bluuebunny/crossref_metadata_2025 huggingface dataset:
Overactivation of Akt Contributes to MEK Inhibitor Primary and Acquired Resistance in Colorectal Cancer Cells
Authors: Tsubaki Masanobu , Takeda Tomoya , Noguchi Masaki , Jinushi Minami , Seki Shiori , Morii Yuusuke , Shimomura Kazunori , Imano Motohiro , Satou Takao , Nishida Shozo
Published: November 2019

RAS and BRAF-mutated colorectal cancers are associated with resistance to chemotherapy and poor prognosis, highlighting the need for new therapeutic strategies. Although these cancers sometimes respond to mitogen activated protein kinase kinase (MEK) inhibitor treatment, they often acquire resistance via mechanisms, which are poorly understood. Here, we investigated the mechanism of MEK inhibitor resistance in primary- and acquired-resistant cells. Cell viability was examined using the trypan blue dye exclusion assay. Protein expression was analyzed by western blotting. Somatic mutations in colorectal cancer cells were investigated using the polymerase chain reaction array. PD0325901 and trametinib induced cell death in LoVo and Colo-205 cells but not in DLD-1 and HT-29 cells, which have a PIK3CA mutation constitutively activating Akt and NF-κB. Treatment with PD0325901 and trametinib suppressed ERK1/2 activation in all four cell lines but only induced Akt and NF-κB activation in DLD-1 and HT-29 cells. Inhibition of Akt but not NF-κB, overcame MEK inhibitor resistance in DLD-1 and HT-29 cells. Acquired-resistant LoVo/PR, Colo-205/PR and LoVo/TR cells have constitutively active Akt due to a M1043V mutation in the kinase activation loop of PIK3CA and Akt inhibitor resensitized these cells to MEK inhibitor. These results demonstrate that the overactivation of Akt plays a critical role in MEK inhibitor primary and acquired resistance and implicate combined Akt/MEK inhibition as a potentially useful treatment for RAS/BRAF-mutated colorectal cancer.
Energy Dissipation in Stepped Spillways with Different Horizontal Face Angles
Authors: Peng Yongqin , Zhang Xujin , Yuan Hao , Li Xia , Xie Chunhang , Yang Shuqing , Bai Zhaoliang
Published: November 2019

Energy dissipation is one of the most important factors in choosing stepped spillways. However, very few studies have investigated energy dissipation with different horizontal face angles. In this paper, the realizable k-ε turbulent model was used to study the flow field, energy dissipation rates and turbulent kinetic energy and its dissipation rate for different stepped spillways with five horizontal face angles in the skimming flow regions. Results showed that the field and direction of the flow were changed by the horizontal face angles of the stepped spillway, which produced some unique characteristics and thus caused better energy dissipation. The fluctuation of free water surface will be larger with increasing horizontal face angles and the energy dissipation rate decreases with an increasing unit discharge and increases for the enlargement of the horizontal face angles. This conclusion could provide a reference for the relevant research of V shaped stepped spillways.
Visualization of Patterned Modified Surfaces in Condensation and Frosting States
Authors: Yang Kai-Shing , Lu Wei , Wu Yu-Lieh
Published: November 2019

In this study, a novel, thorn-shaped, containing, hydrophilic, and hydrophobic surface is proposed to have a better condensate drainage characteristic and to delay the required time for frosting. By using a hydrophilic and hydrophobic mixed thorn-shaped surface created by screen printing, the design makes use of the differences in the wettability gradient to achieve rapid condensate drainage and to lengthen the time for frosting. The results of a frosting experiment indicated that the droplet adsorption and combination and discharge effect in the thorn sample were substantial. The drainage effect increased the surface renewal rate and inhibited ice layer growth on the thorn sample by 52.4% compared with that on pure copper surface. The heat transfer coefficient of the thorn sample during frosting was approximately 16.2% higher than that of pure copper surface. In addition, the defrosting results indicated that the defrosting time of the thorn sample was almost equal to that of the pure copper sample. However, large droplets were easily stagnated at the structural junction due to contact angle hysteresis after defrosting.
Adaptive Rule-Based Energy Management Strategy for a Parallel HEV
Authors: Bagwe Rishikesh Mahesh , Byerly Andy , dos Santos Euzeli Cipriano , Ben-Miled Zina
Published: November 2019

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink®, both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.
Study on the Interaction Mechanism of Hydraulic Fracture and Natural Fracture in Shale Formation
Authors: Zheng Heng , Pu Chunsheng , IL CHOE TONG
Published: November 2019

Hydraulic fracturing is an essential technique for the development of shale gas, due to the low permeability in formation. Abundant natural fractures contained in a formation are indispensable for the development of a fracture network. In this paper, a damage-stress-seepage coupled hydraulic fracture expansion model, based on the extended finite element method, is established. The simulation results show that shear failure occurs when the hydraulic fracture interacts with a frictional natural fracture, while tensile failure occurs when it interacts with a cement natural fracture. Low interaction angles and high tensile strength of the rock are beneficial for the generation of a complex fracture network. Furthermore, under the same geological conditions and injection parameters, frictional natural fractures are more beneficial for the generation of a complex fracture network, when compared with cement natural fractures. This can not only effectively increase the propagation length of the natural fracture, but also effectively reduce its reactive resistance. This research is of great significance for the efficient exploitation of unconventional oil and gas resources.
A Dual-Stator Winding Induction Generator Based Wind-Turbine Controlled via Super-Twisting Sliding Mode
Authors: Talpone Juan I. , Puleston Paul F. , Cendoya Marcelo G. , Barrado-Rodrigo José. A.
Published: November 2019

The dual-stator winding induction generator (DWIG) is a promising electrical machine for wind energy conversion systems, especially in the low/mid power range. Based on previous successful results utilising feed forward control, in this article, a super-twisting (ST) sliding mode improved control set-up is developed to maximise power extraction during low wind regimes. To accomplish this objective, via constant volts/hertz implementation, a ST controller was designed to command the DWIG control winding, such that the tip-speed ratio is robustly maintained at its optimal value. The proposed super-twisting control set-up was experimentally assessed to analyse its performance and to verify its efficiency in an actual generation test bench. The results showed a fast convergence to maximum power operation, avoiding chattering and offsets due to model uncertainties.
Experimental Demonstration of Deterministic Chaos in a Waste Oil Biodiesel Semi-Industrial Furnace Combustion System
Authors: Gao Shengyang , Li Fashe , Xiao Qingtai , Xu Jianxin , Wang Huage , Wang Hua
Published: November 2019

In this paper, the nonlinear dynamic characteristics of the oxygen-enriched combustion of waste oil biodiesel in semi-industrial furnaces were tested by the power spectrum, phase space reconstruction, the largest Lyapunov exponents, and the 0-1 test method. To express the influences of the system parameters, experiments were carried out under different oxygen content conditions (21%, 25%, 28%, 31%, and 33%). Higher oxygen enrichment degrees contribute to finer combustion sufficiency, which produces flames with high luminance. Flame luminance and temperature can be represented by different gray scale values of flame images. The chaotic characteristics of gray scale time series under different oxygen enrichment degrees were studied. With increased oxygen content, the chaotic characteristics of flame gradually developed from weak chaos to strong chaos. Furthermore, the flame maintained a stable combustion process in a high-temperature region. The stronger the chaotic characteristics of the flame, the better the combustion effect. It can be seen that the change of initial combustion conditions has a great influence on the whole combustion process. The results of several chaotic test methods were consistent. Using chaotic characteristics to analyze the waste oil biodiesel combustion process can digitize the combustion process, find the best combustion state, optimize, and precisely control it.
Assessing Socioeconomic Impacts of Integrating Distributed Energy Resources in Electricity Markets through Input-Output Models
Authors: Ramos Carvajal Carmen , García-Muñiz Ana Salomé , Moreno Cuartas Blanca
Published: November 2019

In competitive electricity markets, the growth of electricity generated by renewable sources will reduce the market price of electricity assuming marginal cost pricing. However, small renewable distributed generation (RDG) alone cannot modify the formation of electricity prices. By aggregating small RDG units into a Virtual Power Plants (as a single unit market) they are capable of dealing at the wholesale electricity market analogous to large-scale producer following in changes in wholesale prices. This paper investigates the socioeconomic impacts of different type of RDG technologies on Spanish economic sectors and households. To this end, we applied an input-output price model to detail the activities more sensitive to changes in electricity price due to RDG technologies deployment and the associated modifications in income and total output associated with the households’ consumption variation. Detailed Spanish electricity generation disaggregation of the latest available Spanish Input-Output table, which refers to 2015, was considered. It was found that the integration of RDG units in the electricity market project a better situation for the economy and Spanish households. This paper’s scope and information can be used to benefit decision-making with respect to electricity pricing policies.
A Novel Coding Metasurface for Wireless Power Transfer Applications
Authors: Tran Nguyen Minh , Amri Muhammad Miftahul , Park Je Hyeon , Hwang Sa Il , Kim Dong In , Choi Kae Won
Published: November 2019

We propose and implement a novel 1-bit coding metasurface that is capable of focusing and steering beam for enhancing power transfer efficiency of the electromagnetic (EM) wave-based wireless power transfer systems. The proposed metasurface comprises 16 × 16 unit cells which are designed with a fractal structure and the operating frequency of 5.8 GHz. One PIN diode is incorporated within each unit cell and enables two states with 180 ° phase change of the reflected signal at the unit cell. The two states of the unit cell correspond to the ON and OFF states of the PIN diode or “0” and “1” coding in the metasurface. By appropriately handling the ON/OFF states of the coding metasurface, we can control the reflected EM wave impinged on the metasurface. To verify the working ability of the coding metasurface, a prototype metasurface with a control board has been fabricated and measured. The results showed that the coding metasurface is capable of focusing beam to desired direction. For practical scenarios, we propose an adaptive optimal phase control scheme for focusing the beam to a mobile target. Furthermore, we prove that the proposed adaptive optimal phase control scheme outperforms the random phase control and beam synthesis schemes.
Severity and Influencing Factors of Homophobia in Korean Nursing Students
Authors: Kwak Hye Weon , Kim Min Young , Kim Min Young
Published: November 2019

Sexual minorities are people with non-cis and non-heterosexual gender identities, including LGBT (lesbian, gay, bisexual, and transgender) identities. Korean society is prejudiced against sexual minorities—in our study, we will broadly label this prejudice homophobia. It is possible that sexual minorities do not receive appropriate health management owing to such prejudices. Therefore, it is necessary to reduce homophobia in nursing students. This study aims to measure the degree of homophobia in Korean nursing students and identify the factors that affect homophobia. Our study is a cross-sectional study, which surveys attitudes of 265 nursing students toward homophobia in five Korean cities in January to March, 2019. The average homophobia score was 74.5 out of a possible 120; 92.9% of the participants were classified as homophobic, and 42.3% as highly homophobic. We found that participants who were male, religious, had low self-esteem, and had no family members or acquaintances who might belong to a sexual minority group, were more likely to be homophobic. Nursing students in Korea still exhibit high levels of homophobia. As high levels of homophobia can negatively affect health management and nursing, especially in the case of sexual minorities, we suggest that educational programs should be set up to reduce homophobia in nursing students.
Blockchain Economical Models, Delegated Proof of Economic Value and Delegated Adaptive Byzantine Fault Tolerance and their implementation in Artificial Intelligence BlockCloud
Authors: Deng Qi
Published: November 2019

The Artificial Intelligence BlockCloud (AIBC) is an artificial intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an ecosystem layer (the latter three are the collective “upper-layers”). The AIBC layers have distinguished responsibilities and thus performance and robustness requirements. The upper layers need to follow a set of economic policies strictly and run on a deterministic and robust protocol. While the fundamental layer needs to follow a protocol with high throughput without sacrificing robustness. As such, the AIBC implements a two-consensus scheme to enforce economic policies and achieve performance and robustness: Delegated Proof of Economic Value (DPoEV) incentive consensus on the upper layers, and Delegated Adaptive Byzantine Fault Tolerance (DABFT) distributed consensus on the fundamental layer. The DPoEV uses the knowledge map algorithm to accurately assess the economic value of digital assets. The DABFT uses deep learning techniques to predict and select the most suitable BFT algorithm in order to enforce the DPoEV, as well as to achieve the best balance of performance, robustness, and security. The DPoEV-DABFT dual-consensus architecture, by design, makes the AIBC attack-proof against risks such as double-spending, short-range and 51% attacks; it has a built-in dynamic sharding feature that allows scalability and eliminates the single-shard takeover. Our contribution is four-fold: that we develop a set of innovative economic models governing the monetary, trading and supply-demand policies in the AIBC; that we establish an upper-layer DPoEV incentive consensus algorithm that implements the economic policies; that we provide a fundamental layer DABFT distributed consensus algorithm that executes the DPoEV with adaptability; and that we prove the economic models can be effectively enforced by AIBC’s DPoEV-DABFT dual-consensus architecture.
Comparison between Mechanical Properties and Structures of a Rolled and a 3D-Printed Stainless Steel
Authors: Natali Stefano , Brotzu Andrea , Pilone Daniela
Published: November 2019

In this work selective laser melting was successfully utilized to produce 316 stainless steel bulk specimens. Although this technology provides many advantages compared to conventional shaping processes, little residual porosity may be a problem for some applications where high strength is required. The objective of this work was to determine, through data analysis, a mechanical and metallographic comparison between thin sheets made by using different manufacturing technologies: Cold rolling and additive manufacturing. This comparison was useful to understand whether it could be more advantageous to use the prototyping for new mechanical components. The results show that the additive manufactured steel, due to its microstructure, is characterized by a higher yield strength and by a lower elongation and ultimate tensile strength.
Genome Mining of Marine-Derived Streptomyces sp. SCSIO 40010 Leads to Cytotoxic New Polycyclic Tetramate Macrolactams
Authors: Liu Wei , Zhang Wenjun , Jin Hongbo , Zhang Qingbo , Chen Yuchan , Jiang Xiaodong , Zhang Guangtao , Zhang Liping , Zhang Weimin , She Zhigang , Zhang Changsheng
Published: November 2019

Polycyclic tetramate macrolactams (PTMs) biosynthetic gene cluster are widely distributed in different bacterial types, especially in Streptomyces species. The mining of the genomic data of marine-derived Streptomyces sp. SCSIO 40010 reveals the presence of a putative PTM-encoding biosynthetic gene cluster (ptm′ BGC) that features a genetic organization for potentially producing 5/5/6 type of carbocyclic ring-containing PTMs. A fermentation of Streptomyces sp. SCSIO 40010 led to the isolation and characterization of six new PTMs 1–6. Comprehensive spectroscopic analysis assigned their planar structures and relative configurations, and their absolute configurations were deduced by comparing the experimental electronic circular dichroism (ECD) spectra with the reported spectra of the known PTMs. Intriguingly, compounds 1–6 were determined to have a trans-orientation of H-10/H-11 at the first 5-membered ring, being distinct from the cis-orientation in their known PTM congeners. PTMs 1–5 displayed cytotoxicity against several cancer cell lines, with IC50 values that ranged from 2.47 to 17.68 µM.
Evaluation of Tensile Performance of Steel Members by Analysis of Corroded Steel Surface Using Deep Learning
Authors: Chun Pang-jo , Yamane Tatsuro , Izumi Shota , Kameda Toshihiro
Published: November 2019

To conduct safety checks of corroded steel structures and formulate appropriate maintenance strategies, the residual strength of steel structural members must be assessed with high accuracy. Finite element method (FEM) analyses that precisely recreate the morphology of corroded surfaces using solid elements are expected to accurately assess the strength; however, the cost of conducting these calculations is extremely high. Therefore, a model that uses mean thickness as the thickness of the shell element is widely used but this method has precision issues, particularly regarding overestimation of risk. Thus, this study proposes a method of structural analysis in which the effective thickness of a shell element is assessed using the convolutional neural network (CNN), a type of deep learning performed on tensile structural members. An FEM model is then built based on the shell element that uses this effective thickness. We cross-validated this method by adding a feature extraction layer that reflects the domain knowledge, together with convolutional and pooling layers that are commonly used for CNN and found that a high level of accuracy could be achieved. Furthermore, regarding corroded steel plates and H-section steel, our method demonstrated results that were extremely close to those of models that used solid elements.
Synthesis of Amino Acid–Naphthoquinones and In Vitro Studies on Cervical and Breast Cell Lines
Authors: Rivera-Ávalos Ernesto , de Loera Denisse , Araujo-Huitrado Jorge Gustavo , Escalante-García Ismailia Leilani , Muñoz-Sánchez Miguel Antonio , Hernández Hiram , López Jesús Adrián , López Lluvia
Published: November 2019

We performed an extensive analysis about the reaction conditions of the 1,4-Michael addition of amino acids to 1,4-naphthoquinone and substitution to 2,3-dichloronaphthoquinone, and a complete evaluation of stoichiometry, use of different bases, and the pH influence was performed. We were able to show that microwave-assisted synthesis is the best method for the synthesis of naphthoquinone–amino acid and chloride–naphthoquinone–amino acid derivatives with 79–91% and 78–91% yields, respectively. The cyclic voltammetry profiles showed that both series of naphthoquinone–amino acid derivatives mainly display one quasi-reversible redox reaction process. Interestingly, it was shown that naphthoquinone derivatives possess a selective antitumorigenic activity against cervix cancer cell lines and chloride–naphthoquinone–amino acid derivatives against breast cancer cell lines. Furthermore, the newly synthetized compounds with asparagine–naphthoquinones (3e and 4e) inhibited ~85% of SiHa cell proliferation. These results show promising compounds for specific cervical and breast cancer treatment.
Microfluidic Technologies for High Throughput Screening Through Sorting and On-Chip Culture of C. elegans
Authors: Midkiff Daniel , San-Miguel Adriana
Published: November 2019

The nematode Caenorhabditis elegans is a powerful model organism that has been widely used to study molecular biology, cell development, neurobiology, and aging. Despite their use for the past several decades, the conventional techniques for growth, imaging, and behavioral analysis of C. elegans can be cumbersome, and acquiring large data sets in a high-throughput manner can be challenging. Developments in microfluidic “lab-on-a-chip” technologies have improved studies of C. elegans by increasing experimental control and throughput. Microfluidic features such as on-chip control layers, immobilization channels, and chamber arrays have been incorporated to develop increasingly complex platforms that make experimental techniques more powerful. Genetic and chemical screens are performed on C. elegans to determine gene function and phenotypic outcomes of perturbations, to test the effect that chemicals have on health and behavior, and to find drug candidates. In this review, we will discuss microfluidic technologies that have been used to increase the throughput of genetic and chemical screens in C. elegans. We will discuss screens for neurobiology, aging, development, behavior, and many other biological processes. We will also discuss robotic technologies that assist in microfluidic screens, as well as alternate platforms that perform functions similar to microfluidics.
Strip Adjustment of Airborne LiDAR Data in Urban Scenes Using Planar Features by the Minimum Hausdorff Distance
Authors: Liu Ke , Ma Hongchao , Zhang Liang , Cai Zhan , Ma Haichi
Published: November 2019

In Airborne Light Detection and Ranging (LiDAR) data acquisition practice, discrepancies exist between adjacent strips even though careful system calibrations have been performed. A strip adjustment method using planar features acquired by the Minimum Hausdorff Distance (MHD) is proposed to eliminate these discrepancies. First, semi-suppressed fuzzy C-means and restricted region growing algorithms are used to extract buildings. Second, a binary image is generated from the minimum bounding rectangle that covers overlapping regions. Then, connected components labeling algorithm is applied to process the binary image to extract individual buildings. After that, building matching is performed based on MHD. Third, a coarse-to-fine approach is used to segment building roof planes. Then, plane matching is conducted under the constraints of MHD and normal vectors similarity. The last step is the calculation of the parameters based on Euclidean distance minimization between matched planes. Two different types of datasets, one of which was acquired by a dual-channel LiDAR system Trimble AX80, were selected to verify the proposed method. Experimental results show that the corresponding planar features that meet adjustment requirements can be successfully detected without any manual operations or auxiliary data or transformation of raw data, while the discrepancies between strips can be effectively eliminated. Although adjustment results of the proposed method slightly outperform the comparison alternative, the proposed method also has the advantage of processing the adjustment in a more automatic manner than the comparison method.
Preliminary Design of a Model-Free Synthetic Sensor for Aerodynamic Angle Estimation for Commercial Aviation
Authors: Lerro Angelo , Brandl Alberto , Battipede Manuela , Gili Piero
Published: November 2019

Heterogeneity of the small aircraft category (e.g., small air transport (SAT), urban air mobility (UAM), unmanned aircraft system (UAS)), modern avionic solution (e.g., fly-by-wire (FBW)) and reduced aircraft (A/C) size require more compact, integrated, digital and modular air data system (ADS) able to measure data from the external environment. The MIDAS project, funded in the frame of the Clean Sky 2 program, aims to satisfy those recent requirements with an ADS certified for commercial applications. The main pillar lays on a smart fusion between COTS solutions and analytical sensors (patented technology) for the identification of the aerodynamic angles. The identification involves both flight dynamic relationships and data-driven state observer(s) based on neural techniques, which are deterministic once the training is completed. As this project will bring analytical sensors on board of civil aircraft as part of a redundant system for the very first time, design activities documented in this work have a particular focus on airworthiness certification aspects. At this maturity level, simulated data are used, real flight test data will be used in the next stages. Data collection is described both for the training and test aspects. Training maneuvers are defined aiming to excite all dynamic modes, whereas test maneuvers are collected aiming to validate results independently from the training set and all autopilot configurations. Results demonstrate that an alternate solution is possible enabling significant savings in terms of computational effort and lines of codes but they show, at the same time, that a better training strategy may be beneficial to cope with the new neural network architecture.
Infrared Image Super-Resolution Reconstruction Based on Quaternion and High-Order Overlapping Group Sparse Total Variation
Authors: Liu Xingguo , Chen Yingpin , Peng Zhenming , Wu Juan
Published: November 2019

Owing to the limitations of imaging principles and system imaging characteristics, infrared images generally have some shortcomings, such as low resolution, insufficient details, and blurred edges. Therefore, it is of practical significance to improve the quality of infrared images. To make full use of the information on adjacent points, preserve the image structure, and avoid staircase artifacts, this paper proposes a super-resolution reconstruction method for infrared images based on quaternion total variation and high-order overlapping group sparse. The method uses a quaternion total variation method to utilize the correlation between adjacent points to improve image anti-noise ability and reconstruction effect. It uses the sparsity of a higher-order gradient to reconstruct a clear image structure and restore smooth changes. In addition, we performed regularization by using the denoising method, alternating direction method of multipliers, and fast Fourier transform theory to improve the efficiency and robustness of our method. Our experimental results show that this method has excellent performance in objective evaluation and subjective visual effects.
A Weather Forecast Model Accuracy Analysis and ECMWF Enhancement Proposal by Neural Network
Authors: Frnda Jaroslav , Durica Marek , Nedoma Jan , Zabka Stanislav , Martinek Radek , Kostelansky Michal
Published: November 2019

This paper presents a neural network approach for weather forecast improvement. Predicted parameters, such as air temperature or precipitation, play a crucial role not only in the transportation sector but they also influence people’s everyday activities. Numerical weather models require real measured data for the correct forecast run. This data is obtained from automatic weather stations by intelligent sensors. Sensor data collection and its processing is a necessity for finding the optimal weather conditions estimation. The European Centre for Medium-Range Weather Forecasts (ECMWF) model serves as the main base for medium-range predictions among the European countries. This model is capable of providing forecast up to 10 days with horizontal resolution of 9 km. Although ECMWF is currently the global weather system with the highest horizontal resolution, this resolution is still two times worse than the one offered by limited area (regional) numeric models (e.g., ALADIN that is used in many European and north African countries). They use global forecasting model and sensor-based weather monitoring network as the input parameters (global atmospheric situation at regional model geographic boundaries, description of atmospheric condition in numerical form), and because the analysed area is much smaller (typically one country), computing power allows them to use even higher resolution for key meteorological parameters prediction. However, the forecast data obtained from regional models are available only for a specific country, and end-users cannot find them all in one place. Furthermore, not all members provide open access to these data. Since the ECMWF model is commercial, several web services offer it free of charge. Additionally, because this model delivers forecast prediction for the whole of Europe (and for the whole world, too), this attitude is more user-friendly and attractive for potential customers. Therefore, the proposed novel hybrid method based on machine learning is capable of increasing ECMWF forecast outputs accuracy to the same level as limited area models provide, and it can deliver a more accurate forecast in real-time.
Pre-Processing of Panchromatic Images to Improve Object Detection in Pansharpened Images
Authors: Sekrecka Aleksandra , Kedzierski Michal , Wierzbicki Damian
Published: November 2019

In recent years, many techniques of fusion of multi-sensors satellite images have been developed. This article focuses on examining and improvement the usability of pansharpened images for object detection, especially when fusing data with a high GSD ratio. A methodology to improve an interpretative ability of pansharpening results is based on pre-processing of the panchromatic image using Logarithmic-Laplace filtration. The proposed approach was used to examine several different pansharpening methods and data sets with different spatial resolution ratios, i.e., from 1:4 to 1:60. The obtained results showed that the proposed approach significantly improves an object detection of fused images, especially for imagery data with a high-resolution ratio. The interpretative ability was assessed using qualitative method (based on image segmentation) and quantitative method (using an indicator based on the Speeded Up Robust Features (SURF) detector). In the case of combining data acquired with the same sensor the interpretative potential had improved by a dozen or so per cent. However, for data with a high resolution ratio, the improvement was several dozen, or even several hundred per cents, in the case of images blurred after pansharpening by the classic method (with original panchromatic image). Image segmentation showed that it is possible to recognize narrow objects that were originally blurred and difficult to identify. In addition, for panchromatic images acquired by WorldView-2, the proposed approach improved not only object detection but also the spectral quality of the fused image.
Characteristics and Performance Evaluation of QZSS Onboard Satellite Clocks
Authors: Xie Wei , Huang Guanwen , Cui Bobin , Li Pingli , Cao Yu , Wang Haohao , Chen Zi , Shao Bo
Published: November 2019

In the Global Navigation Satellite System (GNSS) community, the Quasi-Zenith Satellite System (QZSS) is an augmentation system for users in the Asia-Pacific region. However, the characteristics and performance of four QZSS satellite clocks in a long-term scale are unknown at present. However, it is crucial to the positioning, navigation and timing (PNT) services of users, especially in Asia-Pacific region. In this study, the characteristics and performance variation of four QZSS satellite clocks, which including the phase, frequency, frequency drift, fitting residuals, frequency accuracy, periodic terms, frequency stability and short-term clock prediction, are revealed in detail for the first time based on the precise satellite clock offset products of nearly 1000 days. The important contributions are as follows: (1) It is detected that the times of phase and frequency jump are 2.25 and 1.5 for every QZSS satellite clock in one year. The magnitude of the frequency drift is about 10−18. The periodic oscillation of frequency drift of J01 and J02 satellite clocks is found. The clock offset model precision of QZSS is 0.33 ns. (2) The two main periods of QZSS satellite clock are 24 and 12 hours, which is the influence of the satellite orbit; (3) The frequency stability of 100, 1000 and 10,000 s are 1.98 × 10−13, 6.59 × 10−14 and 5.39 × 10−14 for QZSS satellite clock, respectively. The visible “bump” is found at about 400 s for J02 and J03 satellite clocks. The short-term clock prediction accuracy of is 0.12 ns. This study provides a reference for the state monitoring and performance variation of the QZSS satellite clock.
Prediction of the Levodopa Challenge Test in Parkinson’s Disease Using Data from a Wrist-Worn Sensor
Authors: Khodakarami Hamid , Ricciardi Lucia , Contarino Maria , Pahwa Rajesh , Lyons Kelly , Geraedts Victor , Morgante Francesca , Leake Alison , Paviour Dominic , De Angelis Andrea , Horne Malcolm
Published: November 2019

The response to levodopa (LR) is important for managing Parkinson’s Disease and is measured with clinical scales prior to (OFF) and after (ON) levodopa. The aim of this study was to ascertain whether an ambulatory wearable device could predict the LR from the response to the first morning dose. The ON and OFF scores were sorted into six categories of severity so that separating Parkinson’s Kinetigraph (PKG) features corresponding to the ON and OFF scores became a multi-class classification problem according to whether they fell below or above the threshold for each class. Candidate features were extracted from the PKG data and matched to the class labels. Several linear and non-linear candidate statistical models were examined and compared to classify the six categories of severity. The resulting model predicted a clinically significant LR with an area under the receiver operator curve of 0.92. This study shows that ambulatory data could be used to identify a clinically significant response to levodopa. This study has also identified practical steps that would enhance the reliability of this test in future studies.
The Design and Optimization of a Compressive-Type Vector Sensor Utilizing a PMN-28PT Piezoelectric Single-Crystal
Authors: Yeo Hong Goo , Choi Junhee , Jin Changzhu , Pyo Seonghun , Roh Yongrae , Choi Hongsoo
Published: November 2019

Underwater sensors that detect the distance and direction of acoustic sources are critical for surveillance monitoring and target detection in the water. Here, we propose an axial vector sensor that utilizes a small (~1 cm3) compressive-type piezoelectric accelerometer using piezoelectric single crystals. Initially, finite element analysis (FEA) was used to optimize the structure that comprised piezoelectric Pb(Mb1/3Nb2/3)O3-28%PbTiO3 single crystals on a tungsten seismic mass. The receiving voltage sensitivity (RVS) was enhanced through geometric optimization of the thickness and sensing area of the piezoelectric material and the seismic mass. The estimated maximum RVS of the optimized vector sensor was −212 dB. FEA simulations and practical measurements were used to verify the directivity of the vector sensor design, which exhibited a dipole pattern. The dipole beam pattern was used to obtain cardioid patterns using the simulated and measured results for comparison. The results clearly showed the feasibility of using the proposed piezoelectric single-crystal accelerometer for a compressive-type vector sensor.
Traffic Patrolling Routing Problem with Drones in an Urban Road System
Authors: Luo He , Zhang Peng , Wang Jiajie , Wang Guoqiang , Meng Fanhe
Published: November 2019

The remarkable development of various sensor equipment and communication technologies has stimulated many application platforms of automation. A drone is a sensing platform with strong environmental adaptability and expandability, which is widely used in aerial photography, transmission line inspection, remote sensing mapping, auxiliary communication, traffic patrolling, and other fields. A drone is an effective supplement to the current patrolling business in road traffic patrolling with complex urban buildings and road conditions and a limited ground perspective. However, the limited endurance of patrol drones can be directly solved by vehicles that cooperate with drones on patrolling missions. In this paper, we first proposed and studied the traffic patrolling routing problem with drones (TPRP-D) in an urban road system. Considering road network equations and the heterogeneity of patrolling tasks in the actual patrolling process, we modeled the problem as a double-layer arc routing problem (DL-ARP). Based on graph theory and related research work, we present the mixed integer linear programming formulations and two-stage heuristic solution approaches to solve practical-sized problems. Through analysis of numerical experiments, the solution method proposed in this paper can quickly provide an optimal path planning scheme for different test sets, which can save 9%–16% of time compared with traditional vehicle patrol. At the same time, we analyze several relevant parameters of the patrol process to determine the effect of coordinated traffic patrol. Finally, a case study was completed to verify the practicability of the algorithm.
The Verhulst-Like Equations: Integrable OΔE and ODE with Chaotic Behavior
Authors: Andrianov Igor , Starushenko Galina , Kvitka Sergey , Khajiyeva Lelya
Published: November 2019

In this paper, we study various variants of Verhulst-like ordinary differential equations (ODE) and ordinary difference equations (O Δ E). Usually Verhulst ODE serves as an example of a deterministic system and discrete logistic equation is a classic example of a simple system with very complicated (chaotic) behavior. In our paper we present examples of deterministic discretization and chaotic continualization. Continualization procedure is based on Padé approximants. To correctly characterize the dynamics of obtained ODE we measured such characteristic parameters of chaotic dynamical systems as the Lyapunov exponents and the Lyapunov dimensions. Discretization and continualization lead to a change in the symmetry of the mathematical model (i.e., group properties of the original ODE and O Δ E). This aspect of the problem is the aim of further research.
Parameter Optimization for Computer Numerical Controlled Machining Using Fuzzy and Game Theory
Authors: Chuang Kai-Chi , Lan Tian-Syung , Zhang Lie-Ping , Chen Yee-Ming , Dai Xuan-Jun
Published: November 2019

Under the strict restrictions of international environmental regulations, how to reduce environmental hazards at the production stage has become an important issue in the practice of automated production. The precision computerized numerical-controlled (CNC) cutting process was chosen as an example of this, while tool wear and cutting noise were chosen as the research objectives of CNC cutting quality. The effects of quality optimizing were verified using the depth of cut, cutting speed, feed rate, and tool nose runoff as control parameters and actual cutting on a CNC lathe was performed. Further, the relationships between Fuzzy theory and control parameters as well as quality objectives were used to define semantic rules to perform fuzzy quantification. The quantified output value was introduced into game theory to carry out the multi-quality bargaining game. Through the statistics of strategic probability, the strategy with the highest total probability was selected to obtain the optimum plan of multi-quality and multi-strategy. Under the multi-quality optimum parameter combination, the tool wear and cutting noise, compared to the parameter combination recommended by the cutting manual, was reduced by 23% and 1%, respectively. This research can indeed ameliorate the multi-quality cutting problem. The results of the research provided the technicians with a set of all-purpose economic prospective parameter analysis methods in the manufacturing process to enhance the international competitiveness of the automated CNC industry.
teatro de sombras, una estrategia pedagógica para el manejo de las expresiones y comunicaciones entre estudiantes
Authors: Medinaceli Cruz Patricia
Published: November 2019

El artículo tiene como propósito dar a conocer la utilización del teatro de sombras como estrategia pedagógica para el desarrollo de capacidades expresivas comunicativas en estudiantes de quinto grado de educación primaria comunitaria vocacional. La metodología empleada fue a través de la investigación proyectiva debido a que se dio para resolver una situación problemática diagnosticada, el diseño usado fue de campo. Los resultados enmarcados fueron la consideración y la ampliación de los procesos de capacitación de los docentes con relación a las actividades dentro del aula, obtenidos por parte de los alumnos. Por lo que se consideró importante señalar la creación y elaboración de un modelo enmarcado en los lineamientos del Enfoque Comunicativo en el teatro. Para finalizar se pretendió dar respuesta a los problemas y necesidades que se producen durante el proceso de enseñanza y aprendizaje presentes en este estudio.
BAITUL MAL WAT TAMWIL KOPERASI MIKRO SYARIAH UNTUK MENSEJAHTERAKAN MASYARAKAT KELAS BAWAH
Authors: Mahfudz Mahfudz
Published: November 2019

BMT merupakan salah satu jenis lembaga keuangan bukan bank yang bergerak dalam skala mikro sebagaimana koperasi simpan pinjam (KSP). Badan hukum adalah koperasi, karena itu secara otomatis dibawah pembinaan Kementerian Koperasi dan Usaha Kecil dan Menengah. Dengan demikian, peraturan yang mengikat BMT juga dari kementerian ini. BMT lebih dari sekedar lembaga keuangan yang memiliki visi danmisi bagi perkembangan ekonomi syariah di Indonesia, tetapi juga berorientasi pada pemberdayaan ekonomi masyarakat serta kalangan usaha kecil dan menengah. Berdasarkan hal tersebut, BMT perlu memaksimalkan peran dan eksistensinya ke depan, khususnya ketika memasuki era pasar bebas. Persaingan usaha dan iklim ekonomi pada era pasar bebas akan menjadi daya tarik dan tantangan baru yang berat bagi BMT untuk menjadi lembaga keuangan mitra usaha kecil dan menengah. BMT perlu merestrukturisasi kelembagaannya dan mengoptimalkan perannya dalam membantu masyarakat dalam membangun ekonomi umat.
Kepribadian Sebelum Dan Setelah Perubahan Pada Tokoh Utama Haruki Shiga Dalam Novel Kimi No Suizou Wo Tabetai Karya Sumino Yoru
Authors: Firdaus Muhammad Dena
Published: November 2019

Abstrak

 

Penelitian ini bertujuan untuk mengetahui kepribadian sebelum dan setelah mengalami perubahan pada tokoh utama Haruki Shiga dalam novel Kimi No Suizou Wo Tabetai karya Sumino Yoru. Metode penelitian yang digunakan oleh penulis yaitu metode deskriptif analisis pada tokoh dengan pendekatan psikologi sastra. Teori yang digunakan pada penelitian ini yaitu teori tentang penokohan dan plot dengan cara menggunakan metode penokohan yaitu metode langsung (telling) dan metode tidak langsung (showing) untuk mengidentifikasi kepribadian sebelum dan setelah perubahan tokoh utama Haruki Shiga dalam novel Kimi No Suizou Wo Tabetai karya Sumino Yoru. Data yang menjadi objek penelitian berupa kutipan-kutipan penokohan pada Haruki yang menggambarkan kepribadian tokoh Haruki sebelum mengalami perubahan kepribadian dan setelah mengalami perubahan kepribadian. Hasil dari kepribadian tokoh utama Haruki sebelum mengalami perubahan kepribadian yaitu adanya sifat yang tertutup, acuh tak acuh dan pemalu. Sedangkan hasil dari kepribadian tokoh utama Haruki setelah mengalami perubahan yaitu lebih peduli dan lebih membuka diri. Kesimpulan dari penelitian ini yaitu dalam meneliti kepribadian sebelum dan setelah perubahan tokoh utama dapat menggunakan metode penokohan supaya mendapatkan hasil secara langsung yang dilihat dari sifat tokoh utama dan plot dalam cerita.  

 

Kata Kunci : Novel, Metode langsung dan tidak langsung

 

Abstract

 

This study aims to determine the personality before and after experiencing a change in the main character Haruki Shiga in the novel Kimi No Suizou Wo Tabetai by Sumino Yoru. The research method used by the author is a descriptive method of analysis of figures with a literary psychology approach. The theory used in this research is the theory of characterizations and plots by using the characterization method, namely the direct method (telling) and the indirect method (showing) to identify the personality before and after the change of the main character Haruki Shiga in Kimi's No Suizou Wo Tabetai novel by Sumino Yoru The data are the object of research in the form of characterizations in Haruki characterizations that describe the personality of Haruki's character before experiencing changes in personality and after experiencing changes in personality. The results of the personality of the main character Haruki before experiencing personality changes are the nature of being closed, indifferent and shy . While the results of the personality of the main character Haruki after undergoing change are more caring and more open. The conclusion of this research is in examining the personality before and after the change of the main character can use the characterization method in order to get results directly as seen from the character's main character and plot in the story.

 

Keywords : Novel, telling method and showing method