. In the present article, the electromechanical system with two degrees-of-freedom is considered. An additional element (dynamical vibration absorber or DVA) is attached to the main mass, whose vibrations are to be reduced. The DVA consists of a spring, damping, and piezo-electric elements for energy harvesting. The goal is to reduce the maximal possible responses of the main structure at the vicinity of external 1:1 resonance and at the same time collect energy from the vibration of the system. An analytical approach is proposed to find the solution of the problem. We show that the piezo-electric element allows effective energy harvesting and at the same has a very limited influence on reducing the amplitude of oscillations of the main mass. The theoretical results are confirmed by numerical experiments.
A Novel Event-Triggered Active Model Predictive Control for Synchronization of Discrete-Time Chaotic Systems
Authors: Boruah Namita , Roy Binoy Krishna
Published: June 2020

In this paper, synchronization of two identical discrete-time chaotic systems is considered in networked control environment where communication plays a significant role along with the synchronization performance. A new event-triggered (ET) active model predictive control (MPC) technique is proposed in the presence of constraints. With the help of active control, a linear MPC is sufficient to control a chaotic system. The active controller is not present all the time, rather only activated when a triggering condition is fulfilled. The MPC also solves the optimization problem only when an event is triggered. A triggering condition is designed to ensure a required performance bound. This technique reduces the computational burden as well as the frequency of communication between sensors and controller and controller and actuator. The effectiveness of the proposed scheme is illustrated by two simulation examples. A trade-off analysis between network traffic and synchronization performance, and its dependence on the prediction horizon is done for the considered system. It reveals that an optimum trade-off can be achieved according to the desired requirement.
Does lymph node morphology using ultrasound reflect aetiology? A pictorial essay, part II, malignant lymphadenopathy
Authors: Trenker Corinna , Görg Christian , Hollerweger Alois , Jenssen Christian , Dong Yi , Cui Xin-Wu , Dietrich Christoph F
Published: June 2020

The evaluation of lymph nodes (LN) using ultrasound requires a high level of clinical and sonographic competence. This “pictorial essay” is intended to illustrate eye-catching examples of relevant “clinical-sonographic visual diagnoses” of LNs. We provide typical images and take home messages of eye-catching features to illustrate the featured publications.The first part included the introduction into the subject, indications for US examination and the widely accepted recognized features for LN characterization. The key features for the differential diagnosis of suspected lymphadenopathy and benign lymphadenopathy are illustrated. In the second part eye-catching features of malignant lymphadenopathy and the differential diagnosis of carcinoma and lymphoma are shown
An experimental study of trailing edge noise from a heaving airfoil
Authors: Zhou Teng , Zhang Xin , Zhong Siyang
Published: June 2020

In this study, the far-field noise and near-field flow properties from a heaving NACA 0012 airfoil at the Reynolds number of 6.6×104 were investigated experimentally in a 0.4 m2 anechoic wind tunnel. The airfoil had an incident angle of 0° and followed a sinusoidal heaving motion. The Strouhal number, controlled by changing the heaving frequency and amplitude, varied from 0.0024 to 0.008. The acoustic properties were measured by a free-field microphone placed at a distance of 1.2 m away from the tunnel central line, and the flow structures near the trailing edge were acquired using the particle image velocimetry. It was found that the heaving motion could reduce the sound pressure level (SPL) of the primary peak in the time-averaged spectra. The spectrograms obtained by the short-time Fourier transform revealed that the discrete tones were produced when the airfoil passed through the maximum heaving position. During the corresponding period, a sequence of large-scaled vortices convected on the airfoil surface was observed, and then was shed from the trailing edge to the wake region at the same frequency as the primary tone of the induced sound. With the increase of Strouhal number, the sound signals tended to be broadband, and the overall SPL was increased in the far field.
Socialization Experiences of First-Year Adapted Physical Education Teachers With a Master’s Degree
Authors: Holland Steven K. , Haegele Justin A.
Published: June 2020

The purpose of this study was to examine the meaning that first-year adapted physical education teachers with a master’s degree ascribed to their occupational socialization experiences. An interpretative phenomenological analysis research approach was used, and occupational socialization theory was adopted as the theoretical framework. Five teachers participated in this study. The sources of data were a semistructured focus group interview, semistructured one-to-one interviews, and reflective interview notes. Thematic development involved a three-step analysis process informed by the research approach. Three themes were constructed: (a) interactions with individuals with disabilities and activity experiences, (b) recruitment of adapted physical education teacher education students, and (c) graduate training and initial workplace experiences. The constructed themes provide unique insight into how teachers are socialized into adapted physical education and the meaning they ascribe to various socialization experiences, such as the limited impact that interactions with individuals with disabilities had on the decision to pursue this career.
Effect of Differential Training on Female Volleyball Spike-Jump Technique and Performance
Authors: Fuchs Philip X. , Fusco Andrea , Bell Jeffrey W. , von Duvillard Serge P. , Cortis Cristina , Wagner Herbert
Published: June 2020

Purpose:To determine the effect of in-season differential training on volleyball spike-jump technique and performance in elite-level female players.Methods:During the season, spike jumps of 12 elite female players (Austrian Volleyball League Women) were recorded by 13 Qualisys Oqus cameras (250 Hz) and an AMTI force plate (1000 Hz). First measurement was made at the beginning of the investigation. Two identical measurements were repeated after a first and a second interval. The first interval served as control phase. The second interval was comparable in length and regular program but included differential training (6 wk, 8 sessions of 15–20 min) as a modified warm-up. It addressed specific performance determinants. Analyses of variances were calculated for the 3 measurements and for the development during control and intervention phase.Results:Initial jump height (0.44 [0.09] m) changed by −4.5% during the control phase and +11.9% during the intervention (P < .001,). All approach variables, arm backswing, and velocity-conversion strategy improved compared with the control phase (Δ%: 6.1–51.2%,P < .05,). Joint angles, countermovement depth, maximal angular velocities, and torso incline were not affected (Δ%: −2.9–9.1%,P = .066–.969,).Conclusions:In-season differential training led to technical adaptations and increased spike-jump height in elite female players. The differential training program allowed players to experience a range of adaptability and to adjust toward an individual optimum in technical components of performance determinants. Coaches are encouraged to apply technical differential training to elite athletes and to target biomechanical performance factors specifically.
The COVID-19 pandemic and health inequalities
Authors: Bambra Clare , Riordan Ryan , Ford John , Matthews Fiona
Published: June 2020

This essay examines the implications of the COVID-19 pandemic for health inequalities. It outlines historical and contemporary evidence of inequalities in pandemics—drawing on international research into the Spanish influenza pandemic of 1918, the H1N1 outbreak of 2009 and the emerging international estimates of socio-economic, ethnic and geographical inequalities in COVID-19 infection and mortality rates. It then examines how these inequalities in COVID-19 are related to existing inequalities in chronic diseases and the social determinants of health, arguing that we are experiencing asyndemicpandemic. It then explores the potential consequences for health inequalities of the lockdown measures implemented internationally as a response to the COVID-19 pandemic, focusing on the likely unequal impacts of the economic crisis. The essay concludes by reflecting on the longer-term public health policy responses needed to ensure that the COVID-19 pandemic does not increase health inequalities for future generations.
Comparative effect of bovine buttermilk, whey, and lactoferrin on the innate immunity receptors and oxidative status of intestinal epithelial cells
Authors: Buey Berta , Bellés Andrea , Latorre Eva , Abad Inés , Pérez María Dolores , Grasa Laura , Mesonero José Emilio , Sánchez Lourdes
Published: June 2020

Milk contains bioactive molecules with important functions as defensive proteins; among them are the whey protein lactoferrin and proteins of the milk fat globule membrane (MFGM) present in buttermilk. The aim of this study has been to investigate the effects of lactoferrin, whey, and buttermilk as modulators of intestinal innate immunity and oxidative stress on intestinal epithelial cells, to evaluate its potential use for the development of functional foods. The mRNA expression levels of innate immune system Toll-like receptors (TLR2, TLR4, and TLR9), lipid peroxidation (malondialdehyde + 4-hydroxyalkenals) and protein expression levels of carbonyl were analyzed in enterocyte-like Caco-2/TC7 cells treated for 24 h with different concentrations of lactoferrin, whey, or buttermilk. None of the substances analyzed caused oxidative damage; however, whey significantly decreased the levels of lipid peroxidation. Furthermore, both lactoferrin and whey reduced the oxidative stress induced by lipopolysaccharide. With respect to TLR receptors, lactoferrin, whey, and buttermilk specifically altered the expression of TLR2, TLR4, and TLR9 receptors, with a strong decrease in the expression levels of TLR4. These results suggest that lactoferrin, whey, and buttermilk are potentially interesting ingredients for functional foods because they seem to modulate oxidative stress and the inflammatory response induced by the activation of TLRs.
Iron line reverberation mapping in Ghasemi-Nodehi–Bambi background
Authors: Ghasemi-Nodehi M.
Published: June 2020

The reverberation associated with the iron line is the time lag between direct photons from the corona and the photons reflected from the disk. The resulting line spectrum is called the 2D transfer function. The shape of the 2D transfer function is determined by the geometry of spacetime and the properties of BH. In a paper (Ghasemi-Nodehi and Bambi in EPJC 76:290, 2016), the authors have proposed a parametrization. This parametrization is aimed to test the Kerr nature of astrophysical black hole candidates. In this paper, I provide a reverberation mapping of the Ghasemi-Nodehi–Bambi metric in order to constrain the parameter of spacetime. All parameters can be constrained with the exception of$$b_{11}$$b11. The parameter$$b_4$$b4is harder to constrain too.
Enhancing sensitivity to non-standard neutrino interactions at INO combining muon and hadron information
Authors: Khatun Amina , Chatterjee Sabya Sachi , Thakore Tarak , Agarwalla Sanjib Kumar
Published: June 2020

In this paper, we explore the impact of flavor violating neutral current non-standard interaction (NSI) parameter $$\varepsilon _{\mu \tau }$$εμτ in the oscillation of atmospheric neutrinos and antineutrinos separately using the 50 kt magnetized ICAL detector at INO. We find that due to non-zero $$\varepsilon _{\mu \tau }$$εμτ, $$\nu _\mu \rightarrow \nu _\mu $$νμ→νμ and $${\bar{\nu }}_\mu \rightarrow {\bar{\nu }}_\mu $$ν¯μ→ν¯μ transition probabilities get modified substantially at higher energies and longer baselines, where vacuum oscillation dominates. We demonstrate for the first time that by adding the hadron energy information along with the muon energy and muon direction in each event, the sensitivity of ICAL to the NSI parameter $$\varepsilon _{\mu \tau }$$εμτ can be enhanced significantly. The most optimistic bound on $$\varepsilon _{\mu \tau }$$εμτ that we obtain is $$-\,\,0.01< \varepsilon _{\mu \tau } < 0.01 $$-0.01<εμτ<0.01 at 90$$\%$$% C.L. using 500 kt$$\cdot $$·yr exposure and considering $$E_\mu $$Eμ, $$\cos \theta _\mu $$cosθμ, and $$E'_{\mathrm{had}}$$Ehad′ as observables in their ranges of [1, 21] GeV, [−  1, 1], and [0, 25] GeV, respectively. We discuss for the first time the importance of the charge identification capability of the ICAL detector to have better constraints on $$\varepsilon _{\mu \tau }$$εμτ. We also study the impact of non-zero $$\varepsilon _{\mu \tau }$$εμτ on mass hierarchy determination and precision measurement of oscillation parameters.
On the enumeration and asymptotic growth of free quasigroup words
Authors: Smith Jonathan D. H. , Wang Stefanie G.
Published: June 2020

This paper counts the number of reduced quasigroup words of a particular length in a certain number of generators. Taking account of the relationship with the Catalan numbers, counting words in a free magma, we introduce the term peri-Catalan number for the free quasigroup word counts. The main result of this paper is an exact recursive formula for the peri-Catalan numbers, structured by the Euclidean Algorithm. The Euclidean Algorithm structure does not readily lend itself to standard techniques of asymptotic analysis. However, conjectures for the asymptotic behavior of the peri-Catalan numbers, substantiated by numerical data, are presented. A remarkable aspect of the observed asymptotic behavior is the so-called asymptotic irrelevance of quasigroup identities, whereby cancelation resulting from quasigroup identities has a negligible effect on the asymptotic behavior of the peri-Catalan numbers for long words in a large number of generators.
Specializing trees and answer to a question of Williams
Authors: Golshani Mohammad , Shelah Saharon
Published: June 2020

We show that if [Formula: see text] then any nontrivial [Formula: see text]-closed forcing notion of size [Formula: see text] is forcing equivalent to [Formula: see text] the Cohen forcing for adding a new Cohen subset of [Formula: see text] We also produce, relative to the existence of suitable large cardinals, a model of [Formula: see text] in which [Formula: see text] and all [Formula: see text]-closed forcing notion of size [Formula: see text] collapse [Formula: see text] and hence are forcing equivalent to [Formula: see text] These results answer a question of Scott Williams from 1978. We also extend a result of Todorcevic and Foreman–Magidor–Shelah by showing that it is consistent that every partial order which adds a new subset of [Formula: see text] collapses [Formula: see text] or [Formula: see text]
Iterative regularization method for an abstract ill-posed generalized elliptic equation
Authors: Roumaissa Sassane , Nadjib Boussetila , Faouzia Rebbani , Abderafik Benrabah
Published: June 2020

A preconditioning version of the Kozlov–Maz’ya iteration method for the stable identification of missing boundary data is presented for an ill-posed problem governed by generalized elliptic equations. The ill-posed data identification problem is reformulated as a sequence of well-posed fractional elliptic equations in infinite domain. Moreover, some convergence results are established. Finally, numerical results are included showing the accuracy and efficiency of the proposed method.
Anatomy of Metadata for Data Curation
Authors: Visengeriyeva Larysa , Abedjan Ziawasch
Published: June 2020

Real-world datasets often suffer from various data quality problems. Several data cleaning solutions have been proposed so far. However, data cleaning remains a manual and iterative task that requires domain and technical expertise. Exploiting metadata promises to improve the tedious process of data preparation, because data errors are detectable through metadata. This article investigates the intrinsic connection between metadata and data errors. In this work, we establish a mapping that reflects the connection between data quality issues and extractable metadata using qualitative and quantitative techniques. Additionally, we present a taxonomy based on a closed grammar that covers all existing metadata and allows the composition of novel types of metadata. We provide a case-study to show the practical application of the grammar for generating new metadata for data quality assessment.
Tell Me About Yourself
Authors: Xiao Ziang , Zhou Michelle X. , Liao Q. Vera , Mark Gloria , Chi Changyan , Chen Wenxi , Yang Huahai
Published: June 2020

The rise of increasingly more powerful chatbots offers a new way to collect information through conversational surveys, where a chatbot asks open-ended questions, interprets a user’s free-text responses, and probes answers whenever needed. To investigate the effectiveness and limitations of such a chatbot in conducting surveys, we conducted a field study involving about 600 participants. In this study with mostly open-ended questions, half of the participants took a typical online survey on Qualtrics and the other half interacted with an AI-powered chatbot to complete a conversational survey. Our detailed analysis of over 5,200 free-text responses revealed that the chatbot drove a significantly higher level of participant engagement and elicited significantly better quality responses measured by Gricean Maxims in terms of their informativeness, relevance, specificity, and clarity. Based on our results, we discuss design implications for creating AI-powered chatbots to conduct effective surveys and beyond.
Ordinary User Experiences at Work
Authors: Clemmensen Torkil , Hertzum Morten , Abdelnour-Nocera Jose
Published: June 2020

We investigate professional greenhouse growers’ user experience (UX) when using climate-management systems in their daily work. We build on the literature on UX, in particular UX at work, and extend it to
ordinary UX at work
. In a 10-day diary study, we collected data with a general UX instrument (AttrakDiff), a domain-specific instrument, and interviews. We find that AttrakDiff is valid at work; its three-factor structure of pragmatic quality (PQ), hedonic identification quality, and hedonic stimulation quality is recognizable in the growers’ responses. In this article, UX at work is understood as interactions among technology, tasks, structure, and actors. Our data support the recent proposal for the ordinariness of UX at work. We find that during continued use, UX at work is middle-of-the-scale, remains largely constant over time, and varies little across use situations. For example, the largest slope of the four AttrakDiff constructs when regressed over the 10 days was as small as 0.04. The findings contrast existing assumptions and findings in UX research, which is mainly about extraordinary and positive experiences. In this way, the present study contributes to UX research by calling attention to the mundane, unremarkable, and ordinary UXs at work.
Geosocial Co-Clustering
Authors: Kim Jungeun , Lee Jae-Gil , Lee Byung Suk , Liu Jiajun
Published: June 2020

As location-based services using mobile devices have become globally popular these days, social network analysis (especially, community detection) increasingly benefits from combining social relationships with geographic preferences. In this regard, this article addresses the emerging problem of geosocial community detection. We first formalize the problem of
geosocial co-clustering
, which co-clusters the users in social networks and the locations they visited. Geosocial co-clustering detects higher-quality communities than existing approaches by improving the
mapping clusterability
, whereby users in the same community tend to visit locations in the same region. While geosocial co-clustering is soundly formalized as
non-negative matrix tri-factorization
, conventional matrix tri-factorization algorithms suffer from a significant computational overhead when handling large-scale datasets. Thus, we also develop an efficient framework for geosocial co-clustering, called
GEOsocial COarsening and DEcomposition (GEOCODE)
. To achieve efficient matrix tri-factorization, GEOCODE reduces the numbers of users and locations through coarsening and then decomposes the single whole matrix tri-factorization into a set of multiple smaller sub-matrix tri-factorizations. Thorough experiments conducted using real-world geosocial networks show that GEOCODE reduces the elapsed time by 19–69 times while achieving the accuracy of up to 94.8% compared with the state-of-the-art co-clustering algorithm. Furthermore, the benefit of the mapping clusterability is clearly demonstrated through a local expert recommendation application.
CRSAL
Authors: Ren Xuhui , Yin Hongzhi , Chen Tong , Wang Hao , Hung Nguyen Quoc Viet , Huang Zi , Zhang Xiangliang
Published: June 2020

Recommender systems have been attracting much attention from both academia and industry because of their ability to capture user interests and generate personalized item recommendations. As the life pace in contemporary society speeds up, traditional recommender systems are inevitably limited by their disconnected interaction styles and low adaptivity to users’ evolving demands. Consequently, conversational recommender systems emerge as a prospective research area, where an intelligent dialogue agent is integrated with a recommender system. Conversational recommender systems possess the ability to accurately understand end-users’ intent or request and generate human-like dialogue responses when performing recommendations. However, existing conversational recommender systems only allow the systems to ask users for more preference information, while users’ further questions and concerns about the recommended items (e.g., enquiring the location of a recommended restaurant) can hardly be addressed. Though the recent task-oriented dialogue systems allow for two-way communications, they are not easy to train because of their high dependence on human guidance in terms of user intent recognition and system response generation. Hence, to enable two-way human-machine communications and tackle the challenges brought by manually crafted rules, we propose Conversational Recommender System with Adversarial Learning (CRSAL), a novel end-to-end system to tackle the task of conversational recommendation. In CRSAL, we innovatively design a fully statistical dialogue state tracker coupled with a neural policy agent to precisely capture each user’s intent from limited dialogue data and generate conversational recommendation actions. We further develop an adversarial Actor-Critic reinforcement learning approach to adaptively refine the quality of generated system actions, thus ensuring coherent human-like dialogue responses. Extensive experiments on two benchmark datasets fully demonstrate the superiority of CRSAL on conversational recommendation tasks.
Towards a Reliable Ground Truth for Drowsiness: A Complexity Analysis on the Example of Driver Fatigue
Authors: Kundinger Thomas , Mayr Celena , Riener Andreas
Published: June 2020

The increasing number and complexity of advanced driver assistance systems (ADAS) pave the way for fully automated driving. Automated vehicles are said to increase road safety and prevent human-made (fatal) accidents, amongst others. In the lower levels of automation, however, the driver is still responsible as a fallback authority. As a consequence, systems that reliably monitor the driver's state, especially the risk factor drowsiness, become increasingly essential to ensure the driver's ability to take over control from the vehicle on time. In research, the use of supervised machine learning for drowsiness detection is the prevalent method. As the ground truth for drowsiness is both application- and user-dependent, and no golden standard exists for its definition, measures are usually applied in the form of observer ratings. Also, in this work, observer ratings were investigated with regard to the required level of detail/complexity. To this end, video data, recorded within a simulator study (N = 30) comprised of each 45-minute manual and automated driving sessions, were evaluated by trained raters. Correlation analysis results show that - depending on the number of drowsiness levels - a comparable ground truth can be generated by reducing the rating frequency and thus the rating complexity by a factor of five. The knowledge gained can be used in future studies in this research area, the collection of a reliable and valid ground truth of drowsiness, as well as for improving the process in developing interactive drowsiness detection systems.
Reducing and eliminating e-waste
Authors: Kirkpatrick Keith
Published: June 2020

We need to mitigate the environmental impact of disposing of electronics at their end of useful life.
Axial Load Monitoring for Concrete Columns Using a Wearable Smart Hoop Based on the Piezoelectric Impedance Frequency Shift: A Feasibility Study
Authors: Liang Yabin , Ye Zhicheng , Feng Qian
Published: June 2020

Concrete columns are critical in supporting the weight of an entire structural frame and also play a key role in force transferring among structural members. Therefore, integrity of the columns, especially their axial load bearing capacity, directly affects the stability and safety of the entire structure. In this study, a wearable smart hoop is designed to monitor the axial load of the concrete columns. The smart hoop measures the shift in impedance frequency of its integrated piezoelectric transducer and correlates the frequency to the structural state of the column. In order to validate the feasibility of the smart hoop, an experiment on two concrete columns with different dimensions is carried out. The smart hoop is installed on each column. Then, an increasing axial load was applied onto the specimen, and the admittance of the PZT patch is acquired under different load levels by using an impedance analyzer. Finally, frequencies corresponding to the peak and trough in the susceptance of the admittance signal are collected as the monitoring index to estimate the axial load variation on the specimen. The experimental results demonstrated a downward shift in frequency corresponding to an increase of axial load. The results validate the feasibility of the wearable smart hoop in monitoring axial load for concrete columns and show potential for retrofit on existing columns.
Design Method and Verification of Electroosmosis‐Vacuum Preloading Method for Sand‐Interlayered Soft Foundation
Authors: Cui Yunliang , Tu Jianbo , Wang Xinquan , Diao Hongguo , Ge Qianru
Published: June 2020

The design method of electroosmosis‐vacuum preloading for soft foundation treatment is not systematic and complete, thereby restricting the application of the technology in engineering. A design method for the electroosmosis‐vacuum preloading treatment of sand‐interlayered soft foundation is therefore presented. A compressible electrical prefabricated vertical drain is developed, and a vacuum sealing and draining system is designed for the application of the electroosmosis‐vacuum preloading in sand‐interlayered soft foundation. Calculation formulas of site resistance considering the interlayer and interface resistivity of the electrode are established to design the power supply and electrical circuit. A simple numerical simulation method is proposed to predict the ground settlement treated by electroosmosis‐vacuum preloading. A field test of electroosmosis‐vacuum preloading is designed using the suggested method, and comparison tests between the electroosmosis‐vacuum preloading and the vacuum preloading are performed to verify the proposed technique. The test results show that the proposed design method is reasonable for the design of electroosmosis‐vacuum preloading in engineering.
Two-Dimensional Beampattern Synthesis for Polarized Smart Antenna Array and Its Sparse Array Optimization
Authors: Chen Zhikun , Li Tao , Peng Dongliang , Du Kang
Published: June 2020

Polarized smart antenna array has attracted considerable interest due to its capacity of matched reception or interference suppression for active sensing systems. Existing literature does not take full advantage of the combination of polarization isolation and smart antennas and only focuses on uniform linear array (ULA). In this paper, an innovative synthesis two-dimensional beampattern method with a null that has cross-polarization for polarized planar arrays is proposed in the first stage. This method aims to further enhance the capability of interference suppression whose optimization problem can be solved by second-order conic programming. In the second stage, a new sparse array-optimized method for the polarized antenna array is proposed to reduce the high cost caused by the planar array that is composed of polarized dipole antennas. Numerical examples are provided to demonstrate the advantages of the proposed approach over state-of-the-art methods.
A Robust Two-Machine Flow-Shop Scheduling Model with Scenario-Dependent Processing Times
Authors: Hsu Chia-Lun , Lin Win-Chin , Duan Lini , Liao Jan-Ray , Wu Chin-Chia , Chen Juin-Han
Published: June 2020

In many scheduling studies, researchers consider the processing times of jobs as constant numbers. This assumption sometimes is at odds with practical manufacturing process due to several sources of uncertainties arising from real-life situations. Examples are the changing working environments, machine breakdowns, tool quality variations and unavailability, and so on. In light of the phenomenon of scenario-dependent processing times existing in many applications, this paper proposes to incorporate scenario-dependent processing times into a two-machine flow-shop environment with the objective of minimizing the total completion time. The problem under consideration is never explored. To solve it, we first derive a lower bound and two optimality properties to enhance the searching efficiency of a branch-and-bound method. Then, we propose 12 simple heuristics and their corresponding counterparts improved by a pairwise interchange method. Furthermore, we set proposed 12 simple heuristics as the 12 initial seeds to design 12 variants of a cloud theory-based simulated annealing (CSA) algorithm. Finally, we conduct simulations and report the performances of the proposed branch-and-bound method, the 12 heuristics, and the 12 variants of CSA algorithm.
Leveraging Micro‐Level Building Information Modeling for Managing Sustainable Design: United Kingdom Experience
Authors: Liu Zhen , Wang Yifang , Osmani Mohamed , Demian Peter
Published: June 2020

Although the literature revealed the challenges and drivers to implement Building Information Modeling (BIM) in the building design industry in general, to date, there are few established methods and processes to overcome challenges of BIM adoption in building design, especially in sustainable building design for managing the project. At the present, BIM adoption in building design at micro level, that is, the level of architects, mainly focuses on barriers with little attention to method and the process of implementing BIM. Moreover, there is lack of a robust research method, that is, mixed method, to systematically investigate the process of implementing micro‐level BIM in building design, which is related to the factors, such as challenges and drivers to the challenges of BIM adoption. Furthermore, several studies have looked into micro‐level BIM adoption in architecture firms, but few of them focused on sustainable design. This emphasizes a need to investigate and explore micro‐level BIM implementation challenges alongside its drivers in building design and present methods and processes generated from architects’ perspectives to address the challenges during sustainable design for the project management, which is the aim of this paper. The research investigation was through a questionnaire that is followed by interviews with the leading architectural firms within the UK. The research reported in this paper is to present a clear view of challenges to micro‐level BIM adoption and a framework/road‐map to address the key challenges in managing sustainable building design projects, which are related to cultural resistance and culture change, top‐down management support, current key challenges and drivers, and client and project managers’ interests. The methods and processes that enhanced the framework can be instantly adopted for building design and for architectural companies including small‐ and medium‐sized enterprises (SMEs).
Computing Eccentricity-Based Topological Indices of 2-Power Interconnection Networks
Authors: Imran Muhammad , Iqbal Muhammad Azhar , Liu Yun , Baig Abdul Qudair , Khalid Waqas , Zaighum Muhammad Asad
Published: June 2020

In a connected graph G with a vertex v, the eccentricity εv of v is the distance between v and a vertex farthest from v in the graph G. Among eccentricity-based topological indices, the eccentric connectivity index, the total eccentricity index, and the Zagreb index are of vital importance. The eccentric connectivity index of G is defined by ξG = ∑v∈VGdvεv, where dv is the degree of the vertex v and εv is the eccentricity of v in G. The topological structure of an interconnected network can be modeled by using graph explanation as a tool. This fact has been universally accepted and used by computer scientists and engineers. More than that, practically, it has been shown that graph theory is a very powerful tool for designing and analyzing the topological structure of interconnection networks. The topological properties of the interconnection network have been computed by Hayat and Imran (2014), Haynes et al. (2002), and Imran et al. (2015). In this paper, we compute the close results for eccentricity-based topological indices such as the eccentric connectivity index, the total eccentricity index, and the first, second, and third Zagreb eccentricity index of a hypertree, sibling tree, and X-tree for k-level by using the edge partition method.