bluuebunny/crossref_metadata_2025 huggingface dataset:
Glycemic Control during Pregnancy—A Predictor of Vitamin C Status at Labor in Type 1 Diabetic Women?
Authors: Juhl Bente , Lauszus Finn F. , Lykkesfeldt Jens
Published: May 2019

Several experimental studies have suggested that vitamin C (vitC) deficiency during pregnancy may be detrimental to fetal development, and observational studies have shown that vitC status is lower during pregnancy and in people with diabetes. A cross-sectional study in pregnant type 1 diabetic women found that poor maternal vitC status was a significant predictor for obstetric complications of pregnancy when measured within four weeks before labor. The plasma vitC concentration was significantly negatively correlated to HbA1c, the biomarker of glycemic control well-known to be associated with the outcome of the diabetic pregnancy. Here, we evaluated HbA1c during pregnancy in relation to the measured vitC levels in late pregnancy based on data from 46 women from the same cohort. Regression analysis showed that HbA1c of first trimester, the combined mean HbA1c of first and second trimester, mean HbA1c of the whole pregnancy (first, second and third trimester combined), and HbA1c of third trimester alone were all associated with vitC in late pregnancy (p = 0.03, n = 45; p = 0.034, n = 43; p = 0.017, n = 42; and p = 0.008, n = 46, respectively). In third trimester, when adjusted for creatinine clearance, the association between vitC and HbA1c persisted (p = 0.029). Women in third trimester with HbA1c above 7.0% had an increased risk of having poor vitC status compared to women with HbA1c below this level (11 out of 21 vs. 2 out of 25 women, p < 0.001). The results suggest that high HbA1c is associated with poor maternal vitC status and potentially inadequate supply of vitC for the neonate. HbA1c may thus be a relevant substitute biomarker for identifying pregnant women who might benefit from vitC supplementation.
A YOLOv2 Convolutional Neural Network-Based Human–Machine Interface for the Control of Assistive Robotic Manipulators
Authors: Giuffrida Gianluca , Meoni Gabriele , Fanucci Luca
Published: May 2019

During the last years, the mobility of people with upper limb disabilities and constrained on power wheelchairs is empowered by robotic arms. Nowadays, even though modern manipulators offer a high number of functionalities, some users cannot exploit all those potentialities due to their reduced manual skills, even if capable of driving the wheelchair by means of proper Human–Machine Interface (HMI). Owing to that, this work proposes a low-cost manipulator realizing only simple tasks and controllable by three different graphical HMI. The latter are empowered using a You Only Look Once (YOLO) v2 Convolutional Neural Network that analyzes the video stream generated by a camera placed on the robotic arm end-effector and recognizes the objects with which the user can interact. Such objects are shown to the user in the HMI surrounded by a bounding box. When the user selects one of the recognized objects, the target position information is exploited by an automatic close-feedback algorithm which leads the manipulator to automatically perform the desired task. A test procedure showed that the accuracy in reaching the desired target is 78%. The produced HMIs were appreciated by different user categories, obtaining a mean score of 8.13/10.
Simultaneous Supercritical Fluid Extraction of Heather (Calluna vulgaris L.) and Marigold (Calendula officinalis L.) and Anti-Inflammatory Activity of the Extracts
Authors: Villanueva-Bermejo David , Vázquez Erika , Villalva Marisol , Santoyo Susana , Fornari Tiziana , Reglero Guillermo , Rodriguez García-Risco Mónica
Published: May 2019

Heather (Calluna vulgaris L.) and marigold (Calendula officinalis L.) are two rich sources of bioactive pentacyclic triterpenes. The supercritical carbon dioxide (SCCO2) extraction of these two plants was explored at a pressure range of 25–50 MPa, 50 °C, with or without fractionation, different extraction times (1.5–4.0 h) and using ethanol as a co-solvent (0 and 10% w/w). In order to determine potential synergisms, a combined extraction (heather + marigold 50:50) was also studied. In general, higher extraction yields were achieved when the co-solvent was added. Higher concentrations of total triterpenic acids were obtained in heather extracts, specially using ethanol. The co-solvent did not increase the terpene concentration in marigold extracts. For the combined extraction, an antagonist effect in the triterpene concentration was observed in absence of a co-solvent, whereas a synergistic effect was exhibited in its presence, especially for ursolic acid. In general, the extracts showed a certain anti-inflammatory effect, although a straight correlation with the analyzed triterpenic acids concentration was not exhibited. Moreover, the combined extraction exposed a similar anti-inflammatory activity in comparison with the individual plant extracts.
Study on the Effect Mechanism of MRD to Rotor System
Authors: Wang Jun , Zhang Junhong , Ma Liang , Yu Yangyang
Published: May 2019

Magnetorheological damper (MRD), a semi-active control device, has the stability of the passive control device and the adaptive ability of the active control device. It is considered to be an ideal replacement for the squeeze film damper (SFD) and has been extensively investigated. However, the effect mechanism of MRD to a rotor system is still unclear, which will influence the structural design and control strategy of MRD. This paper aims to propose a general MRD excitation model for a rotor system and discover the effect mechanism. First, the effects of current and eccentricity on mechanical properties of MRD are studied in detail and approaches suppressing the vibration amplitude of a rotor system are put forward. Then, a general model considering MRD, ball bearing and squirrel cage is proposed. Based on the finite element method, the dynamic equations of a rotor-bearing-squirrel cage system with MRD and mass imbalance are presented. Finally, the influences of MRD on the dynamic characteristics of the rotor system are investigated, and the effect mechanism is discovered. In addition, the nonlinearity which is not desirable as it causes fluctuating stresses in the main components of the rotor system and eventually leads to their failure due to fatigue, are observed. The changes of damping and stiffness of MRD can alter the damping performance of MRD and the suitable range of current forms the zone of effective damping, which lays helpful guidance for the design and application of the MRD.
Study of 2,4-D Spectral Characteristics and Its Detection in Zizania Latifolia Using Terahertz Time-Domain Spectroscopy
Authors: Nie Pengcheng , Cai Chengyong , Qu Fangfang , Lin Lei , Dong Tao , He Yong
Published: May 2019

2,4-Dichlorophenoxyacetic acid (2,4-D) is a common plant growth regulator, which can remain in food and, with long-term consumption, threaten human health. Therefore, it is necessary to propose an effective detection method. Terahertz time-domain spectroscopy technique (THz-TDS) has good advantages in the quantitative and qualitative analysis of most biomolecules due to its rich fingerprint characteristics. In this paper, density functional theory (DFT) was applied to geometry optimization and frequency vibration calculation of 2,4-D, and THz-TDS was used to quantitatively detect 2,4-D in Zizania latifolia. The results showed that there were three characteristic absorption peaks of 2,4-D at 1.36, 1.60, and 2.38 THz, respectively, and the theoretical spectra were in good consistency with experimental spectra, with slight discrepancies. Additionally, the absorption peak at 1.36 THz had the best absorption characteristics and was chosen as the main peak for 2,4-D quantitative analysis. It was demonstrated that the limits of detection (LOD) of 2,4-D in Zizania latifolia were found to be as low as 5%, the absorbance intensity at 1.36 THz showed a good linear relationship (R2 = 0.9854) with 2,4-D concentration from 5% to 30%, and the recovery was 93.29%–98.75%. Overall, this work enriched the fingerprint database of pesticide molecules on the basis of terahertz spectroscopy and could provide a technical support for the detection of 2,4-D in food by terahertz spectroscopy.
Low-Input Crops as Lignocellulosic Feedstock for Second-Generation Biorefineries and the Potential of Chemometrics in Biomass Quality Control
Authors: Alzagameem Abla , Bergs Michel , Do Xuan Tung , Klein Stephanie Elisabeth , Rumpf Jessica , Larkins Michael , Monakhova Yulia , Pude Ralf , Schulze Margit
Published: May 2019

Lignocellulose feedstock (LCF) provides a sustainable source of components to produce bioenergy, biofuel, and novel biomaterials. Besides hard and soft wood, so-called low-input plants such as Miscanthus are interesting crops to be investigated as potential feedstock for the second generation biorefinery. The status quo regarding the availability and composition of different plants, including grasses and fast-growing trees (i.e., Miscanthus, Paulownia), is reviewed here. The second focus of this review is the potential of multivariate data processing to be used for biomass analysis and quality control. Experimental data obtained by spectroscopic methods, such as nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR), can be processed using computational techniques to characterize the 3D structure and energetic properties of the feedstock building blocks, including complex linkages. Here, we provide a brief summary of recently reported experimental data for structural analysis of LCF biomasses, and give our perspectives on the role of chemometrics in understanding and elucidating on LCF composition and lignin 3D structure.
Intelligent Thermal Imaging-Based Diagnostics of Turbojet Engines
Authors: Andoga Rudolf , Főző Ladislav , Schrötter Martin , Češkovič Marek , Szabo Stanislav , Bréda Róbert , Schreiner Michal
Published: May 2019

There are only a few applications of infrared thermal imaging in aviation. In the area of turbojet engines, infrared imaging has been used to detect temperature field anomalies in order to identify structural defects in the materials of engine casings or other engine parts. In aviation applications, the evaluation of infrared images is usually performed manually by an expert. This paper deals with the design of an automatic intelligent system which evaluates the technical state and diagnoses a turbojet engine during its operation based on infrared thermal (IRT) images. A hybrid system interconnecting a self-organizing feature map and an expert system is designed for this purpose. A Kohonen neural network (the self-organizing feature map) is successfully applied to segment IRT images of a turbojet engine with high precision, and the expert system is then used to create diagnostic information from the segmented images. This paper represents a proof of concept of this hybrid system using data from a small iSTC-21v turbojet engine operating in laboratory conditions.
Hierarchical Feature Aggregation from Body Parts for Misalignment Robust Person Re-Identification
Authors: Liu Yuting , Yang Hongyu , Zhao Qijun
Published: May 2019

In this work, we focus on the misalignment problem in person re-identification. Human body parts commonly contain discriminative local representations relevant with identity recognition. However, the representations are easily affected by misalignment that is due to varying poses or poorly detected bounding boxes. We thus present a two-branch Deep Joint Learning (DJL) network, where the local branch generates misalignment robust representations by pooling the features around the body parts, while the global branch generates representations from a holistic view. A Hierarchical Feature Aggregation mechanism is proposed to aggregate different levels of visual patterns within body part regions. Instead of aggregating each pooled body part features from multi-layers with equal weight, we assign each with the learned optimal weight. This strategy also mitigates the scale differences among multi-layers. By optimizing the global and local features jointly, the DJL network further enhances the discriminative capability of the learned hybrid feature. Experimental results on Market-1501 and CUHK03 datasets show that our method could effectively handle the misalignment induced intra-class variations and yield competitive accuracy particularly on poorly aligned pedestrian images.
Optimal Multiculture Network Design for Maximizing Resilience in the Face of Multiple Correlated Failures
Authors: Prieto Yasmany , Boettcher Nicolás , Restrepo Silvia Elena , Pezoa Jorge E.
Published: May 2019

Current data networks are highly homogeneous because of management, economic, and interoperability reasons. This technological homogeneity introduces shared risks, where correlated failures may entirely disrupt the network operation and impair multiple nodes. In this paper, we tackle the problem of improving the resilience of homogeneous networks, which are affected by correlated node failures, through optimal multiculture network design. Correlated failures regarded here are modeled by SRNG events. We propose three sequential optimization problems for maximizing the network resilience by selecting as different node technologies, which do not share risks, and placing such nodes in a given topology. Results show that in the 75% of real-world network topologies analyzed here, our optimal multiculture design yields networks whose probability that a pair of nodes, chosen at random, are connected is 1, i.e., its ATTR metric is 1. To do so, our method efficiently trades off the network heterogeneity, the number of nodes per technology, and their clustered location in the network. In the remaining 25% of the topologies, whose average node degree was less than 2, such probability was at least 0.7867. This means that both multiculture design and topology connectivity are necessary to achieve network resilience.
Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections
Authors: Ly Hai-Bang , Le Lu Minh , Duong Huan Thanh , Nguyen Thong Chung , Pham Tuan Anh , Le Tien-Thinh , Le Vuong Minh , Nguyen-Ngoc Long , Pham Binh Thai
Published: May 2019

The main aim of this study is to develop different hybrid artificial intelligence (AI) approaches, such as an adaptive neuro-fuzzy inference system (ANFIS) and two ANFISs optimized by metaheuristic techniques, namely simulated annealing (SA) and biogeography-based optimization (BBO) for predicting the critical buckling load of structural members under compression, taking into account the influence of initial geometric imperfections. With this aim, the existing results of compression tests on steel columns were collected and used as a dataset. Eleven input parameters, representing the slenderness ratios and initial geometric imperfections, were considered. The predicted target was the critical buckling load of columns. Statistical criteria, namely the correlation coefficient (R), the root mean squared error (RMSE), and the mean absolute error (MAE) were used to evaluate and validate the three proposed AI models. The results showed that SA and BBO were able to improve the prediction performance of the original ANFIS. Excellent results using the BBO optimization technique were achieved (i.e., an increase in R by 7.15%, RMSE by 40.48%, and MAE by 38.45%), and those using the SA technique were not much different (i.e., an increase in R by 5.03%, RMSE by 26.68%, and MAE by 20.40%). Finally, sensitivity analysis was performed, and the most important imperfections affecting column buckling capacity was found to be the initial in-plane loading eccentricity at the top and bottom ends of the columns. The methodology and the developed AI models herein could pave the way to establishing an advanced approach to forecasting damages of columns under compression.
A Mechatronics-Embedded Pneumatic Soft Modular Robot Powered via Single Air Tube
Authors: Zhang Yu , Liu Yubin , Sui Xin , Zheng Tianjiao , Bie Dongyang , Wang Yulin , Zhao Jie , Zhu Yanhe
Published: May 2019

Soft modular robots have advantages, including infinite degrees of freedom and various configurations. Most soft robots are actuated by inflating air pressure into their chambers. However, each chamber is connected to a tube that provides the air supply, which incurs drag and intertwining problems that influence the robot’s motion. Moreover, the number of chambers directly affects the deformations and motion capabilities of the robot. Therefore, the crucial issue is the structure of a soft modular robot that can share an air source without reducing the number of chambers and can guarantee the deformations of the robot. In this paper, a novel mechatronics-embedded soft module was designed and manufactured, which has an air supply sharing function. Therefore, the soft modular robot can be powered via a single air tube. In addition, a wireless platform to control the air pressure of the module was built, and an experimental model was established to obtain the relationship between the deformation and pressure of the module. Four experiments were performed under different conditions. The experiments’ results indicate the bending capability of the module. Moreover, hooking object, twisting motion, and bionic gesture experiments demonstrate the validity of the module’s air pressure sharing function. Therefore, the air sharing supply approach proposed in this paper can be used as a reference to solve the tube drag problem of soft modular robots.
Energy Demand and Supply Simultaneous Optimization to Design a Nearly Zero-Energy House
Authors: Ferrara Maria , Prunotto Federico , Rolfo Andrea , Fabrizio Enrico
Published: May 2019

The effective design of nearly zero-energy buildings depends on a large set of interdependent variables, which affect both energy demand and supply. Considering them simultaneously is fundamental when searching for optimal design of nearly zero-energy buildings, as encouraged by the EU in the second recast of the Energy Performance of Building Directive (EPBD). This paper presents the application of the new energy demand and supply simultaneous optimization (EDeSSOpt) methodology to optimize the design of a single-family house in the Italian context. Both primary energy optimization and financial optimization are carried out in the context of European regulations. Robustness of the resulting optimal solution is studied through analysis of optimum neighborhoods. The resulting cost-optimized solution relies on a moderately insulated envelope, a highly efficient system, and 34% of coverage from renewables. The energy-optimized solution requires a higher level of insulation and a higher coverage from renewables, demonstrating that there is still a gap between energy and cost optimums. Beyond the results, integrated optimization by means of EDeSSOpt is demonstrated to better minimize cost functions while improving the robustness of results.
Thermodynamic Simulations for Determining the Recycling Path of a Spent Lead-Acid Battery Electrolyte Sample with Ca(OH)2
Authors: Gu Shuai , Fu Bitian , Fujita Toyohisa , Ahn Ji Whan
Published: May 2019

By utilizing thermodynamic calculations, the possible removal path of spent lead-acid battery electrolytes was modeled. The process was divided into precipitation and carbonation processes. In the carbonation process, two scenarios were discussed, namely carbonation with and without pre-filtration of the precipitates resulted from the precipitation process. The results showed that in the precipitation process, the theoretical limit for the chemical removal of SO42− was 99.15%, while in the following carbonation process without filtration, only 69.61% of SO42− was removed due to the fact that CO2 reacts with Ca2+ ion in the solution, and thus leads to the production of CaCO3 and SO42− ions in the solution. In the carbonation process without filtration, with the increase of CO2 in the solution the removal ratio of SO42− further decreases. Thermodynamic simulation was effective in predicting the theoretical removal limits and helps in understanding and optimizing the removal process.
Cooperative Optimization of Electric Vehicles and Renewable Energy Resources in a Regional Multi-Microgrid System
Authors: Chen Jin , Chen Changsong , Duan Shanxu
Published: May 2019

By integrating renewable energy sources (RESs) with electric vehicles (EVs) in microgrids, we are able to reduce carbon emissions as well as alleviate the dependence on fossil fuels. In order to improve the economy of an integrated system and fully exploit the potentiality of EVs’ mobile energy storage while achieving a reasonable configuration of RESs, a cooperative optimization method is proposed to cooperatively optimize the economic dispatching and capacity allocation of both RESs and EVs in the context of a regional multi-microgrid system. An across-time-and-space energy transmission (ATSET) of the EVs was considered, and the impact of ATSET of EVs on economic dispatching and capacity allocation of multi-microgrid system was analyzed. In order to overcome the difficulty of finding the global optimum of the non-smooth total cost function, an improved particle swarm optimization (IPSO) algorithm was used to solve the cooperative optimization problem. Case studies were performed, and the simulation results show that the proposed cooperative optimization method can significantly decrease the total cost of a multi-microgrid system.
Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory
Authors: Piotrowski Robert , Paul Aleksander , Lewandowski Mateusz
Published: May 2019

Authors of this paper take under investigation the optimization of biological processes during the wastewater treatment in sequencing batch reactor (SBR) plant. A designed optimizing supervisory controller generates the dissolved oxygen (DO) trajectory for the lower level parts of the hierarchical control system. Proper adjustment of this element has an essential impact on the efficiency of the wastewater treatment process as well as on the costs generated by the plant, especially by the aeration system. The main goal of the presented solution is to reduce the plant energy consumption and to maintain the quality of effluent in compliance with the water-law permit. Since the optimization is nonlinear and includes variations of different types of variables, to solve the given problem the authors performed simulation tests and decided to implement a hybrid of two different optimization algorithms: artificial bee colony (ABC) and direct search algorithm (DSA). Simulation tests for the wastewater treatment plant case study are presented.
Retrieving Performances of Vortex Beams with GS Algorithm after Transmitting in Different Types of Turbulences
Authors: Dedo Maxime Irene , Wang Zikun , Guo Kai , Sun Yongxuan , Shen Fei , Zhou Hongping , Gao Jun , Sun Rui , Ding Zhizhong , Guo Zhongyi
Published: May 2019

The transmission of the orbital angular momentum (OAM) beam has attracted a lot of attention in the field of free-space optical (FSO) communication. Usually, after transmitting in atmospheric turbulences, the helical phase-front of OAM beams will be severely distorted, and there will exist the intermode crosstalk. As a result, the performance of the communication system will degrade significantly. In this paper, we have investigated the influences of the level of the turbulence strength to the transmitting OAM beams by changing the refractive-index structural parameter of C n 2 and the number of turbulence random phase screens of N in simulation environment. Then, by adopting the Gerchberg-Saxton (GS) algorithm, which can be used to compute the pre-compensation phase and correct the distorted OAM beams, the retrieving performances of transmitting single and multiplexed OAM beams under different turbulence strengths were also investigated. The simulation results show that with increasing the atmospheric-turbulence strength levels determined by the parameters C n 2 and N, the retrieving performances decrease dramatically. When the turbulence strength level is selected within an appropriate range, the OAM beams can be effectively retrieved by adopting GS algorithm and observing the power density spectrum. Notably, the retrieving performance for the transmission of a single OAM beam is better than that of the multiplexing OAM beam.
An Interview with Frieder Nake
Authors: Smith Glenn W.
Published: May 2019

In this interview, mathematician and computer art pioneer Frieder Nake addresses the emergence of the algorithm as central to our understanding of art: just as the craft of computer programming has been irreplaceable for us in appreciating the marvels of the DNA genetic code, so too has computer-generated art—and with the algorithm as its operative principle—forever illuminated its practice by traditional artists.
Evolution of Electronic Noses from Research Objects to Engineered Environmental Odour Monitoring Systems: A Review of Standardization Approaches
Authors: Cipriano Domenico , Capelli Laura
Published: May 2019

Since electronic noses are used more and more for air quality monitoring purposes, and in some countries are starting to have a legal value, there is a need for standardization and programs for the quality verification of instruments. Such quality programs have the aim to guarantee the main characteristics of the instrument for both the final user and local authorities, let the user establish a suitable maintenance procedure and give information on measurement uncertainty. One critical aspect when dealing with electronic noses for environmental odour monitoring is that environmental odours are complex mixtures that are not repeatable nor reproducible, giving that they are not suitable for quality verifications. This paper aims to review and discuss the different approaches that can be adopted in order to perform quality checks on electronic noses (e-noses) used for environmental odour monitoring, thereby referring to existing technical standards, such as the Dutch NTA 9055:2012, the new German VDI 3518-3:2018, and the Italian UNI 1605848 project, which directly refer to electronic noses. Moreover, also the European technical standards that are prescriptive for automatic measuring systems (AMSs) are taken into consideration (i.e., EN 14181:2014 and EN 15267:2009), and their possible applicability to electronic noses is investigated. Finally, the pros and cons of the different approaches are presented and discussed in the conclusions section.
Diagnosis and Seismic Behavior Evaluation of the Church of São Miguel de Refojos (Portugal)
Authors: Ramírez Rafael , Mendes Nuno , Lourenço Paulo B.
Published: May 2019

The Benedictine Monastery of São Miguel de Refojos, located in Cabeceiras de Basto (Portugal), is a monumental complex and a distinctive example of the 18th century Portuguese Baroque architecture. This study addresses the state of conservation of the church as well as the evaluation of its structural behavior and seismic performance. An initial inspection and diagnosis campaign revealed that the structure presents low to moderate damage and other non-structural issues generally associated with high levels of moisture and water infiltration. In order to study the structural performance, a three-dimensional (3D) numerical model was prepared based on the finite element method. This model was calibrated with respect to dynamic identification tests and nonlinear static analyses were then performed to evaluate the seismic behavior. Capacity curves, deformations, crack patterns, and failure mechanisms were used to characterize the structural response. Additionally, the safety evaluation for horizontal actions was verified by means of limit analysis. An overall good agreement was found between the results of the pushover and the limit analyses. To conclude, the present work provides a comprehensive evaluation of the state of conservation of the church and verifies the safety condition of the structure for seismic actions.
A BIM-based PSS Approach for the Management of Maintenance Operations of Building Equipment
Authors: Fargnoli Mario , Lleshaj Antoneta , Lombardi Mara , Sciarretta Nicolò , Di Gravio Giulio
Published: May 2019

The service-centered economy has grown considerably in the last few years, shifting from product-based solutions towards service centered offerings, i.e., Product-Service System (PSS) solutions. Such an approach is also emerging in the context of building equipment, where maintenance activities play a fundamental role in facility management. In this field, Building Information Modeling (BIM) based tools are diffusely used to improve the performances of facility management. However, few studies have addressed the above issues while considering a shift from product-based approaches in favor of more advanced servitization models. The study aims at integrating BIM based approaches in a PSS context for the improvement of the management of maintenance operations of building equipment. A general framework for maintenance management has been developed, merging the implementation of the PSS components in a BIM model for the definition of maintenance management. A first application of this methodology to a real case study concerning the elevators of an existing building has shown the efficacy of the proposed approach. The study highlighted the benefits that can be achieved, especially in terms of reduced periods of equipment unavailability, reduced costs and augmented customer satisfaction, while enhancing the information exchange between the PSS actors. Hence, although further research is still needed for its validation, the proposed approach can offer practical insights for the development of promising BIM-based PSS solutions for facility management in the construction industry.
Detection of Epstein-Barr Virus Infection in Non-Small Cell Lung Cancer
Authors: Kheir Fayez , Zhao Mengmeng , Strong Michael J. , Yu Yi , Nanbo Asuka , Flemington Erik K. , Morris Gilbert F. , Reiss Krzysztof , Li Li , Lin Zhen
Published: May 2019

Previous investigations proposed a link between the Epstein-Barr virus (EBV) and lung cancer (LC), but the results are highly controversial largely due to the insufficient sample size and the inherent limitation of the traditional viral screening methods such as PCR. Unlike PCR, current next-generation sequencing (NGS) utilizes an unbiased method for the global assessment of all exogenous agents within a cancer sample with high sensitivity and specificity. In our current study, we aim to resolve this long-standing controversy by utilizing our unbiased NGS-based informatics approaches in conjunction with traditional molecular methods to investigate the role of EBV in a total of 1127 LC. In situ hybridization analysis of 110 LC and 10 normal lung samples detected EBV transcripts in 3 LC samples. Comprehensive virome analyses of RNA sequencing (RNA-seq) data sets from 1017 LC and 110 paired adjacent normal lung specimens revealed EBV transcripts in three lung squamous cell carcinoma and one lung adenocarcinoma samples. In the sample with the highest EBV coverage, transcripts from the BamHI A region accounted for the majority of EBV reads. Expression of EBNA-1, LMP-1 and LMP-2 was observed. A number of viral circular RNA candidates were also detected. Thus, we for the first time revealed a type II latency-like viral transcriptome in the setting of LC in vivo. The high-level expression of viral BamHI A transcripts in LC suggests a functional role of these transcripts, likely as long non-coding RNA. Analyses of cellular gene expression and stained tissue sections indicated an increased immune cell infiltration in the sample expressing high levels of EBV transcripts compared to samples expressing low EBV transcripts. Increased level of immune checkpoint blockade factors was also detected in the sample with higher levels of EBV transcripts, indicating an induced immune tolerance. Lastly, inhibition of immune pathways and activation of oncogenic pathways were detected in the sample with high EBV transcripts compared to the EBV-low LC indicating the direct regulation of cancer pathways by EBV. Taken together, our data support the notion that EBV likely plays a pathological role in a subset of LC.
Amplification of the EGFR and CCND1 Are Coordinated and Play Important Roles in the Progression of Oral Squamous Cell Carcinomas
Authors: Chien Huei-Tzu , Cheng Sou-De , Liao Chun-Ta , Wang Hung-Ming , Huang Shiang-Fu
Published: May 2019

Oral squamous cell carcinoma (OSCC) is a common cancer in Taiwan and worldwide. To provide some clues for clinical management of OSCC, 72 advanced-stage OSCCs were analyzed using two microarray platforms (26 cases with Affymetrix 500 K and 46 cases with Affymetrix SNP 6.0). Genomic identification of significant targets in cancer analyses were used to identify significant copy number alterations (CNAs) using a q-value cutoff of 0.25. Among the several significant regions, 12 CNAs were common between these two platforms. Two gain regions contained the well-known oncogenes EGFR (7p11.2) and CCND1 (11q13.3) and several known cancer suppressor genes, such as FHIT (3p14.2–p12.1), FAT1 (4q35.1), CDKN2A (9p21.3), and ATM (11q22.3–q24.3), reside within the 10 deletion regions. Copy number gains of EGFR and CCND1 were further confirmed by fluorescence in situ hybridization and TaqMan CN assay, respectively, in 257 OSCC cases. Our results indicate that EGFR and CCND1 CNAs are significantly associated with clinical stage, tumor differentiation, and lymph node metastasis. Furthermore, EGFR and CCND1 CNAs have an additive effect on OSCC tumor progression. Thus, current genome-wide CNA analysis provides clues for future characterization of important oncogenes and tumor suppressor genes associated with the behaviors of the disease.
Differential Kinase Activation in Peripheral Blood Mononuclear Cells from Non-Small-Cell Lung Cancer Patients Treated with Nivolumab
Authors: Noé Gaëlle , Bellesoeur Audrey , Golmard Lisa , Thomas-Schoemann Audrey , Boudou-Rouquette Pascaline , Tiako Meyo Manuela , Puszkiel Alicja , Arrondeau Jennifer , Alexandre Jérome , Goldwasser François , Blanchet Benoit , Vidal Michel
Published: May 2019

In the era of precision medicine, research of biomarkers for identification of responders to nivolumab therapy is a major challenge. Peripheral blood mononuclear cells (PBMC) could be an interesting surrogate tissue for identifying pharmacodynamic biomarkers. The aim of this exploratory study was to investigate the global serine/threonine kinase (STK) activity in PBMC from non-small-cell lung cancer (NSCLC) patients using a high throughput kinomic profiling method. PamChip® microarrays were used to explore the STK kinomic profile in PBMC from 28 NSCLC patients before nivolumab initiation (D0) and on day 14 (D14) of the first administration. Two clusters of patients (A and B) were identified at D0, median overall survival (OS) tended to be longer in cluster A than in B (402 vs. 112.5 days, respectively; p = 0.15). Interestingly, the PD-L1 tumor cell score (p = 0.045), the count of CD8+ cells (p = 0.023) and the total body weight (p = 0.038) were statistically different between the clusters. On D14, clusters C and D were identified. Greater activity of most STK, especially those of the PI3K/Akt signaling pathway, was noticed among cluster C. No significant difference between C and D was observed regarding OS. Considering the small number of patients, results from this preliminary study are not conclusive. However, the 4-fold longer median OS in cluster A paves the way to further investigate, in a larger cohort of NSCLC patients, the benefit of basal STK kinomic profile in PBMC to identify responders to nivolumab therapy.
Osteopontin Gene Polymorphism and Urinary OPN Excretion in Patients with Immunoglobulin A Nephropathy
Authors: Kaleta Beata , Krata Natalia , Zagożdżon Radosław , Mucha Krzysztof
Published: May 2019

Osteopontin (OPN) is a glycoprotein involved in the pathogenesis of multiple autoimmune and inflammatory conditions. However, the association of variants of secreted phosphoprotein 1 gene (SPP1), which encodes OPN, with immunoglobulin A nephropathy (IgAN) has not been examined up to date. Moreover, the role of OPN in disease pathogenesis and clinical manifestations is not fully known. Therefore, the aim of the study was to determine the frequency of four single nucleotide polymorphisms (SNiPs) of SPP1 gene, as well as the urinary OPN excretion in IgAN patients and healthy controls. In total, 58 Caucasian patients with biopsy-proven IgAN and 184 gender-, age-, and ethnically-matched healthy controls were genotyped for rs1126616, rs1126772, rs9138, and rs7687316/rs3841116 polymorphisms by real time polymerase chain reaction (RT-PCR). Urinary OPN concentration was determined by enzyme-linked immunosorbent assay (ELISA) in 58 IgAN patients and 19 controls. SPP1 SNiPs, as well as urinary OPN excretion, were analyzed in relation to their possible associations with the clinicopathological parameters. The frequency of the minor TT/CT genotypes of rs1126616 was significantly higher in IgAN patients compared to controls (P = 0.0217). Similarly, the minor (CC/AC) genotypes and the C allele of rs9138 were more frequent in IgAN patients (P = 0.0425 and P = 0.0112, respectively). Moreover, these two SNiPs were associated with the higher urinary OPN excretion (P < 0.05). These findings suggest that rs1126616, as well as rs9138, may be associated with IgAN development, however future studies in this field are required.
Optimizing Processing Parameters for Multi-Track Laser Cladding Utilizing Multi-Response Grey Relational Analysis
Authors: Lian Guofu , Zhang Hao , Zhang Yang , Tanaka Martin L. , Chen Changrong , Jiang Jibin
Published: May 2019

Multi-track laser cladding is the primary technology used in industrial applications for surface reinforcement and remanufacturing of broken parts. In this study, the influence of processing parameters on multi-track laser cladding was investigated using a Taguchi orthogonal experimental design. A multi-response grey relational analysis (GRA) was employed to identify laser cladding processing parameters that simultaneously optimize the flatness ratio of the coating and the cladding efficiency. The optimal parameters setting found by GRA were validated experimentally. Results showed that the flatness ratio and cladding efficiency were closely correlated to the overlap rate and laser power, where the overlap rate shows the most significant impact on the flatness ratio and the laser power shows the most significant impact on cladding efficiency. Results from the validation experiment were within one percent (0.97% error) of the predicted value. This demonstrates the benefits of utilizing GRA in laser cladding process optimization. The methods presented in this paper can be used to identify ideal processing parameters for multi-response multi-track laser cladding processes or other industrial applications.
Crack-Resistance Behavior of an Encapsulated, Healing Agent Embedded Buffer Layer on Self-Healing Thermal Barrier Coatings
Authors: Song Dowon , Song Taeseup , Paik Ungyu , Lyu Guanlin , Jung Yeon-Gil , Choi Baig-Gyu , Kim In-Soo , Zhang Jing
Published: May 2019

In this work, a novel thermal barrier coating (TBC) system is proposed that embeds silicon particles in coating as a crack-healing agent. The healing agent is encapsulated to avoid unintended reactions and premature oxidation. Thermal durability of the developed TBCs is evaluated through cyclic thermal fatigue and jet engine thermal shock tests. Moreover, artificial cracks are introduced into the buffer layer’s cross section using a microhardness indentation method. Then, the indented TBC specimens are subject to heat treatment to investigate their crack-resisting behavior in detail. The TBC specimens with the embedded healing agents exhibit a relatively better thermal fatigue resistance than the conventional TBCs. The encapsulated healing agent protects rapid large crack openings under thermal shock conditions. Different crack-resisting behaviors and mechanisms are proposed depending on the embedding healing agents.
Q-Learning of Straightforward Gait Pattern for Humanoid Robot Based on Automatic Training Platform
Authors: Wong Ching-Chang , Liu Chih-Cheng , Xiao Sheng-Ru , Yang Hao-Yu , Lau Meng-Cheng
Published: May 2019

In this paper, an oscillator-based gait pattern with sinusoidal functions is designed and implemented on a field-programmable gate array (FPGA) chip to generate a trajectory plan and achieve bipedal locomotion for a small-sized humanoid robot. In order to let the robot can walk straight, the turning direction is viewed as a parameter of the gait pattern and Q-learning is used to obtain a straightforward gait pattern. Moreover, an automatic training platform is designed so that the learning process is automated. In this way, the turning direction can be adjusted flexibly and efficiently under the supervision of the automatic training platform. The experimental results show that the proposed learning framework allows the humanoid robot to gradually walk straight in the automated learning process.
Performance Enhancement Methods for the Distributed Acoustic Sensors Based on Frequency Division Multiplexing
Authors: Hu Yanzhu , Meng Zhen , Zabihi Mohammadmasoud , Shan Yuanyuan , Fu Siyi , Wang Feng , Zhang Xuping , Zhang Yixin , Zeng Bin
Published: May 2019

The last years have witnessed the wide application of Distributed Acoustic Sensor (DAS) systems in several fields, such as submarine cable monitoring, seismic wave detection, structural health monitoring, etc. Due to their distributed measurement ability and high sensitivity, DAS systems can be employed as a promising tool for the phase sensitive optical time domain reflectometry (Φ-OTDR). However, it is also well-known that the traditional Φ-OTDR system suffers from Rayleigh backscattering (RBS) fading effects, which induce dead zones in the measurement results. Worse still, in practice it is difficult to achieve the optimum matching between spatial resolution (SR) and signal to noise ratio (SNR). Further, the overall frequency response range (FRR) of the traditional Φ-OTDR is commonly limited by the length of the fiber in order to prevent RBS signals from overlapping with each other. Additionally, it is usually difficult to reconstruct high frequency vibration signals accurately for long range monitoring. Aiming at solving these problems, we introduce frequency division multiplexing (FDM) that makes it easier to improve the system performance with less system structure changes. We propose several novel Φ-OTDR schemes based on Frequency Division Multiplexing (FDM) technology to solve the above problems. Experimental results showed that the distortion induced by fading effects could be suppressed to 1.26%; when the SR of Φ-OTDR is consistent with the length of the vibration region, the SNR of the sensing system is improved by 3 dB compared to the average SNR with different SRs; vibration frequencies up to 440 kHz have been detected along 330 m artificial microstructures. Thus, the proposed sensing system offers a promising solution for the performance enhancement of DAS systems that could achieve high SNR, broadband FRR and dead zone-free measurements at the same time.
Analyzing the Performance and Control of a Hydronic Pavement System in a District Heating Network
Authors: Blomqvist Stefan , Amiri Shahnaz , Rohdin Patrik , Ödlund Louise
Published: May 2019

A hydronic pavement system (HPS) is an alternative method to clear snow and ice, which avoids the use of salt, sand, and fossil fuel in conventional snow clearance, and minimizes the risk of accidents. The aim is to analyze the performance of different control strategies for a 35,000 m2 HPS utilizing heat from a district heating and cooling (DHC) system. The key performance indicators are (1) energy performance of the HPS, and (2) primary energy use, (3) electricity production and (4) greenhouse gas (GHG) emissions from the DHC system. The methodology uses a simulation model of the HPS and an optimization model of the DHC system. Three operational strategies are analyzed: A reference scenario based on the current control strategy, and scenarios where the HPS is shut down at temperatures below −10 °C and −5 °C. The study shows that the DHC return temperature is suitable for use. By operational strategies, use during peak demand in the DHC system can be avoided, resulting in reduced use of fossil fuel. Moreover, the energy use of the HPS could be reduced by 10% and the local GHG emissions by 25%. The study emphasizes that the HPS may have positive effects on global GHG emissions, as it enables electricity production from renewable resources.
Energy and Economics Analyses of Condenser Evaporative Precooling for Various Climates, Buildings and Refrigerants
Authors: Shen Bo , New Joshua , Ally Moonis
Published: May 2019

Condenser evaporative pre-coolers provide a low cost retrofit option for existing packaged rooftop air conditioning application units. This paper aimed to provide a comprehensive study to assess energy savings and peak power reductions of condenser evaporative cooling. Condenser evaporative cooling leads to a lower temperature of the air entering the condenser of a rooftop unit, which results in smaller compressor power consumption. Using EnergyPlus building energy simulations, we mapped the impacts on energy savings and energy reductions at peak ambient temperatures in three building types and 16 locations with levels of pad effectiveness and demonstrated the effects on air conditioner using either R22 or R410A as refrigerants. Economics and control strategy to maximize the cost saving were also investigated. The results demonstrate that energy savings are much greater for HVAC systems with the refrigerant R410A than they are with R22, and evaporative pre-cooling provides the opportunity for annual energy savings and peak demand reductions, with significant potential in hot, dry climates. Additionally, we validated an improved mathematical model for estimating the condenser pre-cooling wet bulb efficiency which shows clear advantage over the current EnergyPlus model.
Reliability Investigation of a Carbon Nanotube Array Thermal Interface Material
Authors: Nylander Andreas , Hansson Josef , Kabiri Samani Majid , Chandra Darmawan Christian , Borta Boyon Ana , Divay Laurent , Ye Lilei , Fu Yifeng , Ziaei Afshin , Liu Johan
Published: May 2019

As feature density increases within microelectronics, so does the dissipated power density, which puts an increased demand on thermal management. Thermal interface materials (TIMs) are used at the interface between contacting surfaces to reduce the thermal resistance, and is a critical component within many electronics systems. Arrays of carbon nanotubes (CNTs) have gained significant interest for application as TIMs, due to the high thermal conductivity, no internal thermal contact resistances and an excellent conformability. While studies show excellent thermal performance, there has to date been no investigation into the reliability of CNT array TIMs. In this study, CNT array TIMs bonded with polymer to close a Si-Cu interface were subjected to thermal cycling. Thermal interface resistance measurements showed a large degradation of the thermal performance of the interface within the first 100 cycles. More detailed thermal investigation of the interface components showed that the connection between CNTs and catalyst substrate degrades during thermal cycling even in the absence of thermal expansion mismatch, and the nature of this degradation was further analyzed using X-ray photoelectron spectroscopy. This study indicates that the reliability will be an important consideration for further development and commercialization of CNT array TIMs.