bluuebunny/crossref_metadata_2025_split huggingface dataset:
Open Experimental Data-Sets to Reveal Behavioural Insights of High-Deck Coach Evacuations
Authors: Huang Rong , Zhao Xuan , Yuan Yufei , Yu Qiang , Daamen Winnie 
Published: May 2022

AbstractNumerous evacuation performance data for the utilization in evacuation modelling and simulations have been established for the conventional/widely studied scenarios, such as building evacuation scenarios. However, such data are typically scarce for a new scenario in literature — evacuation from high-deck coaches. This paper fulfills this gap by presenting empirical high-deck coach evacuation data-sets that can be used for model configuration and validation. To this end, firstly, five essential and commonly used performance metrics, i.e., evacuation time, flow rate, alighting time gap, velocity on stairways and exit choice, were collected and derived from two series of controlled experiments with 7 and 22 runs that involved 44 and 96 participants respectively. Then, all these datasets were structured in the distribution form, based on which three critical behavioural insights are revealed regardless of the evacuation conditions (the types of high-deck coaches, lighting conditions, and age groups). First, the evacuation behaviour in normal (experimental) conditions conforms to a multi-stage pattern (a modified four-stage pattern, i.e., reaction, acceleration, fluctuation and saturation stages). Second, the instantaneous flow rate can be well captured by the Burr, Loglogistic and Lognormal distributions, and the alighting time gap can be represented by the Burr distribution. Third, more than 50% of passengers evacuate through the rear door in the front-and-rear-door evacuations. The frequency of choosing the front door is found to shift towards the direction of the rear door compared to the ideal results (based on the shortest distance calculation) with a magnitude of approximately 1.95 seat rows. The presented data-sets are valuable resources for the development of high-deck coach evacuation models. The empirical findings promote the understanding upon the evacuation behaviour of high-deck coach passengers.
Splittings in Subreducts of Hoops
Authors: Aglianò Paolo 
Published: May 2022

AbstractIn this paper we extend to various classes of subreducts of hoops some results about splitting algebras. In particular we prove that every finite chain in the purely implicational fragment of basic hoops is splitting and that every finite chain in the $$\{\wedge ,\rightarrow \}$$

{
∧
,
→
}

fragment of hoops is splitting. We also produce explicitly the splitting equations in most cases.
Higher levels of nonylphenol were found in human urine and drinking water from rural areas as compared to metropolitan regions of Wuhan, China
Authors: Xu Chunyan , Ling Haibo , Fan Chuangang , Xiang Luojing , Zhang Shu , Li Weiwei , Yi Chuan 
Published: May 2022

AbstractThe suspected endocrine disruptor nonylphenol (NP) is closely associated with anthropogenic activities; therefore, studies on this compound have been clustered in urban areas. This study investigated the NP concentrations in drinking water sources (n = 8), terminal tap water (n = 36), and human urine samples (n = 127) collected from urban and rural areas in Wuhan, China. The mean concentrations of NP measured in drinking water sources in urban and rural areas were 92.3 ± 7.5 and 11.0 ± 0.8 ng/L (mean ± SD), respectively, whereas the mean levels in urban and rural tap waters were 5.0 ± 0.7 and 44.2 ± 2.6 ng/L (mean ± SD), respectively. Nevertheless, NP was detected in 74.1% and 75.4% of the human urine samples from urban and rural participants, with geometric mean concentrations of 0.19 ng/mL (0.26 µg/g creat) and 0.27 ng/mL (0.46 µg/g creat), respectively. Although the NP concentrations measured in the drinking water sources of urban areas were significantly higher than those in rural areas (P < 0.05), the tap water and urine NP concentrations measured in urban areas were unexpectedly lower than those of rural areas (P < 0.05). Additionally, this investigation showed that the materials comprising household water supply pipelines and drinking water treatment processes in the two areas were also different. Our results indicated that the levels of exposure to NP in drinking water and human urine in rural areas were not necessarily lower than those in urban areas. Thus, particular attention should be paid to rural areas in future studies of NP.
A stochastic Asset Liability Management model for life insurance companies
Authors: Di Francesco Marco , Simonella Roberta 
Published: May 2022

Abstract
We build a stochastic Asset Liability Management (ALM) model for a life insurance company. Therefore, we deal with both an asset portfolio, made up of bonds, equity and cash, and a liability portfolio, comprising with-profit life insurance policies. We define a mortality model and a surrender model, as well as a new production model. First, with the purpose of ensuring the solvency of the company and the achievement of a competitive return, in the interest of both shareholders and policyholders, the insurer’s portfolio is periodically rebalanced according to the solution of a nonlinearly constrained optimization problem that aims to match asset and liability durations, subject to the attainment of a target return. In addition, several real-world constraints are imposed. When computing the company balance sheet projections, we consider not only future maturity and death payments, but also future surrender payments and all the cash flows due to new production, in order to obtain estimates that are as reliable as possible. The estimation of the timing and of the numbers of future surrenders and of future new policyholders requires the approximation of conditional expectations: To this end, we employ the least squares Monte Carlo technique. Secondly, for each bonds asset class and for equity asset class we propose a sectorial optimization problem with the aim of maximizing the expected value of a chosen utility function, subject to the results obtained from the first stage of portfolio rebalancing. Finally, we analyze a case study.
COVID-19 and bank performance in dual-banking countries: an empirical analysis
Authors: Alabbad Amal , Schertler Andrea 
Published: May 2022

AbstractWe explore how banks’ income and stock prices respond to the COVID-19 policy measures in countries with the dual-banking system, and whether Islamic banks over- or underperform compared to conventional banks. Applying two-way fixed-effect regressions, we document that the changes in Islamic banks’ finance income as well as net income decline as much during the COVID-19 pandemic as the changes in interest and net income of conventional banks. Event-study tests show that the stock prices of Islamic banks respond as negatively as the ones of conventional banks to workplace closures. We do, however, document that the two types of banks respond differently to income support schemes. The change in Islamic banks’ finance income and net income increase significantly more compared to that of their conventional peers when governments install income support initiatives. Also, Islamic banks’ stock prices respond more positively to the income support programs than the ones of conventional banks. Because we control for investment banking activities and services to large clients, our findings on the stronger response of Islamic banks to income support programs seem to result from Islamic banks’ focus on private customers who are supported during the pandemic. Overall, we conclude that theShariahcompliance does not limit the adverse impact of the COVID-19 crisis on Islamic banking, but that Islamic banks’ performance responds more positively to income support initiatives than the one of conventional banks.
Overview of the clinical efficacy and safety of eldecalcitol for the treatment of osteoporosis
Authors: Cui Lijia , Xia Weibo , Yu Chuan , Dong Shuangshuang , Pei Yu 
Published: May 2022

AbstractSummaryEldecalcitol (ELD) is a new oral analog of the active form of vitamin D with anti-resorptive properties. We conducted a meta-analysis to investigate the efficacy and safety of ELD in osteoporosis. Compared with alfacalcidol, ELD significantly lowered vertebral facture risk, increased bone mineral density, but also had a higher risk of hypercalciuria.PurposeThis study aimed to investigate the efficacy and safety of eldecalcitol (ELD) in osteoporosis by examining fracture rates, bone mineral density (BMD), bone turnover markers, and adverse events as outcomes.MethodsPubMed, EMBASE, and Cochrane Library were searched up to July 20, 2020, to identify eligible randomized controlled trials. The odds ratio (OR) or weighted mean difference (WMD) with 95% confidence interval was calculated by the random-effects model.ResultsELD significantly increased lumbar BMD (WMD: 2.80; 95% CI: 1.60, 4.00;P < 0.001, 2 studies involved), total hip BMD (WMD: 2.11; 95% CI: 0.68, 3.55;P = 0.004, 2 studies involved), and femoral neck BMD (WMD: 1.78; 95% CI: 0.76, 2.79;P = 0.001, 1 study involved) compared with alfacalcidol. Moreover, ELD caused a significantly lower rate of vertebral fracture (OR: 0.52; 95% CI: 0.29–0.95;P = 0.034, 2 studies involved) than alfacalcidol, but did not lower the rate of non-vertebral facture (OR: 0.44; 95% CI: 0.06–3.05;P = 0.405, 2 studies involved) compared with alfacalcidol. ELD significantly reduced the percentage change in bone-specific alkaline phosphatase (WMD: − 15.40; 95% CI: − 20.30, − 10.60;P < 0.001, 1 study involved) and serum type I collagen C-telopeptide (WMD: − 38.50; 95% CI: − 50.00, − 27.10;P < 0.001, 1 study involved) as compared with alfacalcidol. ELD was also associated with higher risk of hypercalciuria compared with alfacalcidol (OR: 1.64; 95% CI: 1.22, 2.20;P = 0.001, 2 studies involved).ConclusionsThis systematic review indicated that ELD was superior than alfacalcidol for improving vertebral fracture risk and BMD. Further large-scale trials should be conducted to verify the long-term effects and safety of ELD in osteoporosis.Prospero registration numberCRD42020147518.
Quantitative Microstructural Characterization of Precipitates and Oxide Inclusions in Inconel 625 Superalloy Additively Manufactured by L-PBF Method
Authors: Staroń S. , Dubiel B. , Gola K. , Kalemba-Rec I. , Gajewska M. , Pasiowiec H. , Wróbel R. , Leinenbach Ch. 
Published: May 2022

AbstractIn this study, we perform quantitative characterization of precipitates and oxide inclusions in Inconel 625 additively manufactured by the laser powder-bed fusion (L-PBF) process. The application of different microscopy techniques allowed us to characterize the microstructure at micro- and nano-scale in the as-built and stress-relieved condition and correlate the features of grains and cellular substructure with parameters of particles along the planes parallel and perpendicular to the build direction. The optimized imaging conditions and image analysis procedure allowed easily distinguishing precipitates and oxide inclusions and performing their quantitative analysis. The results showed that intercellular areas are the preferential sites of precipitation of the Laves phase and NbC carbides with diameters in the range of 10 to 440 nm. Moreover, aluminum oxide inclusions with diameters in the range of 30 to 300 nm are randomly distributed. Regardless of the processing conditions of the examined samples, the influence of the stress-relief annealing on the secondary phases was not observed. In both the as-built and stress-relieved samples, the size of precipitates is in submicrometer scale. The analysis provided detailed information about the parameters of particles depending on the orientation versus the build direction. It was demonstrated that despite the tendency for columnar grain morphology and the anisotropy of the cellular substructure, the particle distribution is almost uniform throughout the volume of the additively manufactured L-PBF Inconel 625.Graphical Abstract
Preparation of Ceramic Foam Filters With a Lithium-Containing Surface
Authors: Voigt Claudia , Schramm Alina , Fankhänel Beate , Schmid Ekaterina , Malczyk Piotr , Hubálková Jana , Stelter Michael , Charitos Alexandros , Aneziris Christos G. 
Published: May 2022

Abstract
Hydrogen in aluminum causes the formation of detrimental hydrogen porosity in castings. In order to reduce the formation of hydrogen pores, an approach was targeted using lithium as target for hydrogen. This approach utilizes the affinity of lithium for hydrogen, whereby spodumene (a lithium aluminum silicate) and lithium aluminate were used as lithium providers. Within the scope of this study, the preparation of ceramic foam filters with a coating of lithium-containing raw materials (spodumene) was investigated. Those investigations revealed that the spodumene coating has a detrimental influence on the bending strength of the foams when a certain level of spodumene is exceeded. This observation might be explainable by the intrusion of the spodumene into the alumina matrix of the skeleton foam. Two wetting tests at different temperatures were conducted, verifying the significant influence of the temperature on the reaction between the spodumene and AlSi7Mg. Furthermore, test filters coated with raw materials exhibiting different amounts of lithium were conducted. The hydrogen pores were evaluated by light microscopy and computed tomography. The analyzed pore size distribution in the aluminum did not elucidate the proximate influence of the lithium-coating on the ceramic foam filter on the hydrogen porosity in the aluminum.
Electron Beam-Induced Modifications in Dielectric and AC Electrical Properties of Gelatin-Acrylic Acid Blends
Authors: Radwan S. I. , Shehata M. M. , Abdel Samad S. , El-Khabeary H. 
Published: May 2022

AbstractThe main aim of this work is to investigate the dielectric and electrical properties of synthesized acrylic acid–gelatin blends of different acrylic acid weight concentrations with gelatin. An electron beam (EB) with different doses of 50–150 kGy irradiated the synthesized blend while it was also subjected to an applied electric field in the range of 70 Hz–5 MHz to determine the variation in the dielectric parameters and electrical conductivity. The lowest kHz gives the highest dielectric parameters and lowest AC electrical conductivity (σac) values for both the blank and EB-irradiated blends. The lowest dielectric parameters and σac values were at 0.4 g acrylic acid concentration, and the highest values were for the 0.2 g acrylic acid concentration. Comparing the different EB doses for each acrylic acid concentration, it was found that the order of the lowest dielectric constant, έ, was 0.579 for (0.2 g + 100 kGy) > 0.475 for (0.6 g + 50 kGy) > 0.412 for (1 g + 50 kGy) > 0.315 for (0.4 g + 100 kGy) at 0.5 kHz. However, the order of the highest σac was 1.71 × 10−4 S/m for (0.2 g + 150 kGy) > 1.39 × 10−4 S/m for (0.6 g + 75 kGy) > 1.08 × 10−4 S/m for (1 g + 75 kGy) > 8.56 × 10−5 S/m for (0.4 g + 150 kGy) at 5 MHz. A modified equation was deduced for the AC conductivity as a function of the frequency of the applied field and the concentration of acrylic acid mixed with gelatin at room temperature.
Corporate lobbying and product recalls: an investigation in the U.S. medical device industry
Authors: Giannetti Verdiana , Srinivasan Raji 
Published: May 2022

AbstractWhile corporate political activity is increasing, its effects on firms’ marketing-relevant outcomes have been largely overlooked in the literature. We propose that corporate lobbying will decrease a firm’s emphasis on product safety and, in turn, increase its product recalls. We further propose that the positive indirect effect of corporate lobbying on a firm’s product recalls via lower emphasis on product safety will be moderated by the firm’s (a) CEO’s functional background and (b) focus on radical (vs. incremental) innovation. We provide empirical support for the proposed model using data on 86 U.S. medical device firms from 2005–2018. The findings extend the literature on the effects of non-market forces on firms’ marketing-relevant outcomes. They also extend the literature on the antecedents of product recalls, which has, hitherto, overlooked the role of non-market forces. The findings on the moderating roles of the firm’s marketing CEO and focus on radical (vs. incremental) innovation generate actionable managerial implications.
Modern Learning from Big Data in Critical Care: Primum Non Nocere
Authors: Gravesteijn Benjamin Y. , Steyerberg Ewout W. , Lingsma Hester F. 
Published: May 2022

AbstractLarge and complex data sets are increasingly available for research in critical care. To analyze these data, researchers use techniques commonly referred to as statistical learning or machine learning (ML). The latter is known for large successes in the field of diagnostics, for example, by identification of radiological anomalies. In other research areas, such as clustering and prediction studies, there is more discussion regarding the benefit and efficiency of ML techniques compared with statistical learning. In this viewpoint, we aim to explain commonly used statistical learning and ML techniques and provide guidance for responsible use in the case of clustering and prediction questions in critical care. Clustering studies have been increasingly popular in critical care research, aiming to inform how patients can be characterized, classified, or treated differently. An important challenge for clustering studies is to ensure and assess generalizability. This limits the application of findings in these studies toward individual patients. In the case of predictive questions, there is much discussion as to what algorithm should be used to most accurately predict outcome. Aspects that determine usefulness of ML, compared with statistical techniques, include the volume of the data, the dimensionality of the preferred model, and the extent of missing data. There are areas in which modern ML methods may be preferred. However, efforts should be made to implement statistical frameworks (e.g., for dealing with missing data or measurement error, both omnipresent in clinical data) in ML methods. To conclude, there are important opportunities but also pitfalls to consider when performing clustering or predictive studies with ML techniques. We advocate careful valuation of new data-driven findings. More interaction is needed between the engineer mindset of experts in ML methods, the insight in bias of epidemiologists, and the probabilistic thinking of statisticians to extract as much information and knowledge from data as possible, while avoiding harm.
Possibilities for Exploitation of Invasive Species, Arundo donax L., as a Source of Phenol Compounds
Authors: Míguez Clara , Cancela Ángeles , Sánchez Ángel , Álvarez Xana 
Published: May 2022

AbstractRecycling and reuse are a fundamental pillar for reducing global pollution. In this context, the use of waste generated by invasive species control actions, as a natural raw material for the exploitation of their bioactive compounds, provides a great interest for a more sustainable industry. In this study, phenolic compounds were determined from the different parts that compose the invasive species Arundo donax L. The experiments were carried out using response surface methodology (RSM) by the Box-Behnken method, allowing us to evaluate the factors (temperature, time and type of solvent) and the values that optimized the extraction. The highest concentration of total phenolic compounds equivalent in gallic acid (GAE) was obtained from extracts with distilled water, with the fraction of leaves (7.43 mg GAE /g) in first place, followed by inflorescences (5.15 mg GAE /g) and finally stems (2.73 mg GAE /g).These optimum values were obtained using conditions of 6 h and 45 °C for leaves and stems and 4 h and 35 °C for inflorescences.. Identification and quantification of phenolic acids and flavonoids were carried out by HPLC–MS/MS analytical technique. In general, stem extracts were the most abundant in phenolic acids with potential pharmacological properties. These studies provided promising results for the Arundo donax L. species as a source of polyphenols, making full use of its residue and aiming to boost the circular economy in important industry sectors.
Graphical Abstract
Validation of an open-source ambulatory assessment system in support of replicable activity studies
Authors: Van Laerhoven Kristof , Hoelzemann Alexander , Pahmeier Iris , Teti Andrea , Gabrys Lars 
Published: May 2022

AbstractPurpose: Inertial-based trackers have become a common tool in data capture for ambulatory studies that aim at characterizing physical activity. Many systems that perform remote recording of accelerometer data use commercial trackers and black-box aggregation algorithms, often resulting in data that are locked into proprietary formats and metrics that make later replication or comparison difficult.Methods: The primary purpose of this manuscript is to validate an open-source ambulatory assessment system that consists of hardware devices, algorithms, and software components of our approach. We report on two validation experiments, one lab-based treadmill study on a convenience sample of 16 volunteers and one ’in vivo’ study with 28 volunteers suffering from diabetes or cardiovascular disease.Results: A comparison between data from ActiGraph GT9X trackers and our proposed system reveals that the original inertial sensor signals at the wrist strongly correlate (Pearson correlation coefficients for raw inertial sensor signals of 0.97 in the controlled treadmill-walking setting) and that estimated steps from an open-source wrist-based detection approach correlate with the hip-worn ActiGraph output (average Pearson correlation coefficients of 0.81 for minute-wise comparisons of detected steps) in day-long ambulatory data.Conclusion: Recording inertial sensor data in a standardized form and relying on open-source algorithms on these data form a promising methodology that ensures that datasets can be replicated or enriched long after the wearable trackers have been decommissioned.
In vitro antioxidant activities of copper mixed oxide (CuO/Cu2O) nanoparticles produced from the leaves of Phoenix dactylifera L
Authors: Djamila Berra , Eddine Laouini Salah , Abderrhmane Bouafia , Nassiba Allag , Barhoum Ahmed 
Published: May 2022

AbstractBiosynthesis of antioxidant nanoparticles using plant extracts is a simple, rapid, environmentally friendly, and cost-effective approach. In this study, in vitro antioxidant copper mixed oxide nanoparticles (CuO/Cu2O) were prepared from the alcoholic extract of Phoenix Dactylifera L. and different aqueous concentrations of CuSO4·5H2O. The composition, crystallinity, morphology, and particle size of CuO/Cu2O NPs were tuned by increasing the CuSO4·5H2O concentration from 4 to 10 mM. Ultraviolet–visible (UV–Vis) and Fourier-transform infrared (FTIR) spectroscopy confirmed the reduction of CuSO4·5H2O and the formation of the CuO/Cu2O NPs. X-ray diffraction (XRD) confirmed the crystalline nature of the CuO/Cu2O NPs with a crystallite size varying from 18 to 35 nm. Scanning electron micrographs (SEM) showed that the CuO/Cu2O NPs have a spherical morphology with particle sizes ranging from 25 to 100 nm. The best antioxidant CuO/Cu2O NPs have a phase ratio of about 1:1 CuO/Cu2O with a half-maximal inhibitory concentration (IC50) of 0.39 mg/ml, an iron-containing reducing antioxidant power (FRAP) of 432 mg EFeSO4/100 mg NPs, and a total antioxidant capacity (TAC) of 65 mg EAA/gNPs. The results suggest that the synthesized CuO/Cu2O NPs are excellent antioxidants for therapeutic applications.
Graphical abstract