bluuebunny/crossref_metadata_2025_split huggingface dataset:
Moving Beyond Uber
Authors: Kirchner Stefan , Dittmar Nele , Ziegler Emilia Sophie 
Published: May 2022

AbstractDiscussions on organizational models and work in the platform economy often center on Uber as a prominent example of a digital marketplace that relies on venture capital and gig labor from self-employed drivers. This focus on Uber underestimates the diversity of organizational models and work types that likely arise from struggles between firms seeking to dominate emerging fields. Our exploratory results coming out of the field of “shared mobility” in Germany show that the platform economy harbors two modes: a fewdigital marketplaceswithgig laborand manyapp-enabled firmsthat build on smartphones to operate their mobility services with employees that performapp-enabled labor. In addition, some firms that rely on venture capital face several firms financed by incumbents from adjacent fields—in particular, car manufacturing. Overall, we find an absorption of platform technology by incumbents alongside disruption induced by start-ups. We conclude that German shared mobility comprises a diversity of organizational models and work types beyond the Uber model, the mapping of which helps toward a better understanding of the platform economy.
The association of stress and physical activity: Mind the ecological fallacy
Authors: Reichert Markus , Brüßler Sarah , Reinhard Iris , Braun Urs , Giurgiu Marco , Hoell Andreas , Zipf Alexander , Meyer-Lindenberg Andreas , Tost Heike , Ebner-Priemer Ulrich W. 
Published: May 2022

AbstractPsychological stress and physical activity are interrelated, constituting a relevant association to human health, especially in children. However, the association’s nature remains elusive, i.e., why psychological stress predicts both decreased and increased physical activity. To test whether effects vary as a function of the level of analyses, we derived intensive longitudinal data via accelerometers and stress questionnaires from 74 children across 7 days as they went about their daily routines (n = 513 assessments). Multilevel modelling analyses revealed that between children, higher psychological stress predicted decreased physical activity (standardized beta coefficient = −0.14; p = 0.046). Concurrently, within those children, higher psychological stress predicted increased physical activity across days (standardized beta coefficient = 0.09; p = 0.015). Translated to practice, children who experienced more stress than others moved less, but children were more active on days when they experienced heightened stress. This suggests that the analyses level is crucial to the understanding of the association between psychological stress and physical activity and should be considered to receive unequivocal results. If replicated, e.g., including high-frequency sampling and experimental manipulation in everyday life for in-depth insights on underlying mechanisms and causality, our findings may be translated to individually tailored (digital) prevention and intervention strategies which target children’s distress-feelings despite impairing their heightened physical activity in stressful situations and identify tipping points of chronic stress phases. Therefore, we especially call for more intensive longitudinal data approaches to tackle thus far neglected within-subject issues in the field of physical activity, sport and exercise research.
Developing an optimal design model of furrow irrigation based on the minimum cost and maximum irrigation efficiency
Authors: Ostad-Ali-Askari Kaveh 
Published: May 2022

AbstractThe foremost aim of the channel irrigation is a suitable choice of preparation and decision-making flexibles. These flexibles are the channel length, current degree to the channel and cutoff period. These flexibles are calculated through optimization depending on diminishing the overall irrigation cost and maximizing the application competence of irrigation. The goal meaning has been shaped depending on costs of the water, employee and head channel and channel excavation. So, in the impartial purpose, an equation should be measured for calculating the water advance period in an indistinct and detailed way. Subsequently, none of the careful approaches applied for advance channel irrigation such as zero inactivity calculate the advance time overtly; therefore, in this investigation the Valiantzas equation has been applied which has been assumed from the consequences of the zero inertia prototypical. In the impartial purpose, in addition to the preparation flexibles, soil features, channel and net irrigation condition have been included. So, the project variables and irrigation competence can be calculated for each kind of soil and exact herbal. An example of this project has been existed in this investigation.
Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration
Authors: Elbeltagi Ahmed , Raza Ali , Hu Yongguang , Al-Ansari Nadhir , Kushwaha N. L. , Srivastava Aman , Kumar Vishwakarma Dinesh , Zubair Muhammad 
Published: May 2022

AbstractFor developing countries, scarcity of climatic data is the biggest challenge, and model development with limited meteorological input is of critical importance. In this study, five data intelligent and hybrid metaheuristic machine learning algorithms, namely additive regression (AR), AR-bagging, AR-random subspace (AR-RSS), AR-M5P, and AR-REPTree, were applied to predict monthly mean daily reference evapotranspiration (ET0). For this purpose, climatic data of two meteorological stations located in the semi-arid region of Pakistan were used from the period 1987 to 2016. The climatic dataset includes maximum and minimum temperature (Tmax, Tmin), average relative humidity (RHavg), average wind speed (Ux), and sunshine hours (n). Sensitivity analysis through regression methods was applied to determine effective input climatic parameters for ET0 modeling. The results of performed regression analysis on all input parameters proved that Tmin, RHAvg, Ux, and n were identified as the most influential input parameters at the studied station. From the results, it was revealed that all the selected models predicted ET0 at both stations with greater precision. The AR-REPTree model was located furthest and the AR-M5P model was located nearest to the observed point based on the performing indices at both the selected meteorological stations. The study concluded that under the aforementioned methodological framework, the AR-M5P model can yield higher accuracy in predicting ET0 values, as compared to other selected algorithms.
Volume reduction of water samples to increase sensitivity for radioassay of lead contamination
Authors: Aguilar-Arevalo A. , Canet C. , Cruz-Pérez M. A. , Deisting A. , Dias A. , D’Olivo J. C. , Favela-Pérez F. , Garcés E. A. , González Muñoz A. , Guerra-Pulido J. O. , Mancera-Alejandrez J. , Marín-Lámbarri D. J. , Martinez Montero M. , Monroe J. R. , Paling S. , Peeters S. J. M. , Scovell P. R. , Türkoğlu C. , Vázquez-Jáuregui E. , Walding J. 
Published: May 2022

AbstractThe World Health Organisation (WHO) presents an upper limit for lead in drinking water of 10 parts per billion ppb. Typically, to reach this level of sensitivity, expensive metrology is required. To increase the sensitivity range of low-cost devices, this paper explores the prospects of using a volume reduction technique of a boiled water sample doped with Lead-210 ($${}^{210}$$

210

Pb), as a means to increase the solute’s concentration. $${}^{210}$$

210

Pb is a radioactive lead isotope and its concentration in a water sample can be measured with e.g. High Purity Germanium (HPGe) detectors at the Boulby Underground Germanium Suite. Concentrations close to the WHO limit have not been examined. This paper presents a measurement of the volume reduction technique retaining $$99\pm (9)$$

99
±
(
9
)

% of $${}^{210}$$

210

Pb starting from a concentration of $$1.9 \times 10^{-6}$$

1.9
×

10

-
6

ppb before reduction and resulting in $$2.63 \times 10^{-4}$$

2.63
×

10

-
4

ppb after reduction. This work also applies the volume reduction technique to London tap water and reports the radioassay results from gamma counting in HPGe detectors. Among other radio-isotopes, $${}^{40}$$

40

K, $${}^{210}$$

210

Pb, $${}^{131}$$

131

I and $${}^{177}$$

177

Lu were identified at measured concentrations of $$2.83 \times 10^{3}$$

2.83
×

10
3

ppb, $$2.55 \times 10^{-7}$$

2.55
×

10

-
7

ppb, $$5.06 \times 10^{-10}$$

5.06
×

10

-
10

ppb and $$5.84 \times 10^{-10}$$

5.84
×

10

-
10

ppb in the London tap water sample. This technique retained $${90 \pm 50}{\%}$$

90
±
50

%

of $${}^{40}$$

40

K. Stable lead was inferred from the same water sample at a measured concentration of 0.012 ppb, prior to reduction.
Efficient heavy metals and salts rejection using a novel modified polysulfone nanofiltration membrane
Authors: Gholami F. , Asadi A. , Zinatizadeh A. A. 
Published: May 2022

AbstractRecent research proclivity is about supplying water for drinking, urban and industrial applications which is recognized as one of the most significant challenges that threaten humanity. Giving its simplicity and high efficient yield, membrane technology has been preferred compared to other separation technologies for water and wastewater treatment. In the present research, KIT-6 (KIT: Korea Advanced Institute of Science and Technology) was functionalized by H-acid to improve hydrophilic functional groups on KIT-6 surface. Different characterization tests were performed to prove the insertion of H-acid on KIT-6 (H-KIT-6), e.g., FT-IR, XRD, zeta potential and FESEM analysis. Also, the effects of different loading of KIT-6 and H-KIT-6 on the morphology, characteristics and performance of Polysulfone (PSf) nanofiltration (NF) membranes were investigated. The maximum pure water flux (30.2 kg/m2 h), the lowest irreversible fouling ratio (3.96%) and the highest flux recovery ratio (96.04%) were obtained for the membrane embedded with 0.1 wt.% H-KIT-6 (optimum membrane). Also, the performance of the synthesized membranes was evaluated by rejection of four different salts (K2SO4, MgSO4, KCl and NaCl) and heavy metal ions (As3+ and Hg2+). The NF membrane embedded with 0.1 wt.% H-KIT-6 also presented the highest rejection of different salts and heavy metal ions (As3+ = 99.85% and Hg2+  = 99.27%) compared to the others. Finally, the performance of the optimum membrane to treat a real case of Gachsaran brackish water was assessed. As a result, by applying the optimum membrane, 565 mg/l, 28 mg/l and 27 mg/l of Ca2+, SO42− and Mg2+ were rejected, respectively.
Reservoir characterization analysis in glacial reservoirs
Authors: Al-Dawood Ahmed , Al-Shuhail Abdullatif 
Published: May 2022

AbstractThis research aims to characterize reservoir properties by applying rock physics and AVO analysis followed by pre-stack inversion. Two approaches are investigated: One approach addresses the case in which there are wells and seismic data, and the other addresses cases where only seismic data are available. The former approach is achieved by using well-log cross-plots for rock physics modeling to determine the feasibility and pay zone through gas fluid substitution followed by AVO analysis. Pre-stack inversion is then used to predict porosity and gas saturation. In the second approach, a synthetic seismogram is generated and compared to the observed seismic trace at the location of interest by forward modeling P-wave interval velocity and density. The best-matching P-wave velocity and density are subsequently used to generate synthetic well logs at the same location. Pre-stack inversion is then performed on these synthetic wells to predict porosity and gas saturation. Property prediction is performed by a feasibility study and pay zone calculation using rock physics modeling of the nearest well to the seismic block. Finally, the results of this case are validated using real wells. This new approach of reservoir characterization using synthetic wells is applied on reservoir channels and yielded a fairly good porosity prediction but a less accurate prediction of gas saturation.
MIRSIG position paper: the use of image registration and fusion algorithms in radiotherapy
Authors: Lowther Nicholas , Louwe Rob , Yuen Johnson , Hardcastle Nicholas , Yeo Adam , Jameson Michael ,   the Medical Image and Registration Special Interest Group (MIRSIG) of the ACPSEM
Published: May 2022

AbstractThe report of the American Association of Physicists in Medicine (AAPM) Task Group No. 132 published in 2017 reviewed rigid image registration and deformable image registration (DIR) approaches and solutions to provide recommendations for quality assurance and quality control of clinical image registration and fusion techniques in radiotherapy. However, that report did not include the use of DIR for advanced applications such as dose warping or warping of other matrices of interest. Considering that DIR warping tools are now readily available, discussions were hosted by the Medical Image Registration Special Interest Group (MIRSIG) of the Australasian College of Physical Scientists & Engineers in Medicine in 2018 to form a consensus on best practice guidelines. This position statement authored by MIRSIG endorses the recommendations of the report of AAPM task group 132 and expands on the best practice advice from the ‘Deforming to Best Practice’ MIRSIG publication to provide guidelines on the use of DIR for advanced applications.
Isolated Congenital Left Ventricular Diverticulum of the Fetal Heart in a Twin Pregnancy: Case Report and Literature Review
Authors: Binfadel Maha , Hrfi Abdah , Al Sehly Abdullah 
Published: May 2022

AbstractWe report a rare congenital heart disease in the form of isolated fetal left ventricular diverticulum in a spontaneous twin pregnancy, detected at 30 weeks of gestation. The diagnosis was confirmed postnatally with Echocardiography and Cardiac MRI. The case highlights the relevance of antenatal screening in detecting cardiac anomalies as early as possible to allow early postnatal work up and intervention if needed. The patient is currently 6 years old, and is followed regularly and is completely asymptomatic with no intervention required
Treatment with bortezomib for recurrent proliferative glomerulonephritis with monoclonal IgG deposits in kidney allograft. Case report and review of the literature
Authors: Oki Rikako , Unagami Kohei , Taneda Sekiko , Takagi Toshio , Ishida Hideki 
Published: May 2022

AbstractProliferative glomerulonephritis with monoclonal immunoglobulin IgG deposits (PGNMID) is an already described form of renal involvement by monoclonal gammopathy. PGNMID is known to recur in kidney allografts. Bortezomib has shown clinical success in the treatment of multiple myeloma. However, its effect for recurrent PGNMID in kidney allografts has rarely been reported. We present the case of a 61-year-old woman who developed recurrent PGNMID 3 weeks after kidney transplantation. This patient was initially treated with steroid pulses (500 mg/day for 2 days) and two cycles of rituximab therapy (200 mg/body). However, disease progression was observed with mesangial matrix expansion and subendothelial deposits by light microscopy and stronger staining for IgG3 and kappa in the mesangial area by Immunofluorescence (IF) microscopy. Thus, we started treatment with bortezomib therapy (1.3 mg/m2, once weekly, on days 1, 8, 15, and 22 in a 5-week cycle, for a total of six cycles). Bortezomib therapy reduced massive proteinuria, although monoclonal immune deposits on IF and the serum creatinine level did not change during the treatment period. Seven months after completion of the first bortezomib course, we decided to prescribe a second course of bortezomib with the same regimen. Each course resulted in a > 50% reduction of proteinuria. Bortezomib may delay the progress of PGNMID in kidney allograft patients.
Student achievement prediction using deep neural network from multi-source campus data
Authors: Li Xiaoyong , Zhang Yong , Cheng Huimin , Li Mengran , Yin Baocai 
Published: May 2022

AbstractFinding students at high risk of poor academic performance as early as possible plays an important role in improving education quality. To do so, most existing studies have used the traditional machine learning algorithms to predict students’ achievement based on their behavior data, from which behavior features are extracted manually thanks to expert experience and knowledge. However, owing to an increase in the varieties and overall volume of behavioral data, it has become more and more challenging to identify high-quality handcrafted features. In this paper, we propose an end-to-end deep learning model that automatically extracts features from students’ multi-source heterogeneous behavior data to predict academic performance. The key innovation of this model is that it uses long short-term memory networks to capture inherent time-series features for each type of behavior, and it takes two-dimensional convolutional networks to extract correlation features among different behaviors. We conducted experiments with four types of daily behavior data from students of the university in Beijing. The experimental results demonstrate that the proposed deep model method outperforms several machine learning algorithms.
The Equidistant Dimension of Graphs
Authors: González A. , Hernando C. , Mora M. 
Published: May 2022

AbstractA subset S of vertices of a connected graph G is a distance-equalizer set if for every two distinct vertices $$x, y \in V (G) {\setminus } S$$

x
,
y
∈
V
(
G
)
\
S

there is a vertex $$w \in S$$

w
∈
S

such that the distances from x and y to w are the same. The equidistant dimension of G is the minimum cardinality of a distance-equalizer set of G. This paper is devoted to introduce this parameter and explore its properties and applications to other mathematical problems, not necessarily in the context of graph theory. Concretely, we first establish some bounds concerning the order, the maximum degree, the clique number, and the independence number, and characterize all graphs attaining some extremal values. We then study the equidistant dimension of several families of graphs (complete and complete multipartite graphs, bistars, paths, cycles, and Johnson graphs), proving that, in the case of paths and cycles, this parameter is related to 3-AP-free sets. Subsequently, we show the usefulness of distance-equalizer sets for constructing doubly resolving sets.
A review of geometric dimensioning and tolerancing (GD&T) of additive manufacturing and powder bed fusion lattices
Authors: Pei Eujin , Kabir Israt , Breški Tomislav , Godec Damir , Nordin Axel 
Published: May 2022

AbstractTo increase industrial adoption, part qualification and certification of the additive manufacturing (AM) process are crucial through geometric benchmarking as well as optimising the properties and process parameters. However, an extensive research gap remains concerning the geometric dimensioning and tolerancing (GD&T) of AM parts. This paper presents a review on the state-of-art GD&T benchmarking of powder bed fusion techniques enabling complex geometrical features like lattices. The study found a lack of design guidelines and standardised measurement techniques for lattice features and profiles.
Einmal begeistert, immer begeistert? Eine Experience-Sampling Studie zur wahrgenommen Unterrichtsqualität und Motivation von Schülerinnen und Schülern im Kunstunterricht
Authors: Rakoczy Katrin , Frick Ulrich , Weiß-Wittstadt Susanne , Tallon Miles , Wagner Ernst 
Published: May 2022

ZusammenfassungZahlreiche Studien in der quantitativ-empirischen Unterrichtsforschung folgen zwar theoretisch der Angebots-Nutzungskonzeption unterrichtlicher Wirkungen, basieren jedoch auf retrospektiv erhobenen Unterrichtswahrnehmungen oder Beobachtungsdaten und können daher wenig Aussagen über das subjektive Erleben von Lernenden während des Unterrichts machen. Befunde zur intraindividuellen Varianz von wahrgenommener Unterrichtsqualität und Motivation im Unterricht sowie zu intraindividuellen Zusammenhängen würden helfen, unterrichtliche Wirkungen unter Angebots-Nutzungsperspektive noch besser zu verstehen. Dieses Desiderat aufgreifend wurden in vorliegender Studie Lernende mittels Experience-Sampling Methode zu mehreren Zeitpunkten im Verlauf zweier Doppelstunden Kunstunterricht zu ihrer Unterrichtsqualitätswahrnehmung und Motivation befragt. Darüber hinaus wurde die Erfüllung der Bedürfnisse nach Kompetenz und Autonomie als Indikatoren für die individuelle Nutzung des Angebots als potenzielle Mediatorvariablen erfragt. Auf Basis einer Stichprobe von 222 Lernenden aus 9 Klassen der 9. Jahrgangsstufe des Gymnasiums und der Integrierten Gesamtschule zeigten sich folgende Ergebnisse: 1) Der größte Teil der Varianz in den Einschätzungen aller Konstrukte der Lernenden lag zwischen den Zeitpunkten, gefolgt von der Varianz zwischen den Personen; zwischen den Klassen variierten die Einschätzungen kaum. 2) Es konnten charakteristische Verlaufsformen einiger erhobener Einschätzungen über die beiden Doppelstunden ermittelt werden. 3) Vor allem auf intraindividueller Ebene wurden neben direkten Effekten der Unterrichtswahrnehmungen auf die selbstbestimmte Motivation auch indirekte über die wahrgenommene Autonomieunterstützung sichtbar. Die Ergebnisse helfen zu verstehen, wie wahrgenommene Unterrichtsqualität, individuelle Nutzung (Erfüllung des Bedürfnisses nach Autonomie) und selbstbestimmte Motivation im Unterrichtsverlauf zusammenspielen und es wird diskutiert, welche weiterführenden Studien folgen sollten.
Evaluating Nursing Staff Perception of Hospital Readiness for Continuity of Essential Health Care Services and Surge Capacity in Line With COVID-19
Authors: Farghaly Abdelaliem Sally Mohammed , El Hessewi Ghada Moh Samir , Alsenany Samira Ahmed , Baghdadi Nadiah A. , Alkhaldi Sarah Ali Mabaouj 
Published: May 2022

Abstract

Objective:
To evaluate nursing staff’ perception of hospital readiness for continuity of essential health care services and surge capacity in line with COVID-19.

Methods:
A total of 300 nurses were recruited from one hospital in Saudi Arabia. They completed self-administered, online questionnaires. The questionnaire assessed participants’ socio-demographic data and their perceptions regarding hospital readiness for continuity of essential health care services and surge capacity in line with COVID-19.

Results:
The findings revealed that nursing staff had a moderate mean score regarding hospital readiness for continuity of health care services (3.89 ± 0.61) and an average mean value regarding surge capacity of 3.83 ± 0.63. Also, the value of R2 of surge capacity in healthcare can predict 82.9% of the variance in hospital readiness for continuity of health care services in terms of surge capacity.

Conclusion:
Hospital administrators could propose hospital regulations and protocols for the management of confirmed and suspected COVID-19 patients in addition to designing a continuing education program for health professionals at all levels related to prevention, control, and management of COVID-19 suspected and confirmed patients.