bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction Optimization and Evaluation of the Antioxidant and α-Glucosidase Inhibitory Activity of Polysaccharides from Chrysanthemum morifolium cv. Hangju
Authors: Hou Xiaoyan , Huang Xia , Li Jianlong , Jiang Guangyang , Shen Guanghui , Li Shanshan , Luo Qingying , Wu Hejun , Li Meiliang , Liu Xingyan , Chen Anjun , Ye Meng , Zhang Zhiqing
Published: January 2020

In order to evaluate the antioxidant and α-glucosidase activities of polysaccharides from Chrysanthemum morifolium cv. Hangju (CMPs), the response surface methodology was applied to optimize the parameters for extraction progress of CMPs by ultrasound, with heat reflex extraction (HRE) performed as the control. The difference in the physicochemical properties of polysaccharides obtained by the two methods were also investigated. The maximum yields (8.29 ± 0.18%) of polysaccharides extracted by ultrasonic assisted extraction (UAE) were obtained under the optimized conditions of ultrasonic power 501 W, extraction time 19 min, and ratio of liquid-to-raw material 41 mL/g. Polysaccharides extracted by UAE possessed lower protein contents (2.56%) and higher uronic acids contents (7.08%) and low molecular weight fractions than that by HRE. No significant differences were found in monosaccharide composition and Fourier transform infrared (FT-IR) spectra of polysaccharides extracted by UAE and HRE, while polysaccharides by UAE possessed stronger antioxidant and α-glucosidase inhibitory activities. Therefore, UAE was an efficient way to obtain CMPs.
ABTS On-Line Antioxidant, α-Amylase, α-Glucosidase, Pancreatic Lipase, Acetyl- and Butyrylcholinesterase Inhibition Activity of Chaenomeles Fruits Determined by Polyphenols and other Chemical Compounds
Authors: Turkiewicz Igor Piotr , Wojdyło Aneta , Tkacz Karolina , Nowicka Paulina , Golis Tomasz , Bąbelewski Przemysław
Published: January 2020

This study aimed to identify and quantify the chemical composition and polyphenolic profile of 19 cultivars of Chaenomeles × superba, Chaenomeles japonica, and Chaenomeles speciosa by liquid chromatography coupled with photodiode array detector and quadrupole time-of-flight electrospray ionization mass spectrometry (LC-PDA-QTOF-ESI-MS). Antioxidant (ABTS on-line, ABTS, FRAP, and ORAC), as well as in vitro biological activities, i.e., the ability to inhibit α-amylase, α-glucosidase, pancreatic lipase, acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), and 15-lipoxygenase (15-LOX) were determined. Most of the Chaenomeles species and cultivars analyzed in this study have not been examined in this respect until now. Fruits contained 30.26 to 195.05 mg of vitamin C, 0.65 to 1.69 g of pectin, 0.32 to 0.64 g of ash, 0.60 to 3.98 g of sugars, and 41.64 to 110.31 g of organic acids in 100 g fresh weight. The lowest content of total polyphenols showed C. speciosa ‘Rubra’ (57.84 g/kg dry weight, dw) while C. × superba ’Nicoline’ (170.38 g/kg dw) exhibited the highest concentration of those compounds. In the phenolic compounds, polymeric procyanidin fraction predominated (65%) with procyanidin B2, C1, and (−)-epicatechin the most abundant. The antioxidant capacity measured by ABTS assay was mainly formed by polymeric procyanidins and flavan-3-ols, which was confirmed by ABTS on-line profiling. Chaenomeles fruits showed high potential for inhibition of α-glucosidase and pancreatic lipase. The analyzed cultivars displayed greater potential for acetylcholinesterase (AChE) inhibition than for butyrylcholinesterase (BuChE). The data indicate that Chaenomeles fruits could be regarded as a promising source of bioactive functional food.
A Mechanism of Gold Nanoparticle Aggregation by Immunoglobulin G Preparation
Authors: Sotnikov Dmitriy V. , Safenkova Irina V. , Zherdev Anatoly V. , Avdienko Vadim G. , Kozlova Irina V. , Babayan Suren S. , Gergert Vladislav Ya. , Dzantiev Boris B.
Published: January 2020

Conjugates of gold nanoparticles (GNPs) and antibodies are widely used in various fields of biochemistry and microbiology. However, the procedure for obtaining such conjugates remains precarious, and the properties of conjugates differ significantly for different antibody clones. One of the most common problems is the aggregation of GNPs in the course of their conjugation with antibodies. This article considers an example of the conjugation of monoclonal antibodies with non-stable aggregating product. The composition of the antibody preparation was studied using electrophoresis, asymmetrical flow field-flow fractionation, and ultracentrifugation. It was shown that the component that causes the aggregation of the GNPs is the light chains of immunoglobulins that appear due to the spontaneous decay of the antibodies. After separation of the fraction with a molecular weight of less than 30 kDa, stable conjugates of antibodies with GNPs were obtained. The high functional activity of the obtained conjugates was confirmed by immunochromatography.
An Efficient Algorithm for Cardiac Arrhythmia Classification Using Ensemble of Depthwise Separable Convolutional Neural Networks
Authors: Ihsanto Eko , Ramli Kalamullah , Sudiana Dodi , Gunawan Teddy Surya
Published: January 2020

Many algorithms have been developed for automated electrocardiogram (ECG) classification. Due to the non-stationary nature of the ECG signal, it is rather challenging to use traditional handcraft methods, such as time-based analysis of feature extraction and classification, to pave the way for machine learning implementation. This paper proposed a novel method, i.e., the ensemble of depthwise separable convolutional (DSC) neural networks for the classification of cardiac arrhythmia ECG beats. Using our proposed method, the four stages of ECG classification, i.e., QRS detection, preprocessing, feature extraction, and classification, were reduced to two steps only, i.e., QRS detection and classification. No preprocessing method was required while feature extraction was combined with classification. Moreover, to reduce the computational cost while maintaining its accuracy, several techniques were implemented, including All Convolutional Network (ACN), Batch Normalization (BN), and ensemble convolutional neural networks. The performance of the proposed ensemble CNNs were evaluated using the MIT-BIH arrythmia database. In the training phase, around 22% of the 110,057 beats data extracted from 48 records were utilized. Using only these 22% labeled training data, our proposed algorithm was able to classify the remaining 78% of the database into 16 classes. Furthermore, the sensitivity ( S n ), specificity ( S p ), and positive predictivity ( P p ), and accuracy ( A c c ) are 99.03%, 99.94%, 99.03%, and 99.88%, respectively. The proposed algorithm required around 180 μs, which is suitable for real time application. These results showed that our proposed method outperformed other state of the art methods.
Programming of Industrial Robots Using Virtual Reality and Digital Twins
Authors: Burghardt Andrzej , Szybicki Dariusz , Gierlak Piotr , Kurc Krzysztof , Pietruś Paulina , Cygan Rafał
Published: January 2020

The article presents a method of programming robots using virtual reality and digital twins. The virtual environment is a digital twin of a robotic station, built based on CAD models of existing station elements. The virtual reality system is used to record human movements in a virtual environment, which are then reproduced by a real robot. The method developed is dedicated mainly to such situations in which it is necessary for the robot to reproduce the movements of a human performing a process that is complicated from the point of view of robotization. An example of using the method for programming a robot implementing the process of cleaning ceramic casting moulds is presented.
Advanced Methods for Photovoltaic Output Power Forecasting: A Review
Authors: Mellit Adel , Massi Pavan Alessandro , Ogliari Emanuele , Leva Sonia , Lughi Vanni
Published: January 2020

Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into the grid. The design of accurate photovoltaic output forecasters remains a challenging issue, particularly for multistep-ahead prediction. Accurate PV output power forecasting is critical in a number of applications, such as micro-grids (MGs), energy optimization and management, PV integrated in smart buildings, and electrical vehicle chartering. Over the last decade, a vast literature has been produced on this topic, investigating numerical and probabilistic methods, physical models, and artificial intelligence (AI) techniques. This paper aims at providing a complete and critical review on the recent applications of AI techniques; we will focus particularly on machine learning (ML), deep learning (DL), and hybrid methods, as these branches of AI are becoming increasingly attractive. Special attention will be paid to the recent development of the application of DL, as well as to the future trends in this topic.
Data Sharing System Integrating Access Control Mechanism using Blockchain-Based Smart Contracts for IoT Devices
Authors: Sultana Tanzeela , Almogren Ahmad , Akbar Mariam , Zuair Mansour , Ullah Ibrar , Javaid Nadeem
Published: January 2020

In this paper, a blockchain-based data sharing and access control system is proposed, for communication between the Internet of Things (IoT) devices. The proposed system is intended to overcome the issues related to trust and authentication for access control in IoT networks. Moreover, the objectives of the system are to achieve trustfulness, authorization, and authentication for data sharing in IoT networks. Multiple smart contracts such as Access Control Contract (ACC), Register Contract (RC), and Judge Contract (JC) are used to provide efficient access control management. Where ACC manages overall access control of the system, and RC is used to authenticate users in the system, JC implements the behavior judging method for detecting misbehavior of a subject (i.e., user). After the misbehavior detection, a penalty is defined for that subject. Several permission levels are set for IoT devices’ users to share services with others. In the end, performance of the proposed system is analyzed by calculating cost consumption rate of smart contracts and their functions. A comparison is made between existing and proposed systems. Results show that the proposed system is efficient in terms of cost. The overall execution cost of the system is 6,900,000 gas units and the transaction cost is 5,200,000 gas units.
A Quantitative Study on the Void Defects Evolving into Damage in Wind Turbine Blade Based on Internal Energy Storage
Authors: Zhou Bo , Yu Fangai , Li He , Xin Wen
Published: January 2020

As manufacturing defects, voids in wind turbine blades may cause damage under fatigue loads. In this paper, the internal energy storage is used as an indicator to identify the critical moment when a defect evolves into damage. The heat transfer equation of composites material containing void defects is derived based upon the theory of the thermodynamics of irreversible processes. In order to obtain the numerical calculation model of the internal energy storage of the evolving process, the thermal conductivity along the transverse direction is homogenized as the temperature date along this direction is acquired by a thermal camera. Specimens with different void fractions are tested with infrared thermal imaging under fatigue load, during which the stress, strain and temperature data are acquired to establish the curve of internal energy storage against the fatigue cycle. This relationship curve can be used to identify the critical moment when void defects evolve into damage. The feasibility of this method is proven by microscopic observation.
Design of a 35 kW Solar Cooling Demonstration Facility for a Hotel in Spain
Authors: Martínez Pedro J. , Martínez Pedro , Soto Victor M. , Bujedo Luis A. , Rodriguez Juan
Published: January 2020

Solar cooling systems have the advantage of the coincidence between the hours of cooling demand and the hours of solar radiation availability, and they can contribute to reduce the energy consumption in buildings. However, the high cost of thermal solar cooling facilities with absorption chillers, maintenance issues, legionella risk and water consumption (associated to the necessary cooling tower) have limited the use of these systems to demonstration projects. A simplified Transient System Simulation Tool (TRNSYS) model was developed to provide the owner of the demonstration facility the information he needs for design decision-making. This model was validated with experimental data registered in a solar cooling system designed and built by the authors. Different collector field surfaces, hot water storage tank volumes, and absorption machine driving temperatures were analyzed for a hotel demonstration facility. In terms of the energy delivered to the absorption chiller the optimum dimensioning corresponded to the lowest values of the driving temperature (75 °C) and specific storage volume (15 Lm2). From an economic point of view, the saving of 1515 euros per year when compared with an electric compression chiller does not compensate the investment of 3000 euros per kW of cooling capacity that cost the thermal solar cooling facility.
Semantic Information for Robot Navigation: A Survey
Authors: Crespo Jonathan , Castillo Jose Carlos , Mozos Oscar Martinez , Barber Ramon
Published: January 2020

There is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In contrast with the early years, when navigation relied on geometric navigators that interpreted the environment as a series of accessible areas or later developments that led to the use of graph theory, semantic information has moved robot navigation one step further. This work presents a survey on the concepts, methodologies and techniques that allow including semantic information in robot navigation systems. The techniques involved have to deal with a range of tasks from modelling the environment and building a semantic map, to including methods to learn new concepts and the representation of the knowledge acquired, in many cases through interaction with users. As understanding the environment is essential to achieve high-level navigation, this paper reviews techniques for acquisition of semantic information, paying attention to the two main groups: human-assisted and autonomous techniques. Some state-of-the-art semantic knowledge representations are also studied, including ontologies, cognitive maps and semantic maps. All of this leads to a recent concept, semantic navigation, which integrates the previous topics to generate high-level navigation systems able to deal with real-world complex situations.
Partial Order Rank Features in Colour Space
Authors: Smeraldi Fabrizio , Bianconi Francesco , Fernández Antonio , González Elena
Published: January 2020

Partial orders are the natural mathematical structure for comparing multivariate data that, like colours, lack a natural order. We introduce a novel, general approach to defining rank features in colour spaces based on partial orders, and show that it is possible to generalise existing rank based descriptors by replacing the order relation over intensity values by suitable partial orders in colour space. In particular, we extend a classical descriptor (the Texture Spectrum) to work with partial orders. The effectiveness of the generalised descriptor is demonstrated through a set of image classification experiments on 10 datasets of colour texture images. The results show that the partial-order version in colour space outperforms the grey-scale classic descriptor while maintaining the same number of features.
GPS-Based Indoor/Outdoor Detection Scheme Using Machine Learning Techniques
Authors: Bui Van , Le Nam Tuan , Vu Thanh Luan , Nguyen Van Hoa , Jang Yeong Min
Published: January 2020

Recent advances in mobile communication require that indoor/outdoor environment information be available for both individual applications and wireless signal transmission in order to improve interference control and serve upper-layer applications. In this paper, we present a scheme to identify the indoor/outdoor environment using GPS signals combined with machine learning classification techniques. Compared to traditional schemes, which are based on received signal strength indicator (RSSI), the proposed scheme promises a robust approach with high accuracy, smooth operation when moving between indoor and outdoor environments, as well as easy implementation and training. The proposed scheme combined information from a certain number of GPS satellites, using the GPS sensor on mobile devices. Then, data are collected, preprocessed, and classified as indoor or outdoor environment using a machine learning model that is optimized for the best performance. The GPS input data were collected in the Kookmin University area and included 850 training samples and 170 test samples. The overall accuracy reached 97%.
Novel Methodology for Condition Monitoring of Gear Wear Using Supervised Learning and Infrared Thermography
Authors: Resendiz-Ochoa Emmanuel , Saucedo-Dorantes Juan J. , Benitez-Rangel Juan P. , Osornio-Rios Roque A. , Morales-Hernandez Luis A.
Published: January 2020

In gearboxes, the occurrence of unexpected failures such as wear in the gears may occur, causing unwanted downtime with significant financial losses and human efforts. Nowadays, noninvasive sensing represents a suitable tool for carrying out the condition monitoring and fault assessment of industrial equipment in continuous operating conditions. Infrared thermography has the characteristic of being installed outside the machinery or the industrial process under assessment. Also, the amount of information that sensors can provide has become a challenge for data processing. Additionally, with the development of condition monitoring strategies based on supervised learning and artificial intelligence, the processing of signals with significant improvements during the classification of information has been facilitated. Thus, this paper proposes a novel noninvasive methodology for the diagnosis and classification of different levels of uniform wear in gears through thermal analysis with infrared imaging. The novelty of the proposed method includes the calculation of statistical time-domain features from infrared imaging, the consideration of a dimensionality reduction stage by means of Linear Discriminant Analysis, and automatic fault diagnosis performed by an artificial neural network. The proposed method is evaluated under an experimental laboratory data set, which is composed of the following conditions: healthy, and three severity degrees of uniform wear in gears, namely, 25%, 50%, and 75% of uniform wear. Finally, the obtained results are compared with classical condition monitoring approaches based on vibration analysis.
Variability of Physical and Chemical Properties of TLUD Stove Derived Biochars
Authors: Masís-Meléndez Federico , Segura-Chavarría Diana , García-González Carlos A , Quesada-Kimsey Jaime , Villagra-Mendoza Karolina
Published: January 2020

Biochar is a carbon-rich organic material, obtained by the thermochemical conversion of biomass in an oxygen-limited environment, used as a soil amendment to stimulate soil fertility and improve soil quality. There is a clear need in developing countries for access to low cost, low technology options for biochar production, for example, top-lit updraft (TLUD) stoves, which are popular and spread worldwide. However, TLUD biochars are inevitably very variable in their properties for a variety of reasons. We present laboratory triplicate tests carried out on TLUD biochars obtained from waste pinewood and a Guadua bamboo. Analyzed properties include specific surface area (A-BET), porosity, skeletal density, hydrophobicity, proximal and elemental composition, cation exchange capacity (CEC), relative liming capacity and pH. SEM images of the bamboo and wood biochars are compared. The biochars were mixed with composted human excreta at 5% and 10% biochar content, and available water content (AWC) was analyzed. Operating temperatures in the TLUD were recorded, showing different behaviors among the feedstocks during the process. Differences in operating temperatures during charring of the bamboo samples seem to have led to differences in A-BET, hydrophobicity and CEC, following unprecedented trends. For the mixtures of the biochars with compost, at 5% biochar no significant differences were observed for AWC. However, in the 10% biochar mixtures, bamboo biochar showed an unexpectedly high AWC. Overall, variations of chemical and physical properties between bamboo biochars were greater, while pinewood biochars showed similar properties, consistent with more homogeneous charring temperatures.
Jet Noise in Airframe Integration and Shielding
Authors: Salehian Saman , Mankbadi Reda
Published: January 2020

This paper reviews and presents new results on the effect of airframe integration and shielding on jet noise. Available experimental data on integration effects are analyzed. The available options for the computation of jet noise are discussed, and a practical numerical approach for the present topic is recommended. Here, it is demonstrated how a hybrid large eddy simulation—unsteady Reynolds-averaged Navier-Stokes approach can be implemented to simulate the effect of shielding on radiated jet noise. This approach provides results consistent with the experiment and suggests a framework for studying more complex geometries involving airframe integration effects.
Adaptive State Observer for Robot Manipulators Diagnostics and Health Degree Assessment
Authors: Dang Sanlei , Kong Zhengmin , Peng Long , Ji Yilin , Zhang Yongwang
Published: January 2020

To avoid serious damages caused by the dynamic environment, fault detection and health assessment are essential for an integrated robotic system. In this paper, we propose a fault detection algorithm and a health degree assessment approach for a robot manipulator system. Both the internal disturbance and the output measurement disturbance are considered in the proposed method. In addition, an adaptive observer is utilized to reconstruct the real system of robot manipulators. Under the proposed observer, the real system is estimated to detect the fault and obtain the health degree of the robot manipulator. The feasibility and reliability of the proposed fault detection algorithm and health degree assessment index for robot manipulator systems are proved by simulation experiments.
Fluorene–Triphenylamine-Based Bipolar Materials: Fluorescent Emitter and Host for Yellow Phosphorescent OLEDs
Authors: Braveenth Ramanaskanda , Jung Hasu , Kim Keunhwa , Kim Bo Mi , Bae Il-Ji , Kim Miyoung , Chai Kyu Yun
Published: January 2020

In this study, two new bipolar materials were designed and synthesized: N1-(9,9-diphenyl-9H-fluoren-2-yl)-N1-(4,6-diphenylpyrimidin-2-yl)-N4,N4-diphenylbenzene-1,4-diamine (FLU-TPA/PYR) and N1-(4-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-N1-(9,9-diphenyl-9H-fluoren-2-yl)-N4,N4 diphenylbenzene-1,4-diamine (FLU-TPA/TRZ). We fabricated two different devices, namely a yellow phosphorescent organic light-emitting diode (PhOLED) and a non-doped fluorescent OLED emitter with both FLU-TPA/PYR and FLU-TPA/TRZ. The FLU-TPA/PYR host-based yellow PhOLED device showed better maximum current, power and external quantum efficiencies at 21.70 cd/A, 13.64 lm/W and 7.75%, respectively. The observed efficiencies were better than those of the triazine-based FLU-TPA/TRZ. The non-doped fluorescent device with the triazine-based FLU-TPA/TRZ material demonstrated current, power and external quantum efficiencies of 10.30 cd/A, 6.47 lm/W and 3.57%, respectively.
Ultrafast and Wideband Microwave Photonic Frequency-Hopping Systems: A Review
Authors: Liu Qidi , Fok Mable P.
Published: January 2020

The increasing demands to enhance information security in data transmission, providing countermeasures against jamming in military applications, as well as boosting data capacity in mobile and satellite communication, have led to a critical need for high-speed frequency-hopping systems. Conventional electronics-based frequency-hopping systems suffer from low data rate, low hopping speed, and narrow hopping-frequency bandwidth. Unfortunately, those are important aspects to facilitate frequency-hopping in emerging microwave systems. The recent advancement of microwave photonics—the use of light to process microwave signals—provides promising solutions to tackle the challenges faced by electronic frequency-hopping systems. In this paper, the challenges of achieving real-time frequency-hopping systems are examined. The operation principles and results of various microwave photonics-enabled frequency-hopping systems are comprehensively discussed, which have wide hopping-frequency bandwidth and frequency-hopping speed from nanoseconds to tens of picoseconds. Lastly, a bio-inspired jamming-avoidance system that could potentially be used for adaptive frequency-hopping is also introduced.
Disposal and Recycle Economic Assessment for Aircraft and Engine End of Life Solution Evaluation
Authors: Zhao Xiaojia , Verhagen Wim J.C. , Curran Richard
Published: January 2020

The present study proposes an economic indicator to support the evaluation of aircraft End of Life (EoL) strategies in view of the increasing demand with regards to aircraft decommissioning. This indicator can be used to evaluate an economic performance and to facilitate the trade-off studies among different strategies. First, Disposal and Recycle (D&R) scenarios related to stakeholders are investigated to identify the core concepts for the economic evaluation. Next, we extracted the aircraft D&R process from various real-life practices. In order to obtain the economic measure for the engineering process, a method of estimating the D&R cost and values are developed by integrating product, process and cost properties. This analysis is demonstrated on an averaged data set and two EoL aircraft cases. In addition, sensitivity analysis is performed to evaluate the impact of the D&R cost, residual value, and salvage value. Results show that the disassembly and dismantling of an aircraft engine possesses relatively more economic gains than that for the aircraft. The main factors influencing the proposed D&R economic indicator are the salvage value and D&R cost for economically efficient D&R cases. In addition, delaying the disposal and recycle process for EoL aircraft can lead to economically unfavorable solutions. The economic indicator combined with the evaluation methods is widely applicable for evaluations of engineering products EoL solutions, and implies a significant contribution of this research to decision making for such complex systems in terms sustainable policy.
The Influence of Display Parameters and Display Devices over Spatial Ability Test Answers in Virtual Reality Environments
Authors: Guzsvinecz Tibor , Sik-Lanyi Cecilia , Orban-Mihalyko Eva , Perge Erika
Published: January 2020

This manuscript analyzes the influence of display parameters and display devices over the spatial skills of the users in virtual reality environments. For this, the authors of this manuscript developed a virtual reality application which tests the spatial skills of the users. 240 students used an LG desktop display and 61 students used the Gear VR for the tests. Statistical data are generated when the users do the tests and the following factors are logged by the application and evaluated in this manuscript: virtual camera type, virtual camera field of view, virtual camera rotation, contrast ratio parameters, the existence of shadows and the device used. The probabilities of correct answers were analyzed based on these factors by logistic regression (logit) analysis method. The influences and interactions of all factors were analyzed. The perspective camera, lighter contrast ratio, no or large camera rotations and the use of the Gear VR greatly and positively influenced the probability of correct answers on the tests. Therefore, for the assessment of spatial ability in virtual reality, the use of these parameters and device present the optimal user-centric human–computer interaction practice.
Southern Hemisphere Sensitivity to ENSO Patterns and Intensities: Impacts over Subtropical South America
Authors: Martín-Gómez Verónica , Barreiro Marcelo , Mohino Elsa
Published: January 2020

El Niño flavors influence Subtropical South American (SSA) rainfall through the generation of one or two quasi-stationary Rossby waves. However, it is not yet clear whether the induced wave trains depend on the El Niño pattern and/or its intensity. To investigate this, we performed different sensitivity experiments using an Atmospheric General Circulation Model (AGCM) which was forced considering separately the Canonical and the El Niño Modoki patterns with sea surface temperature (SST) maximum anomalies of 1 and 3 °C. Experiments with 3 °C show that the Canonical El Niño induces two Rossby wave trains, a large one emanating from the western subtropical Pacific and a shorter one initiated over the central-eastern subtropical South Pacific. Only the shorter wave plays a role in generating negative outgoing longwave radiation (OLR) anomalies over SSA. On the other hand, 3 °C El Niño Modoki experiments show the generation of a large Rossby wave train that emanates from the subtropical western south Pacific and reaches South America (SA), promoting the development of negative OLR anomalies over SSA. Experiments with 1 °C show no impacts on OLR anomalies over SSA associated with El Niño Modoki. However, for the Canonical El Niño case there is a statistically significant reduction of the OLR anomalies over SSA related to the intensification of the upper level jet stream over the region. Finally, our model results suggest that SSA is more sensitive to the Canonical El Niño, although this result may be model dependent.
Internal Structure of Asian Dust Particles over the Western North Pacific: Analyses Using Focused Ion Beam and Transmission Electron Microscopy
Authors: Ueda Sayako , Miki Yusuke , Kato Hiroki , Miura Kazuhiko , Nakayama Hiroyasu , Furutani Hiroshi , Uematsu Mitsuo
Published: January 2020

Mineral dust aerosols, which comprise multiple mineral species, are transported far from their source desert areas to the open ocean. After an Asian dust outflow event was observed over a marine boundary layer in the western North Pacific on February 29, 2012 on research vessel (R/V) Hakuho Maru, two dust particles of about 6 μm diameter were analyzed. First, they were sliced by using a focused ion beam (FIB). Their mineralogical structures and the elemental distribution of their cross-sections were subsequently analyzed with the use of transmission electron microscopy (TEM) and energy-dispersive X ray spectrometry (EDS). These analyses revealed that the dust particles consisted mainly of calcite and silica. Furthermore, Fe-containing domains were found in the submicrometer area surrounded by calcite and silica. A sulfur-containing domain that co-exists with calcium was found in a small domain near the particle surface, but no clear sign of atmospheric aging was found in most of the calcite domain. The inhomogeneous particle structure implies that the dissolution of iron and calcite in dust particles after ocean deposition depends on the physical structures of particles and their degree of aging according to atmospheric conditions during transport. Those factors must be adequately treated when estimating Asian dust effects on marine primary production.
IEQ Field Investigation in High-Performance, Urban Elementary Schools
Authors: Oldham Emily , Kim Hyojin
Published: January 2020

School buildings are one of the most commonly occupied building types for children, second only to their homes. Indoor environmental quality (IEQ) is an ongoing issue in schools, especially in urban environments where students are exposed to higher levels of outdoor pollutants. To examine this issue, five elementary school buildings located in a major city on the East Coast of the United States were selected for one-week of quantitative IEQ measurements, with a satisfaction survey collected from teachers at the selected schools. The schools included three high-performance schools, one recently renovated school, and one conventional school. Despite building designers and operators following the recommendations of current high-performance design standards, the three high-performance school buildings did not have measurably better IEQ than the renovated and conventional school buildings, nor were they perceived as better based on the satisfaction survey. This indicates that current high-performance design standards may not place enough emphasis on reducing health-related pollutants in urban schools.
State-of-Charge Monitoring and Battery Diagnosis of NiCd Cells Using Impedance Spectroscopy
Authors: Kurzweil Peter , Scheuerpflug Wolfgang
Published: January 2020

With respect to aeronautical applications, the state-of-charge (SOC) and state-of-health (SOH) of rechargeable nickel–cadmium batteries was investigated with the help of the frequency-dependent reactance Im Z(ω) and the pseudo-capacitance C(ω) in the frequency range between 1 kHz and 0.1 Hz. The method of SOC monitoring using impedance spectroscopy is evaluated with the example of 1.5-year long-term measurements of commercial devices. A linear correlation between voltage and capacitance is observed as long as overcharge and deep discharge are avoided. Pseudo-charge Q(ω) = C(ω)⋅U at 1 Hz with respect to the rated capacity is proposed as a reliable SOH indicator for rapid measurements. The benefit of different evaluation methods and diagram types for impedance data is outlined.
The Ovarian Transcriptome of Reproductively Aged Multiparous Mice: Candidate Genes for Ovarian Cancer Protection
Authors: Urzúa Ulises , Chacón Carlos , Norambuena Maximiliano , Lizama Luis , Sarmiento Sebastián , Asaki Esther , Powell John I , Ampuero Sandra
Published: January 2020

In middle-aged women, the decline of ovarian follicle reserve below a critical threshold marks menopause, leading to hormonal, inflammatory, and metabolic changes linked to disease. The highest incidence and mortality of sporadic ovarian cancer (OC) occur at post-menopause, while OC risk is reduced by full-term pregnancies during former fertile life. Herein, we investigate how parity history modulates the ovarian transcriptome related to such declining follicle pool and systemic inflammation in reproductively-aged mice. Female C57BL/6 mice were housed under multiparous and virgin (nulliparous) breeding regimens from adulthood until estropause. The ovaries were then subjected to follicle count and transcriptional profiling, while a cytokine panel was determined in the sera. As expected, the follicle number was markedly decreased just by aging. Importantly, a significantly higher count of primordial and total follicles was observed in aged multiparous relative to aged virgin ovaries. Consistently, among the 65 genes of higher expression in aged multiparous ovaries, 27 showed a follicle count-like pattern, 21 had traceable evidence of roles in follicular/oocyte homeostasis, and 7 were transforming-growth factor beta (TGF-β)/bone morphogenetic protein (BMP) superfamily members. The remaining genes were enriched in cell chemotaxis and innate-immunity, and resembled the profiles of circulating CXCL1, CXCL2, CXCL5, CSF3, and CCL3, chemokines detected at higher levels in aged multiparous mice. We conclude that multiparity during reproductive life promotes the retention of follicle remnants while improving local (ovarian) and systemic immune-innate surveillance in aged female mice. These findings could underlie the mechanisms by which pregnancy promotes the long-term reduced OC risk observed at post-menopause.
Galectin Domain Containing Protein from Haemonchus contortus Modulates the Immune Functions of Goat PBMCs and Regulates CD4+ T-Helper Cells In Vitro
Authors: Naqvi Muhammad Ali-ul-Husnain , Memon Muhammad Ali , Jamil Tahseen , Naqvi Sana Zahra , Aimulajiang Kalibixiati , Gadahi Javaid Ali , Xu Lixin , Song Xiaokai , Li Xiangrui , Yan Ruofeng
Published: January 2020

Galectins are glycan-binding proteins that are widely expressed and distributed in mammalian tissues as well as cells of innate and adaptive immune responses. CD4+ T-helper cells differentiate into effector subsets in response to cytokines. T helper 9 cells are one of the recently described subsets of effector T cells that are relatively new and less studied. In this study, galectin domain containing protein from Haemonchus contortus (Hc-GDC) was cloned, expressed in pET32a, and immunoblotting was performed. Localization of recombinant (r)Hc-GDC on outer and inner surface of H. contortus worm and binding with goat Peripheral Blood Mononuclear cells (PBMCs) were performed using immunofluorescence assay. Moreover, effects of rHc-GDC on proliferation, apoptosis, cell migration, and the nitric oxide production in goat PBMCs were evaluated. Furthermore, modulatory effects of rHc-GDC on production of Th1, Th2, and Th9 cells were evaluated by flowcytometry and on interferon gamma, interleukin (IL)-4 and IL-9 were evaluated by quantitative real-time polymerase chain reaction. The results demonstrated that rHc-GDC was successfully cloned, expressed in expression vector as well as in the gut surface of adult H. contortus worm and successful binding with PBMCs surface were observed. Immunoblotting results revealed that rHc-GDC is an important active protein of H. contortus excretory and secretory products. Moreover, the interaction of rHc-GDC with host cells increased the production of Th2, Th9 cells, IL4, IL-9, PBMC proliferation, nitric oxide, and cell migration. No effects of rHc-GDC were observed on PMBC apoptosis, production of Th1 cells, and secretions of IFN-γ and IL-10 cytokines. These findings indicate that recombinant GDC protein from H. contortus modulates the immune functions of goat PBMCs and has the potential to enhance protective immunity by inducing T helper-9-derived IL-9 in vitro.
Sorafenib Inhibits Ribonucleotide Reductase Regulatory Subunit M2 (RRM2) in Hepatocellular Carcinoma Cells
Authors: Yang Pei-Ming , Lin Li-Shan , Liu Tsang-Pai
Published: January 2020

The main curative treatments for hepatocellular carcinoma (HCC) are surgical resection and liver transplantation, which only benefits 15% to 25% of patients. In addition, HCC is highly refractory and resistant to cytotoxic chemotherapy. Although several multi-kinase inhibitors, such as sorafenib, regorafenib, and lenvatinib, have been approved for treating advanced HCC, only a short increase of median overall survival in HCC patients was achieved. Therefore, there is an urgent need to design more effective strategies for advanced HCC patients. Human ribonucleotide reductase is responsible for the conversion of ribonucleoside diphosphate to 2′-deoxyribonucleoside diphosphate to maintain the homeostasis of nucleotide pools. In this study, mining the cancer genomics and proteomics data revealed that ribonucleotide reductase regulatory subunit M2 (RRM2) serves as a prognosis biomarker and a therapeutic target for HCC. The RNA sequencing (RNA-Seq) analysis and public microarray data mining found that RRM2 was a novel molecular target of sorafenib in HCC cells. In vitro experiments validated that sorafenib inhibits RRM2 expression in HCC cells, which is positively associated with the anticancer activity of sorafenib. Although both RRM2 knockdown and sorafenib induced autophagy in HCC cells, restoration of RRM2 expression did not rescue HCC cells from sorafenib-induced autophagy and growth inhibition. However, long-term colony formation assay indicated that RRM2 overexpression partially rescues HCC cells from the cytotoxicity of sorafenib. Therefore, this study identifies that RRM2 is a novel target of sorafenib, partially contributing to its anticancer activity in HCC cells.
Early Attentional Modulation by Working Memory Training in Young Adult ADHD Patients during a Risky Decision-Making Task
Authors: Jaquerod Manon E. , Mesrobian Sarah K. , Villa Alessandro E. P. , Bader Michel , Lintas Alessandra
Published: January 2020

Background: Working memory (WM) deficits and impaired decision making are among the characteristic symptoms of patients affected by attention deficit/hyperactivity disorder (ADHD). The inattention associated with the disorder is likely to be due to functional deficits of the neural networks inhibiting irrelevant sensory input. In the presence of unnecessary information, a good decisional process is impaired and ADHD patients tend to take risky decisions. This study is aimed to test the hypothesis that the level of difficulty of a WM training (WMT) is affecting the top-down modulation of the attentional processes in a probabilistic gambling task. Methods: Event-related potentials (ERP) triggered by the choice of the amount wagered in the gambling task were recorded, before and after WMT with a the dual n-back task, in young ADHD adults and matched controls. For each group of participants, randomly assigned individuals were requested to perform WMT with a fixed baseline level of difficulty. The remaining participants were trained with a performance-dependent adaptive n-level of difficulty. Results: We compared the ERP recordings before and after 20 days of WMT in each subgroup. The analysis was focused on the time windows with at least three recording sites showing differences before and after training, after Bonferroni correction ( p < 0.05 ). In ADHD, the P1 wave component was selectively affected at frontal sites and its shape was recovered close to controls’ only after adaptive training. In controls, the strongest contrast was observed at parietal level with a left hemispheric dominance at latencies near 900 ms, more after baseline than after adaptive training. Conclusion: Partial restoration of early selective attentional processes in ADHD patients might occur after WMT with a high cognitive load. Modified frontal sites’ activities might constitute a neural marker of this effect in a gambling task. In controls, conversely, an increase in late parietal negativity might rather be a marker of an increase in transfer effects to fluid intelligence.
Infants Segment Words from Songs—An EEG Study
Authors: Snijders Tineke M. , Benders Titia , Fikkert Paula
Published: January 2020

Children’s songs are omnipresent and highly attractive stimuli in infants’ input. Previous work suggests that infants process linguistic–phonetic information from simplified sung melodies. The present study investigated whether infants learn words from ecologically valid children’s songs. Testing 40 Dutch-learning 10-month-olds in a familiarization-then-test electroencephalography (EEG) paradigm, this study asked whether infants can segment repeated target words embedded in songs during familiarization and subsequently recognize those words in continuous speech in the test phase. To replicate previous speech work and compare segmentation across modalities, infants participated in both song and speech sessions. Results showed a positive event-related potential (ERP) familiarity effect to the final compared to the first target occurrences during both song and speech familiarization. No evidence was found for word recognition in the test phase following either song or speech. Comparisons across the stimuli of the present and a comparable previous study suggested that acoustic prominence and speech rate may have contributed to the polarity of the ERP familiarity effect and its absence in the test phase. Overall, the present study provides evidence that 10-month-old infants can segment words embedded in songs, and it raises questions about the acoustic and other factors that enable or hinder infant word segmentation from songs and speech.
The Effect of Aging on the ERP Correlates of Feedback Processing in the Probabilistic Selection Task
Authors: West Robert , Huet AnnMarie
Published: January 2020

Feedback processing contributes to efficient learning, decision making, and social interaction. Studies using event-related brain potentials (ERPs) reveal that feedback processing is associated with transient ERP components over the medial frontal and posterior regions of the scalp that distinguish between positive and negative feedback. There is some evidence indicating that aging has differential effects on the ERP correlates of feedback processing in a gambling task, and the current study was designed to extend these findings to a reinforcement learning paradigm. Younger and older adults performed the probabilistic selection task while ERPs elicited by feedback cues indicating a correct or incorrect choice were recorded during the learning phase. The ERPs revealed that the amplitude of the feedback negativity and frontal P3 were attenuated in older adults relative to younger adults. The amplitude of a temporal positivity was also attenuated in older adults; in contrast, the amplitude of an occipital negativity was insensitive to the effects of aging. These findings indicate that aging may be associated with the disruption of both local activity and long-range connectivity between neural structures related to feedback processing.
Insights from a Bibliometric Analysis of Vividness and Its Links with Consciousness and Mental Imagery
Authors: Haustein Stefanie , Vellino André , D’Angiulli Amedeo
Published: January 2020

We performed a bibliometric analysis of the peer-reviewed literature on vividness between 1900 and 2019 indexed by the Web of Science and compared it with the same analysis of publications on consciousness and mental imagery. While we observed a similarity between the citation growth rates for publications about each of these three subjects, our analysis shows that these concepts rarely overlap (co-occur) in the literature, revealing a surprising paucity of research about these concepts taken together. A disciplinary analysis shows that the field of Psychology dominates the topic of vividness, even though the total number of publications containing that term is small and the concept occurs in several other disciplines such as Computer Science and Artificial Intelligence. The present findings suggest that without a coherent unitary framework for the use of vividness in research, important opportunities for advancing the field might be missed. In contrast, we suggest that an evidence-based framework (such as the bibliometric analytic methods as exemplified here) will help to guide research from all disciplines that are concerned with vividness and help to resolve the challenge of epistemic incommensurability amongst published research in multidisciplinary fields.
Coping Strategies and Personality Profile Characteristics of People Whose Parents Were Alcohol Addicts
Authors: Lutsenko Anna M.
Published: January 2020

The relevance of this research is due to the wide prevalence of addictive behavior and the insufficient knowledge of the coping strategies of patients and their families. The purpose of this research was to investigate the resource factors and coping strategies of adults with alcohol-addicted parents and to make recommendations for psychological counseling for these people. The sample consisted of 52 subjects—who were participants in a twelve-step rehabilitation program for adult people whose parents had alcohol addictions—and 50 controls. We used guilt questionnaires (“The Guilt Inventory Questionnaire”, “The Interpersonal Guilt Questionnaire”), quantitative methods for evaluating the coping strategies used by participants (“coping strategies” (Lazarus, Folkman)), and a phenomenological analysis of the interviews with the participants. The results showed that adults with alcohol-addicted parents felt guilty in situations when they took care of somebody because their own parents did not model (and teach them) caretaking behavior. People whose parents were alcohol addicts tend to avoid accepting responsibility for their lives. The resource factors of people with alcohol-addicted parents included keeping a diary, participation in a rehabilitation program, and confidential communication with other people.