bluuebunny/crossref_metadata_2025 huggingface dataset:
NKG2D Polymorphism in Melanoma Patients from Southeastern Spain
Authors: Gimeno Lourdes , Martínez-Banaclocha Helios , Bernardo M. Victoria , Bolarin José Miguel , Marín Luis , López-Hernández Ruth , López-Alvarez M. Rocío , Moya-Quiles M. Rosa , Muro Manuel , Frias-Iniesta José Francisco , Martínez-Escribano Jorge , Alvarez-López M. Rocío , Minguela Alfredo , Campillo José Antonio
Published: March 2019

Background: Natural killer (NK) and CD8+ T cells are involved in the immune response against melanoma. C-Type lectin-like NK cell receptors are located in the Natural Killer Complex (NKC) region 12p13.2-p12.3 and play a critical role in regulating the activity of NK and CD8+ T cells. An association between polymorphisms in the NKC region, including the NKG2D gene and NKG2A promoter, and the risk of cancer has been previously described. The aim of this study was to analyze the association of polymorphisms in the NKC region with cutaneous melanoma in patients from southeastern Spain. Methods: Seven single-nucleotide polymorphisms (SNPs) in the NKG2D gene (NKC3,4,7,9,10,11,12), and one SNP in the NKG2A promoter (NKC17) were genotyped by a TaqMan 5′ Nuclease Assay in 233 melanoma patients and 200 matched healthy controls. Results: A linkage disequilibrium analysis of the SNPs performed in the NKC region revealed two blocks of haplotypes (Hb-1 and Hb-2) with 14 and seven different haplotype subtypes, respectively. The third most frequent haplotype from the block Hb-2—NK3 (CAT haplotype)—was significantly more frequent on melanoma patients than on healthy controls (p = 0.00009, Pc = 0.0006). No further associations were found when NKC SNPs were considered independently. Conclusions: Our results suggest an association between NKG2D polymorphisms and the risk of cutaneous malignant melanoma.
The Role of SVZ Stem Cells in Glioblastoma
Authors: Altmann Christine , Keller Stefanie , Schmidt Mirko H. H.
Published: March 2019

As most common primary brain cancer, glioblastoma is also the most aggressive and malignant form of cancer in the adult central nervous system. Glioblastomas are genetic and transcriptional heterogeneous tumors, which in spite of intensive research are poorly understood. Over the years conventional therapies failed to affect a cure, resulting in low survival rates of affected patients. To improve the clinical outcome, an important approach is to identify the cells of origin. One potential source for these are neural stem cells (NSCs) located in the subventricular zone, which is one of two niches in the adult nervous system where NSCs with the capacity of self-renewal and proliferation reside. These cells normally give rise to neuronal as well as glial progenitor cells. This review summarizes current findings about links between NSCs and cancer stem cells in glioblastoma and discusses current therapeutic approaches, which arise as a result of identifying the cell of origin in glioblastoma.
New Functionalized Polycycles Obtained by Photocatalytic Oxygenation Using Mn(III) Porphyrins in Basic Media
Authors: Vuk Dragana , Horváth Ottó , Škorić Irena
Published: March 2019

According to our earlier observations, the products of photocatalytic oxygenations of furan and thiophene derivatives of benzobicyclo[3.2.1]octadiene with anionic and cationic manganese(III) porphyrin at pH = 7 strongly depended on the type and position of the heteroatom in the aromatic ring, as well as the charge of the photocatalyst. Hence, a significant pH increase (to 10) in these systems offered a reasonable tool to affect the diversity and yields of the oxygenation products. They were quantitatively separated by TLC and identified with NMR analyses. The results clearly indicated that the increase of HO− concentration, in most cases, considerably changed the product yield, e.g., enhanced it to 70% for the hydroxy-furyl derivative. Accordingly, the selectivity of the oxygenation of the furan compound could be improved in this way. In the case of one thienyl compound, however, even an additional product appeared, while the yields of the products of the other thiophene derivative (with cationic catalyst) decreased to zero, suggesting the application of lower pH for preparative purposes. The pH effects indicate that oxygenation reactions in these systems involve more photochemically generated oxidative agents, e.g., •OH and (P)Mn(V)=O), the role of which is affected by the pH increase in various ways.
Mitochondrial Genetic Disorders: Cell Signaling and Pharmacological Therapies
Authors: Djouadi Fatima , Bastin Jean
Published: March 2019

Mitochondrial fatty acid oxidation (FAO) and respiratory chain (RC) defects form a large group of inherited monogenic disorders sharing many common clinical and pathophysiological features, including disruption of mitochondrial bioenergetics, but also, for example, oxidative stress and accumulation of noxious metabolites. Interestingly, several transcription factors or co-activators exert transcriptional control on both FAO and RC genes, and can be activated by small molecules, opening to possibly common therapeutic approaches for FAO and RC deficiencies. Here, we review recent data on the potential of various drugs or small molecules targeting pivotal metabolic regulators: peroxisome proliferator activated receptors (PPARs), sirtuin 1 (SIRT1), AMP-activated protein kinase (AMPK), and protein kinase A (PKA)) or interacting with reactive oxygen species (ROS) signaling, to alleviate or to correct inborn FAO or RC deficiencies in cellular or animal models. The possible molecular mechanisms involved, in particular the contribution of mitochondrial biogenesis, are discussed. Applications of these pharmacological approaches as a function of genotype/phenotype are also addressed, which clearly orient toward personalized therapy. Finally, we propose that beyond the identification of individual candidate drugs/molecules, future pharmacological approaches should consider their combination, which could produce additive or synergistic effects that may further enhance their therapeutic potential.
The Role of Acrolein and NADPH Oxidase in the Granulocyte-Mediated Growth-Inhibition of Tumor Cells
Authors: Jaganjac Morana , Matijevic Glavan Tanja , Zarkovic Neven
Published: March 2019

Although granulocytes are the most abundant leukocytes in human blood, their involvement in the immune response against cancer is not well understood. While granulocytes are known for their “oxidative burst” when challenged with tumor cells, it is less known that oxygen-dependent killing of tumor cells by granulocytes includes peroxidation of lipids in tumor cell membranes, yielding formation of reactive aldehydes like 4-hydroxynonenal (4-HNE) and acrolein. In the present work, we investigate the role of reactive aldehydes on cellular redox homeostasis and surface toll-like receptor 4 (TLR4) expression. We have further study the granulocyte-tumor cell intercellular redox signaling pathways. The data obtained show that granulocytes in the presence of 4-HNE and acrolein induce excessive ROS formation in tumor cells. Acrolein was also shown to induce granulocyte TLR4 expression. Furthermore, granulocyte-mediated antitumor effects were shown to be mediated via HOCl intracellular pathway by the action of NADPH oxidase. However, further studies are needed to understand interaction between TLR4 and granulocyte-tumor cell intercellular signaling pathways.
CFD Design of Hydrogenation Reactor for Transformation of Levulinic Acid to γ-Valerolactone (GVL) by using High Boiling Point Organic Fluids
Authors: Davidy Alon
Published: March 2019

Levulinic acid (LA) has been ranked as one of the “Top 10” building blocks for future bio-refineries as proposed by the US Department of Energy. It is considered one of the most important platform molecules for the production of fine chemicals and fuels based on its compatibility with existing processes, market economics, and industrial ability to serve as a platform for the synthesis of important derivatives. Hydrogenation of LA to produce γ-valerolactone (GVL) is an active area of research due to the potential of GVL to be used as a biofuel in its own right and for its subsequent transformation into hydrocarbon fuels. This paper contains a new design for a simple, cost effective, and safe hydrogenation reactor for the transformation of levulinic acid to γ-valerolactone (GVL) by utilizing high boiling point organic fluid. The hydrogenation reactor is composed of a heating source—organic fluid (called “DOWTHERM A” or “thermex”) and the catalytic reactor. The advantages of high boiling temperature fluids, along with advances in hydrocracking and reforming technologies driven by the oil and gas industries, make the organic concept more suitable and safer (water coming in contact with liquid metal is well understood in the metallurgical industry to be a steam explosion hazard) for heating the hydrogenation reactor. COMSOL multi-physics software version 4.3b was applied in this work and simultaneously solves the continuity, Navier-Stokes (fluid flow), energy (heat transfer), and diffusion with chemical reaction kinetics equations. It was shown that the heat flux supplied by the DOWTHERM A organic fluid could provide the necessary heat flux required for maintaining the hydrogenation process. It was found that the mass fractions of hydrogen and levulinic acid decreased along the reactor axis. The GVL mass fraction increased along the reactor axis.
Removal of Dyes and Cd2+ in Water by Kaolin/Calcium Alginate Filtration Membrane
Authors: Zhao Yujie , Liu Xiaowei , Qi Meng , Bai Tian , Zhao Kongyin , Zhang Xinxin
Published: March 2019

Kaolin/calcium alginate (kaolin/CaAlg) free-standing membranes were prepared by adding different amounts of Kaolin into the sodium alginate (NaAlg) casting solution and crosslinked by Ca2+ using urea as porogen agent. The morphology of the kaolin/CaAlg filtration membrane was characterized by scanning electron microscope (SEM). Then the kaolin/CaAlg membrane was used for the removal of dyes and Cd2+. The kaolin significantly improved the mechanical behavior and flux of the kaolin/CaAlg membrane. The flux reached 17.53 L/m2·h at 0.1 MPa and when the content of Kaolin in NaAlg was 70 wt.%. The filtration of BSA solution and oil-water emulsion indicated that the kaolin/CaAlg composite filtration membrane exhibited good anti-fouling properties. The rejection of Brilliant Blue G250, Congo red, and methylene blue by the kaolin/CaAlg filtration membrane was 100%, 95.22%, and 62.86%, respectively. The removal rate of Cd2+ reached 99.69%, with a flux of 17.06 L/m2·h at 0.1 MPa.
Invertible Autoencoder for Domain Adaptation
Authors: Teng Yunfei , Choromanska Anna
Published: March 2019

The unsupervised image-to-image translation aims at finding a mapping between the source ( A ) and target ( B ) image domains, where in many applications aligned image pairs are not available at training. This is an ill-posed learning problem since it requires inferring the joint probability distribution from marginals. Joint learning of coupled mappings F A B : A → B and F B A : B → A is commonly used by the state-of-the-art methods, like CycleGAN to learn this translation by introducing cycle consistency requirement to the learning problem, i.e., F A B ( F B A ( B ) ) ≈ B and F B A ( F A B ( A ) ) ≈ A . Cycle consistency enforces the preservation of the mutual information between input and translated images. However, it does not explicitly enforce F B A to be an inverse operation to F A B . We propose a new deep architecture that we call invertible autoencoder (InvAuto) to explicitly enforce this relation. This is done by forcing an encoder to be an inverted version of the decoder, where corresponding layers perform opposite mappings and share parameters. The mappings are constrained to be orthonormal. The resulting architecture leads to the reduction of the number of trainable parameters (up to 2 times). We present image translation results on benchmark datasets and demonstrate state-of-the art performance of our approach. Finally, we test the proposed domain adaptation method on the task of road video conversion. We demonstrate that the videos converted with InvAuto have high quality and show that the NVIDIA neural-network-based end-to-end learning system for autonomous driving, known as PilotNet, trained on real road videos performs well when tested on the converted ones.
The Application of Ant Colony Algorithms to Improving the Operation of Traction Rectifier Transformers
Authors: Kulesz Barbara , Sikora Andrzej , Zielonka Adam
Published: March 2019

In this paper, we discuss a technical issue occurring in electric traction. Tram traction may use DC voltage; this is obtained by rectifying AC voltage supplied by the power grid. In the simplest design— one which is commonly used—only diode uncontrolled rectifiers are used. The rectified voltage is not smooth; it always contains a pulsating (AC) component. The amount of pulsation varies. It depends, among other factors, on the design of the transformer-rectifier set. In the 12-pulse system, we use a three-winding transformer, consisting of one primary winding and two secondary windings: one is delta-connected and the other is star-connected. The unbalance of secondary windings is an extra factor increasing the pulsation of DC voltage. To equalize secondary side voltages, a tap changer may be used. The setting of the tap changer is the question resolved in this paper; it is optimized by application of the ACO (ant colony optimization algorithm). We have analyzed different supply voltage variants, and in particular, distorted voltage containing 5th and 7th harmonics. The results of ant colony optimization application are described in this paper.
Sensitization to Fragrance mix-1 in Patients with Contact Dermatitis in Nord-East of Italy: 1996–2016 Time Trend and Gender Effect
Authors: Larese Filon Francesca , Mauro Marcella
Published: March 2019

(1) Background: Fragrance sensitization is common in Italy and their constituents are used in many cosmetics and detergents. The objective of the study was to analyze the temporal trend of sensitivity to fragrance mix-1 in northeastern Italy and to evaluate gender differences; (2) Methods: From 1996 to 2016, 27,381 consecutive patients with suspected allergic contact dermatitis were patch tested. Individual characteristics were collected through a standardized questionnaire in six departments of dermatology or occupational medicine; (3) Results: The overall prevalence of sensitization to fragrance mix-1 was 7.3%; the prevalence was significantly higher in women (7.7%) than in men (6.3%). From 1996 to 2016, we observed an increase of this sensitization, ranging from 6.2% to 7.7% in males and from 7.2% to 9.1% in females; (4) Conclusions: Our study showed that contact allergy to fragrance mix-1 is important in both sexes and prevalence is increasing over time, despite the introduction of new fragrances with lower sensitization potential. There is the need to reduce the use of fragrances mix-1 to stop the increase of sensitization in exposed subjects.
T4SS Effector Protein Prediction with Deep Learning
Authors: Açıcı Koray , Aşuroğlu Tunç , Erdaş Çağatay Berke , Oğul Hasan
Published: March 2019

Extensive research has been carried out on bacterial secretion systems, as they can pass effector proteins directly into the cytoplasm of host cells. The correct prediction of type IV protein effectors secreted by T4SS is important, since they are known to play a noteworthy role in various human pathogens. Studies on predicting T4SS effectors involve traditional machine learning algorithms. In this work we included a deep learning architecture, i.e., a Convolutional Neural Network (CNN), to predict IVA and IVB effectors. Three feature extraction methods were utilized to represent each protein as an image and these images fed the CNN as inputs in our proposed framework. Pseudo proteins were generated using ADASYN algorithm to overcome the imbalanced dataset problem. We demonstrated that our framework predicted all IVA effectors correctly. In addition, the sensitivity performance of 94.2% for IVB effector prediction exhibited our framework’s ability to discern the effectors in unidentified proteins.
Removal of Positive Elevation Bias of Digital Elevation Models for Sea-Level Rise Planning
Authors: Burke Watson Elizabeth , Haaf LeeAnn , Raper Kirk , Reilly Erin
Published: March 2019

Digital elevation models (DEMs) based on LiDAR surveys provide critical information for predicting the vulnerability of coastal areas to sea-level rises. Due to the poor penetration of LiDAR pulses in marsh vegetation, bare-earth DEMs for coastal wetlands are often subject to positive elevation bias, and thus underestimate vulnerability. This data publication includes comprehensive elevation surveys from seven coastal wetlands in coastal New Jersey, and an evaluation of the accuracy and positive elevation bias of each publically available DEM. Resampling the DEMs at a coarser resolution, replacing cell values using the minimum value in a wider search window (4 m), removed this positive elevation bias with no loss of accuracy.
Planetary Defense Mitigation Gateway: A One-Stop Gateway for Pertinent PD-Related Contents
Authors: Shams Ishan , Li Yun , Yang Jingchao , Yu Manzhu , Yang Chaowei , Bambacus Myra , Lewis Ruthan , Nuth Joseph A. , Oman Luke , Leung Ronald , Seery Bernard D. , Plesko Catherine , Greenaugh Kevin C. , Syal Megan B.
Published: March 2019

Planetary Defense (PD) has become a critical effort of protecting our home planet by discovering potentially hazardous objects (PHOs), simulating the potential impact, and mitigating the threats. Due to the lack of structured architecture and framework, pertinent information about detecting and mitigating near earth object (NEO) threats are still dispersed throughout numerous organizations. Scattered and unorganized information can have a significant impact at the time of crisis, resulting in inefficient processes, and decisions made on incomplete data. This PD Mitigation Gateway (pd.cloud.gmu.edu) is developed and embedded within a framework to integrate the dispersed, diverse information residing at different organizations across the world. The gateway offers a home to pertinent PD-related contents and knowledge produced by the NEO mitigation team and the community through (1) a state-of-the-art smart-search discovery engine based on PD knowledge base; (2) a document archiving and understanding mechanism for managing and utilizing the results produced by the PD science community; (3) an evolving PD knowledge base accumulated from existing literature, using natural language processing and machine learning; and (4) a 4D visualization tool that allows the viewers to analyze near-Earth approaches in a three-dimensional environment using dynamic, adjustable PHO parameters to mimic point-of-impact asteroid deflections via space vehicles and particle system simulations. Along with the benefit of accessing dispersed data from a single port, this framework is built to advance discovery, collaboration, innovation, and education across the PD field-of-study, and ultimately decision support.
Multifractal and Chaotic Properties of Solar Wind at MHD and Kinetic Domains: An Empirical Mode Decomposition Approach
Authors: Alberti Tommaso , Consolini Giuseppe , Carbone Vincenzo , Yordanova Emiliya , Marcucci Maria Federica , De Michelis Paola
Published: March 2019

Turbulence, intermittency, and self-organized structures in space plasmas can be investigated by using a multifractal formalism mostly based on the canonical structure function analysis with fixed constraints about stationarity, linearity, and scales. Here, the Empirical Mode Decomposition (EMD) method is firstly used to investigate timescale fluctuations of the solar wind magnetic field components; then, by exploiting the local properties of fluctuations, the structure function analysis is used to gain insights into the scaling properties of both inertial and kinetic/dissipative ranges. Results show that while the inertial range dynamics can be described in a multifractal framework, characterizing an unstable fixed point of the system, the kinetic/dissipative range dynamics is well described by using a monofractal approach, because it is a stable fixed point of the system, unless it has a higher degree of complexity and chaos.
Can a Quantum Walk Tell Which Is Which?A Study of Quantum Walk-Based Graph Similarity
Authors: Minello Giorgia , Rossi Luca , Torsello Andrea
Published: March 2019

We consider the problem of measuring the similarity between two graphs using continuous-time quantum walks and comparing their time-evolution by means of the quantum Jensen-Shannon divergence. Contrary to previous works that focused solely on undirected graphs, here we consider the case of both directed and undirected graphs. We also consider the use of alternative Hamiltonians as well as the possibility of integrating additional node-level topological information into the proposed framework. We set up a graph classification task and we provide empirical evidence that: (1) our similarity measure can effectively incorporate the edge directionality information, leading to a significant improvement in classification accuracy; (2) the choice of the quantum walk Hamiltonian does not have a significant effect on the classification accuracy; (3) the addition of node-level topological information improves the classification accuracy in some but not all cases. We also theoretically prove that under certain constraints, the proposed similarity measure is positive definite and thus a valid kernel measure. Finally, we describe a fully quantum procedure to compute the kernel.
Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection
Authors: Hržić Franko , Štajduhar Ivan , Tschauner Sebastian , Sorantin Erich , Lerga Jonatan
Published: March 2019

The paper proposes a segmentation and classification technique for fracture detection in X-ray images. This novel rotation-invariant method introduces the concept of local entropy for de-noising and removing tissue from the analysed X-ray images, followed by an improved procedure for image segmentation and the detection of regions of interest. The proposed local Shannon entropy was calculated for each image pixel using a sliding 2D window. An initial image segmentation was performed on the entropy representation of the original image. Next, a graph theory-based technique was implemented for the purpose of removing false bone contours and improving the edge detection of long bones. Finally, the paper introduces a classification and localisation procedure for fracture detection by tracking the difference between the extracted contour and the estimation of an ideal healthy one. The proposed hybrid method excels at detecting small fractures (which are hard to detect visually by a radiologist) in the ulna and radius bones—common injuries in children. Therefore, it is imperative that a radiologist inspecting the X-ray image receives a warning from the computerised X-ray analysis system, in order to prevent false-negative diagnoses. The proposed method was applied to a data-set containing 860 X-ray images of child radius and ulna bones (642 fracture-free images and 218 images containing fractures). The obtained results showed the efficiency and robustness of the proposed approach, in terms of segmentation quality and classification accuracy and precision (up to 91.16 % and 86.22 % , respectively).
Optimization of the KNN Supervised Classification Algorithm as a Support Tool for the Implantation of Deep Brain Stimulators in Patients with Parkinson’s Disease
Authors: Bellino Gabriel Martin , Schiaffino Luciano , Battisti Marisa , Guerrero Juan , Rosado-Muñoz Alfredo
Published: March 2019

Deep Brain Stimulation (DBS) of the Subthalamic Nuclei (STN) is the most used surgical treatment to improve motor skills in patients with Parkinson’s Disease (PD) who do not adequately respond to pharmacological treatment, or have related side effects. During surgery for the implantation of a DBS system, signals are obtained through microelectrodes recordings (MER) at different depths of the brain. These signals are analyzed by neurophysiologists to detect the entry and exit of the STN region, as well as the optimal depth for electrode implantation. In the present work, a classification model is developed and supervised by the K-nearest neighbour algorithm (KNN), which is automatically trained from the 18 temporal features of MER registers of 14 patients with PD in order to provide a clinical support tool during DBS surgery. We investigate the effect of different standardizations of the generated database, the optimal definition of KNN configuration parameters, and the selection of features that maximize KNN performance. The results indicated that KNN trained with data that was standardized per cerebral hemisphere and per patient presented the best performance, achieving an accuracy of 94.35% (p < 0.001). By using feature selection algorithms, it was possible to achieve 93.5% in accuracy in selecting a subset of six features, improving computation time while processing in real time.
Analysis Methodology for Evaluation of Time-Delay Impact on Network-Based System for Droop-Controlled AC Microgrid
Authors: Zhang Yao
Published: March 2019

Potential performance improvements can be obtained by introducing communication techniques in the power electronic systems. However, network-induced time-delay could bring negative consequences of degrading performance or destabilizing the system in many cases. To investigate and handle the impacts of time-delay, a suit of analytical methodology is proposed, where both delay-insensitive and delay-sensitive control strategies of network-based system have their theoretical methods and different problem-solving paths. The former is to predict the maximum allowable boundaries of time-delay for releasing more network resources, and the latter is to use the controller-altering method for changing its original instability, respectively. The proposed methodology is concretely applied in network-based system of droop-controlled AC (Alternating Current) microgrid in islanded mode. Two different current-sharing strategies are mathematically analyzed and given to verify their validity. Experimental results also show the effectiveness of the proposed methodology in droop-controlled AC microgrid system, which provides theoretical guidance on how to use network-based control for the other power electronic systems.
Analysis of Memory Matrices with HfO2 Memristors in a PSpice Environment
Authors: Mladenov Valeri
Published: March 2019

The investigation of new memory circuits is very important for the development of future generations’ non-volatile and Random Access Memories (RAM) memories and modern schemes for in-memory calculations. The purpose of the present research is to propose a detailed analysis of passive and hybrid memristor-based memory crossbars with separating metal oxide semiconductor (MOS) transistors. The considered memristors are based on HfO2. The transistors are applied to eliminate the parasitic paths in the schemes. For simulations, a previously proposed strongly nonlinear modified window function by the author together with a physical nonlinear memristor model is used. The considered model is adjusted according to the experimental i–v relationship of HfO2 memristors. The i–v relationship obtained by the simulation is successfully fitted to the respective relationship derived by physical measurements. A good coincidence between these characteristics is established. Several basic window functions are also applied for comparison to the corresponding results. The proposed model is analyzed in Personal Simulation Program with Integrated Circuit Emphasis (PSpice) and it is also used for simulation of a 5 × 5 fragment of a memristor memory crossbar with isolating transistors and for the analysis of a 6 × 6 passive memory matrix. The investigated matrices are simulated for writing, reading, and erasing information. It is established that the model proposed could be used for simulations of complex memristor circuits.
Improving Angle Stability by Switching Shunt Reactors in Mixed Overhead Cable Lines. An Italian 400 kV Case Study
Authors: Ippolito Mariano Giuseppe , Massaro Fabio , Musca Rossano
Published: March 2019

Stringent environmental constraints make the construction of new transmission overhead lines more and more difficult. Alternatively, today it is possible to use cable lines for high (HV) and extra-high (EHV) voltage systems. The configuration of the so-called mixed lines can create some problems in the operation of the electrical system, both during steady-state and transient conditions. In particular, the system stability is one of the main concerns when analyzing the dynamic response of power systems. In this paper, the study of angular stability of a system containing a mixed line is presented: a specific control logic applied to the shunt reactors of the mixed line is proposed as improvement of the overall system stability. The proposed switching logic is first discussed from a theoretical point of view and validated with two different testing systems. Then, the existing overhead-cable lines connecting Sicily to the rest of continental Europe 400 kV power system are taken as case study for the application of the proposed switching strategy. Several simulations are performed in the power system analysis software NEPLAN360: the results show the fundamental role of the timing of the control actions applied on the shunt reactors in helping the system to keep the stability. The proposed control proves to be an effective support to the system subjected to critical contingencies, contributing decisively to avoid the angular separation between areas and therefore to preserve the stability of the system.
Design and Analysis of District Heating Systems Utilizing Excess Heat in Japan
Authors: Fujii Shin , Furubayashi Takaaki , Nakata Toshihiko
Published: March 2019

District heating systems (DHSs) which utilize excess heat play an important role in energy infrastructure in many European countries. In contrast to Europe, the DHS is not common and excess heat is not reused effectively in Japan. Almost all the DHSs in Japan were designed as first-generation district heating (1GDH) systems or 2GDH systems. No 4GDH systems have been introduced in Japan. The present study designs a 4GDH system utilizing excess heat from a wide area of Northern Japan and evaluates its feasibility. First, available heat amounts from two excess heat resources were calculated: waste incineration plants and thermal power plants. Second, heat demand from both residential and commercial sectors was estimated using a 1 km mesh, and a heat load curve was created for each mesh based on load curve data. Third, the DHS was designed with excess heat plants as a supply-side heat resource, and spatial information of the demand side made use of the geographical information system (GIS). Further analysis was conducted on selected DHSs in three cities in order to evaluate those systems’ feasibility based on energy efficiency, CO2 emissions, and economic aspects. The result shows that 70.5 PJ of heat can be supplied by DHS in Northern Japan, replacing imported fossil fuels such as petroleum and LPG with regional excess heat. The designed DHS could supply heat with equivalent costs compared to European countries.
Insulator Detection Method in Inspection Image Based on Improved Faster R-CNN
Authors: Zhao Zhenbing , Zhen Zhen , Zhang Lei , Qi Yincheng , Kong Yinghui , Zhang Ke
Published: March 2019

The detection of insulators in power transmission and transformation inspection images is the basis for insulator state detection and fault diagnosis in thereafter. Aiming at the detection of insulators with different aspect ratios and scales and ones with mutual occlusion, a method of insulator inspection image based on the improved faster region-convolutional neural network (R-CNN) is put forward in this paper. By constructing a power transmission and transformation insulation equipment detection dataset and fine-tuning the faster R-CNN model, the anchor generation method and non-maximum suppression (NMS) in the region proposal network (RPN) of the faster R-CNN model were improved, thus realizing a better detection of insulators. The experimental results show that the average precision (AP) value of the faster R-CNN model was increased to 0.818 with the improved anchor generation method under the VGG-16 Net. In addition, the detection effect of different aspect ratios and different scales of insulators in the inspection images was improved significantly, and the occlusion of insulators could be effectively distinguished and detected using the improved NMS.
Hydraulic Experiments on a Small-Scale Wave Energy Converter with an Unconventional Dummy Pto
Authors: Martinelli Luca , Volpato Matteo , Favaretto Chiara , Ruol Piero
Published: March 2019

This paper investigates on a Wave Energy Converter (WEC) named Energy & Protection, 4th generation (EP4). The WEC couples the energy harvesting function with the purpose of protecting the coast from erosion. It is formed by a flap rolling with a single degree of freedom around a lower hinge. Small-scale tests were carried out in the wave flume of the maritime group of Padua University, aiming at the evaluation of the device efficiency. The test peculiarity is represented by the system used to simulate the Power Take Off (PTO). Such dummy PTO permits a free rotation of two degrees before engaging the shaft, allowing the flap to gain some inertia, and then applying a constant resistive moment. The EP4 was observed to reach a 35% efficiency, under short regular waves. The effects, in terms of coastal protection, are small but not negligible, at least for the shortest waves.
A Trapezoidal Velocity Profile Generator for Position Control Using a Feedback Strategy
Authors: Heo Hong-Jun , Son Yungdeug , Kim Jang-Mok
Published: March 2019

Position control is usually achieved using a position controller and a profile generator. The profile generator produces a desired position trajectory from a position reference and predefined profiles. The position controller forces the actual position to trace the generated position trajectory. A time-based profile generator is the most famous profile generator due to its capability of generating various profiles. However, time base difference in analysis and implementation causes a steady-state error. In order to remove the steady-state error, this paper proposes a novel profile generator for a trapezoidal velocity profile generation. The proposed generator is based on a cascaded P-PI position controller which is designed to trace the position reference. A dynamic range limiter is adopted to provide the acceleration and velocity restrictions which are basic functions for generating the trapezoidal profile. In spite of these restrictions, it cannot make a desired velocity profile only using the limiter because deceleration point is inaccurate. To adjust the deceleration point, a feedback compensator is designed which requires the velocity of the deceleration point. The velocity of the deceleration point is estimated from the initial position error. The compensator moves the deceleration point to the appropriate point which can generate the desired velocity profile. The proposed profile generator can remove the steady-state error, and the position response can be easily adjusted to be either overdamped or underdamped by selecting the two gains appropriately. Several experimental results are presented to verify the usefulness of the proposed generator.
A Study on Join Operations in MongoDB Preserving Collections Data Models for Future Internet Applications
Authors: Celesti Antonio , Fazio Maria , Villari Massimo
Published: March 2019

Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has to be changed or a set of operations have to be performed to address particular queries on data. Thus, open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported? What is the quality of NoSQL solutions in such cases? In this paper, we deal with such issues specifically considering one of the major NoSQL document oriented DB available on the market: MongoDB. In particular, we discuss an approach to perform join operations at application layer in MongoDB that allows us to preserve data models. We analyse performance of the proposes approach discussing the introduced overhead in comparison with SQL-like DBs.
Social Behavior and Welfare in Nile Tilapia
Authors: Gonçalves-de-Freitas Eliane , Bolognesi Marcela Cesar , Gauy Ana Carolina dos Santos , Brandão Manuela Lombardi , Giaquinto Percilia Cardoso , Fernandes-Castilho Marisa
Published: March 2019

Fish social behavior can be affected by artificial environments, particularly by factors that act upon species that show aggressive behavior to set social rank hierarchy. Although aggressive interactions are part of the natural behavior in fish, if constant and intense, such interactions can cause severe body injuries, increase energy expenditure, and lead the animals to suffer from social stress. The immediate consequence of these factors is a reduced welfare in social fish species. In this paper, we consider the factors that impact on the social behavior and welfare of Nile tilapia, an African cichlid fish widely used both in fish farms and in research; this species is frequently used as a model for physiology and behavior research. This is a polygynous species whose males interact aggressively, establishing a territorial based hierarchy, where a dominant male and several subordinate males arise. When social stability is shrunk, the negative effects of prolonged fighting emerge. In this paper, we summarized how some of the common practices in aquaculture, such as classifying individuals by matching their sizes, water renewal, stock density, and environment lighting affect Nile tilapia social aggressive interactions and, in turn, impact on its welfare. We also discuss some ways to decrease the effects of aggressive interactions in Nile tilapia, such as environment color and body tactile stimulation.
Efficiently Generating Mixing by Combining Differing Small Amplitude Helical Geometries
Authors: Cookson Andrew N. , Doorly Denis J. , Sherwin Spencer J.
Published: March 2019

Helical geometries have been used in recent years to form cardiovascular prostheses such as stents and shunts. The helical geometry has been found to induce swirling flow, promoting in-plane mixing. This is hypothesised to reduce the formation of thrombosis and neo-intimal hyperplasia, in turn improving device patency and reducing re-implantation rates. In this paper we investigate whether joining together two helical geometries, of differing helical radii, in a repeating sequence, can produce significant gains in mixing effectiveness, by embodying a ‘streamline crossing’ flow environment. Since the computational cost of calculating particle trajectories over extended domains is high, in this work we devised a procedure for efficiently exploring the large parameter space of possible geometry combinations. Velocity fields for the single geometries were first obtained using the spectral/hp element method. These were then discontinuously concatenated, in series, for the particle tracking based mixing analysis of the combined geometry. Full computations of the most promising combined geometries were then performed. Mixing efficiency was evaluated quantitatively using Poincaré sections, particle residence time data, and information entropy. Excellent agreement was found between the idealised (concatenated flow field) and the full simulations of mixing performance, revealing that a strict discontinuity between velocity fields is not required for mixing enhancement, via streamline crossing, to occur. Optimal mixing was found to occur for the combination R = 0.2 D and R = 0.5 D , producing a 70 % increase in mixing, compared with standard single helical designs. The findings of this work point to the benefits of swirl disruption and suggest concatenation as an efficient means to determine optimal configurations of repeating geometries for future designs of vascular prostheses.
Impact of Inflow Boundary Conditions on the Calculation of CT-Based FFR
Authors: Lo Ernest W. C. , Menezes Leon J. , Torii Ryo
Published: March 2019

Background: Calculation of fractional flow reserve (FFR) using computed tomography (CT)-based 3D anatomical models and computational fluid dynamics (CFD) has become a common method to non-invasively assess the functional severity of atherosclerotic narrowing in coronary arteries. We examined the impact of various inflow boundary conditions on computation of FFR to shed light on the requirements for inflow boundary conditions to ensure model representation. Methods: Three-dimensional anatomical models of coronary arteries for four patients with mild to severe stenosis were reconstructed from CT images. FFR and its commonly-used alternatives were derived using the models and CFD. A combination of four types of inflow boundary conditions (BC) was employed: pulsatile, steady, patient-specific and population average. Results: The maximum difference of FFR between pulsatile and steady inflow conditions was 0.02 (2.4%), approximately at a level similar to a reported uncertainty level of clinical FFR measurement (3–4%). The flow with steady BC appeared to represent well the diastolic phase of pulsatile flow, where FFR is measured. Though the difference between patient-specific and population average BCs affected the flow more, the maximum discrepancy of FFR was 0.07 (8.3%), despite the patient-specific inflow of one patient being nearly twice as the population average. Conclusions: In the patients investigated, the type of inflow boundary condition, especially flow pulsatility, does not have a significant impact on computed FFRs in narrowed coronary arteries.
Identifying Selection Signatures for Backfat Thickness in Yorkshire Pigs Highlights New Regions Affecting Fat Metabolism
Authors: Ma Haoran , Zhang Saixian , Zhang Kaili , Zhan Huiwen , Peng Xia , Xie Shengsong , Li Xinyun , Zhao Shuhong , Ma Yunlong
Published: March 2019

Identifying the genetic basis of improvement in pigs contributes to our understanding of the role of artificial selection in shaping the genome. Here we employed the Cross Population Extended Haplotype Homozogysity (XPEHH) and the Wright’s fixation index (FST) methods to detect trait-specific selection signatures by making phenotypic gradient differential population pairs, and then attempted to map functional genes of six backfat thickness traits in Yorkshire pigs. The results indicate that a total of 283 and 466 single nucleotide polymorphisms (SNPs) were identified as trait-specific selection signatures using FST and XPEHH, respectively. Functional annotation suggested that the genes overlapping with the trait-specific selection signatures such as OSBPL8, ASAH2, SMCO2, GBE1, and ABL1 are responsible for the phenotypes including fat metabolism, lean body mass and fat deposition, and transport in mouse. Overall, the study developed the methods of gene mapping on the basis of identification of selection signatures. The candidate genes putatively associated with backfat thickness traits can provide important references and fundamental information for future pig-breeding programs.
DNA Methylation Reprogramming during Mammalian Development
Authors: Zeng Yang , Chen Taiping
Published: March 2019

DNA methylation (5-methylcytosine, 5mC) is a major form of DNA modification in the mammalian genome that plays critical roles in chromatin structure and gene expression. In general, DNA methylation is stably maintained in somatic tissues. However, DNA methylation patterns and levels show dynamic changes during development. Specifically, the genome undergoes two waves of global demethylation and remethylation for the purpose of producing the next generation. The first wave occurs in the germline, initiated with the erasure of global methylation in primordial germ cells (PGCs) and completed with the establishment of sex-specific methylation patterns during later stages of germ cell development. The second wave occurs after fertilization, including the erasure of most methylation marks inherited from the gametes and the subsequent establishment of the embryonic methylation pattern. The two waves of DNA methylation reprogramming involve both distinct and shared mechanisms. In this review article, we provide an overview of the key reprogramming events, focusing on the important players in these processes, including DNA methyltransferases (DNMTs) and ten-eleven translocation (TET) family of 5mC dioxygenases.
Geospatial Sciences and Space Law: Legal Aspects of Earth Observation, Remote Sensing and Geoscientific Ground Investigations in Africa
Authors: Oduntan Gbenga
Published: March 2019

Geospatial sciences play crucial roles in and have effects on the socioeconomic, political and security fortunes of states. Earth observation, remote sensing and geoscientific ground investigation increasingly occupy vantage positions in the legal order of states, particularly in evidential terms and in the verification of facts under international law. How then do these aspects of space law and space sciences affect contemporary Africa and the commercial fortunes, as well as international relations among some African states? What impact do they have in relation to: (a) international boundaries disputes and demarcation activities; (b) management and the preservation of the African heritage; (c) disaster and conservation management? The paper will test the hypothesis that it is crucial for the development of the continent especially in the areas mentioned above that states should sustain and increase investment in the following areas: archaeological prospection, condition assessment of heritage assets; Geographic Information System (GIS) analysis of spatial settlement patterns in modern landscapes and assessment of natural or human-induced threats to conservation.
James Bond’s Biopolitics
Authors: Schwanebeck Wieland
Published: March 2019

This chapter traces Foucauldian technologies of power in the James Bond universe and characterises the Bond franchise’s biopolitics in the cultural environment of the 1960s and 1970s, when 007 became a mass phenomenon. The majority of the chapter is dedicated to a case study of On Her Majesty’s Secret Service, Ian Fleming’s tenth Bond novel (1963) and the sixth film in the EON series (1969). The chapter highlights the intersection between reproduction and fertility on the one hand and the infliction of death and mass genocide on the other, and it examines how James Bond juxtaposes the disciplinary means that are directed against the body (as an organism) on the one hand, and the state-powered regulation of biological processes that control the population on the other. The two versions of On Her Majesty’s Secret Service amount to the franchise’s most straightforward foray into the realm of biopolitics and would pave the way for the franchise’s subsequent biopolitical and eugenic moments, like when the figure of the genocidal villain gets to articulate the franchise’s own subliminal agenda regarding population control and the future of the (British) species.