bluuebunny/crossref_metadata_2025 huggingface dataset:
Description, Staging and Quantification of Pulmonary Artery Angiophagy in a Large Animal Model of Chronic Thromboembolic Pulmonary Hypertension
Authors: Perros Frédéric , Ghigna Maria-Rosa , Loisel Fanny , Chemla Denis , Decante Benoit , de Montpreville Vincent , Montani David , Humbert Marc , Fadel Elie , Mercier Olaf , Boulate David
Published: November 2020

Angiophagy has been described as a non-fibrinolytic mechanism of pulmonary artery (PA) patency restoration after distal (<50 µm in diameter) pulmonary embolism in mice. We hypothesized that angiophagy could achieve muscularized PA patency restoration after pulmonary embolism in piglets and humans. Angiophagy was defined by pathological assessment as the moving of an embolic specimen from the lumen to the interstitium according to three stages in a pig model of chronic thromboembolic pulmonary hypertension (CTEPH) 6 to 10 weeks after embolization with enbucrilate: the embolic specimen is (I) covered by endothelial cells, (II) covered by endothelial cells and smooth muscle cells, and (III) located in the adventitia. In animals, we observed the three stages of the pulmonary angiophagy of enbucrilate emboli in <300 µm PA. Stages II and III were observed in 300 to 1000 μm PA, and only Stage I was observed in larger-diameter PA (>1000 μm). In lung samples from patients with histories of pulmonary embolisms, we observed PA angiophagy stigma for embolic specimens derived from blood clots and from bone marrow emboli. This study provides an original pathological description and staging of PA angiophagy in a large animal model of CTEPH and in humans after pulmonary embolism.
Voltammetric Determination of Phenylalanine Using Chemically Modified Screen-Printed Based Sensors
Authors: Dinu Ancuta , Apetrei Constantin
Published: November 2020

This paper describes the sensitive properties of screen-printed carbon electrodes (SPCE) modified by using three different electroactive chemical compounds: Meldola’s Blue, Cobalt Phthalocyanine and Prussian Blue, respectively. It was demonstrated that the Prussian Blue (PB) modified SPCE presented electrochemical signals with the highest performances in terms of electrochemical process kinetics and sensitivity in all the solutions analyzed. PB-SPCE was demonstrated to detect Phe through the influence it exerts on the redox processes of PB. The PB-SPCE calibration have shown a linearity range of 0.33–14.5 µM, a detection limit (LOD) of 1.23 × 10−8 M and the standard deviation relative to 3%. The PB-SPCE sensor was used to determine Phe by means of calibration and standard addition techniques on pure samples, on simple pharmaceutical samples or on multicomponent pharmaceutical samples. Direct determination of the concentration of 4 × 10−6–5 × 10−5 M Phe in KCl solution showed that the analytical recovery falls in the range of 99.75–100.28%, and relative standard deviations in the range of 2.28–3.02%. The sensors were successfully applied to determine the Phe in pharmaceuticals. The validation of the method was performed by using the FTIR, and by comparing the results obtained by PB-SPCE in the analysis of three pharmaceutical products of different concentrations with those indicated by the producer.
Urban Morphological Controls on Surface Thermal Dynamics: A Comparative Assessment of Major European Cities with a Focus on Athens, Greece
Authors: Agathangelidis Ilias , Cartalis Constantinos , Santamouris Mat
Published: November 2020

Variations in urban form lead to the development of distinctive intra-urban surface thermal patterns. Previous assessment of the relation between urban structure and satellite-based Land Surface Temperature (LST) has generally been limited to single-city cases. Here, examining 25 European cities (June–August 2017), we estimated the statistical association between surface parameters—the impervious fraction (λimp), the building fraction (λb), and the building height (H)—and the neighborhood scale (1000 × 1000 m) LST variations, as captured by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Correlation analysis, multiple linear regression, and spatial regression were used. As expected, λimp had a consistent positive influence on LSTs. In contrast, the relation of LST with λb and H was generally weaker or negative in the daytime, whereas at night it shifted to a robust positive effect. In particular, daytime LSTs of densely built, high-rise European districts tended to have lower values. This was especially the case for the city of Athens, Greece, where a more focused analysis was conducted, using further surface parameters and the Local Climate Zone (LCZ) scheme. For the urban core of the city, the canyon aspect ratio H/W had a statistically significant (p <0.01) negative relationship with LST by day (Spearman’s rho = −0.68) and positive during nighttime (rho = 0.45). The prevailing intra-urban surface thermal variability in Athens was well reproduced by a 5-day numerical experiment using the meteorological Weather Research and Forecasting Model (WRF) model and a modified urban parameterization scheme. Although the simulation resulted in some systematic errors, the overall accuracy of the model was adequate, regarding the surface temperature (RMSE = 2.4 K) and the near-surface air temperature (RMSE = 1.7 K) estimations.
Computational Insights into Industrial Chemistry
Authors: Novikov Alexander S.
Published: November 2020

This brief Editorial is dedicated to announcing the Special Issue “Computational Insights into Industrial Chemistry”. The Special Issue covers the most recent progress in the rapidly growing field of computational chemistry, and the application of computer modeling in topics relevant to industrial chemistry (chemical industrial processes and materials, environmental effects caused by chemical industry activities, computer-aided design of catalysts, green chemistry, etc.).
Distinguishability and Disturbance in the Quantum Key Distribution Protocol Using the Mean Multi-Kings’ Problem
Authors: Yoshida Masakazu , Nakayama Ayumu , Cheng Jun
Published: November 2020

We introduce a quantum key distribution protocol using mean multi-kings’ problem. Using this protocol, a sender can share a bit sequence as a secret key with receivers. We consider a relation between information gain by an eavesdropper and disturbance contained in legitimate users’ information. In BB84 protocol, such relation is known as the so-called information disturbance theorem. We focus on a setting that the sender and two receivers try to share bit sequences and the eavesdropper tries to extract information by interacting legitimate users’ systems and an ancilla system. We derive trade-off inequalities between distinguishability of quantum states corresponding to the bit sequence for the eavesdropper and error probability of the bit sequence shared with the legitimate users. Our inequalities show that eavesdropper’s extracting information regarding the secret keys inevitably induces disturbing the states and increasing the error probability.
4D Travel-Time Tomography as a Tool for Tracking Fluid-Driven Medium Changes in Offshore Oil–Gas Exploitation Areas
Authors: De Landro Grazia , Amoroso Ortensia , Russo Guido , Zollo Aldo
Published: November 2020

The monitoring of rock volume where offshore exploitation activities take place is crucial to assess the corresponding seismic hazard. Fluid injection/extraction operations generate a pore fluid pressure perturbation into the volume hosting the reservoir which, in turn, may trigger new failures and induce changes in the elastic properties of rocks. Our purpose is to evaluate the feasibility of reconstructing pore pressure perturbation diffusion in the host medium by imaging the 4D velocity changes using active seismic. We simulated repeated active offshore surveys and imaged the target volume. We constructed the velocity model perturbed by the fluid injection using physical modeling and evaluated under which conditions the repeated surveys could image the velocity changes. We found that the induced pressure perturbation causes seismic velocity variations ranging between 2–5% and 15–20%, depending on the different injection conditions and medium properties. So, in most cases, time-lapse tomography is very efficient in tracking the perturbation. The noise level characterizing the recording station sites is a crucial parameter. Since we evaluated the feasibility of the proposed 4D imaging strategy under different realistic environmental and operational conditions, our results can be directly applied to set up and configure the acquisition layout of surveys aimed at retrieving fluid-induced medium changes in the hosting medium. Moreover, our results can be considered as a useful starting point to design the guidelines to monitor exploitation areas.
Forecasting Electricity Consumption in Commercial Buildings Using a Machine Learning Approach
Authors: Hwang Junhwa , Suh Dongjun , Otto Marc-Oliver
Published: November 2020

Article [...]
A Methodology to Systematically Identify and Characterize Energy Flexibility Measures in Industrial Systems
Authors: Tristán Alejandro , Heuberger Flurina , Sauer Alexander
Published: November 2020

Industrial energy flexibility enables companies to optimize their energy-associated production costs and support the energy transition towards renewable energy sources. The first step towards achieving energy flexible operation in a production facility is to identify and characterize the energy flexibility measures available in the industrial systems that comprise it. These industrial systems are both the manufacturing systems that directly execute the production tasks and the systems performing supporting tasks or tasks necessary for the operation of these manufacturing systems. Energy flexibility measures are conscious and quantifiable actions to carry out a defined change of operative state in an industrial system. This work proposes a methodology to identify and characterize the available energy flexibility measures in industrial systems regardless of the task they perform in the facility. This methodology is the basis of energy flexibility-oriented industrial energy audits, in juxtaposition with the current industrial energy audits that focus on energy efficiency. This audit will provide industrial enterprises with a qualitative and quantitative understanding of the capabilities of their industrial systems, and hence their production facilities, for energy flexible operation. The audit results facilitate a company’s decision making towards the implementation, evaluation and management of these capabilities.
The Effect of Fuel Cell and Battery Size on Efficiency and Cell Lifetime for an L7e Fuel Cell Hybrid Vehicle
Authors: Fletcher Tom , Ebrahimi Kambiz
Published: November 2020

The size of the fuel cell and battery of a Fuel Cell Hybrid Electric Vehicle (FCHEV) will heavily affect the overall performance of the vehicle, its fuel economy, driveability, and the rates of fuel cell degradation observed. An undersized fuel cell may experience accelerated ageing of the fuel cell membrane and catalyst due to excessive heat and transient loading. This work describes a multi-objective design exploration exercise of fuel cell size and battery capacity comparing hydrogen fuel consumption, fuel cell lifetime, vehicle mass and running cost. For each system design considered, an individually optimised Energy Management Strategy (EMS) has been generated using Stochastic Dynamic Programming (SDP) in order to prevent bias to the results due to the control strategy. It has been found that the objectives of fuel efficiency, lifetime and running cost are largely complimentary, but degradation and running costs are much more sensitive to design changes than fuel efficiency and therefore should be included in any optimisation. Additionally, due to the expense of the fuel cell, combined with the dominating effect of start/stop cycling degradation, the optimal design from an overall running cost perspective is slightly downsized from one which is optimised purely for high efficiency.
Life Cycle Assessment (LCA) of Environmental and Energy Systems
Authors: Ciacci Luca , Passarini Fabrizio
Published: November 2020

The transition towards renewable energy sources and “green” technologies for energy generation and storage is expected to mitigate the climate emergency in the coming years [...]
Personalization of Products in the Industry 4.0 Concept and Its Impact on Achieving a Higher Level of Sustainable Consumption
Authors: Saniuk Sebastian , Grabowska Sandra , Gajdzik Bożena
Published: November 2020

Sustainability is among the most important directions in global development. The challenge today is to reconcile the fastest possible economic growth and the pursuit of prosperity with concern for the environment. One of the important problems of modern economies and societies is to reduce overall consumption and implement new patterns of sustainable consumption and production. The main aim of this article was to analyze consumer preferences in terms of purchasing personalized production offered by implementing the concept of Industry 4.0 and ensuring sustainable consumption and production (SCP). Based on the analysis of the literature and the results of our own research, an attempt was made to estimate the impact of personalized production offered by the Industry 4.0 concept on SCP and thus the sustainable development of the economy. This article presents the results of a survey conducted on a selected group of consumers, focusing on learning about expectations, consumer preferences for personalized products and conscious consumption, and the results of a survey conducted using the Servqual method, determining the level of customer satisfaction with the purchase of personalized products. The most important achievement was to demonstrate a high level of consumer satisfaction with buying personalized products and the positive impact of personalized production on sustainable consumption. At the same time, the importance of developing the Industry 4.0 concept for supporting sustainable consumption-oriented consumer behavior is emphasized.
Link between Energy Efficiency and Sustainable Economic and Financial Development in OECD Countries
Authors: Ziolo Magdalena , Jednak Sandra , Savić Gordana , Kragulj Dragana
Published: November 2020

The growing risk of climate change caused by the emission of greenhouse gases poses new challenges to contemporary countries. The development of economies is usually related to increasing levels of greenhouse gas emissions. Therefore, the question arises whether it is possible to achieve sustainable economic and financial development and simultaneously reduce greenhouse gas emissions. This paper assumes it is possible if energy efficiency is increased. The aim of the paper is to show the link between energy efficiency and sustainable economic and financial development in Organisation for Economic Co-operation and Development (OECD) countries for the period 2000–2018 by using data envelopment analysis (DEA) and regression analysis. The results show a slight upward trend of total factor energy efficiency (TFEE) in OECD countries for the analysed period; however, there is a difference in TFEE levels. Developed OECD countries have higher TFEE levels than developing OECD countries. The links between total factor energy efficiency and sustainable economic and financial development reveal different impacts depending on the variables taken into consideration.
Investigation of the Potential Use of Curauá Fiber for Reinforcing Mortars
Authors: Azevedo Afonso R. G. de , Klyuev Sergey , Marvila Markssuel T. , Vatin Nikolai , Alfimova Nataliya , Lima Thuany E.S. de , Fediuk Roman , Olisov Andrej
Published: November 2020

Curauá is a bromeliad of Amazonian origin, present in some states in the northern region of Brazil and in other countries in South America. Its natural fibers have several technological advantages for application in composite materials. The objective of this research was to investigate the potential of using the fiber of Curauá as a reinforcement element in mortars for wall covering. Mortars were made with a 1:1:6 ratio (cement:lime:sand) in relation to their mass, evaluating the effect of adding 1%, 2% and 3% of Curauá fiber natural and fiber treated in NaOH solution in relation to the mass of cement, compared to the reference mixture (0%). Technological properties such as consistency, water retention and incorporated air content, compressive strength, water absorption and durability in wetting and drying cycles were evaluated. The results showed that the addition of the Curauá fiber causes an improvement in the mechanical properties of mortars, and at levels of addition 3% or more, it causes problems of workability and incorporation of air into the dough, thus, the fiber addition in 2% presented better results for application in coating mortars, in relation a Brazilian norm, even improving the durability of external coatings.
OpenFOAM Simulations of Late Stage Container Draining in Microgravity
Authors: McCraney Joshua , Weislogel Mark , Steen Paul
Published: November 2020

In the reduced acceleration environment aboard orbiting spacecraft, capillary forces are often exploited to access and control the location and stability of fuels, propellants, coolants, and biological liquids in containers (tanks) for life support. To access the ‘far reaches’ of such tanks, the passive capillary pumping mechanism of interior corner networks can be employed to achieve high levels of draining. With knowledge of maximal corner drain rates, gas ingestion can be avoided and accurate drain transients predicted. In this paper, we benchmark a numerical method for the symmetric draining of capillary liquids in simple interior corners. The free surface is modeled through a volume of fluid (VOF) algorithm via interFoam, a native OpenFOAM solver. The simulations are compared with rare space experiments conducted on the International Space Station. The results are also buttressed by simplified analytical predictions where practicable. The fact that the numerical model does well in all cases is encouraging for further spacecraft tank draining applications of significantly increased geometric complexity and fluid inertia.
Changes in Protein Non-Covalent Bonds and Aggregate Size during Dough Formation
Authors: Iwaki Sonoo , Aono Shiro , Hayakawa Katsuyuki , Fu Bin Xiao , Otobe Chikako
Published: November 2020

This research investigated changes in the amounts and sizes of monomeric proteins and protein aggregates during dough mixing, with a focus on the contribution of non-covalent bonds in the aggregation of gluten proteins. High protein flour (HF) and low protein flour (LF) were used in this study. As dough mixing progressed from flour to overmixed dough, the total amount of protein aggregates increased while the amount of monomeric protein decreased. Omega-gliadin was the major monomeric protein that decreased in quantity. Interestingly, the amount of larger-sized protein aggregates decreased and that of smaller-sized protein aggregates increased. The amount of gluten protein macro-polymer aggregated through strong non-covalent bonds decreased whereas aggregates formed with weaker non-covalent bonds increased. LF dough behaved similar to HF dough. Large-sized gluten protein aggregates disaggregated due to the weakening of non-covalent bonds and became smaller. Omega-gliadin was incorporated into gluten protein aggregates during dough mixing.
Reduction in Spoilage Microbiota and Cyclopiazonic Acid Mycotoxin with Chestnut Extract Enriched Chitosan Packaging: Stability of Inoculated Gouda Cheese
Authors: Kõrge Kristi , Šeme Helena , Bajić Marijan , Likozar Blaž , Novak Uroš
Published: November 2020

Active chitosan-based films, blended with fibrous chestnut (Castanea sativa Mill.) tannin-rich extract were used to pack Gouda cheese that has been contaminated with spoilage microflora Pseudomonas fluorescens, Escherichia coli, and fungi Penicillium commune. A comprehensive experimental plan including active chitosan-based films with (i) chestnut extract (CE), (ii) tannic acid (TA), and (iii) without additives was applied to evaluate the film′s effect on induced microbiological spoilage reduction and chemical indices of commercial Gouda cheese during 37 days while stored at 4 °C and 25 °C, respectively. The cheese underwent microbiology analysis and chemical assessments of ultra-high-performance liquid chromatography (UHPLC) (cyclopiazonic acid), pH, and moisture content. The biopackaging used for packing cheese was characterized by mechanical properties before food packaging and analyzed with the same chemical analysis. The cheese microbiology showed that the bacterial counts were most efficiently decreased by the film without additives. However, active films with CE and TA were more effective as they did not break down around the cheese and showed protective properties against mycotoxin, moisture loss, and pH changes. Films themselves, when next to high-fat content food, changed their pH to less acidic, acted as absorbers, and degraded without plant-derived additives.
Review about Non-Lipid Components and Minor Fat-Soluble Bioactive Compounds of Almond Kernel
Authors: Roncero José M. , Álvarez-Ortí Manuel , Pardo-Giménez Arturo , Rabadán Adrián , Pardo José E.
Published: November 2020

This work presents a bibliographic review about almond kernel non-lipid components, in particular about the protein fraction, the carbohydrates and the mineral fraction. In addition, other fat-soluble phytochemicals which are present in minor concentrations but show important antioxidant activities are reviewed. Almond kernel is a rich protein food (8.4–35.1%), in which the globulin–albumin fraction dominates, followed by glutelins and prolamins. Within the almond kernel protein profile, amandine dominates. Free amino acids represent a small amount of the total nitrogen quantity, highlighting the presence of glutamic acid and aspartic acid, followed by arginine. Carbohydrates that appear in almond kernels (14–28%) are soluble sugars (mainly sucrose), starch and other polysaccharides such as cellulose and non-digestible hemicelluloses. Regarding the mineral elements, potassium is the most common, followed by phosphorus; both macronutrients represent more than 70% of the total mineral fraction, without taking into account nitrogen. Microminerals include sodium, iron, copper, manganese and zinc. Within the phytochemical compounds, tocopherols, squalene, phytosterols, stanols, sphingolipids, phospholipids, chlorophylls, carotenoids, phenols and volatile compounds can be found.
Predictors of Staying at Home during the COVID-19 Pandemic and Social Lockdown based on Protection Motivation Theory: A Cross-Sectional Study in Japan
Authors: Okuhara Tsuyoshi , Okada Hiroko , Kiuchi Takahiro
Published: November 2020

During the COVID-19 pandemic, a social lockdown should be put in place and individuals should stay at home. Behavioral change is the only way to prevent the pandemic and overwhelmed healthcare systems until vaccines are available. We aimed to examine the psychological factors that predict staying at home during the COVID-19 pandemic and social lockdown. A total of 1980 participants in Japan completed a survey for this study from 9 to 11 May 2020, when the state of emergency covered all prefectures in the country. Self-reported behavior in terms of staying at home, the perceived severity of the pandemic, vulnerability to the pandemic, response efficacy, and self-efficacy based on protection motivation theory were assessed. Multiple regression analysis showed that perceived severity (standardized β = 0.11, p < 0.001) and self-efficacy (standardized β = 0.32, p < 0.001) significantly predicted greater levels of staying at home, after controlling for socio-demographics. However, perceived vulnerability and response efficacy did not. To encourage people to stay at home during the pandemic and social lockdown, increasing the perceived severity of infection by COVID-19 and self-efficacy in terms of exercising restraint with respect to going out may consequently encourage people to stay at home.
Compilation and Analysis of Web-Based Orthopedic Personalized Predictive Tools: A Scoping Review
Authors: Curtin Patrick , Conway Alexandra , Martin Liu , Lin Eugenia , Jayakumar Prakash , Swart Eric
Published: November 2020

Web-based personalized predictive tools in orthopedic surgery are becoming more widely available. Despite rising numbers of these tools, many orthopedic surgeons may not know what tools are available, how these tools were developed, and how they can be utilized. The aim of this scoping review is to compile and synthesize the profile of existing web-based orthopedic tools. We conducted two separate PubMed searches—one a broad search and the second a more targeted one involving high impact journals—with the aim of comprehensively identifying all existing tools. These articles were then screened for functional tool URLs, methods regarding the tool’s creation, and general inputs and outputs required for the tool to function. We identified 57 articles, which yielded 31 unique web-based tools. These tools involved various orthopedic conditions (e.g., fractures, osteoarthritis, musculoskeletal neoplasias); interventions (e.g., fracture fixation, total joint arthroplasty); outcomes (e.g., mortality, clinical outcomes). This scoping review highlights the availability and utility of a vast array of web-based personalized predictive tools for orthopedic surgeons. Increased awareness and access to these tools may allow for better decision support, surgical planning, post-operative expectation management, and improved shared decision-making.
An Improved Approach to Direct Simulation of an Actual Almen Shot Peening Intensity Test with a Large Number of Shots
Authors: Wang Chengyu , Li Weigang , Jiang Jianjun , Chao Xin , Zeng Weikui , Xu Jiang , Yang Jie
Published: November 2020

In existing simulations of the Almen intensity test, arc height is indirectly obtained by an equivalent method including a representative cell, a few shots and equivalent loading. Most of these equivalent methods cannot consider the transverse deformation of the strip, the complex stress state of the plastic hardening layer and process parameters, resulting in deviation from the actual test. This paper introduces an improved and experimentally validated discrete element model (DEM)-finite element model (FEM) to predict the actual Almen intensity. The improvement of this model is mainly reflected in the large and real number of shots involved in the actual Almen intensity test, shot–shot interactions, and real-size solid finite element model of the Almen strip. A new method for calculating the shot stream is proposed based on the test and considering test process parameters such as the mass flowrate, nozzle movement speed and nozzle–workpiece distance. The shot stream impacting the strip with a fully restrained underside was first simulated in improved DEM-FEM to bring the forming energy. As a second step, an implicit solver of the Almen strip FEM calculates the spring-back to simulate strip removal from the holder. The results achieved by the present approach are compared with the results obtained by the experimental results and those in the literature. The results show that the arc height and Almen intensity obtained by the present approach match much better with the literature than the traditional method. Some new results obtained by the improved coupling DEM-FEM method are presented. The influences of the transverse deformation and surface plastic layer on the deformation of the Almen strip are discussed. This improved method provides an alternative characterization method for precision peen forming simulation.
Extended Fuzzy Analytic Hierarchy Process (E-FAHP): A General Approach
Authors: Reig-Mullor Javier , Pla-Santamaria David , Garcia-Bernabeu Ana
Published: November 2020

Fuzzy analytic hierarchy process (FAHP) methodologies have witnessed a growing development from the late 1980s until now, and countless FAHP based applications have been published in many fields including economics, finance, environment or engineering. In this context, the FAHP methodologies have been generally restricted to fuzzy numbers with linear type of membership functions (triangular numbers—TN—and trapezoidal numbers—TrN). This paper proposes an extended FAHP model (E-FAHP) where pairwise fuzzy comparison matrices are represented by a special type of fuzzy numbers referred to as (m,n)-trapezoidal numbers (TrN (m,n)) with nonlinear membership functions. It is then demonstrated that there are a significant number of FAHP approaches that can be reduced to the proposed E-FAHP structure. A comparative analysis of E-FAHP and Mikhailov’s model is illustrated with a case study showing that E-FAHP includes linear and nonlinear fuzzy numbers.
Microbial Shifts Following Five Years of Cover Cropping and Tillage Practices in Fertile Agroecosystems
Authors: Kim Nakian , Zabaloy María C. , Riggins Chance W. , Rodríguez-Zas Sandra , Villamil María B.
Published: November 2020

Metagenomics in agricultural research allows for searching for bioindicators of soil health to characterize changes caused by management practices. Cover cropping (CC) improves soil health by mitigating nutrient losses, yet the benefits depend on the tillage system used. Field studies searching for indicator taxa within these systems are scarce and narrow in their scope. Our goal was to identify bioindicators of soil health from microbes that were responsive to CC (three levels) and tillage (chisel tillage, no-till) treatments after five years under field conditions. We used rRNA gene-based analysis via Illumina HiSeq2500 technology with QIIME 2.0 processing to characterize the microbial communities. Our results indicated that CC and tillage differentially changed the relative abundances (RAs) of the copiotrophic and oligotrophic guilds. Corn–soybean rotations with legume–grass CC increased the RA of copiotrophic decomposers more than rotations with grass CC, whereas rotations with only bare fallows favored stress-tolerant oligotrophs, including nitrifiers and denitrifiers. Unlike bacteria, fewer indicator fungi and archaea were detected; fungi were poorly identified, and their responses were inconsistent, while the archaea RA increased under bare fallow treatments. This is primary information that allows for understanding the potential for managing the soil community compositions using cover crops to reduce nutrient losses to the environment.
Exosomes of Epstein-Barr Virus-Associated Gastric Carcinoma Suppress Dendritic Cell Maturation
Authors: Hinata Munetoshi , Kunita Akiko , Abe Hiroyuki , Morishita Yasuyuki , Sakuma Kei , Yamashita Hiroharu , Seto Yasuyuki , Ushiku Tetsuo , Fukayama Masashi
Published: November 2020

The Epstein-Barr virus (EBV)-associated gastric carcinoma (EBVaGC) is characterized by the infiltration of lymphocytes and a unique tumor microenvironment. Exosomes from cancer cells are essential for intercellular communication. The aims of this study were to investigate the secretion of EBVaGC exosomes and their physiological effect on dendritic cell maturation in vitro and to characterize dendritic cells (DCs) in EBVaGC in vivo. Western blotting analysis of CD63 and CD81 of exosomes from EBV-infected gastric cancer cell lines indicated an increase in exosome secretion. The fraction of monocyte-derived DCs positive for the maturation marker CD86 was significantly suppressed when incubated with exosomes from EBV-infected gastric cancer cell lines. Immunohistochemical analysis of GC tissues expressing DC markers (S100, Langerin, CD1a, CD83, CD86, and BDCA-2) indicated that the density of DCs was generally higher in EBVaGC than in EBV-negative GC, although the numbers of CD83- and CD86-positive DCs were decreased in the group with high numbers of CD1a-positive DCs. A low number of CD83-positive DCs was marginally correlated with worse prognosis of EBVaGC in patients. EBVaGC is a tumor with abundant DCs, including immature and mature DCs. Moreover, the maturation of DCs is suppressed by exosomes from EBV-infected epithelial cells.
The Tres Arroyos Granitic Aplite-Pegmatite Field (Central Iberian Zone, Spain): Petrogenetic Constraints from Evolution of Nb-Ta-Sn Oxides, Whole-Rock Geochemistry and U-Pb Geochronology
Authors: Garate-Olave Idoia , Roda-Robles Encarnación , Gil-Crespo Pedro Pablo , Pesquera Alfonso , Errandonea-Martin Jon
Published: November 2020

Abundant Li-Cs-Ta aplite-pegmatite dykes were emplaced in the western Central Iberian Zone of the Iberian Massif during the Variscan Orogeny. Their origin and petrogenetic relationships with the widespread granitoids have led to a currently rekindled discussion about anatectic vs. granitic origin for the pegmatitic melts. To deal with these issues, the aplite-pegmatite dykes from the Tres Arroyos area, which constitute a zoned pegmatitic field related to the Nisa-Alburquerque granitic batholith, have been studied. This work comprises a complete study of Nb-Ta-Sn oxides’ mineralogy, whole-rock geochemistry, and U-Pb geochronology of the aplite-pegmatites that have been grouped as barren, intermediate, and Li-rich. The most abundant Nb-Ta-Sn oxides from Tres Arroyos correspond to columbite-(Fe), columbite-(Mn) and cassiterite. Niobium-Ta oxides show a marked increase in the Mn/(Mn+Fe) ratio from the barren aplite-pegmatites up to the Li-rich bodies, whereas variations in the Ta/(Ta+Nb) ratio are not continuous. The probable factors controlling fractionation of Mn/Fe and Ta/Nb reflected in Nb-Ta oxides may be attributed to the crystallization of tourmaline, phosphates and micas. The lack of a progressive Ta/Nb increase with the fractionation may be also influenced by the high F and P availability in the parental pegmatitic melts. Most of the primary Nb-Ta oxides would have crystallized by punctual chemical variations in the boundary layer, whereas cassiterite formation would be related to an undercooling of the system. Whole-rock composition of the distinguished lithotypes reflects similar tendencies to those observed in mineral chemistry, supporting a single path of fractional crystallization from the parental Nisa-Alburquerque monzogranite up to the most evolved Li-rich aplite-pegmatites. The age of 305 ± 9 Ma, determined by LA-ICP-MS U-Pb dating of columbite-tantalite oxides, reinforces the linkage of the studied aplite-pegmatites and the cited parental monzogranite.
Intentions to “Reuse” Medication in the Future Modelled and Measured Using the Theory of Planned Behavior
Authors: Alhamad Hamza , Donyai Parastou
Published: November 2020

Background: A range of pro-environmental behaviors are recognized, promoted, and investigated, but urgent action is also needed to tackle the direct and indirect environmental impact of medication waste. One solution is to reissue medicines, returned unused to pharmacies (i.e., reuse medicines). Yet, if medicines reuse is to be formally introduced in the UK, it is imperative also to understand people’s willingness to take part in such a scheme and importantly, the underpinning drivers. This study aimed to develop, validate, and evaluate a Theory of Planned Behavior model aimed at predicting medicines reuse behavioral intentions. Methods: The behavior of interest, medicines reuse, was defined according to its Target, Action, Context, and Time. Then themes from an existing qualitative study were used in order to draft, validate and pilot a Theory of Planned Behavior-based questionnaire before its completion by a representative sample (n = 1003) of participants from across the UK. Results: The majority expressed pro-medicines reuse intentions. The three direct measures accounted for 73.4% of the variance in relation to people’s intention to reuse medicines in the future, which was statistically significant at p < 0.001. People’s specific beliefs about medicines reuse and how they evaluate other people’s expectations of them had a substantial impact on their intentions to reuse medication in the future, mediated in an intricate way via attitudes, subjective norms and perceived behavioral control (PBC). Conclusions: This study shows how people could embrace medicines reuse via practical measures that illustrate the safety and quality assurance of reissued medicines, educational interventions that bolster beliefs about the pro-environmental benefits, and norm-based interventions encouraging doctors and pharmacists to endorse the practice. The findings add to the emerging work on medicines reuse and, significantly, provide a theoretical framework to guide policymakers and other organizations looking to decrease the impact of medication waste through medicines reuse schemes.
Generalized Inequalities to Optimize the Fitting Method for Track Reconstruction
Authors: Landi Gregorio , Landi Giovanni E.
Published: November 2020

A standard criterium in statistics is to define an optimal estimator as the one with the minimum variance. Thus, the optimality is proved with inequality among variances of competing estimators. The demonstrations of inequalities among estimators are essentially based on the Cramer, Rao and Frechet methods. They require special analytical properties of the probability functions, globally indicated as regular models. With an extension of the Cramer–Rao–Frechet inequalities and Gaussian distributions, it was proved the optimality (efficiency) of the heteroscedastic estimators compared to any other linear estimator. However, the Gaussian distributions are a too restrictive selection to cover all the realistic properties of track fitting. Therefore, a well-grounded set of inequalities must overtake the limitations to regular models. Hence, the inequalities for least-squares estimators are generalized to any model of probabilities. The new inequalities confirm the results obtained for the Gaussian distributions and generalize them to any irregular or regular model. Estimators for straight and curved tracks are considered. The second part deals with the shapes of the distributions of simplified heteroscedastic track models, reconstructed with optimal estimators and the standard (non-optimal) estimators. A comparison among the distributions of these different estimators shows the large loss in resolution of the standard least-squares estimators.
Sustainable Production–Inventory Model in Technical Cooperation on Investment to Reduce Carbon Emissions
Authors: Pan JiaLiang , Chiu Chui-Yu , Wu Kun-Shan , Yen Hsiu-Feng , Wang Yen-Wen
Published: November 2020

Carbon cap-and-trade and carbon offsets are common and important carbon emission reduction policies in many countries. In addition, carbon emissions from business activities can be effectively reduced through specific capital investments in green technologies. Nevertheless, such capital investments are costly and not all enterprises can afford these investments. Therefore, if all members of a supply chain agree to share the investments in the facilities, the supply chain can reduce carbon emissions and generate more profit. Under carbon cap-and-trade and carbon tax policies, this study proposes a production–inventory model in which the buyer and vendor in the integrated supply chain agree to co-invest funds to reduce carbon emissions. We planned to integrate production, delivery, replenishment, and technology to reduce carbon emissions so as to maximize the total profit of the supply chain system. Several examples are simulated and the sensitivity analysis of the main parameters is carried out. The optimal solutions and joint total profit under various carbon emission policies are also compared. The future carbon emission control trend is expected to enable companies to share risks by co-investing and developing sustainable supply chains.
Influence of Tip Clearance on Flow Characteristics of Axial Compressor
Authors: Song Moru , Xie Hong , Yang Bo , Zhang Shuyi
Published: November 2020

This paper studies the influence of tip clearance on the flow characteristics related to the performance. Based on full-passage numerical simulation with experimental validation, several clearance models are established and the performance curves are obtained. It is found that there exists an optimum clearance for the stable working range. By analyzing the flow field in tip region, the role of the tip leakage flow is illustrated. In the zero-clearance model, the separation and blockage along the suction side is the main reason for rotating stall. As the tip clearance is increased to the optimum value, the separation is suppressed by the tip leakage flow. However, with the continuing increasing of the tip clearance, the scale and strength of the tip clearance vortex is increased correspondingly. When the tip clearance is larger than the optimum value, the tip clearance vortex gradually dominates the flow field in the tip region, which can increase the unsteadiness in the tip region and trigger forward spillage in stall onset.
Extraction of Anthocyanins from Red Raspberry for Natural Food Colorants Development: Processes Optimization and In Vitro Bioactivity
Authors: Rocha Rosiane , Pinela José , Abreu Rui M.V. , Añibarro-Ortega Mikel , Pires Tânia C.S.P. , Saldanha Ana Luísa , Alves Maria José , Nogueira António , Ferreira Isabel C.F.R. , Barros Lillian
Published: November 2020

Heat (HAE)- and ultrasound (UAE)-assisted extraction methods were implemented to recover anthocyanins from red raspberry. Processing time, ethanol concentration, and temperature or ultrasonic power were the independent variables combined in five-level rotatable central composite designs coupled with response surface methodology (RSM) for processes optimization. The extraction yield and levels of cyanidin-3-O-sophoroside (C3S) and cyanidin-3-O-glucoside (C3G) were monitored by gravimetric and HPLC-DAD-ESI/MSn methods, respectively, and used as response criteria. The constructed theoretical models were successfully fitted to the experimental data and used to determine the optimal extraction conditions. When maximizing all responses simultaneously, HAE originated slightly higher response values (61% extract weight and 8.7 mg anthocyanins/g extract) but needed 76 min processing at 38 °C, with 21% ethanol (v/v), while the UAE process required 16 min sonication at 466 W, using 38% ethanol (v/v). The predictive models were experimentally validated, and the purple-red extracts obtained under optimal condition showed antioxidant activity through lipid peroxidation and oxidative hemolysis inhibition, and antibacterial effects against food-related microorganisms, such as Escherichia coli and Enterococcus faecalis. These results highlight the potential of red raspberry extracts as natural food colorants with bioactive effects and could be exploited by industries interested in the production of anthocyanin-based products.
Classification of the Complex Agricultural Planting Structure with a Semi-Supervised Extreme Learning Machine Framework
Authors: Feng Ziyi , Huang Guanhua , Chi Daocai
Published: November 2020

Many approaches have been developed to analyze remote sensing images. However, for the classification of large-scale problems, most algorithms showed low computational efficiency and low accuracy. In this paper, the newly developed semi-supervised extreme learning machine (SS-ELM) framework with k-means clustering algorithm for image segmentation and co-training algorithm to enlarge the sample sets was used to classify the agricultural planting structure at large-scale areas. Data sets collected from a small-scale area within the Hetao Irrigation District (HID) at the upper reaches of the Yellow River basin were used to evaluate the SS-ELM framework. The results of the SS-ELM algorithm were compared with those of the random forest (RF), ELM, support vector machine (SVM) and semi-supervised support vector machine (S-SVM) algorithms. Then the SS-ELM algorithm was applied to analyze the complex planting structure of HID in 1986–2010 by comparing the remote sensing estimated results with the statistical data. In the small-scale case, the SS-ELM algorithm performed better than the RF, ELM, SVM, and S-SVM algorithms. For the SS-ELM algorithm, the average overall accuracy (OA) was in a range of 83.00–92.17%. On the contrary, for the other four algorithms, their average OA values ranged from 56.97% to 92.84%. Whereas, in the classification of planting structure in HID, the SS-ELM algorithm had an excellent performance in classification accuracy and computational efficiency for three major planting crops including maize, wheat, and sunflowers. The estimated areas by using the SS-ELM algorithm based on the remote sensing images were consistent with the statistical data, and their difference was within a range of 3–25%. This implied that the SS-ELM framework could be served as an effective method for the classification of complex planting structures with relatively fast training, good generalization, universal approximation capability, and reasonable learning accuracy.
The Sensitivity Improvement Characterization of Distributed Strain Sensors Due to Weak Fiber Bragg Gratings
Authors: Stepanov Konstantin V. , Zhirnov Andrey A. , Chernutsky Anton O. , Koshelev Kirill I. , Pnev Alexey B. , Lopunov Alexey I. , Butov Oleg V.
Published: November 2020

Weak fiber Bragg gratings (WFBGs) in a phase-sensitive optical time-domain reflectometer (phi-OTDR) sensor offer opportunities to significantly improve the signal-to-noise ratio (SNR) and sensitivity of the device. Here, we demonstrate the process of the signal and noise components’ formation in the device reflectograms for a Rayleigh scattering phi-OTDR and a WFBG-based OTDR. We theoretically calculated the increase in SNR when using the same optical and electrical components under the same external impacts for both setups. The obtained values are confirmed on experimental installations, demonstrating an improvement in the SNR by about 19 dB at frequencies of 20, 100, and 400 Hz. In this way, the minimum recorded impact (at the threshold SNR = 10) can be reduced from 100 nm per 20 m of fiber to less than 5 nm per 20 m of fiber sensor.
A Two-Phase Distributed Filtering Algorithm for Networked Uncertain Systems with Fading Measurements under Deception Attacks
Authors: Caballero-Águila Raquel , Hermoso-Carazo Aurora , Linares-Pérez Josefa
Published: November 2020

In this paper, the distributed filtering problem is addressed for a class of discrete-time stochastic systems over a sensor network with a given topology, susceptible to suffering deception attacks, launched by potential adversaries, which can randomly succeed or not with a known success probability, which is not necessarily the same for the different sensors. The system model integrates some random imperfections and features that are frequently found in real networked environments, namely: (1) fading measurements; (2) multiplicative noises in both the state and measurement equations; and (3) sensor additive noises cross-correlated with each other and with the process noise. According to the network communication scheme, besides its own local measurements, each sensor receives the measured outputs from its adjacent nodes. Based on such measurements, a recursive algorithm is designed to obtain the least-squares linear filter of the state. Thereafter, each sensor receives the filtering estimators previously obtained by its adjacent nodes, and these estimators are all fused to obtain the desired distributed filter as the minimum mean squared error matrix-weighted linear combination of them. The theoretical results are illustrated by a simulation example, where the efficiency of the developed distributed estimation strategy is discussed in terms of the error variances.