bluuebunny/crossref_metadata_2025 huggingface dataset:
TGFβ Imprinting During Activation Promotes Natural Killer Cell Cytokine Hypersecretion
Authors: Foltz Jennifer A. , Moseman Jena E. , Thakkar Aarohi , Chakravarti Nitin , Lee Dean A.
Published: November 2018

Transforming growth factor-beta (TGFβ) is a potent immunosuppressive cytokine that inhibits the anti-tumor responses of NK cells and T cells. However, the stimulation of natural killer (NK) cells with pro-inflammatory cytokines decreases NK cell sensitivity to TGFβ. Herein, we sought to determine if TGFβ imprinting (TGFβi) during NK cell activation and expansion would decrease NK cell sensitivity to TGFβ suppression. To this end, we demonstrate that the activation of NK cells during chronic IL-2 stimulation and TGFβi potently induces NK cell hypersecretion of interferon-gamma (IFNγ) and tumor necrosis factor-alpha (TNFα) in response to tumor targets which persists for at least one month in vitro after the removal of TGFβ. TGFβi NK cell cytokine hypersecretion is induced following both cytokine and tumor activation. Further, TGFβi NK cells have a marked suppression of SMAD3 and T-bet which is associated with altered chromatin accessibility. In contrast to their heightened cytokine secretion, TGFβi NK cells downregulate several activating receptors, granzyme and perforin, and upregulate TRAIL, leading to cell-line-specific alterations in cytotoxicity. These findings may impact our understanding of how TGFβ affects NK cell development and anti-tumor function.
Population Based Testing for Primary Prevention: A Systematic Review
Authors: Manchanda Ranjit , Gaba Faiza
Published: November 2018

The current clinical model for genetic testing is based on clinical-criteria/family-history (FH) and a pre-defined mutation probability threshold. It requires people to develop cancer before identifying unaffected individuals in the family to target prevention. This process is inefficient, resource intensive and misses >50% of individuals or mutation carriers at risk. Population genetic-testing can overcome these limitations. It is technically feasible to test populations on a large scale; genetic-testing costs are falling and acceptability and awareness are rising. MEDLINE, EMBASE, Pubmed, CINAHL and PsychINFO databases were searched using free-text and MeSH terms; retrieved reference lists of publications were screened; additionally, web-based platforms, Google, and clinical-trial registries were searched. Quality of studies was evaluated using appropriate check-lists. A number of studies have evaluated population-based BRCA-testing in the Jewish population. This has been found to be acceptable, feasible, clinically-effective, safe, associated with high satisfaction rates and extremely cost-effective. Data support change in guidelines for population-based BRCA-testing in the Jewish population. Population panel testing for BRCA1/BRCA2/RAD51C/RAD51D/BRIP1/PALB2 gene mutations is the most cost-effective genetic-testing strategy in general-population women and can prevent thousands more breast and ovarian cancers than current clinical-criteria based approaches. A few ongoing studies are evaluating population-based genetic-testing for multiple cancer susceptibility genes in the general population but more implementation studies are needed. A future population-testing programme could also target other chronic diseases.
Leukocyte Telomere Length and Chronic Conditions in Older Women of Northeast Brazil: A Cross-Sectional Study
Authors: Oliveira Bruna , Pirkle Catherine M. , Zunzunegui Maria , Batistuzzo de Medeiros Silvia , Thomasini Ronaldo , Guerra Ricardo
Published: November 2018

This study assessed whether telomere length is related to chronic conditions, cardiovascular risk factors, and inflammation in women aged 65 to 74 from Northeast Brazil. Participants were selected from two sources, a representative sample of the International Mobility in Aging Study (n = 57) and a convenience sample (n = 49) recruited at senior centers. Leukocyte telomere length was measured by quantitative polymerase chain reaction from blood samples in 83 women. Natural log-transformed telomere/single copy gene ratio was used as the dependent variable in the analysis. Blood analyses included inflammatory markers (high-sensitivity C-reactive protein and interleukin-6), total, low-density lipoprotein and high-density lipoprotein cholesterol, triglycerides, glucose and glycosylated hemoglobin. Self-rated health, chronic conditions, cardiovascular risk factors and inflammatory markers were not associated with telomere length. No significant independent association was found between telomere length and anthropometric measures or blood markers, even after adjusting for age, education and adverse childhood events among these older women in Northeast Brazil. Our results did not confirm the hypothesis that chronic conditions, cardiovascular risk factors or inflammation are associated with shorter telomere length in these women who have exceptional survival relative to the life expectancy of their birth cohort.
Inferring Novel Autophagy Regulators Based on Transcription Factors and Non-Coding RNAs Coordinated Regulatory Network
Authors: Wang Shuyuan , Wang Wencan , Meng Qianqian , Zhou Shunheng , Liu Haizhou , Ma Xueyan , Zhou Xu , Liu Hui , Chen Xiaowen , Jiang Wei
Published: November 2018

Autophagy is a complex cellular digestion process involving multiple regulators. Compared to post-translational autophagy regulators, limited information is now available about transcriptional and post-transcriptional regulators such as transcription factors (TFs) and non-coding RNAs (ncRNAs). In this study, we proposed a computational method to infer novel autophagy-associated TFs, micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) based on TFs and ncRNAs coordinated regulatory (TNCR) network. First, we constructed a comprehensive TNCR network, including 155 TFs, 681 miRNAs and 1332 lncRNAs. Next, we gathered the known autophagy-associated factors, including TFs, miRNAs and lncRNAs, from public data resources. Then, the random walk with restart (RWR) algorithm was conducted on the TNCR network by using the known autophagy-associated factors as seeds and novel autophagy regulators were finally prioritized. Leave-one-out cross-validation (LOOCV) produced an area under the curve (AUC) of 0.889. In addition, functional analysis of the top 100 ranked regulators, including 55 TFs, 26 miRNAs and 19 lncRNAs, demonstrated that these regulators were significantly enriched in cell death related functions and had significant semantic similarity with autophagy-related Gene Ontology (GO) terms. Finally, extensive literature surveys demonstrated the credibility of the predicted autophagy regulators. In total, we presented a computational method to infer credible autophagy regulators of transcriptional factors and non-coding RNAs, which would improve the understanding of processes of autophagy and cell death and provide potential pharmacological targets to autophagy-related diseases.
Dysregulation of the Immune System in HIV/HCV-Coinfected Patients According to Liver Stiffness Status
Authors: Garcia-Broncano Pilar , Medrano Luz , Berenguer Juan , González-García Juan , Jiménez-Sousa Mª , Carrero Ana , Hontañón Victor , Guardiola Josep , Crespo Manuel , Quereda Carmen , Sanz José , García-Gómez Ana , Jimenez Jose , Resino Salvador ,   The GESIDA 3603b Study Group
Published: November 2018

Background: Advanced cirrhosis is related to alterations in immunity. We aimed to evaluate the levels of peripheral CD4+ T cells (Tregs) and plasma cytokine in patients coinfected with human immunodeficiency virus and hepatitis C virus (HIV/HCV) according to liver fibrosis stages [evaluated as liver stiffness measure (LSM)] and their linear relationship. Methods: We performed a cross-sectional study on 238 HIV/HCV-coinfected patients (119 had <12.5 kPa, 73 had 12.5–25 kPa, and 46 had >25 kPa). Peripheral T-cell subsets were phenotyped by flow cytometry, plasma biomarkers were assessed by multiplex immunoassays, and LSM was assessed by transient elastography. Results: We found HIV/HCV-coinfected patients had higher values of CD4+ Tregs (p < 0.001), memory Tregs (p ≤ 0.001), and plasma cytokine levels [IFN-γ (p ≤ 0.05) and IL-10 (p ≤ 0.01)] compared with healthy donors and HIV-monoinfected patients. In the multivariate analysis, higher LSM values were associated with reduced levels of IL-10 (adjusted arithmetic mean ratio (aAMR) = 0.83; p = 0.019), IL-2 (aAMR = 0.78; p = 0.017), TNF-α (aAMR = 0.67; p < 0.001), and IL-17A (aAMR = 0.75; p = 0.006). When we focus on HIV/HCV-coinfected patients analyzed by LSM strata, patients with ≥25 kPa had lower values of IL-2 (aAMR = 0.66; p = 0.021), TNF-α (aAMR = 0.565; p = 0.003), and IL-17A (aAMR = 0.58; p = 0.003) than patients with <12.5 kPa. Conclusion: HIV/HCV-coinfected patients showed an immunosuppressive profile compared to healthy controls and HIV-monoinfected patients. Additionally, HIV/HCV-coinfected patients with advanced cirrhosis (LSM ≥ 25 kPa) had the lowest plasma values of cytokines related to Th1 (IL-2 and TNF-α) and Th17 (IL-17A) response.
Dynamic Properties of Mixed Cationic/Nonionic Adsorbed Layers at the N-Hexane/Water Interface: Capillary Pressure Experiments Under Low Gravity Conditions
Authors: Loglio Giuseppe , Kovalchuk Volodymyr I. , Bykov Alexey G. , Ferrari Michele , Krägel Jürgen , Liggieri Libero , Miller Reinhard , Noskov Boris A. , Pandolfini Piero , Ravera Francesca , Santini Eva
Published: November 2018

Capillary pressure experiments are performed in microgravity conditions on board the International Space Station to quantify the dynamic interfacial behavior of mixed adsorption layers of TTAB and C13DMPO at the water/hexane interface. While the non-ionic surfactant C13DMPO is soluble in both bulk phases, water and hexane, the cationic surfactant TTAB is only soluble in the aqueous phase. The interfacial layer is thus formed by TTAB molecules adsorbing from the aqueous phase while the C13DMPO molecules adsorb from the aqueous phase, and transfer partially into the hexane phase until both the equilibrium of adsorption and the distribution between the two adjacent liquid phases is established. The experimental constrains as well as all possible influencing parameters, such as interfacial and bulk phase compressibility, interfacial curvature, calibration of pressure and absolute geometry size, are discussed in detail. The experimental results in terms of the dilational interfacial viscoelasticity of the mixed adsorption layers in a wide range of oscillation frequencies show that the existing theoretical background had to be extended in order to consider the effect of transfer of the non-ionic surfactant across the interface, and the curvature of the water/hexane interface. A good qualitative agreement between theory and experiment was obtained, however, for a quantitative comparison, additional accurate information on the adsorption isotherms and diffusion coefficients of the two studied surfactants in water and hexane, alone and in a mixed system, are required.
Crystal Dislocations: Their Impact on Physical Properties of Crystals
Authors: Lagerlof Peter
Published: November 2018

It is rare to find technical applications involving a material of any crystal structure that is not impacted by dislocations—which affect the material’s mechanical properties, interfaces, martensitic phase transformations, crystal growth, and electronic properties, to name a few. [...]
An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components
Authors: Babichev Sergii
Published: November 2018

This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components. The information technology is presented as a structural block-chart, which contains all stages of the studied data processing. The hybrid model of objective clustering based on the SOTA algorithm and the technology of gene regulatory networks reconstruction have been investigated to evaluate the stability to the level of the noise components. The results of the simulation have shown that the hybrid model of the objective clustering has high level of stability to noise components and vice versa, the technology of gene regulatory networks reconstruction is rather sensitive to the level of noise component. The obtained results indicate the importance of gene expression profiles preprocessing at the early stage of the gene regulatory network reconstruction in order to remove background noise and non-informative genes in terms of the used criteria.
The Neglect and Fast Spread of Some Arboviruses: A Note for Healthcare Providers in Nigeria
Authors: Kolawole Olatunji M. , Seriki Adebimpe A. , Irekeola Ahmad A. , Ogah Jeremiah I.
Published: November 2018

Arboviruses are distributed worldwide and constitute significant health burden globally. Outbreaks of arboviruses have been reported in Africa and beyond. In Nigeria, like in many other countries, arbovirus infections are more often than not neglected. As the early clinical features of arbovirus infections are generally nonspecific, most healthcare providers mistake them for other diseases. Outbreaks have been reported in Africa and beyond. The consequence of missed diagnosis of diseases cannot be overstated. In this review, some epidemiological data, classical syndromes, and risk factors for five human arboviruses (yellow fever YF, dengue DENV, chikungunya CHIKV, Rift Valley fever RVF, and West Nile virus WNV) found in Nigeria are presented. Health practitioners should ensure in-depth analysis rather than a superficial diagnosis of diseases before declaring a course of treatment.
Higher Order Geometric Theory of Information and Heat Based on Poly-Symplectic Geometry of Souriau Lie Groups Thermodynamics and Their Contextures: The Bedrock for Lie Group Machine Learning
Authors: Barbaresco Frédéric
Published: November 2018

We introduce poly-symplectic extension of Souriau Lie groups thermodynamics based on higher-order model of statistical physics introduced by Ingarden. This extended model could be used for small data analytics and machine learning on Lie groups. Souriau geometric theory of heat is well adapted to describe density of probability (maximum entropy Gibbs density) of data living on groups or on homogeneous manifolds. For small data analytics (rarified gases, sparse statistical surveys, …), the density of maximum entropy should consider higher order moments constraints (Gibbs density is not only defined by first moment but fluctuations request 2nd order and higher moments) as introduced by Ingarden. We use a poly-sympletic model introduced by Christian Günther, replacing the symplectic form by a vector-valued form. The poly-symplectic approach generalizes the Noether theorem, the existence of moment mappings, the Lie algebra structure of the space of currents, the (non-)equivariant cohomology and the classification of G-homogeneous systems. The formalism is covariant, i.e., no special coordinates or coordinate systems on the parameter space are used to construct the Hamiltonian equations. We underline the contextures of these models, and the process to build these generic structures. We also introduce a more synthetic Koszul definition of Fisher Metric, based on the Souriau model, that we name Souriau-Fisher metric. This Lie groups thermodynamics is the bedrock for Lie group machine learning providing a full covariant maximum entropy Gibbs density based on representation theory (symplectic structure of coadjoint orbits for Souriau non-equivariant model associated to a class of co-homology).
Improved Cryptanalysis and Enhancements of an Image Encryption Scheme Using Combined 1D Chaotic Maps
Authors: Zhu Congxu , Wang Guojun , Sun Kehui
Published: November 2018

This paper presents an improved cryptanalysis of a chaos-based image encryption scheme, which integrated permutation, diffusion, and linear transformation process. It was found that the equivalent key streams and all the unknown parameters of the cryptosystem can be recovered by our chosen-plaintext attack algorithm. Both a theoretical analysis and an experimental validation are given in detail. Based on the analysis of the defects in the original cryptosystem, an improved color image encryption scheme was further developed. By using an image content–related approach in generating diffusion arrays and the process of interweaving diffusion and confusion, the security of the cryptosystem was enhanced. The experimental results and security analysis demonstrate the security superiority of the improved cryptosystem.
Generalized Distance-Based Entropy and Dimension Root Entropy for Simplified Neutrosophic Sets
Authors: Cui Wen-Hua , Ye Jun
Published: November 2018

In order to quantify the fuzziness in the simplified neutrosophic setting, this paper proposes a generalized distance-based entropy measure and a dimension root entropy measure of simplified neutrosophic sets (NSs) (containing interval-valued and single-valued NSs) and verifies their properties. Then, comparison with the existing relative interval-valued NS entropy measures through a numerical example is carried out to demonstrate the feasibility and rationality of the presented generalized distance-based entropy and dimension root entropy measures of simplified NSs. Lastly, a decision-making example is presented to illustrate their applicability, and then the decision results indicate that the presented entropy measures are effective and reasonable. Hence, this study enriches the simplified neutrosophic entropy theory and measure approaches.
Stock Prices of Renewable Energy Firms: Are There Asymmetric Responses to Oil Price Changes?
Authors: Lee Donggyu , Baek Jungho
Published: November 2018

This article revisits the question of whether crude oil prices have a positive effect on stock the prices of renewable energy firms. To examine this question carefully, we allow for the asymmetric effects of oil price changes in our modeling process, using the nonlinear autoregressive distributed lag (ARDL) approach. We find that changes in oil prices indeed have a significant, positive short-run effect on renewable energy stock prices in an asymmetric manner. However, this short-run effect does not appear to last in the long-run.
Ignatian Pedagogy as a Frame for Universal Design in College: Meeting Learning Needs of Generation Z
Authors: Pousson J. Mark , Myers Karen A.
Published: November 2018

In viewing the principles of Universal Instructional Design (UID), both inside and outside the classroom, a direct connection may be made to the principles of Ignatian pedagogy—a 500-year old tradition of education—in meeting the learning needs of today’s college students, Generation Z. The Ignatian pedagogy as a frame for universal instructiosnal design principles can guide instructors to understand how college students can learn best and facilitate that knowledge acquisition to serve the common good. This article addresses Generation Z’s experience with digital technology and illustrates how the Ignatian pedagogical model tenets (i.e., context, experience, reflection, action, and evaluation) connect with UID practices in a higher education curriculum. Examples of UID, as it applies to each tenet and to web access, are included.
An Energy Management Platform for Public Buildings
Authors: Ferreira Joao C. , Afonso Jose A. , Monteiro Vitor , Afonso Joao L.
Published: November 2018

This paper describes the development and implementation of an electronic platform for energy management in public buildings. The developed platform prototype is based on the installation of a network of wireless sensors using the emerging Long Range (LoRa) low power long-range wireless network technology. This network is used to collect sensor data, which is stored online and manipulated to extract knowledge and generate actions toward energy saving solutions. In this process, gamification approaches were used to motivate changes in the users’ behavior towards more sustainable actions in public buildings. These actions and the associated processes can be implemented as public services, and they can be replicated to different public buildings, contributing to a more energy-sustainable world. The developed platform allows the monitoring and management of the heating/cooling, electric power consumption, and lighting levels. In order to validate the proposed electronic platform, sensor information was collected in the context of a university campus, which was used as an application scenario in public buildings.
40 dB-Isolation, 1.85 dB-Insertion Loss Full CMOS SPDT Switch with Body-Floating Technique and Ultra-Small Active Matching Network Using On-Chip Solenoid Inductor for BLE Applications
Authors: Nga Truong Thi Kim , Lee DongSoo , Kim SungJin , Lee Minjae , Hwang KeumCheol , Yang Youngoo , Lee Kang-Yoon
Published: November 2018

In the IoT/wearable devices, the antenna is shared with the receiver and transmitter of the transceiver. This requires the control of the switch between the antenna and the control circuitry to achieve both low insertion loss and high isolation. This paper presents a low insertion loss and high isolation switch based on Single Pole Double Throw (SPDT) switch for 2.4 GHz Bluetooth low power (BLE) transceiver. The body-floating technique is used to improve the insertion loss’s performance. An ultra-small on-chip matching network with high Q-factor is proposed. The shunt transistors are used as active shunt capacitors that create the active matching network to improve isolation characteristics. The proposed SDPT switch was designed using 55 nm CMOS process with the total area of 110 μm × 210 μm. The insertion loss and isolation characteristics of the proposed SPDT switch observed at 2.4 GHz are 1.85 dB and 40 dB, respectively.
Acoustic-Based Fault Diagnosis of Commutator Motor
Authors: Glowacz Adam
Published: November 2018

In the paper, the author presents acoustic-based fault diagnosis of a commutator motor (CM). Five states of the commutator motor were considered: healthy commutator motor, commutator motor with broken rotor coil, commutator motor with shorted stator coils, commutator motor with broken tooth on sprocket, commutator motor with damaged gear train. A method of feature extraction MSAF-15-MULTIEXPANDED-8-GROUPS (Method of Selection of Amplitudes of Frequency Multiexpanded 8 Groups) was described and implemented. Classification methods, such as nearest neighbour (NN), nearest mean (NM), self-organizing map (SOM), backpropagation neural network (BNN) were used for acoustic analysis of the commutator motor. The paper provides results of acoustic analysis of the commutator motor. The results had a good recognition rate. The results of acoustic analysis were in the range of 88.4–94.6%. The NM classifier and the MSAF-15-MULTIEXPANDED-8-GROUPS provided TERCM = 94.6%.
Asymmetric Impacts of Oil Price on Inflation: An Empirical Study of African OPEC Member Countries
Authors: Bala Umar , Chin Lee
Published: November 2018

This study investigates the asymmetric impacts of oil price changes on inflation in Algeria, Angola, Libya, and Nigeria. Three different kinds of oil price data were applied in this study: the actual spot oil price of individual countries, the OPEC reference basket oil price, and an average of the Brent, WTI, and Dubai oil price. Autoregressive distributed lag (ARDL) dynamic panels were used to estimate the short- and long-term impacts. Also, we partitioned the oil price into positive and negative changes to capture asymmetric impacts and found that both the positive and negative oil price changes positively influenced inflation. However, the impact was found to be more significant when the oil prices dropped. We also found that the money supply, the exchange rate, and the gross domestic product (GDP) are positively related to inflation, while food production is negatively related to inflation. Accordingly, policy-makers should be cautious when formulating policies between the positive and negative changes in oil prices, as it was shown that inflation increased when the oil price dropped. Additionally, the use of a contractionary monetary policy would help to reduce the inflation rate. Lastly, we suggest that the government should encourage domestic food production, both in quantity and quality, to reduce inflation.
Brine-Dependent Recovery Processes in Carbonate and Sandstone Petroleum Reservoirs: Review of Laboratory-Field Studies, Interfacial Mechanisms and Modeling Attempts
Authors: Awolayo Adedapo N. , Sarma Hemanta K. , Nghiem Long X.
Published: November 2018

Brine-dependent recovery, which involves injected water ionic composition and strength, has seen much global research efforts in the past two decades because of its benefits over other oil recovery methods. Several studies, ranging from lab coreflood experiments to field trials, indicate the potential of recovering additional oil in sandstone and carbonate reservoirs. Sandstone and carbonate rocks are composed of completely different minerals, with varying degree of complexity and heterogeneity, but wettability alteration has been widely considered as the consequence rather than the cause of brine-dependent recovery. However, the probable cause appears to be as a result of the combination of several proposed mechanisms that relate the wettability changes to the improved recovery. This paper provides a comprehensive review on laboratory and field observations, descriptions of underlying mechanisms and their validity, the complexity of the oil-brine-rock interactions, modeling works, and comparison between sandstone and carbonate rocks. The improvement in oil recovery varies depending on brine content (connate and injected), rock mineralogy, oil type and structure, and temperature. The brine ionic strength and composition modification are the two major frontlines that have been well-exploited, while further areas of investigation are highlighted to speed up the interpretation and prediction of the process efficiency.
A Sequential Approach for Integrated Coal and Gas Mining of Closely-Spaced Outburst Coal Seams: Results from a Case Study Including Mine Safety Improvements and Greenhouse Gas Reductions
Authors: Cheng Liang , Ge Zhaolong , Chen Jiufu , Ding Hao , Zou Lishuang , Li Ke
Published: November 2018

Closely-spaced outburst coal seams (COCS) is the main condition of coal seams in southwest China, and gas disasters are one of the major problems affecting coal mine safety. Mining a protective seam and pre gas extraction are the most safety way to improve the efficiency of mining under these conditions. However, low pre-mining gas extraction efficiency coupled with the close proximity of adjacent working faces is a problem. When mining at an old working face has been completed but the new working face is not yet ready to be mined, coal-bed gasses can flow into the new working face from adjacent seams and this commonly causes methane monitoring instruments to sound an alarm. These gas extraction difficulties lead to a conflict between mine safety and profit. To solve these problems, a sequential approach for integrated coal and gas mining of closely-spaced outburst coal seams is introduced in this paper. Two fundamental principles are proposed: (1) Fully coordinating the spatiotemporal relationships between gas extraction, roadway development, and coal mining to maximize both mine safety and coal and gas production; (2) Defining a mining sequence for outburst coal seams and choosing the coal seam with the weakest outburst risk as the protective seam. A system for comprehensive gas extraction in underground coal mines is divided into four stages for gas extraction: gas extraction before coal roadway tunneling, gas extraction before coal mining, gas extraction during coal mining, and gas extraction from the goaf after coal mining. The Songzao mining area, China, is used as a case study to demonstrate the effectiveness of this model, and it brings three major benefits: it improves underground coal mine safety with physical gas accidents decreased by 66.8%, it makes underground coal-bed methane (CBM) extraction more efficient with the average gas extraction rate were respectively 45.13 m3/t and 62.4%, the highest in China, and it reduces greenhouse gas emissions equivalent to 3.5 million tonnes of carbon dioxide. This study could be used as a valuable example for other coal deposits being mined under similar geological conditions.
Energy Commodity Price Forecasting with Deep Multiple Kernel Learning
Authors: Huang Shian-Chang , Wu Cheng-Feng
Published: November 2018

Oil is an important energy commodity. The difficulties of forecasting oil prices stem from the nonlinearity and non-stationarity of their dynamics. However, the oil prices are closely correlated with global financial markets and economic conditions, which provides us with sufficient information to predict them. Traditional models are linear and parametric, and are not very effective in predicting oil prices. To address these problems, this study developed a new strategy. Deep (or hierarchical) multiple kernel learning (DMKL) was used to predict the oil price time series. Traditional methods from statistics and machine learning usually involve shallow models; however, they are unable to fully represent complex, compositional, and hierarchical data features. This explains why traditional methods fail to track oil price dynamics. This study aimed to solve this problem by combining deep learning and multiple kernel machines using information from oil, gold, and currency markets. DMKL is good at exploiting multiple information sources. It can effectively identify the relevant information and simultaneously select an apposite data representation. The kernels of DMKL were embedded in a directed acyclic graph (DAG), which is a deep model and efficient at representing complex and compositional data features. This provided a solid foundation for extracting the key features of oil price dynamics. By using real data for empirical testing, our new system robustly outperformed traditional models and significantly reduced the forecasting errors.
Simultaneous Extraction and Emulsification of Food Waste Liquefaction Bio-Oil
Authors: Längauer David , Lin Yu-Ying , Chen Wei-Hsin , Wang Chao-Wen , Šafář Michal , Čablík Vladimír
Published: November 2018

Biomass-derived bio-oil is a sustainable and renewable energy resource, and liquefaction is a potential conversion way to produce bio-oil. Emulsification is a physical upgrading technology, which blends immiscible liquids into a homogeneous emulsion through the addition of an emulsifier. Liquefaction bio-oil from food waste is characterized by its high pour point when compared to diesel fuel. In order to partially replace diesel fuel by liquefaction bio-oil, this study aimed to develop a method to simultaneously extract and emulsify the bio-oil using a commercial surfactant (Atlox 4914, CRODA, Snaith, UK). The solubility and stability of the emulsions at various operating conditions such as the bio-oil-to-emulsifier ratio (B/E ratio), storage temperature and duration, and co-surfactant (methanol) addition were analyzed. The results demonstrate that higher amounts of bio-oil (7 g) and emulsifier (7 g) at a B/E ratio = 1 in an emulsion have a higher solubility (66.48 wt %). When the B/E ratio was decreased from 1 to 0.556, the bio-oil solubility was enhanced by 45.79%, even though the storage duration was up to 7 days. Compared to the emulsion stored at room temperature (25 °C), its storage at 100 °C presented a higher solubility, especially at higher B/E ratios. Moreover, when methanol was added as a co-surfactant during emulsification at higher B/E ratios (0.714 to 1), it rendered better solubility (58.83–70.96 wt %). Overall, the emulsified oil showed greater stability after the extraction-emulsification process.
Experimental and Numerical Collaborative Latching Control of Wave Energy Converter Arrays
Authors: Thomas Simon , Eriksson Mikael , Göteman Malin , Hann Martyn , Isberg Jan , Engström Jens
Published: November 2018

A challenge while applying latching control on a wave energy converter (WEC) is to find a reliable and robust control strategy working in irregular waves and handling the non-ideal behavior of real WECs. In this paper, a robust and model-free collaborative learning approach for latchable WECs in an array is presented. A machine learning algorithm with a shallow artificial neural network (ANN) is used to find optimal latching times. The applied strategy is compared to a latching time that is linearly correlated with the mean wave period: It is remarkable that the ANN-based WEC achieved a similar power absorption as the WEC applying a linear latching time, by applying only two different latching times. The strategy was tested in a numerical simulation, where for some sea states it absorbed more than twice the power compared to the uncontrolled WEC and over 30% more power than a WEC with constant latching. In wave tank tests with a 1:10 physical scale model the advantage decreased to +3% compared to the best tested constant latching WEC, which is explained by the lower advantage of the latching strategy caused by the non-ideal latching of the physical power take-off model.
Hybrid Approach for Detecting and Classifying Power Quality Disturbances Based on the Variational Mode Decomposition and Deep Stochastic Configuration Network
Authors: Cai Kewei , Alalibo Belema Prince , Cao Wenping , Liu Zheng , Wang Zhiqiang , Li Guofeng
Published: November 2018

This paper proposes a novel, two-stage and hybrid approach based on variational mode decomposition (VMD) and the deep stochastic configuration network (DSCN) for power quality (PQ) disturbances detection and classification in power systems. Firstly, a VMD technique is applied to discriminate between stationary and non-stationary PQ events. Secondly, the key parameters of VMD are determined as per different types of disturbance. Three statistical features (mean, variance, and kurtosis) are extracted from the instantaneous amplitude (IA) of the decomposed modes. The DSCN model is then developed to classify PQ disturbances based on these features. The proposed approach is validated by analytical results and actual measurements. Moreover, it is also compared with existing methods including wavelet network, fuzzy and S-transform (ST), adaptive linear neuron (ADALINE) and feedforward neural network (FFNN). Test results have proved that the proposed method is capable of providing necessary and accurate information for PQ disturbances in order to plan PQ remedy actions accordingly.
Assessing the Translucence and Color-Change Methods for Estimating Sapwood Depth in Three Boreal Species
Authors: Quiñonez-Piñón M. Rebeca , Valeo Caterina
Published: November 2018

The translucence and color change in wood methods, which are commonly used to differentiate sapwood from heartwood in tree cores, are compared against the microscopic analysis of wood anatomy method for determining sapwood depth. The translucence method was tested on collected wood cores of White Spruce (Picea glauca (Moench) Voss) and Jack Pine (Pinus banksiana Lamb.). The color change in wood method was tested on Trembling Aspen (Populus tremuloides Michx.). For every statistical comparison, sapwood depth values obtained with the translucence or color-change methods were significantly different from those obtained using the microscopic analysis. Using the sapwood depth values obtained with microscopy as a reference, the bias associated with the translucence or color-change methods used on Picea glauca, Pinus banksiana and Populus tremuloides constantly under- or overestimated sapwood depths within −0.3 cm to 1.6 cm; −4.9 cm to 0.5 cm; and 0 to 1.8 cm, respectively. The different ranges of over- and underestimation arise from species-specific anatomical characteristics. Estimates for the errors in sapwood depth, when the depth is measured using either the translucence or color-change methods, are presented. These relationships and research outcomes will lead to more efficient forest monitoring and improved estimates of forest water balance, which in turn will lead to improved forest management in the face of climate change.
Design and Implementation of a RFID Reader/Router in RFID-WSN Hybrid System
Authors: Ji Wusheng , Li Li , Zhou Weiwei
Published: November 2018

In order to put Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) in a hybrid system, this paper presents the design and implementation of a RFID reader/router that can obtain information of both RFID tags and WSN sensor nodes and transmit the information through the WSN to the PC server. The RFID reader and WSN router are combined with both hardware and software. In hardware structure, CC2530 is used as micro controller and RF module for ZigBee wireless communication, and MF RC522 is used as reader RF chip. The software deals with both identity and sensing information and controls the routing. Experiment results show that the RFID reader/router achieves long distance identification, flexibility, scalability, and low cost. It also provides reliable and secured data transmission and broadens the communication range and application scope of RFID readers.
Composting as a Service: A Real-World IoT Implementation
Authors: Nikoloudakis Yannis , Panagiotakis Spyridon , Manios Thrasivoulos , Markakis Evangelos , Pallis Evangelos
Published: November 2018

Composting is the delicate procedure of supervised decomposition of organic waste, which gradually transforms waste to nutrient-rich manure. It requires deep knowledge and constant attention by experts to achieve a quality outcome in a timely fashion. Nevertheless, due to the bizarre nature of the materials and the overall procedure, along with the space required and emitted odors, it is required that composting infrastructures and machinery are installed away from residential areas, rendering supervision a very tedious task. Automatic composting machinery is a promising new idea, but still cannot substitute the insightfulness of a human supervisor. In this paper, we introduce COMPosting as a Service (COMPaaS). COMPaaS is a novel cloud service in composition with specialized Internet of Things (IoT)-based composting machinery that allows for unsupervised composting. The focus of this work is on the tiered IT approach that is adopted following the edge-computing paradigm. More specifically, composting machinery, enriched with several sensors and actuators, performs a set of basic routine tasks locally and sends sensor values to a cloud service which performs real-time data analysis and instructs the composting machinery to perform the appropriate actions based on the outcome of the analysis. The overall composting procedure is performed in a completely unsupervised manner, and field evaluation has shown an up to 30% faster outcome in comparison to traditional supervised composting.
Determinants of Equilibrium Selection in Network Formation: An Experiment
Authors: Hoyer Britta , Rosenkranz Stephanie
Published: November 2018

Theoretical models on network formation focus mostly on the stability and efficiency of equilibria, but they cannot deliver an understanding of why specific equilibrium networks are selected or whether they are all actually reachable from any starting network. To study factors affecting equilibrium selection, we designed a network formation experiment with multiple equilibria, which can be categorized in terms of the demand on players’ farsightedness and robustness to errors. In a second scenario, we increase the need for farsighted behavior by players, as well as the perceived riskiness of equilibria by adding a stage in which the network is disrupted. This setting allows us to analyze the interplay between the need for farsightedness and perceived risk of errors and its effect on network formation and equilibrium selection.
Learning Dynamics and Norm Psychology Supports Human Cooperation in a Large-Scale Prisoner’s Dilemma on Networks
Authors: Realpe-Gómez John , Vilone Daniele , Andrighetto Giulia , Nardin Luis G. , Montoya Javier A.
Published: November 2018

In this work, we explore the role of learning dynamics and social norms in human cooperation on networks. We study the model recently introduced in [Physical Review E, 97, 042321 (2018)] that integrates the well-studied Experience Weighted Attraction learning model with some features characterizing human norm psychology, namely the set of cognitive abilities humans have evolved to deal with social norms. We provide further evidence that this extended model—that we refer to as Experience Weighted Attraction with Norm Psychology—closely reproduces cooperative patterns of behavior observed in large-scale experiments with humans. In particular, we provide additional support for the finding that, when deciding to cooperate, humans balance between the choice that returns higher payoffs with the choice in agreement with social norms. In our experiment, agents play a prisoner’s dilemma game on various network structures: (i) a static lattice where agents have a fixed position; (ii) a regular random network where agents have a fixed position; and (iii) a dynamic lattice where agents are randomly re-positioned at each game iteration. Our results show that the network structure does not affect the dynamics of cooperation, which corroborates results of prior laboratory experiments. However, the network structure does seem to affect how individuals balance between their self-interested and normative choices.
James Joyce and the Epiphanic Inscription: Towards an Art of Gesture as Rhythm
Authors: Tondello Alberto
Published: November 2018

In Agency and Embodiment, Carrie Noland describes gesture as “a type of inscription, a parsing of the body into signifying and operational units”, considering it as a means to read and decode the human body. Through an analysis of James Joyce’s collection of Epiphanies, my paper will examine how gesture, as a mode of expression of the body, can be transcribed on the written page. Written and collected to record a “spiritual manifestation” shining through “in the vulgarity of speech or gesture, or in a memorable phase of the mind itself”, Joyce’s Epiphanies can be considered as the first step in his sustained attempt to develop an art of gesture-as-rhythm. These short pieces appear as the site in which the author seeks, through the medium of writing, to negotiate and redefine the boundaries of the physical human body. Moving towards a mapping of body and mind through the concept of rhythm, and pointing to a collaboration and mutual influence between interiority and exteriority, the Epiphanies open up a space for the reformulation of the relationship between the human body and its environment. Unpacking the ideas that sit at the heart of the concept of epiphany, the paper will shed light on how this particular mode of writing produces a rhythmic art of gesture, fixing and simultaneously liberating human and nonhuman bodies on the written page.
Food Allergy Prevalence in Salvadoran Schoolchildren Estimated by Parent-Report
Authors: Cabrera-Chávez Francisco , Rodríguez-Bellegarrigue Cecilia Ivonne , Figueroa-Salcido Oscar Gerardo , Lopez-Gallardo Jesús Aristeo , Arámburo-Gálvez Jesús Gilberto , Vergara-Jiménez Marcela de Jesús , Castro-Acosta Mónica Lizzette , Sotelo-Cruz Norberto , Gracia-Valenzuela Martina Hilda , Ontiveros Noé
Published: November 2018

The prevalence of food allergy (FA) has not been estimated at a population level in Central American countries and, consequently, the magnitude and relevance of the problem in the Central American region remains unknown. Thus, our aim was to evaluate the parent-reported prevalence of FA in a population of schoolchildren from the Central American country El Salvador. A Spanish version of a structured questionnaire was utilized. Five hundred and eight (508) parents returned the questionnaire with valid responses (response rate, 32%). The estimated prevalence rates (95% CI) were: adverse food reactions 15.9 (13.0–19.3), “perceived FA, ever” 11.6 (9.1–14.6), “physician-diagnosed FA, ever” 5.7% (4.0–8.0), “immediate-type FA, ever” 8.8% (6.6–11.6), “immediate-type FA, current” 5.3% (3.6–7.6), and anaphylaxis 2.5% (1.5–4.3). The most common food allergens were milk (1.7%), shrimp (1.3), chili (0.7%), chocolate (0.7%), and nuts (0.3%). Most of the “food-dependent anaphylaxis” cases (60.5%) sought medical attention, but only one case reported the prescription of an epinephrine autoinjector. Mild and severe FA cases are not uncommon among Salvadoran schoolchildren and both the prescription of epinephrine autoinjectors by healthcare personnel and the use of the autoinjectors by anaphylactic individuals should be encouraged.
What Protects Adolescents with Youth Subculture Affiliation from Excessive Internet Use?
Authors: Filakovska Bobakova Daniela , Holubcikova Jana , Madarasova Geckova Andrea , Dankulincova Veselska Zuzana
Published: November 2018

Youth subculture affiliation (SA) appears to be an important risk factor with regard to adolescents’ problem behavior. Excessive Internet use (EIU) has emerged as a new type of problem behavior; however, it has not yet been studied in adolescents affiliated with youth subcultures. Thus, the aim of this study was to assess the association between SA and EIU and to explore the role of selected protective factors. We used data from the Health Behaviour in School-aged Children (HBSC) study conducted in 2014 in Slovakia. The final sample for this study comprised 532 adolescents (mean age: 15.4; 49.6% boys). Hierarchical linear regression analysis was conducted to examine the associations of EIU with SA. Adolescents with SA were more likely to report EIU. Adjustment for protective factors decreased the association between EIU and SA. From all tested interactions, only the interaction of SA with family support was found to be significant. The relationship between family support and EIU was mediated via Monitoring by the mother only in adolescents without SA. Our findings imply that the risk of EIU is higher in adolescents with SA. There was a difference in how protective factors worked in adolescents with and without SA.
PARS: Using Augmented 360-Degree Panoramas of Reality for Construction Safety Training
Authors: Eiris Ricardo , Gheisari Masoud , Esmaeili Behzad
Published: November 2018

Improving the hazard-identification skills of construction workers is a vital step towards preventing accidents in the increasingly complex working conditions of construction jobsites. Training the construction workforce to recognize hazards therefore plays a central role in preparing workers to actively understand safety-related risks and make assertive safety decisions. Considering the inadequacies of traditional safety-training methods (e.g., passive lectures, videos, demonstrations), researchers have employed advanced visualization techniques such as virtual reality technologies to enable users to actively improve their hazard-identification skills in a safe and controlled environment. However, current virtual reality techniques sacrifice realism and demand high computational costs to reproduce real environments. Augmented 360-degree panoramas of reality offers an innovative alternative that creates low-cost, simple-to-capture, true-to-reality representations of the actual construction jobsite within which trainees may practice identifying hazards. This proof-of-concept study developed and evaluated a platform using augmented 360-degree panoramas of reality (PARS) for safety-training applications to enhance trainees’ hazard-identification skills for four types of sample hazards. Thirty subjects participated in a usability test that evaluated the PARS training platform and its augmented 360-degree images captured from real construction jobsites. The usability reviews demonstrate that the trainees found the platform and augmentations advantageously to learning hazard identification. The results of this study will foreseeably help researchers in developing engaging training platforms to improve the hazard-identification skills of workers.