bluuebunny/crossref_metadata_2025_split huggingface dataset:
Screening method for the characterization of anabolic steroids seized in Brazil using paper spray mass spectrometry and chemometric tools
Authors: Miguita Ana Gabriella Carvalho , Augusti Rodinei , Nascentes Clésia Cristina , Sena Marcelo Martins 
Published: September 2022

AbstractThis paper reports the use of paper spray mass spectrometry (PS‐MS) combined with chemometric models to analyze seized samples of anabolic steroids. Because many forensic laboratories typically demand high‐throughput analysis for this type of sample, we developed a quicker and simpler alternative analytical method for routine analysis with minimal sample preparation. Oily samples (n = 39) resulting from seizures carried out by Brazilian Federal and State Police units were selected for this study. These samples were analyzed by PS‐MS in the positive ion mode and full scan (50–1000 m/z), providing spectra containing patterns of the respective active ingredients present in each product. A principal component analysis (PCA) model was built, which discriminated samples mainly according to their active ingredients and allowed to detect and characterize some cases of product counterfeiting. The variable selection method ordered predictors selection was employed jointly with PCA to improve sample cluster separation and to provide model simplification. The final PCA model was built with three principal components and using only 28 spectral variables. This model accounted for 69.82% of the variance and discriminated samples according to their specific active ingredients.
Adjusting supply chain involvement in countries with politician turnover: A contingency framework
Authors: Dong Maggie Chuoyan , Huang Qianqian , Liu Zhiqiang 
Published: September 2022

AbstractAlthough the supply chain (SC) literature has discussed the influence of the political environment on global SC decisions, the role of political leaders has been overlooked. To fill this research void, we predict and show that the turnover of a country's top political leader (hereafter, “politician turnover”) increases policy uncertainty in the country, which drives multinational corporations (MNCs) to adjust their SC involvement there. We also identify three politician‐related contingency factors: the market‐friendliness of the successor relative to the incumbent, the length of the successor's political career, and corruption in the turnover country. In an analysis of politician turnover events from 2003 to 2018 and the global supplier‐customer relationships of US‐incorporated MNCs, we find that politician turnover causes MNCs to reduce SC involvement (measured as the proportions of an MNC's customers, suppliers, and the transaction volume that are located in the turnover country). The negative effect of politician turnover on SC involvement is exacerbated by corruption in the turnover country, mitigated when the successor has a long political career, and exacerbated when the successor is less market‐friendly than the incumbent; the effect becomes positive when the successor is more market‐friendly than the incumbent.
Effects of creative atmosphere on tourists' post‐experience behaviors in creative tourism: The mediation roles of tourist inspiration and place attachment
Authors: Wei Min , Liu Min , Peng Yan , Zhou Xing , Li Shuhao 
Published: September 2022

AbstractConsidering the popularity of creative tourism, increasing research has focused on the creative atmosphere in creative tourism destinations. Based on Stimulus–Organism–Response framework, this research examined how creative atmosphere influences tourists' post‐experience behaviors—experience intensification and experience extension—through the mediating roles of tourist inspiration and place attachment. Using survey data from 345 tourists at three representative creative tourism destinations in Xiamen, this study finds that creative atmosphere positively predicts experience intensification and experience extension. Besides, tourist inspiration and place attachment were demonstrated to play significant serial mediating roles in both creative atmosphere–experience intensification and creative atmosphere–experience extension relationships.
Curcumin‐Based Universal Grafting of Poly(OEGMA) Brushes and Their Antibacterial Applications
Authors: Ki So Hyun , Thuy Le Thi , Kim Sunhee , Lee Seulgi , Choi Joon Sig , Cho Woo Kyung 
Published: September 2022

AbstractCatechol and/or pyrogallol groups are recognized as crucial for the formation of polyphenol coatings on various substrates. Meanwhile, studies on polyphenolic molecules that do not contain such groups are relatively rare. The key molecule in turmeric‐based universal (i.e., substrate‐independent) coatings is curcumin, which contains no catechol or pyrogallol groups. As chemically reactive hydroxyl groups would remain after curcumin coating, it is hypothesized that curcumin coating can serve as a reactive layer for controlling interfacial properties. In this study, a curcumin‐based surface modification method is developed to graft polymer brushes from various substrates, including titanium dioxide, gold, glass, stainless steel, and nylon. α‐Bromoisobutyryl bromide, a polymerization initiator, is introduced to the curcumin‐coated substrates via esterification; subsequently, poly(oligo(ethylene glycol) methacrylate) (poly(OEGMA)) is grafted from the surfaces. Compared to the control surfaces, poly(OEGMA)‐grafted surfaces significantly suppress bacterial adhesion by up to 99.4%, demonstrating their antibacterial properties. Considering its facile and versatile surface modification, curcumin‐based polymer grafting can be an efficient method for controlling the chemical/physical properties of surfaces in a substrate‐independent manner.
Surface modification of epichlorohydrin‐modified aramid nanofibers using ionic liquid to improve the fire safety and tensile strength of cotton fabrics
Authors: Wang Yaxuan , Feng Tingting , Piao Junxiu , Ren Jinyong , Ou Mingyu , Wang Yaofei , Lian Richeng , Cui Jiahui , Guan Haocun , Jiao Chuanmei , Chen Xilei 
Published: September 2022

AbstractIn this article, flame‐retardant cotton fabric was prepared by a step‐by‐step dip‐coating method, in which flame retardants were introduced onto the surface of the cotton fabric by hydrogen bonding association and surface grafting reaction. First, the epichlorohydrin‐modified aramid nanofibers (AEP) were accumulated onto the surface of cotton fabric (Cot/AEP) through hydrogen bond association. Subsequently, the ionic liquid (IL) was grafted onto the surface of AEP to obtain Cot/AEP/IL. The fire safe performance of cotton fabrics was investigated by the limiting oxygen index test (LOI), vertical flammability test (VFT), and cone calorimeter test (CCT), and so forth. The LOI value of Cot/AEP/IL was as high as 29.5%. The VFT results showed that Cot/AEP/IL was self‐extinguishing rather than ignited, leaving a char length of 111 mm. The CCT results demonstrated that the peak heat release rate and total heat release of Cot/AEP/IL decreased by 42.5% and 58.8% compared with untreated cotton fabrics, respectively. The TG test showed that Cot/AEP/IL had more residues left than untreated cotton under both N2 and air atmospheres. The presence of phosphorus enables the cotton fabric to generate an aromatic phosphor carbonaceous structure during the combustion process. In addition, the tensile strength of cotton fabric was tested. After the introduction of AEP/IL, the average tensile strength value of untreated cotton improved from 129 to 167 N in the warp direction and 125–155 N in the weft direction. In summary, the introduction of AEP/IL improved both the flame‐retardant and mechanical properties of the cotton fabric significantly.
Co‐infection with Nocardia spp. in a patient with Mycobacterium avium complex pulmonary disease: A case report
Authors: Tokita Nozomi , Urabe Naohisa , Sakamoto Susumu , Yamaguchi Asuka , Sekiguchi Ryo , Kishi Kazuma 
Published: September 2022

AbstractMycobacterium avium complex pulmonary disease (MAC‐PD) is sometimes accompanied by co‐infection with other pathogenic microorganisms such as Pseudomonas aeruginosa and Haemophilus influenzae. However, co‐infection with Nocardia spp. has been rarely reported. We report on a patient diagnosed as having co‐infection with Nocardia after treatment for MAC‐PD, which was successfully treated using trimethoprim‐sulfamethoxazole (TMP‐SMX). A 74‐year‐old woman with MAC‐PD was admitted to our hospital to undergo re‐examination for pathogenic microorganisms because chest computed tomography (CT) findings did not improve after treatment for MAC‐PD. She underwent bronchoscopy and Nocardia spp. was detected from bronchoalveolar lavage fluid culture. Chest CT findings improved after 6 months of treatment using TMP‐SMX. Co‐infection with other pathogenic microorganisms should be considered when chest CT findings worsen after adequate treatment of MAC‐PD. Chest CT findings of Nocardia pulmonary disease in immunocompetent patients can mimic those of MAC‐PD and should therefore be differentiated one from the other.
Detailed crack‐based assessment of a 4‐m deep beam test specimen
Authors: Trandafir Alexandru N. , Proestos Giorgio T. , Mihaylov Boyan I. 
Published: September 2022

AbstractWhen shear cracking occurs in existing reinforced concrete deep members, engineers are faced with the challenge of determining the safety of the members. This paper presents a crack‐based assessment approach that utilizes the Two‐Parameter Kinematic Theory (2PKT) as a framework for the assessment of lightly reinforced concrete deep beams. The paper presents three assessment approaches with progressively increasing levels of approximation (LoAs). The first level of approximation (LoA I) involves using the 2PKT in a predictive manner for situations where the crack shapes are unknown, LoA II improves upon LoA I by incorporating more detailed modeling of the strain in the transverse reinforcement at the location of the critical cracks, and LoA III includes the details of LoA II but also uses the detailed crack geometry as an input in the assessment. Each of the LoAs is presented and compared with experimental data from a 4‐m deep beam test in the literature. The shear carrying mechanisms determined from the kinematic model are evaluated and compared across LoAs. Finally, the paper utilizes LoA III to study the size effect in shear for deep beams. The results quantify the influence of aggregate interlock on the size effect in shear critical deep beams.
Delivering global water security: Embedding water justice as a response to increased irrigation efficiency
Authors: Owens Katherine , Carmody Emma , Grafton Quentin , O'Donnell Erin , Wheeler Sarah , Godden Lee , Allen Richard , Lyster Rosemary , Steduto Pasquale , Jiang Qiang , Kingsford Richard , Quiggin John 
Published: September 2022

AbstractIncreasingly, irrigation infrastructure upgrades have been regarded in global policy as a solution for both water scarcity and low agricultural productivity. However, these technical “fixes” may ultimately prove to be dangerous shortcuts that do little to address the concerns of irrigators, Indigenous People, environmental groups, and local communities about water scarcity, access, security, and sustainability. In the absence of transparent and rigorous governance safeguards, irrigation efficiency upgrades can result in higher water consumption, demand, and ultimately, increased water scarcity. Upgraded irrigation systems also tend to capture return flows and redistribute them to “high value” consumptive water uses, potentially displacing other users and uses, including Indigenous Peoples. In this article, we critique current approaches to governing irrigation efficiency, using a water justice lens to identify four key insights and their implications for governance. We propose new governance pathways and options that take into consideration hydrological realities and the full range of water demands and needs.This article is categorized under:
Human Water > Water Governance
Water and Life > Conservation, Management, and Awareness
Human Water > Water as Imagined and Represented
A Framework for Big Data Sovereignty: The European Industrial Data Space (EIDS)
Authors: Mertens Christoph , Alonso Jesús , Lázaro Oscar , Palansuriya Charaka , Böge Gernot , Nizamis Alexandros , Rousopoulou Vaia , Ioannidis Dimosthenis , Tzovaras Dimitrios , Touma Rizkallah , Tarzán Miquel , Mallada Diego , Figueiras Paulo , Costa Ruben , Graça Diogo , Garcia Gisela , Laibarra Begoña , Celaya Aitor , Sobonski Piotr , Naeem Azzam , Mozo Alberto , Vakaruk Stanislav , Sierra-García J. Enrique , Pastor Antonio , Rodriguez Juan , Hildebrand Marlène , Luniewski Tomasz , Zietak Wojciech , Lange Christoph , Sipsas Konstantinos , Poulakidas Athanasios 
Published: September 2022

AbstractThe path that the European Commission foresees to leverage data in the best possible way for the sake of European citizens and the digital single market clearly addresses the need for a European Data Space. This data space must follow the rules, derived from European values. The European Data Strategy rests on four pillars: (1) Governance framework for access and use; (2) Investments in Europe’s data capabilities and infrastructures; (3) Competences and skills of individuals and SMEs; (4) Common European Data Spaces in nine strategic areas such as industrial manufacturing, mobility, health, and energy. The project BOOST 4.0 developed a prototype for the industrial manufacturing sector, called European Industrial Data Space (EIDS), an endeavour of 53 companies. The publication will show the developed architectural pattern as well as the developed components and introduce the required infrastructure that was developed for the EIDS. Additionally, the population of such a data space with Big Data enabled services and platforms is described and will be enriched with the perspective of the pilots that have been build based on EIDS.
Deploying a Scalable Big Data Platform to Enable a Food Safety Data Space
Authors: Papakonstantinou Mihalis , Karvounis Manos , Stoitsis Giannis , Manouselis Nikos 
Published: September 2022

AbstractThe main goal of this chapter is to share the technical details and best practices for setting up a scalable Big Data platform that addresses the data challenges of the food industry. The amount of data that is generated in our food supply chain is rapidly increasing. The data is published by hundreds of organizations on a daily basis, in many different languages and formats making its aggregation, processing, and exchange a challenge. The efficient linking and mining of the global food data can enable the generation of insights and predictions that can help food safety experts to make critical decisions. All the food companies as well as national authorities and agencies may highly benefit from the data services of such a data platform. The chapter focuses on the architecture and software stack that was used to set up a data platform for a specific business use case. We describe how the platform was designed following data and technology standards to ensure the interoperability between systems and the interconnection of data. We share best practices on the deployment of data platforms such as identification of records, orchestrating pipelines, automating the aggregation workflow, and monitoring of a Big Data platform. The platform was developed in the context of the H2020 BigDataGrapes project, was awarded by communities such as Elasticsearch, and is further developed in H2020 The Food Safety Market project in order to enable the setup of a data space for the food safety sector.
TIKD: A Trusted Integrated Knowledge Dataspace for Sensitive Data Sharing and Collaboration
Authors: Hernandez Julio , McKenna Lucy , Brennan Rob 
Published: September 2022

AbstractThis chapter presents the Trusted Integrated Knowledge Dataspace (TIKD)—a trusted data sharing approach, based on Linked Data technologies, that supports compliance with the General Data Privacy Regulation (GDPR) for personal data handling as part of data security infrastructure for sensitive application environments such as healthcare. State-of-the-art shared dataspaces typically do not consider sensitive data and privacy-aware log records as part of their solutions, defining only how to access data. TIKD complements existing dataspace security approaches through trusted data sharing that includes personal data handling, data privileges, pseudonymization of user activity logging, and privacy-aware data interlinking services. TIKD was implemented on the Access Risk Knowledge (ARK) Platform, a socio-technical risk governance system, and deployed as part of the ARK-Virus Project which aims to govern the risk management of personal protection equipment (PPE) across a group of collaborating healthcare institutions. The ARK Platform was evaluated, both before and after implementing the TIKD, using both the ISO 27001 Gap Analysis Tool (GAT), which determines information security standard compliance, and the ISO 27701 standard for privacy information. The results of the security and privacy evaluations indicated that compliance with ISO 27001 increased from 50% to 85% and compliance with ISO 27701 increased from 64% to 90%. This shows that implementing TIKD provides a trusted data security dataspace with significantly improved compliance with ISO 27001 and ISO 27701 standards to share data in a collaborative environment.
An Organizational Maturity Model forData Spaces: A Data Sharing Wheel Approach
Authors: Curry Edward , Tuikka Tuomo 
Published: September 2022

AbstractThis chapter presents a maturity model for Data Spaces, which provides a management system with associated improvement roadmaps that guide strategies to continuously improve, develop, and manage the data space capability within their organization. It highlights the challenges with data sharing and motivates the benefit of maturity models. This chapter describes the Maturity Model for Data Spaces (MM4DS) and its use to determine an organization’s data space capability maturity. The MM4DS takes an organization’s user-centric/demand-side perspective utilizing a data space. The development process for the MM4DS is discussed, along with the role of design science in the model development process. Finally, the chapter details an illustrative case using the model to benchmark data space capabilities in five fictitious organizations. The MM4DS can be applied within organizations to better manage their data space capabilities, with assessment, providing insights into what they are doing well and where they need to improve.
Data Platforms for Data Spaces
Authors: Anjomshoaa Amin , Elvira Santiago Cáceres , Wolff Christian , Pérez Baún Juan Carlos , Karvounis Manos , Mellia Marco , Athanasiou Spiros , Katsifodimos Asterios , Garatzogianni Alexandra , Trügler Andreas , Serrano Martin , Zappa Achille , Glikman Yury , Tuikka Tuomo , Curry Edward 
Published: September 2022

AbstractIn our societies, there is a growing demand for the production and use of more data. Data is reaching the point that is driving all the social and economic activities in every industry sector. Technology is not going to be a barrier anymore; however, where there is large deployment of technology, the production of data creates a growing demand for better data-driven services, and at the same time the benefits of the production of the data are at large an impulse for a global data economy, Data has become the business’s most valuable asset. In order to achieve its full value and help data-driven organizations to gain competitive advantages, we need effective and reliable ecosystems that support the cross-border flow of data. To this end, data ecosystems are the key enablers of data sharing and reuse within or across organizations. Data ecosystems need to tackle the various fundamental challenges of data management, including technical and nontechnical aspects (e.g., legal and ethical concerns). This chapter explores the Big Data value ecosystems and provides a detailed overview of several data platform implementations as best-effort approaches for sharing and trading industrial and personal data. We also introduce several key enabling technologies for implementing data platforms. The chapter concludes with common challenges encountered by data platform projects and details best practices to address these challenges.
Decomposition of triple collinear splitting functions
Authors: Braun-White Oscar , Glover Nigel 
Published: September 2022

Abstract
In the kinematic region where three particles i, j, k are collinear, the multi-parton scattering amplitudes factorise into a product of a triple collinear splitting function and a multi-parton scattering amplitude with two fewer particles. These triple collinear splitting functions contain both iterated single unresolved contributions, and genuine double unresolved contributions. We make this explicit by rewriting the known triple collinear splitting functions in terms of products of two-particle splitting functions, and a remainder that is explicitly finite when any two of {i, j, k} are collinear. We analyse all of the single unresolved singularities present in the remainder.
Spatial Pointwise Behavior of Time-Periodic Navier–Stokes Flow Induced by Oscillation of a Moving Obstacle
Authors: Hishida Toshiaki 
Published: September 2022

AbstractWe study the spatial decay of time-periodic Navier–Stokes flow at the rate $$|x|^{-1}$$

|
x
|

-
1

with/without wake structure in 3D exterior domains when a rigid body moves periodically in time. In this regime the existence of time-periodic solutions was established first in the 2006 paper by Galdi and Silvestre, however, with little information about spatial behavior at infinity so that uniqueness of solutions was not available. This latter issue has been addressed by Galdi, who has recently succeeded in construction of a unique time-periodic solution with spatial behavior mentioned above if translational and angular velocities of the body fulfill, besides smallness and regularity, either of the following assumptions: (i) translation or rotation is absent; (ii) both velocities are parallel to the same constant vector. This paper shows the existence of a unique time-periodic Navier–Stokes flow in the small with values in the weak-$$L^3$$

L
3

space and then deduces the desired pointwise decay of the solution under some condition on the rigid motion of the body, that covers the cases (i), (ii) mentioned above.
Polynomial whitening for high-dimensional data
Authors: Gillard Jonathan , O’Riordan Emily , Zhigljavsky Anatoly 
Published: September 2022

AbstractThe inverse square root of a covariance matrix is often desirable for performing data whitening in the process of applying many common multivariate data analysis methods. Direct calculation of the inverse square root is not available when the covariance matrix is either singular or nearly singular, as often occurs in high dimensions. We develop new methods, which we broadly call polynomial whitening, to construct a low-degree polynomial in the empirical covariance matrix which has similar properties to the true inverse square root of the covariance matrix (should it exist). Our method does not suffer in singular or near-singular settings, and is computationally tractable in high dimensions. We demonstrate that our construction of low-degree polynomials provides a good substitute for high-dimensional inverse square root covariance matrices, in both $$d < N$$

d
<
N

and $$d \ge N$$

d
≥
N

cases. We offer examples on data whitening, outlier detection and principal component analysis to demonstrate the performance of the proposed method.