bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Driven Corrections of Partial Lotka–Volterra Models
Authors: Morrison Rebecca E.
Published: November 2020

In many applications of interacting systems, we are only interested in the dynamic behavior of a subset of all possible active species. For example, this is true in combustion models (many transient chemical species are not of interest in a given reaction) and in epidemiological models (only certain subpopulations are consequential). Thus, it is common to use greatly reduced or partial models in which only the interactions among the species of interest are known. In this work, we explore the use of an embedded, sparse, and data-driven discrepancy operator to augment these partial interaction models. Preliminary results show that the model error caused by severe reductions—e.g., elimination of hundreds of terms—can be captured with sparse operators, built with only a small fraction of that number. The operator is embedded within the differential equations of the model, which allows the action of the operator to be interpretable. Moreover, it is constrained by available physical information and calibrated over many scenarios. These qualities of the discrepancy model—interpretability, physical consistency, and robustness to different scenarios—are intended to support reliable predictions under extrapolative conditions.
Thermodynamic Evaluation and Sensitivity Analysis of a Novel Compressed Air Energy Storage System Incorporated with a Coal-Fired Power Plant
Authors: Pan Peiyuan , Zhang Meiyan , Peng Weike , Chen Heng , Xu Gang , Liu Tong
Published: November 2020

A novel compressed air energy storage (CAES) system has been developed, which is innovatively integrated with a coal-fired power plant based on its feedwater heating system. In the hybrid design, the compression heat of the CAES system is transferred to the feedwater of the coal power plant, and the compressed air before the expanders is heated by the feedwater taken from the coal power plant. Furthermore, the exhaust air of the expanders is employed to warm partial feedwater of the coal power plant. Via the suggested integration, the thermal energy storage equipment for a regular CAES system can be eliminated and the performance of the CAES system can be improved. Based on a 350 MW supercritical coal power plant, the proposed concept was thermodynamically evaluated, and the results indicate that the round-trip efficiency and exergy efficiency of the new CAES system can reach 64.08% and 70.01%, respectively. Besides, a sensitivity analysis was conducted to examine the effects of ambient temperature, air storage pressure, expander inlet temperature, and coal power load on the performance of the CAES system. The above work proves that the novel design is efficient under various conditions, providing important insights into the development of CAES technology.
A Framework for Big Data Analytical Process and Mapping—BAProM: Description of an Application in an Industrial Environment
Authors: de Carvalho Chrysostomo Giovanni Gravito , de Aguiar Vallim Marco Vinicius Bhering , da Silva Leilton Santos , Silva Leandro A. , de Aguiar Vallim Filho Arnaldo Rabello
Published: November 2020

This paper presents an application of a framework for Big Data Analytical Process and Mapping—BAProM—consisting of four modules: Process Mapping, Data Management, Data Analysis, and Predictive Modeling. The framework was conceived as a decision support tool for industrial business, encompassing the whole big data analytical process. The first module incorporates in big data analytical a mapping of processes and variables, which is not common in such processes. This is a proposal that proved to be adequate in the practical application that was developed. Next, an analytical “workbench” was implemented for data management and exploratory analysis (Modules 2 and 3) and, finally, in Module 4, the implementation of artificial intelligence algorithm support predictive processes. The modules are adaptable to different types of industry and problems and can be applied independently. The paper presents a real-world application seeking as final objective the implementation of a predictive maintenance decision support tool in a hydroelectric power plant. The process mapping in the plant identified four subsystems and 100 variables. With the support of the analytical workbench, all variables have been properly analyzed. All underwent a cleaning process and many had to be transformed, before being subjected to exploratory analysis. A predictive model, based on a decision tree (DT), was implemented for predictive maintenance of equipment, identifying critical variables that define the imminence of an equipment failure. This DT model was combined with a time series forecasting model, based on artificial neural networks, to project those critical variables for a future time. The real-world application showed the practical feasibility of the framework, particularly the effectiveness of the analytical workbench, for pre-processing and exploratory analysis, as well as the combined predictive model, proving effectiveness by providing information on future events leading to equipment failures.
Exergoeconomic and Environmental Modeling of Integrated Polygeneration Power Plant with Biomass-Based Syngas Supplemental Firing
Authors: Abam Fidelis. I. , Diemuodeke Ogheneruona E. , Ekwe Ekwe. B. , Alghassab Mohammed , Samuel Olusegun D. , Khan Zafar A. , Imran Muhammad , Farooq Muhammad
Published: November 2020

There is a burden of adequate energy supply for meeting demand and reducing emission to avoid the average global temperature of above 2 °C of the pre-industrial era. Therefore, this study presents the exergoeconomic and environmental analysis of a proposed integrated multi-generation plant (IMP), with supplemental biomass-based syngas firing. An in-service gas turbine plant, fired by natural gas, was retrofitted with a gas turbine (GT), steam turbine (ST), organic Rankine cycle (ORC) for cooling and power production, a modified Kalina cycle (KC) for power production and cooling, and a vapour absorption system (VAB) for cooling. The overall network, energy efficiency, and exergy efficiency of the IMP were estimated at 183 MW, 61.50% and 44.22%, respectively. The specific emissions were estimated at 122.2, 0.222, and 3.0 × 10−7 kg/MWh for CO2, NOx, and CO, respectively. Similarly, the harmful fuel emission factor, and newly introduced sustainability indicators—exergo-thermal index (ETI) and exergetic utility exponent (EUE)—were obtained as 0.00067, 0.675, and 0.734, respectively. The LCC of $1.58 million was obtained, with a payback of 4 years, while the unit cost of energy was estimated at 0.0166 $/kWh. The exergoeconomic factor and the relative cost difference of the IMP were obtained as 50.37% and 162.38%, respectively. The optimum operating parameters obtained by a genetic algorithm gave the plant’s total cost rate of 125.83 $/hr and exergy efficiency of 39.50%. The proposed system had the potential to drive the current energy transition crisis caused by the COVID-19 pandemic shock in the energy sector.
A Novel Method for Obtaining the Signature of Household Consumer Pairs
Authors: Căiman Dadiana-Valeria , Dragomir Toma-Leonida
Published: November 2020

The management of electricity consumption by household consumers requires multiple ways of consumer monitoring. One of these is the signature i(v) determined by monitoring the consumer voltage-current trajectory. The paper proposes a novel method for obtaining signatures of 2-multiple consumers, i.e., a pair of consumers connected in parallel. Signatures are obtained from samples of the voltage at the consumers’ terminals and of the total current absorbed by the consumers, measured at a frequency of only 20 Hz. Within the method, signatures are calculated using genetic algorithms (GA) and nonlinear regression, according to a procedure developed by the authors in a previous paper. The management of the data selected for the signature assignment represents the novelty. The method proposed in this paper is applied in two case studies, one concerning household consumers within the same power level, the other for household consumers of different power levels. The results confirm the possibility of obtaining signatures of i(v) type.
A Salt-Signaling Network Involving Ethylene, Extracellular ATP, Hydrogen Peroxide, and Calcium Mediates K+/Na+ Homeostasis in Arabidopsis
Authors: Lang Tao , Deng Chen , Yao Jun , Zhang Huilong , Wang Yin , Deng Shurong
Published: November 2020

This work aimed at investigating the interactive effects of salt-signaling molecules, i.e., ethylene, extracellular ATP (eATP), H2O2, and cytosolic Ca2+ ([Ca2+]cyt), on the regulation of K+/Na+ homeostasis in Arabidopsisthaliana. The presence of eATP shortened Col-0 hypocotyl length under no-salt conditions. Moreover, eATP decreased relative electrolyte leakage and lengthened root length significantly in salt-treated Col-0 plants but had no obvious effects on the ethylene-insensitive mutants etr1-1 and ein3-1eil1-1. Steady-state ionic flux kinetics showed that exogenous 1-aminocyclopropane-1-carboxylic acid (ACC, an ethylene precursor) and eATP-Na2 (an eATP donor) significantly increased Na+ extrusion and suppressed K+ loss during short-term NaCl treatment. Moreover, ACC remarkably raised the fluorescence intensity of salt-elicited H2O2 and cytosolic Ca2+. Our qPCR data revealed that during 12 h of NaCl stress, application of ACC increased the expression of AtSOS1 and AtAHA1, which encode the plasma membrane (PM) Na+/H+ antiporters (SOS1) and H+-ATPase (H+ pumps), respectively. In addition, eATP markedly increased the transcription of AtEIN3, AtEIL1, and AtETR1, and ACC treatment of Col-0 roots under NaCl stress conditions caused upregulation of AtRbohF and AtSOS2/3, which directly contribute to the H2O2 and Ca2+ signaling pathways, respectively. Briefly, ethylene was triggered by eATP, a novel upstream signaling component, which then activated and strengthened the H2O2 and Ca2+ signaling pathways to maintain K+/Na+ homeostasis under salinity.
Groundbreaking Anticancer Activity of Highly Diversified Oxadiazole Scaffolds
Authors: Benassi Alessandra , Doria Filippo , Pirota Valentina
Published: November 2020

Nowadays, an increasing number of heterocyclic-based drugs found application in medicinal chemistry and, in particular, as anticancer agents. In this context, oxadiazoles—five-membered aromatic rings—emerged for their interesting biological properties. Modification of oxadiazole scaffolds represents a valid strategy to increase their anticancer activity, especially on 1,2,4 and 1,3,4 regioisomers. In the last years, an increasing number of oxadiazole derivatives, with remarkable cytotoxicity for several tumor lines, were identified. Structural modifications, that ensure higher cytotoxicity towards malignant cells, represent a solid starting point in the development of novel oxadiazole-based drugs. To increase the specificity of this strategy, outstanding oxadiazole scaffolds have been designed to selectively interact with biological targets, including enzymes, globular proteins, and nucleic acids, showing more promising antitumor effects. In the present work, we aim to provide a comprehensive overview of the anticancer activity of these heterocycles, describing their effect on different targets and highlighting how their structural versatility has been exploited to modulate their biological properties.
New In Vitro Model of Oxidative Stress: Human Prostate Cells Injured with 2,2-diphenyl-1-picrylhydrazyl (DPPH) for the Screening of Antioxidants
Authors: Galasso Christian , Piscitelli Concetta , Brunet Christophe , Sansone Clementina
Published: November 2020

The antioxidant activity of natural compounds consists in their ability to modulate gene and protein expression, thus inducing an integrated cell protective response and repair processes against oxidative stress. New screening tools and methodologies are crucial for the actual requirement of new products with antioxidant activity to boost endogenous oxidative stress responsive pathways, Reactive Oxygen Species (ROS) metabolism and immune system activity, preserving human health and wellness. In this study, we performed and tested an integrated oxidative stress analysis, using DPPH assay and PNT2 cells injured with DPPH. We firstly investigated the mechanism of action of the oxidising agent (DPPH) on PNT2 cells, studying the variation in cell viability, oxidative stress genes, inflammatory mediator and ROS levels. The results reveal that DPPH activated ROS production and release of Prostaglandin E2 in PNT2 at low and intermediate doses, while cells switched from survival to cell death signals at high doses of the oxidising agent. This new in vitro oxidative stress model was validated by using Trolox, β-carotene and total extract of the green microalga Testraselmis suecica. Only the T. suecica extract can completely counteract DPPH-induced injury, since its chemical complexity demonstrated a multilevel protecting and neutralising effect against oxidative stress in PNT2.
Therapeutic Effect of Calcimimetics on Osteoclast–Osteoblast Crosslink in Chronic Kidney Disease and Mineral Bone Disease
Authors: Hung Kuo-Chin , Chang Jia-Feng , Hsu Yung-Ho , Hsieh Chih-Yu , Wu Mai-Szu , Wu Mei-Yi , Chiu I-Jen , Syu Ren-Si , Wang Ting-Ming , Wu Chang-Chin , Hung Lie-Yee , Zheng Cai-Mei , Lu Kuo-Cheng
Published: November 2020

We have previously demonstrated calcimimetics optimize the balance between osteoclastic bone resorption and osteoblastic mineralization through upregulating Wingless and int-1 (Wnt) signaling pathways in the mouse and cell model. Nonetheless, definitive human data are unavailable concerning therapeutic effects of Cinacalcet on chronic kidney disease and mineral bone disease (CKD-MBD) and osteoclast–osteoblast interaction. We aim to investigate whether Cinacalcet therapy improves bone mineral density (BMD) through optimizing osteocytic homeostasis in a human model. Hemodialysis patients with persistently high intact parathyroid hormone (iPTH) levels > 300 pg/mL for more than 3 months were included and received fixed dose Cinacalcet (25 mg/day, orally) for 6 months. Bone markers presenting osteoclast–osteoblast communication were evaluated at baseline, the 3rd and the 6th month. Eighty percent of study patients were responding to Cinacalcet treatment, capable of improving BMD, T score and Z score (16.4%, 20.7% and 11.1%, respectively). A significant correlation between BMD improvement and iPTH changes was noted (r = −0.26, p < 0.01). Nonetheless, baseline lower iPTH level was associated with better responsiveness to Cinacalcet therapy. Sclerostin, an inhibitor of canonical Wnt/β-catenin signaling, was decreased from 127.3 ± 102.3 pg/mL to 57.9 ± 33.6 pg/mL. Furthermore, Wnt-10b/Wnt 16 expressions were increased from 12.4 ± 24.2/166.6 ± 73.3 pg/mL to 33.8 ± 2.1/217.3 ± 62.6 pg/mL. Notably, procollagen type I amino-terminal propeptide (PINP), a marker of bone formation and osteoblastic activity, was increased from baseline 0.9 ± 0.4 pg/mL to 91.4 ± 42.3 pg/mL. In contrast, tartrate-resistant acid phosphatase isoform 5b (TRACP-5b), a marker of osteoclast activity, was decreased from baseline 16.5 ± 0.4 mIU/mL to 7.7 ± 2.2 mIU/mL. Moreover, C-reactive protein levels were suppressed from 2.5 ± 0.6 to 0.8 ± 0.5 mg/L, suggesting the systemic inflammatory burden may be benefited after optimizing the parathyroid–bone axis. In conclusion, beyond iPTH suppression, our human model suggests Cinacalcet intensifies BMD through inhibiting sclerostin expression and upregulating Wnt-10b/Wnt 16 signaling that activates osteoblastic bone formation and inhibits osteoclastic bone resorption and inflammation. From the perspective of translation to humans, this research trial brings a meaningful insight into the osteoblast–osteoclast homeostasis in Cinacalcet therapy for CKD-MBD.
Genetic Carriers and Genomic Distribution of cadA6—A Novel Variant of a Cadmium Resistance Determinant Identified in Listeria spp.
Authors: Chmielowska Cora , Korsak Dorota , Szmulkowska Barbara , Krop Alicja , Lipka Kinga , Krupińska Martyna , Bartosik Dariusz
Published: November 2020

Listeria monocytogenes is a pathogen responsible for severe cases of food poisoning. Listeria spp. strains occurring in soil and water environments may serve as a reservoir of resistance determinants for pathogenic L. monocytogenes strains. A large collection of Listeria spp. strains (155) isolated from natural, agricultural, and urban areas was screened for resistance to heavy metals and metalloids, and the presence of resistance determinants and extrachromosomal replicons. Of the tested strains, 35% were resistant to cadmium and 17% to arsenic. Sequence analysis of resistance plasmids isolated from strains of Listeria seeligeri and Listeria ivanovii, and the chromosome of L. seeligeri strain Sr73, identified a novel variant of the cadAC cadmium resistance efflux system, cadA6, that was functional in L. monocytogenes cells. The cadA6 cassette was detected in four Listeria species, including strains of L. monocytogenes, isolated from various countries and sources—environmental, food-associated, and clinical samples. This resistance cassette is harbored by four novel composite or non-composite transposons, which increases its potential for horizontal transmission. Since some cadAC cassettes may influence virulence and biofilm formation, it is important to monitor their presence in Listeria spp. strains inhabiting different environments.
Special Delivery: Potential Mechanisms of Botulinum Neurotoxin Uptake and Trafficking within Motor Nerve Terminals
Authors: Winner Brittany M. , Bodt Skylar M. L. , McNutt Patrick M.
Published: November 2020

Botulinum neurotoxins (BoNTs) are highly potent, neuroparalytic protein toxins that block the release of acetylcholine from motor neurons and autonomic synapses. The unparalleled toxicity of BoNTs results from the highly specific and localized cleavage of presynaptic proteins required for nerve transmission. Currently, the only pharmacotherapy for botulism is prophylaxis with antitoxin, which becomes progressively less effective as symptoms develop. Treatment for symptomatic botulism is limited to supportive care and artificial ventilation until respiratory function spontaneously recovers, which can take weeks or longer. Mechanistic insights into intracellular toxin behavior have progressed significantly since it was shown that toxins exploit synaptic endocytosis for entry into the nerve terminal, but fundamental questions about host-toxin interactions remain unanswered. Chief among these are mechanisms by which BoNT is internalized into neurons and trafficked to sites of molecular toxicity. Elucidating how receptor-bound toxin is internalized and conditions under which the toxin light chain engages with target SNARE proteins is critical for understanding the dynamics of intoxication and identifying novel therapeutics. Here, we discuss the implications of newly discovered modes of synaptic vesicle recycling on BoNT uptake and intraneuronal trafficking.
Discussion on Coupling Effect in Structural Load of FOWT for Condensing Wind and Wave Bins for Spectral Fatigue Analysis
Authors: Inoue Tomoya , Adilah Ahmad , Iijima Kazuhiro , Oh Sho , Suzuki Hideyuki
Published: November 2020

Floating Offshore Wind Turbines (FOWTs) are subject to combined wind and wave loads. The response is not given as a simple sum of the wind-only response and wave-only response due to nonlinear coupling effects, which makes the structural analysis more complex and time-consuming. When a spectral approach for the structural fatigue analysis is considered, it is necessary to accurately estimate the variance of the combined stress taking account of the coupling effect. In this study, firstly the characteristics of the combined response are investigated. It is found out the coupling effects are two-fold; one is the aerodynamic exciting load increase for the forced motion in the wave frequency range. The other is the aerodynamic damping effect due to the increase of the relative wind speed, which is prominent in the structural vibration frequency range. Mathematical models to account for these coupling effects are developed. Then, a series of simulations are performed on three types of FOWTs to validate the models. It is shown that the characteristics of the combined response are different among the three types of the platforms and the developed model can explain the increase/decrease of the variance of the combined stress when compared with two decoupled wave-only and wind-only simulations.
Performance of Aspergillus Galactomannan Lateral Flow Assay on Bronchoalveolar Lavage Fluid for the Diagnosis of Invasive Pulmonary Aspergillosis
Authors: Linder Kathleen A. , Kauffman Carol A. , Miceli Marisa H.
Published: November 2020

Background: Several newly developed biomarker tests for invasive pulmonary aspergillosis (IPA) have been developed, including the IMMY Aspergillus galactomannan lateral flow assay (Aspergillus GM-LFA) evaluated in this study. Methods: Twenty patients with proven/probable IPA (EORTC/MSGERC criteria) were matched by age and underlying disease with 20 patients without IPA. Bronchoalveolar lavage fluid (BALF) was analyzed in duplicate using the Aspergillus GM-LFA. Results were read visually by two blinded observers, and the optical density index (ODI) was obtained digitally with a cube reader. Results: Using a cutoff of ≥0.5 ODI, the Aspergillus GM-LFA had a sensitivity of 40%, specificity of 80%, positive predictive value (PPV) of 67% and negative predictive value (NPV) of 57%. When the cutoff was increased to ≥1.0 ODI, sensitivity remained at 40%, specificity rose to 95%, PPV was 89%, and NPV was 61%. Excellent agreement was found when duplicate samples were read either visually (κ = 1) or with the cube reader (κ = 0.89). Correlation of results obtained by visual inspection and those obtained using the cube reader was excellent (κ = 0.82). Conclusion: The Aspergillus GM-LFA had poor sensitivity but excellent specificity for proven/probable IPA in BALF. The assay was easy to interpret, and there was high concordance between results obtained visually and with a cube reader.
Temperature Differentially Affects Gene Expression in Antarctic Thraustochytrid Oblongichytrium sp. RT2316-13
Authors: Paredes Paris , Larama Giovanni , Flores Liset , Leyton Allison , Ili Carmen Gloria , Asenjo Juan A. , Chisti Yusuf , Shene Carolina
Published: November 2020

Oblongichytrium RT2316-13 synthesizes lipids rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The content of these fatty acids in the total lipids depended on growth temperature. Sequencing technology was used in this work to examine the thraustochytrid’s response to a decrease in growth temperature from 15 °C to 5 °C. Around 4% (2944) of the genes were differentially expressed (DE) and only a few of the DE genes (533 upregulated; 206 downregulated) had significant matches to those in the SwissProt database. Most of the annotated DE genes were related to cell membrane composition (fatty acids, sterols, phosphatidylinositol), the membrane enzymes linked to cell energetics, and membrane structure (cytoskeletal proteins and enzymes). In RT2316-13, the synthesis of long-chain polyunsaturated fatty acids occurred through ω3- and ω6-pathways. Enzymes of the alternative pathways (Δ8-desaturase and Δ9-elongase) were also expressed. The upregulation of the genes coding for a Δ5-desaturase and a Δ5-elongase involved in the synthesis of EPA and DHA, explained the enrichment of total lipid with these two long-chain fatty acids at the low temperature. This molecular response has the potential to be used for producing microbial lipids with a fatty acids profile similar to that of fish oils.
The Microstructure and Mechanical Properties of Cu-20Ni-20Mn Alloy Fabricated by a Compact Preparation Process
Authors: Wang Rui , Fu Yilei , Xie Guoliang , Hao Zifan , Zhang Shuai , Liu Xinhua
Published: November 2020

A novel compact preparation process has been developed to produce a Cu-20Ni-20Mn alloy. This process involves heating-cooling combined mould (HCCM) continuous casting, a solution treatment at 800 °C, rolling at room temperature and a final ageing step at 450 °C. This process eliminates two hot deformation processes, namely, hot forging and hot rolling, greatly improving production efficiency and reducing production costs compared with the traditional preparation process. The alloy fabricated by this process was found to have excellent mechanical properties. Additionally, the formation of precipitated phases during the ageing step is accelerated by this new process. The hardness of the samples reaches 476 HV after ageing for 10 h. Stable, ordered precipitates of Ni3Mn(L12 phase) are observed in the rolled specimen, and the orientation relationship between the copper matrix and ordered Ni3Mn phase (L12 phase) is [200]Cu//[010]Ni3Mn and [011]Cu//[011]Ni3Mn. Precipitation strengthening is the main reason for the increase of strength of the sample during the ageing process. The mechanical properties and ageing precipitation process of the alloy are affected by the rolling process. The precipitation rate of the rolled sample is greatly increased during the ageing process, leading to a larger amount of precipitates.
Neurology International Expands Its’ Scope and Mission: Exploring the Nervous System in Health and Disease with Emphasis on Molecular and Pathologic Aspects
Authors: Meyer Michael A.
Published: November 2020

Having served as editor-in-chief for Neurology International since its inception back in 2009, I am very pleased to see the journal grow and expand, with a major development now taking place with new ownership by MDPI, a world leader in Open Access Journal publication [...]
Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture
Authors: Hassan Syed Rizwan , Ahmad Ishtiaq , Ahmad Shafiq , Alfaify Abdullah , Shafiq Muhammad
Published: November 2020

The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.
An Integrated Deep Learning Method towards Fault Diagnosis of Hydraulic Axial Piston Pump
Authors: Tang Shengnan , Yuan Shouqi , Zhu Yong , Li Guangpeng
Published: November 2020

A hydraulic axial piston pump is the essential component of a hydraulic transmission system and plays a key role in modern industry. Considering varying working conditions and the implicity of frequent faults, it is difficult to accurately monitor the machinery faults in the actual operating process by using current fault diagnosis methods. Hence, it is urgent and significant to investigate effective and precise fault diagnosis approaches for pumps. Owing to the advantages of intelligent fault diagnosis methods in big data processing, methods based on deep learning have accomplished admirable performance for fault diagnosis of rotating machinery. The prevailing convolutional neural network (CNN) displays desirable automatic learning ability. Therefore, an integrated intelligent fault diagnosis method is proposed based on CNN and continuous wavelet transform (CWT), combining the feature extraction and classification. Firstly, CWT is used to convert the raw vibration signals into time-frequency representations and achieve the extraction of image features. Secondly, a new framework of deep CNN is established via designing the convolutional layers and sub-sampling layers. The learning process and results are visualized by t-distributed stochastic neighbor embedding (t-SNE). The results of the experiment present a higher classification accuracy compared with other models. It is demonstrated that the proposed approach is effective and stable for fault diagnosis of a hydraulic axial piston pump.
Novel Time-Resolved Fluorescence Immunochromatography Paper-Based Sensor with Signal Amplification Strategy for Detection of Deoxynivalenol
Authors: Dong Haowei , An Xingshuang , Xiang Yaodong , Guan Fukai , Zhang Qi , Yang Qingqing , Sun Xia , Guo Yemin
Published: November 2020

Immunoassay has the advantages of high sensitivity, high specificity, and simple operation, and has been widely used in the detection of mycotoxins. For several years, time-resolved fluorescence immunochromatography (TRFIA) paper-based sensors have attracted much attention as a simple and low-cost field detection technology. However, a traditional TRFIA paper-based sensor is based on antibody labeling, which cannot easily meet the current detection requirements. A second antibody labeling method was used to amplify the fluorescence signal and improve the detection sensitivity. Polystyrene fluorescent microspheres were combined with sheep anti-mouse IgG to prepare fluorescent probes (Eu-IgGs). After the probe fully reacted with the antibody (Eu-IgGs-Abs) in the sample cell, it was deployed on the paper-based sensor using chromatography. Eu-IgGs-Abs that were not bound to the target were captured on the T-line, while those that were bound were captured on the C-line. The paper-based sensor reflected the corresponding fluorescence intensity change. Because a single molecule of the deoxynivalenol antibody could bind to multiple Eu-IgGs, this method could amplify the fluorescence signal intensity on the unit antibody and improve the detection sensitivity. The working standard curve of the sensor was established under the optimum working conditions. It showed the lower limit of detection and higher recovery rate when it was applied to actual samples and compared with other methods. This sensor has the advantages of high sensitivity, good accuracy, and good specificity, saving the amount of antibody consumed and being suitable for rapid field detection of deoxynivalenol.
Marine Diesel Engine Exhaust Emissions Measured in Ship’s Dynamic Operating Conditions
Authors: Bogdanowicz Artur , Kniaziewicz Tomasz
Published: November 2020

The paper presents the results of research on measuring the emissions from marine diesel engines in dynamic states. The problem is as follows: How to measure emissions of the composition of exhaust gases on board a ship, without direct measurement of fuel consumption and an air flow to marine diesel engine, during maneuvering the ship in the port area. The authors proposed a measurement methodology using an exhaust gas analyzer with simultaneous recording of the load indicator, engine speed, inclinometer, and Global Positioning System (GPS) data. Fuel consumption was calculated based on mean indicated pressure (MIP) tests. Recorded data were processed in the LabView systems engineering software. A simple neural network algorithm was used to model the concentrations of ingredients contained in engine exhaust gases during dynamic states. Using the recorded data, it is possible to calculate the emissions of the composition of exhaust gases from the marine diesel engine and calculate the route emissions of the tested vessel.
Comparison of Subjective and Objective Assessments on Improvement in Gait Function after Carotid Endarterectomy
Authors: Takahashi Tatsuhiko , Fujiwara Shunrou , Igarashi Suguru , Ando Toshihiko , Chida Kohei , Kobayashi Masakazu , Yoshida Kenji , Koji Takahiro , Kubo Yoshitaka , Ogasawara Kuniaki
Published: November 2020

The purpose of the present study was to determine whether objective gait test scores obtained using a tri-axial accelerometer can detect subjective improvement in gait as determined by the patient after carotid endarterectomy (CEA). Each patient undergoing CEA for ipsilateral internal carotid artery stenosis determined whether their gait was subjectively improved at six months after CEA when compared with preoperatively. Gait testing using a tri-axial accelerometer was also performed preoperatively and six months postoperatively. Twelve (15%) of 79 patients reported subjectively improved gait. Areas under the receiver operating characteristic curve for differences between pre- and postoperative test values in stride time, cadence, and ground floor reaction for detecting subjectively improved gait were 0.995 (95% confidence interval (CI), 0.945–1.000), 0.958 (95%CI, 0.887–0.990), and 0.851 (95%CI, 0.753–0.921), respectively. Cut-off points for value differences in detecting subjectively improved gait were identical to mean −1.7 standard deviation (SD) for stride time, mean +1.6 SD for cadence, and mean +0.4 SD for ground floor reaction of control values from normal subjects. Objective gait test scores obtained using the tri-axial accelerometer can detect subjective gait improvements after CEA. When determining significant postoperative improvements in gait using a tri-axial accelerometer, optimal cut-off points for each test value can be defined.
Multi-Branch Convolutional Neural Network for Automatic Sleep Stage Classification with Embedded Stage Refinement and Residual Attention Channel Fusion
Authors: Zhu Tianqi , Luo Wei , Yu Feng
Published: November 2020

Automatic sleep stage classification of multi-channel sleep signals can help clinicians efficiently evaluate an individual’s sleep quality and assist in diagnosing a possible sleep disorder. To obtain accurate sleep classification results, the processing flow of results from signal preprocessing and machine-learning-based classification is typically employed. These classification results are refined based on sleep transition rules. Neural networks—i.e., machine learning algorithms—are powerful at solving classification problems. Some methods apply them to the first two processes above; however, the refinement process continues to be based on traditional methods. In this study, the sleep stage refinement process was incorporated into the neural network model to form real end-to-end processing. In addition, for multi-channel signals, the multi-branch convolutional neural network was combined with a proposed residual attention method. This approach further improved the model classification accuracy. The proposed method was evaluated on the Sleep-EDF Expanded Database (Sleep-EDFx) and University College Dublin Sleep Apnea Database (UCDDB). It achieved respective accuracy rates of 85.7% and 79.4%. The results also showed that sleep stage refinement based on a neural network is more effective than the traditional refinement method. Moreover, the proposed residual attention method was determined to have a more robust channel–information fusion ability than the respective average and concatenation methods.
Reinforcement Learning-Based Data Association for Multiple Target Tracking in Clutter
Authors: Qu Chengzhi , Zhang Yan , Zhang Xin , Yang Yang
Published: November 2020

Data association is a crucial component of multiple target tracking, in which each measurement obtained by the sensor can be determined whether it belongs to the target. However, many methods reported in the literature may not be able to ensure the accuracy and low computational complexity during the association process, especially in the presence of dense clutters. In this paper, a novel data association method based on reinforcement learning (RL), i.e., the so-called RL-JPDA method, has been proposed for solving the aforementioned problem. In the presented method, the RL is leveraged to acquire available information of measurements. In addition, the motion characteristics of the targets are utilized to ensure the accuracy of the association results. Experiments are performed to compare the proposed method with the global nearest neighbor data association method, the joint probabilistic data association method, the fuzzy optimal membership data association method and the intuitionistic fuzzy joint probabilistic data association method. The results show that the proposed method yields a shorter execution time compared to other methods. Furthermore, it can obtain an effective and feasible estimation in the environment with dense clutters.
Reliability Evaluation of the Data Acquisition Potential of a Low-Cost Climatic Network for Applications in Agriculture
Authors: Trilles Sergio , Juan Pablo , Díaz-Avalos Carlos , Ribeiro Sara , Painho Marco
Published: November 2020

Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.
A Quiet Revolution: Central Banks, Financial Regulators, and Climate Finance
Authors: Gunningham Neil
Published: November 2020

If the free market cannot deliver a low carbon financial revolution, what sort of interventions in financial markets might be necessary to do so? Using interviews, participant observation, document analysis, and applying regulatory theory, this article argues for (i) cross cutting mechanisms designed to curb short-termism, to leverage the social license of financial institutions and to expand corporate conceptions of fiduciary duty to embrace climate change; and (ii) approaches tailored to the characteristics of each individual industry sector. Institutional investors and banks are used as case studies to highlight the importance of third-party benchmarking, expanding rights to litigate, requiring pension funds to address climate risks when making investment decisions, and disincentivizing high carbon investments by bank clients. Finally, it shows that a multi-instrumental approach can create a web of regulation that is more resilient and effective than its individual constituents. Its principal contribution is to show how Central Banks and Financial Regulators (CBFRs) might best fast-track a low-carbon financial transition.
Early Creedal Formulations and Theological Discourse
Authors: Moore Mark A.
Published: November 2020

Theology is a grand conversation, comprised of a myriad of voices and viewpoints. A great temptation exists within theology today, however, which could signal the loss of a unique Christian identity. The creedal formulations of the early church were never meant to serve as shackles constricting further theological exploration. They were, and still are, relevant guides in assessing the crowded conversation of theology. Early creedal formulations identified and articulated primary affirmations of the biblical narrative not to put an end to the conversation but rather to focus the conversation on the unique Christian identity of God as presented in Scripture. This book examines the function of early creedal formulations as essential identity markers in theological discourse with the goal of constructing an approach to the various subcategories of systematic theology that mirrors the creedal process. This approach, termed here as "Essential Identity Markers" (or simply EIM), seeks to identify and articulate the essential identity markers of a given theological subcategory, in order to define the proper parameters for theological discourse while still allowing such discourse to develop and expand within the articulated identity markers. The EIM model constructed and proposed in this book offers an approach to theology that mirrors the creedal process and seeks to guide modern theological conversations as the community of faith continues to explore the space framed by these markers.
Formação, provimento e fixação na Estratégia Saúde da Família de um município do Nordeste brasileiro
Authors: Aguiar Santos Bruno Oliveira de , Gondim Ana Paula Soares , Praxedes Ana Carolina Santana
Published: November 2020

A formação, o provimento e a fixação dos médicos na Estratégia Saúde da Família (ESF) são pontos relevantes para o fortalecimento da Atenção Básica no Brasil. O objetivo do trabalho é avaliar a formação e os fatores relacionados ao provimento e à fixação dos médicos da ESF de um município do Nordeste do Brasil, estabelecendo um comparativo com dentistas e enfermeiros. Trata-se de estudo descritivo quantitativo com aplicação de questionário estruturado com 119 profissionais de saúde. Os médicos apresentaram bom índice (68%) de especialização em saúde da família, tempo médio na ESF de 5,2 anos, além de considerarem a bonificação para prova de títulos e a necessidade financeira as principais razões para atuação na ESF. Oitenta por cento da categoria médica advinha do Programa Mais Médicos, sendo esta a grande diferença entre os profissionais não médicos, que são concursados em sua maioria.
A compreensão do papel temático de experienciador de verbos psicológicos realizada por pessoas com síndrome de Down
Authors: Martins Alves Salgado Ana Paula , De Jesus Ramos Ruth
Published: November 2020

Em um paradigma experimental, este trabalho teve por objetivo analisar a compreensão do papel temático de Experienciador de verbos psicológicos realizada por pessoas com Síndrome de Down, por meio da Técnica de Fixação Preferencial do Olhar, pautados nos pressupostos teórico de Cançado (1995) e Paiva et al. (2014). Os resultados do nosso estudo apontam que pessoas com Síndrome de Down compreendem a alternância do Papel Temático de Experienciador de verbos psicológicos, contudo, tal compreensão se torna mais custosa quando o Experienciador está na posição sintática de sujeito. Os dados sugerem, ainda, uma possível influência de fatores socioeducacionais no nível de compreensão de verbos psicológicos de pessoas com Síndrome de Down.
Evidencialidade e polêmica em webcomentários em língua espanhola
Authors: Lopes Batista Victória Glenda , Paulino Pessoa Prata Nadja , Cruz de Menezes Léia
Published: November 2020

Neste trabalho, objetivamos analisar qualitativamente o uso da evidencialidade nos discursos tidos como polêmicos, sob um enfoque funcionalista de análise, buscando integrar postulados teóricos da Gramática Discursivo-Funcional (GDF) com a noção de polêmica, constante em estudos de Análise de Discurso (AD) e de Argumentação Retórica. Conforme expresso em Hengeveld e Mackenzie (2008), a evidencialidade está relacionada à fonte da informação veiculada, ao passo que o discurso polêmico é entendido pela AD e pela Argumentação Retórica como um embate entre duas teses mutuamente excludentes, em geral, mas não obrigatoriamente, vinculadas à emotividade e à paixão. Acreditando que a marcação da evidencialidade é influenciada pela natureza polêmica dos discursos, buscamos, em webcomentários em língua espanhola, compreender o modo como a marcação da fonte é arregimentada pelos falantes de espanhol durante a argumentação em torno de tema polêmico. Constatamos que as fontes atuam na exemplificação de argumentos e no ataque a interlocutores com os quais o embate de ideias é travado, visando o descredenciamento do adversário. A evidencialidade mostrou-se característica do discurso polêmico.
Ser Professor em Portugal
Authors: Neves Rui
Published: November 2020

O presente artigo procura caraterizar e refletir acerca da questão do acesso à formação e à profissão de Ser Professor no atual contexto social e político em Portugal. Para isso, descreve-se o contexto da formação inicial de educadores e professores e sua articulação com o ingresso na profissão. Em sequência, perspetiva-se a atual situação em Portugal, nos seus constrangimentos, desafios e oportunidades. Com um enquadramento em documentação europeia e nacional, traça-se um panorama entre a análise crítica da realidade e as exigências de um processo de desenvolvimento profissional dos professores que para além de atrair as novas gerações, combatam o abandono por meio de políticas de qualificação, credibilização e reconhecimento.
Observação colaborativa de aulas, conhecimento profissional docente e supervisão
Authors: Macedo Lara Susana , Andrade Ana Isabel
Published: November 2020

O estudo centra-se numa experiência de observação colaborativa de aulas, vivida por um grupo de seis professores, numa escola secundária em Portugal, durante uma oficina de formação, entre outubro de 2014 e janeiro de 2015. São analisadas as representações dos professores-formandos relativamente à observação  colaborativa de aulas, procurando compreender os efeitos desta estratégia supervisiva na (re)construção do seu conhecimento profissional. A recolha de dados efetuou-se no início e final da oficina de formação, respetivamente, através da aplicação de questionários, de reflexões individuais e de relatórios de observação colaborativa. A análise dos dados seguiu uma metodologia de natureza qualitativa assente numa abordagem fenomenológico-interpretativa, concretizada através da análise de conteúdo. Os resultados evidenciam as potencialidades formativas da observação colaborativa de aulas na (re)construção do conhecimento profissional docente ao permitir que os docentes conheçam, interpretem e reconstruam o ensino que praticam.