bluuebunny/crossref_metadata_2025_split huggingface dataset:
CIRCULAR ECONOMY AND SUPPLY CHAIN: A SCIENTIFIC CHARACTERIZATION
Authors: Pereira Renan , Ferreira Edivan Alexandre , Alves Josivan Leite , De Nadae Jeniffer , Galvão Graziela Darla Araujo 
Published: November 2020

Goal: To analyze the publications on circular economy and supply chain using a systematic review of the literature and bibliometric analysis, the study was designed to answer the question: How is the international scientific production about Circular Economy and Supply Chain characterized? For such an answer it was found that the first published article was on the subject date from 2006 and 2013 there was a steady increase in the number of publications. Many publications mentioned the use of CE in the supply chain through the management of the green supply chain. The country with more publications about the area in the United Kingdom with 19,1% of papers. Moreover, publications are generally about IT product and service supply chains.
Design/Methodology/Approach: Systematic literature review based on bibliometric theory and social network analysis, linking Circular Economy and Supply Chain.
Results: The articles do not point to studies on a specific supply chain, but only stress the importance of applying Circular Economy to the supply chain to mitigate the environmental impact of materials and products along with the flow from the production process to end consumers.
Limitations of the investigation: This paper contributes by analysing the international literature about the selected topics. In a future research agenda, this study could be applied to survey-based research to answer the research propositions suggested.
Practical implications: The research helps scholars to identify the main hot topics about Circular Economy and Supply Chain, main authors and papers. Also, can help managers to develop Circular Economy business models to improve and mitigate the environmental impacts on the production and supply chain.
Originality / Value: This research sheds light on controversies, discussed in the literature, concerning the effects linking Circular Economy and Supply Chain.
Generalized principal eigenvalues of convex nonlinear elliptic operators in ℝ
N
Authors: Biswas Anup , Roychowdhury Prasun 
Published: November 2020

Abstract
We study the generalized eigenvalue problem in

ℝ
N

{\mathbb{R}^{N}}

for a general convex nonlinear elliptic operator
which is locally elliptic and positively 1-homogeneous.
Generalizing [H. Berestycki and L. Rossi,
Generalizations and properties of the principal eigenvalue of elliptic operators in unbounded domains,
Comm. Pure Appl. Math. 68 2015, 6, 1014–1065], we consider three different notions of generalized eigenvalues
and compare them. We also discuss the maximum principles and uniqueness of principal eigenfunctions.
Complex Interpolation of Lizorkin-Triebel-Morrey Spaces on Domains
Authors: Zhuo Ciqiang , Hovemann Marc , Sickel Winfried 
Published: November 2020

Abstract
In this article the authors study complex interpolation of Sobolev-Morrey spaces and their generalizations, Lizorkin-Triebel-Morrey spaces. Both scales are considered on bounded domains. Under certain conditions on the parameters the outcome belongs to the scale of the so-called diamond spaces.
Production and characterization of psychrophilic α-amylase from a psychrophilic bacterium, Shewanella sp. ISTPL2
Authors: Rathour Rashmi , Gupta Juhi , Tyagi Bhawna , Thakur Indu Shekhar 
Published: November 2020

Abstract
A psychrophilic and halophilic bacterial isolate, Shewanella sp. ISTPL2, procured from the pristine Pangong Lake, Ladakh, Jammu and Kashmir, India, was used for the production and characterization of the psychrophilic and alkalophilic α-amylase enzyme. The α-amylase is a critical enzyme that catalyses the hydrolysis of α-1,4-glycosidic bonds of starch molecules and is predominately utilized in biotechnological applications. The highest enzyme activity of partially purified extracellular α-amylase was 10,064.20 U/mL after 12 h of incubation in a shake flask at pH 6.9 and 10 °C. Moreover, the maximum intracellular α-amylase enzyme activity (259.62 U/mL) was also observed at 6 h of incubation. The extracellular α-amylase was refined to the homogeneity with the specific enzyme activity of 36,690.47 U/mg protein corresponding to 6.87-fold purification. The optimized pH and temperature for the α-amylase were found to be pH 8 and 4 °C, respectively, suggesting its stability at alkaline conditions and low or higher temperatures. The amylase activity was highly activated by Cu2+, Fe2+ and Ca2+, while inhibited by Cd2+, Co2+ and Na2+. As per our knowledge, the current study reports the highest activity of a psychrophilic α-amylase enzyme providing prominent biotechnological potential.
Iudei et ceteri
…
Authors: Wenninger Markus J. 
Published: November 2020

Abstract
This study analyzes the formulation »Jews and (other) merchants« as it appears in sources from the 9th to the early 11th centuries. It addresses Michael Toch’s thesis with an aim to clarify the historical meaning of such formulations. By doing so, this study sheds light on how specific social differences between Jewish and non-Jewish merchants arose, while economic activities among both groups remained the same. Both Jews and non-Jews traded in the whole Frankish Empire and beyond. Both groups, therefore, took part in the lucrative as well as extensive slave trade, which was an essential element of the long-distance trading of the early Middle Ages.
Artificial intelligence and optimization: a way to speed up the security constraint optimal power flow
Authors: Giuntoli Marco , Biagini Veronica , Chioua Moncef 
Published: November 2020

Abstract
Optimal power flow is a widely used tool in power system planning and management. Due to the complexity of the power system both in terms of number of variables, degrees of freedom and uncertainty, there is a continuous effort to find more efficient computational methods to solve optimal power flow problems. This article presents a novel method to speed-up the solution of a security constraint optimal power flow problem. An unconventional warm start based on the training of a neural network is investigated as an option to improve the computational efficiency of the optimization problem. The principle of the method and the validity of the approach is demonstrated by different analysis performed on the IEEE14 test grid and based on a linearized mathematical formulation of the problem. The results show the effectiveness of the method in reducing the number of iterations needed to converge to global optimum.
Occupational Choice and Investments in Human Capital in Informal Economies
Authors: Berniell Lucila 
Published: November 2020

Abstract
Informality is pervasive in many developing countries and it can affect occupational and educational decisions. Cross-country data shows that the rate of entrepreneurship as well as the gap between the skill premium for entrepreneurs and for workers increase with the size of the informal economy. Also, in countries with larger informal sectors the fraction of high-skilled individuals that choose to be entrepreneurs is larger. To explain these facts, I develop a model economy with human capital investments, occupational choice and an informal sector, in which the investment in human capital improves the efficiency of labor as well as managerial skills, and the technology to produce goods exhibits capital-skill complementarity. Model predictions can account for cross-country evidence and also shed light on the mechanisms at work when the level of informality in the economy increases. In particular, a higher level of informality discourages human capital investments for workers while it incentivizes these investments for the case of some managers, mostly informal but talented.
Trend Growth and Robust Monetary Policy
Authors: Hasui Kohei 
Published: November 2020

Abstract
Recent monetary policy studies have shown that the trend productivity growth has non-trivial implications for monetary policy. This paper investigates how trend growth alters the effect of model uncertainty on macroeconomic fluctuations by introducing a robust control problem. We show that an increase in trend growth reduces the effect of the central bank’s model uncertainty and, hence, mitigates the large macroeconomic fluctuations. Moreover, the increase in trend growth contributes to bringing the economy into determinacy regions even if larger model uncertainty exists. These results indicate that trend growth contributes to stabilizing the economy in terms of both variance and determinacy when model uncertainty exists.
Yttrium doped phosphate-based glasses: structural and degradation analyses
Authors: Arafat Abul , Samad Sabrin A. , Titman Jeremy J. , Lewis Andrew L. , Barney Emma R. , Ahmed Ifty 
Published: November 2020

AbstractThis study investigates the role of yttrium in phosphate-based glasses in the system 45(P2O5)–25(CaO)– (30-x)(Na2O)–x(Y2O3) (0≤x≤5) prepared via melt quenching and focuses on their structural characterisation and degradation properties. The structural analyses were performed using a combination of solid-state nuclear magnetic resonance (NMR), Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). 31P NMR analysis showed that depolymerisation of the phosphate network occurred which increased with Y2O3 content as metaphosphate units (Q2) decreased with subsequent increase in pyrophosphate species (Q1). The NMR results correlated well with structural changes observed via FTIR and XPS analyses. XRD analysis of crystallised glass samples revealed the presence of calcium pyrophosphate (Ca2P2O7) and sodium metaphosphate (NaPO3) phases for all the glass formulations explored. Yttrium-containing phases were found for the formulations containing 3 and 5 mol% Y2O3. Degradation analyses performed in Phosphate buffer saline (PBS) and Milli-Q water revealed significantly reduced rates with addition of Y2O3 content. This decrease was attributed to the formation of Y-O-P bonds where the octahedral structure of yttrium (YO6) cross-linked phosphate chains, subsequently leading to an increase in chemical durability of the glasses. The ion release studies also showed good correlation with the degradation profiles.
Using machine learning to develop an autoverification system in a clinical biochemistry laboratory
Authors: Wang Hongchun , Wang Huayang , Zhang Jian , Li Xiaoli , Sun Chengxi , Zhang Yi 
Published: November 2020

Abstract

Objectives
Autoverification systems have greatly improved laboratory efficiency. However, the long-developed rule-based autoverfication models have limitations. The machine learning (ML) algorithm possesses unique advantages in the evaluation of large datasets. We investigated the utility of ML algorithms for developing an artificial intelligence (AI) autoverification system to support laboratory testing. The accuracy and efficiency of the algorithm model were also validated.

Methods
Testing data, including 52 testing items with demographic information, were extracted from the laboratory information system and Roche Cobas® IT 3000 from June 1, 2018 to August 30, 2019. Two rounds of modeling were conducted to train different ML algorithms and test their abilities to distinguish invalid reports. Algorithms with the top three best performances were selected to form the finalized ensemble model. Double-blind testing between experienced laboratory personnel and the AI autoverification system was conducted, and the passing rate and false-negative rate (FNR) were documented. The working efficiency and workload reduction were also analyzed.

Results
The final AI system showed a 89.60% passing rate and 0.95 per mille FNR, in double-blind testing. The AI system lowered the number of invalid reports by approximately 80% compared to those evaluated by a rule-based engine, and therefore enhanced the working efficiency and reduced the workload in the biochemistry laboratory.

Conclusions
We confirmed the feasibility of the ML algorithm for autoverification with high accuracy and efficiency.
A validated LC-MS/MS method for the simultaneous quantification of the novel combination antibiotic, ceftolozane–tazobactam, in plasma (total and unbound), CSF, urine and renal replacement therapy effluent: application to pilot pharmacokinetic studies
Authors: Parker Suzanne L. , Pandey Saurabh , Sime Fekade B. , Stuart Janine , Lipman Jeffrey , Roberts Jason A. , Wallis Steven C. 
Published: November 2020

AbstractObjectivesNovel treatment options for some carbapenem-resistant Gram-negative pathogens have been identified by the World Health Organization as being of the highest priority. Ceftolozane–tazobactam is a novel cephalosporin–beta-lactamase inhibitor combination antibiotic with potent bactericidal activity against the most difficult-to-treat multi-drug resistant and extensively drug resistant Gram-negative pathogens. This study aimed to develop and validate a liquid chromatography – tandem mass spectrometry method for the simultaneous quantification of ceftolozane and tazobactam in plasma (total and unbound), renal replacement therapy effluent (RRTE), cerebrospinal fluid (CSF) and urine.MethodsAnalytes were separated using mixed-mode chromatography with an intrinsically base-deactivated C18 column and a gradient mobile phase consisting of 0.1% formic acid, 10 mM ammonium formate and acetonitrile. The analytes and internal standards were detected using rapid ionisation switching between positive and negative modes with simultaneous selected reaction monitoring.ResultsA quadratic calibration was obtained for plasma (total and unbound), RRTE and CSF over the concentration range of 1–200 mg/L for ceftolozane and 0.5–100 mg/L for tazobactam, and for urine the concentration range of 10–2,000 mg/L for ceftolozane and 5–1,000 mg/L for tazobactam. For both ceftolozane and tazobactam, validation testing for matrix effects, precision and accuracy, specificity and stability were all within the acceptance criteria of ±15%.ConclusionsThis methodology was successfully applied to one pilot pharmacokinetic study in infected critically ill patients, including patients receiving renal replacement therapy, and one case study of a patient with ventriculitis, where all patients received ceftolozane–tazobactam.
Effect of collection matrix, platelet depletion, and storage conditions on plasma extracellular vesicles and extracellular vesicle-associated miRNAs measurements
Authors: Faraldi Martina , Gomarasca Marta , Perego Silvia , Sansoni Veronica , Banfi Giuseppe , Lombardi Giovanni 
Published: November 2020

Abstract

Objectives
The interest around circulating extracellular vesicles and their cargo in diagnostics has greatly increased; however, several pre-analytical variables affect their determination. In this study, we investigated the effects of sample matrix, processing, and plasma storage delay and temperature on extracellular vesicles and their miRNA content.

Methods
Blood was collected from 10 male volunteers in dipotassium ethylendiaminotetraacetate-coated tubes (K2EDTA), either with plasma-preparation tube (PPT) or without (K2E) gel separator. A stepwise centrifugation was applied to K2E aliquots to obtain platelet-poor plasma (PPP). K2E, PPP and PPT plasma, stored under different conditions, were assayed for extracellular vesicles concentration and size distribution, through dynamic laser light scattering, and microRNAs content, by qPCR.

Results
PPP samples were characterized by the lowest extracellular vesicles count and miRNA detectability. Although having no effects on extracellular vesicles total concentration, storage conditions influenced microRNAs detectability, mainly in PPP and PPT samples. Extracellular vesicles-associated miRNAs levels in K2E were, in general, higher than in PPP and to a very limited extent to PPT. Storage temperature and delay did not affect their profile in K2E samples.

Conclusions
Extracellular vesicles count and extracellular vesicles miRNA profile changed under the analyzed pre-analytical variables, showing the greatest stability in K2E samples. Since pre-analytical variables differently affected extracellular vesicles and their miRNA content, they should be considered in each experimental setting and clinical routine.
Non-invasive determination of uric acid in human saliva in the diagnosis of serious disorders
Authors: Vernerová Andrea , Kujovská Krčmová Lenka , Melichar Bohuslav , Švec František 
Published: November 2020

Abstract
This review summarizes and critically evaluates the published approaches and recent trends in sample pre-treatment, as well as both separation and non-separation techniques used for the determination of uric acid (UA) in saliva. UA is the final product of purine nucleotide catabolism in humans. UA concentrations in biological fluids such as serum, plasma, and urine represent an important biomarker of diseases including gout, hyperuricemia, or disorders associated with oxidative stress. Previous studies reported correlation between UA concentrations detected in saliva and in the blood. The interest in UA has been increasing during the past 20 years from a single publication in 2000 to 34 papers in 2019 according to MEDLINE search using term “uric acid in saliva”. The evaluation of salivary UA levels can contribute to non-invasive diagnosis of many serious diseases. Increased salivary UA concentration is associated with cancer, HIV, gout, and hypertension. In contrast, low UA levels are associated with Alzheimer disease, progression of multiple sclerosis, and mild cognitive impairment.
(Meta-)Ground Viewpoint Space and structurally-framed irony: A case study of the mobile game Liyla and the Shadows of War
Authors: Kwon Iksoo , Kim Eunsong 
Published: November 2020

Abstract
Within the framework of Viewpoint Spaces (Dancygier, Barbara. 2012. The language of stories: A cognitive approach. Cambridge: Cambridge University Press), this paper investigates viewpoint interactions in a mobile game’s plot to show how the game’s structural framing leads to meaning construction, specifically the construal of irony. The notion of (meta-)Ground Viewpoint Space is proposed not only to provide a generalized account of a global mental space where local spaces and viewpoints relate to one another, but also to elucidate how the invoked genre-specific expectation makes a significant meaning contribution to the player’s overall construal of the game. This study presents a case study of the mobile game Liyla and the Shadows of War (Abueideh, Rasheed. 2016. Liyla and the Shadows of War) as a viewpoint phenomenon whose construal involves the interaction of multiple viewpoints. The game depicts the consequences of the 2014 Gaza conflict from the perspective of an unnamed Palestinian father struggling to escape the war zone with his daughter Liyla. It deviates from prototypical games in that it is impossible to complete the expected narrative, regardless of the player’s skill, although its ostensible goal is to let the protagonists survive and escape to a safer place. The mismatch between the player’s goal to clear all the stages, the character’s goal to survive, and the developer’s goal to convey a message is a source of ironic meaning, and this study focuses on how the network of multiple viewpoints – of the game developer, the character, and the player – constructs the intended meaning for players.
Did Moses Mendelssohn Lack Historical Thinking?
Authors: Goldenbaum Ursula 
Published: November 2020

Abstract
There is widespread agreement in scholarship that Moses Mendelssohn lacked historical thinking, an opinion accepted even among Mendelssohn experts. This misjudgment is based on a remark in his Jerusalem against Lessing’s Education of Humankind and surely ignores Mendelssohn’s historical work. I will question the misjudgment by a detour: first, I will ask for whom Lessing wrote his Education of Humankind. Then I will turn to the usually celebrated origin of historical thinking in Semler and Herder and question the historicity of their views. It is only in the 3rd section that I will focus directly on Mendelssohn’s historical work and his truly historical understanding of religion, in agreement with Lessing.
Electrochemical studies of the synergistic combination effect of thymus mastichina and illicium verum essential oil extracts on the corrosion inhibition of low carbon steel in dilute acid solution
Authors: Loto Roland Tolulope , Ororo Samuel Keme 
Published: November 2020

AbstractInhibition effect of the synergistic combination of thymus mastichina and illicium verum oil extracts (TMAV) on the corrosion inhibition of low carbon steel in 0.5 M H2SO4and HCl solution was studied by weight loss analysis, potentiodynamic polarization, open circuit potential measurement, ATF-FTIR spectroscopy, and optical microscopy and macroscopic characterization. Results from weight loss shows TMAV performed more effectively in H2SO4solution compared to HCl with optimal inhibition efficiency of 81.24% and 68.33%. Effective inhibition performance was observed at all TMAV concentration in H2SO4compared to HCl where TMAV performed poorly until 5% concentration. The optimal inhibition performances from potentiodynamic polarization are 80.85% and 70.43%. The corresponding corrosion current density and polarization resistance are 7.16 × 105A/cm2and 8.01 × 105A/cm2, and 331.73 and 284 Ω. TMAV exhibited mixed type inhibition effect in both acid solutions, strongly influencing the anodic-cathodic plot configurations with respect to concentration. Open circuit potential plots without TMAV were significantly electronegative compared to the plots at 1% and 5% TMAV concentration which were relative electropositive due to decreased thermodynamic tendency of the carbon steel to corrode. The corresponding plots at 1% and 5% TMAV concentration from HCl solution were thermodynamically unstable with significant active-passive corrosion behaviour. TMAV inhibited through chemisorption adsorption according to Langmuir and Freudlich adsorption isotherms in H2SO4solution, and Frumkin and Freundlich adsorption isotherms in HCl solution with correlation coefficient values between 0.7 and 0.9. FTIR spectroscopic analysis exposed the functional groups and atomic bonds responsible for corrosion inhibition.