bluuebunny/crossref_metadata_2025 huggingface dataset:
Entropy-Based Semi-Fragile Watermarking of Remote Sensing Images in the Wavelet Domain
Authors: Serra-Ruiz Jordi , Qureshi Amna , Megías David
Published: August 2019

This article presents a semi-fragile image tampering detection method for multi-band images. In the proposed scheme, a mark is embedded into remote sensing images, which have multiple frequential values for each pixel, applying tree-structured vector quantization. The mark is not embedded into each frequency band separately, but all the spectral values (known as signature) are used. The mark is embedded in the signature as a means to detect if the original image has been forged. The image is partitioned into three-dimensional blocks with varying sizes. The size of these blocks and the embedded mark is determined by the entropy of each region. The image blocks contain areas that have similar pixel values and represent smooth regions in multispectral or hyperspectral images. Each block is first transformed using the discrete wavelet transform. Then, a tree-structured vector quantizer (TSVQ) is constructed from the low-frequency region of each block. An iterative algorithm is applied to the generated trees until the resulting tree fulfils a requisite criterion. More precisely, the TSVQ tree that matches a particular value of entropy and provides a near-optimal value according to Shannon’s rate-distortion function is selected. The proposed method is shown to be able to preserve the embedded mark under lossy compression (above a given threshold) but, at the same time, it detects possibly forged blocks and their positions in the whole image. Experimental results show how the scheme can be applied to detect forgery attacks, and JPEG2000 compression of the images can be applied without removing the authentication mark. The scheme is also compared to other works in the literature.
Three-Dimensional Resource Allocation in D2D-Based V2V Communication
Authors: Khan Usman Ali , Lee Sang Sun
Published: August 2019

Device-to-Device (D2D) communication is the major enabler of Vehicle-to-Everything communication in 3rd Generation Partnership Project (3GPP) Release 14. The user equipment/device can engage either in direct communication with the infrastructure, use a relay node, or it can communicate directly with another device with or without infrastructure support. The user equipment can be either a hand-held cellular device or a moving vehicle. The coexistence of cellular user equipment with the vehicular user equipment imposes different Quality of Service (QOS) requirements due to the rapid mobility of the vehicles and interference. Resource allocation is an important task by which the user equipment is allocated the required resources based on different QOS parameters. In this paper, we introduced the case of three types of users which share uplink resources: two types of vehicular users, and a third user that acts as a handheld cellular phone, which is nearly static. By keeping in mind, the differential QOS requirements for the three types of users, we have calculated the optimum power and then applied a 3-dimensional graph-based matching and hypergraph coloring based resource block (RB) allocation.
Impact of Video Compression and Multimodal Embedding on Scene Description
Authors: Lee Jin Young
Published: August 2019

Scene description refers to the automatic generation of natural language descriptions from videos. In general, deep learning-based scene description networks utilize multimodalities, such as image, motion, audio, and label information, to improve the description quality. In particular, image information plays an important role in scene description. However, scene description has a potential issue, because it may handle images with severe compression artifacts. Hence, this paper analyzes the impact of video compression on scene description, and then proposes a simple network that is robust to compression artifacts. In addition, a network cascading more encoding layers for efficient multimodal embedding is also proposed. Experimental results show that the proposed network is more efficient than conventional networks.
Triple Notches Bandstop Microstrip Filter Based on Archimedean Spiral Electromagnetic Bandgap Structure
Authors: Zheng Xuemei , Jiang Tao
Published: August 2019

With the development of artificial electromagnetic structures, defective grounding structures (DGS), defective microstrip structures (DMS), and electromagnetic bandgap (EBG) have been widely used in the design of microstrip filters. In this paper, a triple notches ultra wideband bandstop microstrip filter based on Archimedean spiral electromagnetic bandgap structure (ASEBG) structure is proposed. Firstly, the equivalent circuit of ASEBG is analyzed, and L and C values are extracted by using Advanced Design System (ADS). Secondly, the correctness of the lumped parameter model is verified by comparing the High Frequency Structure Simulator (HFSS) simulation results with the measured results. Finally, the influence of ASEBG structure parameters on resonant performance is analyzed by HFSS simulation, and the filter parameters are further optimized. By coupling ASEBG structure to existing double notch microstrip filters, a triple notches ultra wideband bandstop microstrip filter is realized. This method can also be used in the design of other microstrip devices with stopband characteristics. The three bandgap center frequencies of the proposed triple notches ultra wideband bandstop microstrip filter are 3.5, 5.2, and 7.4 GHz, respectively. The corresponding maximum attenuation of the three stopbands is 33.6, 24.8, and 21.7 dB, respectively.
Comparative Analysis of FPGA-Based Pair-HMM Accelerator Structures
Authors: Wang Pengfei , Lei Yuanwu , Dou Yong
Published: August 2019

As one of the most important and computationally-intensive parts in bioinformatics analysis, the Pair Hidden Markov Model (Pair-HMM) forward algorithm is widely recognized and has great potential. Therefore, it is important to accelerate the process of this algorithm. There are various approaches to accelerate Pair-HMM, especially the accelerators stemmed from the Field Programmable Gate Array (FPGA) due to the highly-customizable on-chip resources and deep pipeline potential available to the designer. In this paper, we focus on the FPGA-based accelerators for the Pair-HMM forward algorithm proposed in recent years. The non-cooperation structure, which was proposed in our previous work, is compared with the Systolic Array (SA) structure and PE ring structure in the structure characteristics, calculation mode, computational efficiency, and storage requirement. We build an analysis model to evaluate the performance of the ring structure and our non-cooperative structure. Furthermore, based on this, we provide a detailed analysis of the characteristics of structures of different accelerators and of the selection of a suitable structure for different scenarios. Based on the non-cooperative PE structure, we design a new chain topology for the accelerator. Experimental results show that our non-cooperation structure is superior to the other structures in performance and execution efficiency, and our new topology improves the performance of the accelerator. Finally, we propose some ideas about the improvement of the non-cooperative structure accelerator for future work.
Passive Current Control Design for MMC in HVDC Systems through Energy Reshaping
Authors: Sang Yiyan , Yang Bo , Shu Hongchun , An Na , Zeng Fang , Yu Tao
Published: August 2019

The complexity of the internal dynamics of a modular multi-level converter (MMC) has raised severe issues for designing corresponding controllers. The existing MMC cascaded control strategies, based on classical linear control theory, require a relatively complex structure to achieve control objectives and the parameter tuning processes during the corresponding controller design are normally difficult to solve for the highly non-linear systems with highly coupled states in MMC. On account of this, advanced controllers are required for the regulation tasks of MMC. Passivity is introduced into the MMC control system by the passive control (PC) proposed in this paper. PC can provide an extra damping effect to help save energy through utilizing passivity in the system. A controllable de-coupled form is achieved by passivation of the output calculation. Hence, well-tuned controllers can be designed and employed to effectively regulate the output current and inner differential currents of the MMC under system operating point variation. Simulation results yield numerical data that show significantly improved steady-state and transient-state performances with greatly reduced control costs.
Dynamic Deep Forest: An Ensemble Classification Method for Network Intrusion Detection
Authors: Hu Bo , Wang Jinxi , Zhu Yifan , Yang Tan
Published: August 2019

Network Intrusion Detection System (NIDS) is one of the key technologies to prevent network attacks and data leakage. In combination with machine learning, intrusion detection has achieved great progress in recent years. However, due to the diversity of intrusion types, the representation learning ability of the existing models is still deficient, which limits the further improvement of the detection performance. Meanwhile, with the increasing of model complexity, the training time becomes longer and longer. In this paper, we propose a Dynamic Deep Forest method for network intrusion detection. It uses cascade tree structure to strengthen the representation learning ability. At the same time, the training process is accelerated due to small-scale parameter fitting and dynamic level-growing strategy. The proposed Dynamic Deep Forest is a tree-based ensemble approach and consists of two parts. The first part, Multi-Grained Traversing, uses selectors to pick up features as complete as possible. The selectors are constructed dynamically so that the training process will stop as soon as the optimal feature combination is found. The second part, Cascade Forest, introduces level-by-level tree structures. It has fewer hyper-parameters and follows a dynamic level-growing strategy to reduce model complexity. In experiments, we evaluate our model on network intrusion dataset KDD’99. The results show that the Dynamic Deep Forest method obtains higher recall and precision through a short time of model training. Moreover, the Dynamic Deep Forest method has lower risk of misclassification, which is more stable and reliable in a real network environment.
Power Efficiency Improvement of Three-Phase Split-Output Inverter Using Magnetically Coupled Inductor Switching
Authors: Yang Min-Kwon , Choi Woo-Young
Published: August 2019

The conventional three-phase split-output inverter (SOI) has been used for grid-connected applications because it does not require dead time and has no shoot-through problems. Recently, the conventional inverter uses the silicon carbide (SiC) schottky diodes for the freewheeling diodes because of its no reverse-recovery problem. Nevertheless, in a practical design, the SiC schottky diodes suffer from current overshoots and voltage oscillations. These overshoots and oscillations result in switching-power losses, decreasing the power efficiency of the inverter. To alleviate this drawback, we present a three-phase SOI using magnetically coupled inductor switching technique. The magnetically coupled inductor switching technique uses one auxiliary diode and coupled inductor for each switching leg in the three-phase SOI. By the operation of the coupled inductor, the main diode current is shifted to the auxiliary diode without the reverse-recovery process. The proposed inverter reduces switching-power losses by alleviating current overshoots and voltage oscillations of SiC schottky diodes. It achieves higher power efficiency than the conventional inverter. We discuss experimental results for a 1.0 kW prototype inverter to verify the performance of the proposed inverter.
Ripple Vector Cancellation Modulation Strategy for Single-Phase Quasi-Z-Source Inverter
Authors: Tang Yufeng , Li Zhiyong , Chen Yougen , Wei Renyong
Published: August 2019

The double-frequency (2ω) power flows through the DC side of the single-phase quasi-Z-source inverter (QZSI) leads to the 2ω voltage ripple of capacitors and 2ω current ripple of inductors. This paper proposes a ripple vector cancellation modulation strategy (RVCMS) based on the thought of ripple vector cancellation. By analyzing the mechanism of ripple generation and transmission, we can obtain a variation of a shoot-through duty cycle to generate a compensated 2ω ripple used to cancel the 2ω current ripple of inductors caused by the 2ω ripple of DC link current, and the 2ω compensated variation of a shoot-through duty cycle with a specific amplitude and phase is added to the constant shoot-through duty cycle. Finally, simulation and experimental results demonstrate the correctness and effectiveness of the proposed modulation strategy for the single-phase QZSI.
A Cradle-to-Grave Multi-Pronged Methodology to Obtain the Carbon Footprint of Electro-Intensive Power Electronic Products
Authors: Quintana-Pedraza Giovanni Andrés , Vieira-Agudelo Sara Cristina , Muñoz-Galeano Nicolás
Published: August 2019

This paper proposes the application of a cradle-to-grave multi-pronged methodology to obtain a more realistic carbon footprint (CF) estimation of electro-intensive power electronic (EIPE) products. The literature review shows that methodologies for establishing CF have limitations in calculation or are not applied from the conception (cradle) to death (grave) of the product; therefore, this paper provides an extended methodology to overcome some limitations that can be applied in each stage during the life cycle assessment (LCA). The proposed methodology is applied in a cradle-to-grave scenario, being composed of two approaches of LCA: (1) an integrated hybrid approach based on an economic balance and (2) a standard approach based on ISO 14067 and PAS 2050 standards. The methodology is based on a multi-pronged assessment to combine conventional with hybrid techniques. The methodology was applied to a D-STATCOM prototype which contributes to the improvement of the efficiency. Results show that D-STATCOM considerably decreases CF and saves emissions taken place during the usage stage. A comparison was made between Sweden and China to establish the environmental impact of D-STATCOM in electrical networks, showing that saved emissions in the life cycle of D-STATCOM were 5.88 and 391.04 ton CO2eq in Sweden and China, respectively.
Development of Thermal Comfort-Based Controller and Potential Reduction of the Cooling Energy Consumption of a Residential Building in Kuwait
Authors: Park Jaesung , Kim Taeyeon , Lee Chul-sung
Published: August 2019

In Kuwait, where the government subsidizes approximately 95% of residential electricity bills, most of the country’s energy consumption is for residential use. In particular, air-conditioning (AC) systems for cooling, which are used throughout the year, are responsible for residential electric energy consumption. This study aimed to reduce the amount of energy consumed for cooling purposes by developing a thermal comfort-based controller. Our study commenced by using a simulation model to investigate the possibility of energy reduction when using the predicted mean vote (PMV) for optimal control. The result showed that control optimization would enable the cooling energy consumption to be reduced by 33.5%. The influence of six variables on cooling energy consumption was then analyzed to develop a thermal comfort-based controller. The analysis results showed that the indoor air temperature was the most influential factor, followed by the mean radiant temperature, the metabolic rate, and indoor air velocity. The thermal comfort-based controller-version 1 (TCC-V1) was developed based on the analysis results and experimentally evaluated to determine the extent to which the use of the controller would affect the energy consumed for cooling. The experiments showed that the implementation of TCC-V1 control made it possible to reduce the electric energy consumption by 39.5% on a summer representative day. The results of this study indicate that it is possible to improve indoor thermal comfort while saving energy by using the thermal comfort-based controller in residential buildings in Kuwait.
A Discussion on the Effective Ventilation Distance in Dead-End Tunnels
Authors: García-Díaz Manuel , Sierra Carlos , Miguel-González Celia , Pereiras Bruno
Published: August 2019

Forcing ventilation is the most widely used system to remove noxious gases from a working face during tunnel construction. This system creates a region near the face (dead zone), in which ventilation takes place by natural diffusion, rather than being directly swept by the air current. Despite the extensive use of this system, there is still a lack of parametrical studies discerning the main parameters affecting its formation as well as a correlation indicating their interrelation. With this aim in mind, computational fluid dynamics (CFDs) models were used to define the dead zone based on the airflow field patterns. The formation of counter vortices, which although maintain the movement of air hinder its renewal, allowed us to discuss the old paradigm of defining the dead zone as a very low air velocity zone. Moreover, further simulations using a model of air mixed with NO2 offered an idea of NO2 concentrations over time and distance to the face, allowing us to derive at a more realistic equation for the effective distance. The results given here confirm the degree of conservativism of present-day regulations and may assist engineers to improve ventilation efficiency in tunnels by modifying the duct end-to-face distance.
Cool Roof Impact on Building Energy Need: The Role of Thermal Insulation with Varying Climate Conditions
Authors: Piselli Cristina , Pisello Anna Laura , Saffari Mohammad , de Gracia Alvaro , Cotana Franco , Cabeza Luisa F.
Published: August 2019

Cool roof effectiveness in improving building thermal-energy performance is affected by different variables. In particular, roof insulation level and climate conditions are key parameters influencing cool roofs benefits and whole building energy performance. This work aims at assessing the role of cool roof in the optimum roof configuration, i.e., combination of solar reflectance capability and thermal insulation level, in terms of building energy performance in different climate conditions worldwide. To this aim, coupled dynamic thermal-energy simulation and optimization analysis is carried out. In detail, multi-dimensional optimization of combined building roof thermal insulation and solar reflectance is developed to minimize building annual energy consumption for heating–cooling. Results highlight how a high reflectance roof minimizes annual energy need for a small standard office building in the majority of considered climates. Moreover, building energy performance is more sensitive to roof solar reflectance than thermal insulation level, except for the coldest conditions. Therefore, for the selected building, the optimum roof typology presents high solar reflectance capability (0.8) and no/low insulation level (0.00–0.03 m), except for extremely hot or cold climate zones. Accordingly, this research shows how the classic approach of super-insulated buildings should be reframed for the office case toward truly environmentally friendly buildings.
PMU’s Behavior with Flicker-Generating Voltage Fluctuations: An Experimental Analysis
Authors: Castello Paolo , Muscas Carlo , Pegoraro Paolo , Sulis Sara
Published: August 2019

Phasor measurement units (PMUs), which are the key components of a synchrophasor-based wide area monitoring system (WAMS), were historically conceived for transmission networks. The current trend to extend the benefits of the synchrophasor technology to distribution networks requires the PMU to also provide trustworthy information in the presence of signals that can occur in a typical distribution grid, including the presence of severe power quality (PQ) issues. In this framework, this paper experimentally investigates the performance of PMUs in the presence of one of the most important PQ phenomena, namely the presence of voltage fluctuations that generate the disturbance commonly known as flicker. The experimental tests are based on an ad-hoc high-accuracy measurement setup, where the devices under test are considered as “black boxes” to be characterized in the presence of the relevant signals. Two simple indices are introduced for the comparison among the different tested PMUs. The results of the investigation highlight possible critical situations in the interpretation of the measured values and provide a support for both the design of a new generation of PMUs and the possible development of an updated synchrophasor standard targeted to distribution systems.
Towards a Shared Understanding of the Concept of Heritage in the European Context
Authors: Petti Luigi , Trillo Claudia , Makore Busisiwe Chikomborero Ncube
Published: August 2019

The purpose of this paper is to develop an understanding of commonalities and differences in the concept of cultural heritage in Europe. This was achieved through a comprehensive academic and non-academic literature review focused on different definitions and conceptualisations related to cultural heritage internationally and in the European context. This is complemented with a comparative study in three European countries. This paper frames cultural heritage using the foundation set up by the United Nations Educational, Scientific and Cultural Organisation (UNESCO). It further discusses the European actors involved in defining heritage today. Finally, it focuses on three European countries and verifies that they share an understanding of cultural heritage including classifications, categorisation and heritage values. Findings from the overall study show how the definition of cultural heritage across Europe is reasonably homogeneous, and this is confirmed by the analysis of the three chosen test case studies. This finding is relevant to policy makers as it allows the support of potential common frameworks for heritage management at the European level, including risk management and risk reduction common methodologies. Further studies will shed light on the implementation issues which may arise from the creation of a common European framework for cultural heritage management, with emphasis on risk management and risk reduction of cultural heritage.
Deterioration of World Heritage Cave Monument of Ajanta, India: Insights to Important Biological Agents and Environment Friendly Solutions
Authors: Singh Sunidhi , Dhyani Shalini , Kokate Piyush , Chakraborty Soumya , Nimsadkar Sagar
Published: August 2019

Heritage monuments across the world are affected by a variety of physical and biological stresses. Damage to heritage monuments due to insects and pests is growing with increasing anthropogenic pressure and changing climatic conditions. Cave monuments are habitats to microbes, algae, fungi, and insects, and are unique biodiversity sites due to their low temperature, little to no sunlight, and high moisture conditions. This study takes stock of available information on important factors that facilitate the growth of insect pests and degrade heritage monuments. Ajanta Caves, a UNESCO world heritage site in India, is a human marvel, important archaeological and heritage site of immense cultural and historic values. The present paper is an attempt to understand a variety of stresses and factors with a focus on insect pests that have substantially affected Ajanta cave paintings in the last few decades. The study also provides information on available approaches for damage control including the need for an integrated insect pest management for protecting cave monuments against rapid degradation across the country in general and Ajanta caves in particular. A light-based approach is the key highlight of the study that can be used as an effective and efficient approach to protect archaeological sites especially cave paintings from insect pests without disturbing the pollinator diversity and surrounding environment.
Accelerometer-Assessed Physical Activity and Sedentary Time at School for Children with Disabilities: Seasonal Variation
Authors: Sit Cindy H.P. , Huang Wendy Y. , Yu Jane J. , McKenzie Thomas L.
Published: August 2019

Schools are salient locations for children with disabilities to accrue physical activity (PA) and to diminish sedentary time (ST). We examined seasonal variation in accelerometer-assessed PA and ST among children with disabilities during the school day in three school settings (physical education (PE) lessons, recess and lunchtime). Children (n = 270) from 13 special schools for those with five disability types (visual impairments, hearing impairments, physical disabilities, intellectual disabilities (ID), and social development problems) participated. Their PA and ST were assessed during three winter and three summer school days using accelerometry. Linear mixed models were performed to determine seasonal variation in the proportion of time they spent in moderate-to-vigorous physical activity (MVPA) and ST in the three settings. On average, the children spent 4.5% (18.6 min) and 4.0% (15.6 min) in MVPA at school during winter and summer days, respectively. They were more physically active during winter (especially during recess and lunchtime), but there were no seasonal differences for ST. Thus, children’s year-round engagement in PA needs to be promoted, especially during summer.
Risk of Dementia in Patients with Leptospirosis: A Nationwide Cohort Analysis
Authors: Chiu Chun-Hsiang , Chen Po-Chung , Wang Ying-Chuan , Lin Cheng-Li , Lee Feng-You , Wu Chia-Chang , Chang Kuang-Hsi
Published: August 2019

Background: Studies have linked some bacterial infections with an increased likelihood for development of dementia. However, there is a paucity of data on the relationship between dementia and leptospirosis. In view of this, we conducted a retrospective cohort study to determine whether leptospirosis is a risk factor for dementia. Methods: Data were collected from the Taiwan National Health Insurance Research Databases (2000–2010) to investigate the incidence of and risk factors for dementia in patients with leptospirosis. Patients with leptospirosis who did not have a history of dementia were enrolled in the study. For each leptospirosis patient, four controls were randomly selected after frequency matching of age, sex, and index date. Cox proportional hazard regression models were used for the analyses of dementia risk. Results: A greater risk of dementia was observed in the leptospirosis cohort than in the non-leptospirosis cohort both in patients without any comorbidity (adjusted HR (aHR) = 1.23, 95% CI = 1.06–1.43) and with a comorbidity (aHR = 2.06, 95% CI = 1.7–2.5). Compared with the non-leptospirosis cohort without these comorbidities, the leptospirosis cohort with ≥2 comorbidities exhibited a significantly increased risk of dementia (aHR = 6.11, 95% CI = 3.15–11.9), followed by those with any one comorbidity (adjusted HR = 3.62, 95% CI = 1.76–7.46). Conclusions: Patients with leptospirosis were at a 1.89-fold greater risk of subsequent dementia, but potential genetic susceptibility bias in the study group is a major confound.
Physical Condition Factors that Predict a Better Quality of Life in Women with Fibromyalgia
Authors: Sempere-Rubio Núria , Aguilar-Rodríguez Marta , Inglés Marta , Izquierdo-Alventosa Ruth , Serra-Añó Pilar
Published: August 2019

What physical qualities can predict the quality of life (QoL) in women with fibromyalgia (FM)? QoL is a very complex outcome affected by multiple comorbidities in people with fibromyalgia. This study aims to determine which physical qualities can predict the quality of life in women with FM. Also, a comparison between the physical qualities of women with FM and healthy counterparts was conducted. In total, 223 women participated in this cross-sectional study, 123 with FM, with ages ranging between 45 and 70 years. The study was conducted at several fibromyalgia associations and specialized medical units. QoL was measured as the main outcome. In addition, functional capacity, muscular strength, maintenance of thoracic posture, postural control, flexibility, pain threshold, and anxiety were measured. Prediction of the QoL was conducted with multiple linear regression analysis and comparison between groups, using the Mann–Whitney U test. There were significant differences between groups in all the variables measured (p < 0.01). The multiple linear regression model showed that factors influencing QoL in women with FM for all the variables measured were functional capacity, handgrip strength and bicep strength, maintenance of thoracic posture, pain threshold, and anxiety (R2 = 0.53, p < 0.05). To conclude, women with FM show a significantly lower QoL than their healthy counterparts, and the factors that predict their perceived QoL are functional capacity, muscular strength, postural maintenance, pain threshold, and anxiety.
Foreign Direct Investment Dynamic Performance with Low-Carbon Influence: A Provincial Comparative Application in China
Authors: Zhao Xinna , Tang Yuhang , Lu Milin , Zhang Xiaohong
Published: August 2019

Cross-border capital flows have been a major force driving economic globalization. Foreign direct investment (FDI) plays a decisive role in seeking out market technology brands and enhancing the global competitiveness among international inflows. With the requirement of economic development, this paper focused on a performance evaluation of FDI in China. However, because of the planned transformation to a market economy in China, FDI has been promoted with a regional cascade structure. Similar to the development track of the Chinese economy, it is necessary to evaluate FDI quality more than purely quantity from a provincial point of view. Therefore, this paper evaluated the Chinese provincial FDI total factor productivity using the dynamic Malmquist model. In contrast to traditional evaluations, this paper focused on inter-temporal influence in FDI performance evaluation. To understand the inter-temporal effects, physical capital stock was defined as a dynamic variable in FDI sustainability performance. Additionally, with the pressure to reduce emissions, energy consumption was also considered during the evaluation. The empirical results revealed that the dynamic variable is the bottleneck in FDI performance for most Chinese provinces. It is only efficient in a few municipalities and provinces, such as Shanghai and Guangdong. Additionally, energy conservation was more efficient in the performance evaluation of eastern regions in China.
A Filtering-Based Approach for Improving Crowdsourced GNSS Traces in a Data Update Context
Authors: Ivanovic Stefan S. , Olteanu-Raimond Ana-Maria , Mustière Sébastien , Devogele Thomas
Published: August 2019

Traces collected by citizens using GNSS (Global Navigation Satellite System) devices during sports activities such as running, hiking or biking are now widely available through different sport-oriented collaborative websites. The traces are collected by citizens for their own purposes and frequently shared with the sports community on the internet. Our research assumption is that crowdsourced GNSS traces may be a valuable source of information to detect updates in authoritative datasets. Despite their availability, the traces present some issues such as poor metadata, attribute incompleteness and heterogeneous positional accuracy. Moreover, certain parts of the traces (GNSS points composing the traces) are results of the displacements made out of the existing paths. In our context (i.e., update authoritative data) these off path GNSS points are considered as noise and should be filtered. Two types of noise are examined in this research: Points representing secondary activities (e.g., having a lunch break) and points representing errors during the acquisition. The first ones we named secondary human behaviour (SHB), whereas we named the second ones outliers. The goal of this paper is to improve the smoothness of traces by detecting and filtering both SHB and outliers. Two methods are proposed. The first one allows for the detection secondary human behaviour by analysing only traces geometry. The second one is a rule-based machine learning method that detects outliers by taking into account the intrinsic characteristics of points composing the traces, as well as the environmental conditions during traces acquisition. The proposed approaches are tested on crowdsourced GNSS traces collected in mountain areas during sports activities.
A Sightseeing Support System Using Augmented Reality and Pictograms within Urban Tourist Areas in Japan
Authors: Sasaki Ryo , Yamamoto Kayoko
Published: August 2019

Though tourists can search for necessary information on the internet while sightseeing, it takes effort and is inconvenient to obtain available information related to specific sightseeing spots among the copious amount of information online. Targeting urban tourist areas in Japan, the present study aims to develop a system that can provide guidance and information concerning sightseeing spots by integrating location-based augmented reality (AR) and object-recognition AR and by using pictograms. The system enables users to efficiently obtain the directions to sightseeing spots and nearby facilities within urban tourist areas and sightseeing spot information. Additionally, the city of Chofu in the metropolis of Tokyo was selected as the operation target area. The operation of the system was conducted for 1 month, targeting those inside and outside the operation target area, and a web questionnaire survey was conducted with a total number of 50 users. From the evaluation results of the web questionnaire survey, the usefulness of the original functions of integrating location-based AR and object-recognition AR and by using pictograms, as well as of the entire system, was analyzed. From the results of the access analysis of users’ log data, it is expected that users will further utilize each function. Additionally, it is evident that location-based AR was used more often than was object-recognition AR.
Parameters for Optoperforation-Induced Killing of Cancer Cells Using Gold Nanoparticles Functionalized With the C-terminal Fragment of Clostridium Perfringens Enterotoxin
Authors: Becker Annegret , Lehrich Tina , Kalies Stefan , Heisterkamp Alexander , Ngezahayo Anaclet
Published: August 2019

Recently, we used a recombinant produced C-terminus (D194-F319) of the Clostridium perfringens enterotoxin (C-CPE) to functionalize gold nanoparticles (AuNPs) for a subsequent specific killing of claudin expressing tumor cells using the gold nanoparticle-mediated laser perforation (GNOME-LP) technique. For a future in vivo application, it will be crucial to know the physical parameters and the biological mechanisms inducing cell death for a rational adaptation of the system to real time situation. Regarding the AuNP functionalization, we observed that a relationship of 2.5 × 10−11 AuNP/mL to 20 µg/mL C-CPE maximized the killing efficiency. Regardingphysical parameters, a laser fluence up to 30 mJ/cm2 increased the killing efficiency. Independent from the applied laser fluence, the maximal killing efficiency was achieved at a scanning velocity of 5 mm/s. In 3D matrigel culture system, the GNOME-LP/C-CPE-AuNP completely destroyed spheroids composed of Caco-2 cells and reduced OE-33 cell spheroid formation. At the biology level, GNOME-LP/C-CPE-AuNP-treated cells bound annexin V and showed reduced mitochondria activity. However, an increased caspase-3/7 activity in the cells was not found. Similarly, DNA analysis revealed no apoptosis-related DNA ladder. The results suggest that the GNOME-LP/C-CPE-AuNP treatment induced necrotic than apoptotic reaction in tumor cells.
Molecular Subtyping and Prognostic Assessment Based on Tumor Mutation Burden in Patients with Lung Adenocarcinomas
Authors: Wang Changzheng , Liang Han , Lin Cong , Li Fuqiang , Xie Guoyun , Qiao Sitan , Shi Xulian , Deng Jianlian , Zhao Xin , Wu Kui , Zhang Xiuqing
Published: August 2019

The distinct molecular subtypes of lung cancer are defined by monogenic biomarkers, such as EGFR, KRAS, and ALK rearrangement. Tumor mutation burden (TMB) is a potential biomarker for response to immunotherapy, which is one of the measures for genomic instability. The molecular subtyping based on TMB has not been well characterized in lung adenocarcinomas in the Chinese population. Here we performed molecular subtyping based on TMB with the published whole exome sequencing data of 101 lung adenocarcinomas and compared the different features of the classified subtypes, including clinical features, somatic driver genes, and mutational signatures. We found that patients with lower TMB have a longer disease-free survival, and higher TMB is associated with smoking and aging. Analysis of somatic driver genes and mutational signatures demonstrates a significant association between somatic RYR2 mutations and the subtype with higher TMB. Molecular subtyping based on TMB is a potential prognostic marker for lung adenocarcinoma. Signature 4 and the mutation of RYR2 are highlighted in the TMB-High group. The mutation of RYR2 is a significant biomarker associated with high TMB in lung adenocarcinoma.
The Emerging Proteomic Research Facilitates in-Depth Understanding of the Biology of Honeybees
Authors: Altaye Solomon Zewdu , Meng Lifeng , Lu Yao , Li Jianke
Published: August 2019

Advances in instrumentation and computational analysis in proteomics have opened new doors for honeybee biological research at the molecular and biochemical levels. Proteomics has greatly expanded the understanding of honeybee biology since its introduction in 2005, through which key signaling pathways and proteins that drive honeybee development and behavioral physiology have been identified. This is critical for downstream mechanistic investigation by knocking a gene down/out or overexpressing it and being able to attribute a specific phenotype/biochemical change to that gene. Here, we review how emerging proteome research has contributed to the new understanding of honeybee biology. A systematic and comprehensive analysis of global scientific progress in honeybee proteome research is essential for a better understanding of research topics and trends, and is potentially useful for future research directions.
HSP-Target of Therapeutic Agents in Sepsis Treatment
Authors: Vulczak Anderson , Catalão Carlos Henrique Rocha , Freitas Luiz Alexandre Pedro de , Rocha Maria José Alves
Published: August 2019

Sepsis is a syndrome characterized by a dysregulated inflammatory response, cellular stress, and organ injury. Sepsis is the main cause of death in intensive care units worldwide, creating need for research and new therapeutic strategies. Heat shock protein (HSP) analyses have recently been developed in the context of sepsis. HSPs have a cytoprotection role in stress conditions, signal to immune cells, and activate the inflammatory response. Hence, HSP analyses have become an important focus in sepsis research, including the investigation of HSPs targeted by therapeutic agents used in sepsis treatment. Many therapeutic agents have been tested, and their HSP modulation showed promising results. Nonetheless, the heterogeneity in experimental designs and the diversity in therapeutic agents used make it difficult to understand their efficacy in sepsis treatment. Therefore, future investigations should include the analysis of parameters related to the early and late immune response in sepsis, HSP localization (intra or extracellular), and time to the onset of treatment after sepsis. They also should consider the differences in experimental sepsis models. In this review, we present the main results of studies on therapeutic agents in targeting HSPs in sepsis treatment. We also discuss limitations and possibilities for future investigations regarding HSP modulators.
CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA–Disease Associations
Authors: Xuan Ping , Sheng Nan , Zhang Tiangang , Liu Yong , Guo Yahong
Published: August 2019

It is well known that the unusual expression of long non-coding RNAs (lncRNAs) is closely related to the physiological and pathological processes of diseases. Therefore, inferring the potential lncRNA–disease associations are helpful for understanding the molecular pathogenesis of diseases. Most previous methods have concentrated on the construction of shallow learning models in order to predict lncRNA-disease associations, while they have failed to deeply integrate heterogeneous multi-source data and to learn the low-dimensional feature representations from these data. We propose a method based on the convolutional neural network with the attention mechanism and convolutional autoencoder for predicting candidate disease-related lncRNAs, and refer to it as CNNDLP. CNNDLP integrates multiple kinds of data from heterogeneous sources, including the associations, interactions, and similarities related to the lncRNAs, diseases, and miRNAs. Two different embedding layers are established by combining the diverse biological premises about the cases that the lncRNAs are likely to associate with the diseases. We construct a novel prediction model based on the convolutional neural network with attention mechanism and convolutional autoencoder to learn the attention and the low-dimensional network representations of the lncRNA–disease pairs from the embedding layers. The different adjacent edges among the lncRNA, miRNA, and disease nodes have different contributions for association prediction. Hence, an attention mechanism at the adjacent edge level is established, and the left side of the model learns the attention representation of a pair of lncRNA and disease. A new type of lncRNA similarity and a new type of disease similarity are calculated by incorporating the topological structures of multiple bipartite networks. The low-dimensional network representation of the lncRNA-disease pairs is further learned by the autoencoder based convolutional neutral network on the right side of the model. The cross-validation experimental results confirm that CNNDLP has superior prediction performance compared to the state-of-the-art methods. Case studies on stomach cancer, breast cancer, and prostate cancer further show the ability of CNNDLP for discovering the potential disease lncRNAs.
Telmisartan Lowers Elevated Blood Pressure in Psoriatic Mice without Attenuating Vascular Dysfunction and Inflammation
Authors: Wild Johannes , Schüler Rebecca , Knopp Tanja , Molitor Michael , Kossmann Sabine , Münzel Thomas , Daiber Andreas , Waisman Ari , Wenzel Philip , Karbach Susanne Helena
Published: August 2019

Background: Psoriasis is hallmarked by vascular dysfunction, arterial hypertension, and an increased risk for cardiovascular diseases. We have shown recently that skin-driven interleukin (IL)-17A expression promotes psoriasis-like disease in mice, and this is associated with vascular inflammation, vascular dysfunction, and hypertension. As an intensive risk-factor reduction is recommended for psoriasis patients, we aimed to elucidate the impact of the angiotensin II receptor type 1 (AT1) antagonist telmisartan in a mouse model of severe psoriasis-like skin disease. Methods and Results: Elevated blood pressure measured by tail-cuff plethysmography in mice with keratinocyte-specific IL-17A overexpression (K14-IL-17Aind/+ mice) was significantly reduced in response to telmisartan. Importantly, vascular dysfunction, as assessed by isometric tension studies of isolated aortic rings, vascular inflammation measured by flow cytometry analysis of CD45+CD11b+ immune cells, as well as the increased peripheral oxidative stress levels assessed by L-012-enhanced chemiluminescence were not attenuated by telmisartan treatment of K14-IL-17Aind/+ mice, nor was the persisting skin inflammation. Conclusion: We provide first evidence for an effective antihypertensive treatment in experimental psoriasis by AT1 blockade, but without any impact on vascular inflammation and dysfunction in our mouse model of severe psoriasis-like skin disease. This suggests that vascular function and inflammation in psoriasis might not be attenuated as long as skin inflammation persists.
Membrane Lipid Remodeling in Response to Salinity
Authors: Guo Qi , Liu Lei , Barkla Bronwyn J.
Published: August 2019

Salinity is one of the most decisive environmental factors threatening the productivity of crop plants. Understanding the mechanisms of plant salt tolerance is critical to be able to maintain or improve crop yield under these adverse environmental conditions. Plant membranes act as biological barriers, protecting the contents of cells and organelles from biotic and abiotic stress, including salt stress. Alterations in membrane lipids in response to salinity have been observed in a number of plant species including both halophytes and glycophytes. Changes in membrane lipids can directly affect the properties of membrane proteins and activity of signaling molecules, adjusting the fluidity and permeability of membranes, and activating signal transduction pathways. In this review, we compile evidence on the salt stress responses of the major membrane lipids from different plant tissues, varieties, and species. The role of membrane lipids as signaling molecules in response to salinity is also discussed. Advances in mass spectrometry (MS)-based techniques have largely expanded our knowledge of salt-induced changes in lipids, however only a handful studies have investigated the underlying mechanisms of membrane lipidome regulation. This review provides a comprehensive overview of the recent works that have been carried out on lipid remodeling of plant membranes under salt treatment. Challenges and future perspectives in understanding the mechanisms of salt-induced changes to lipid metabolisms are proposed.
THP-1 Cells and Pro-Inflammatory Cytokine Production: An In Vitro Tool for Functional Characterization of NOD1/NOD2 Antagonists
Authors: Jakopin Žiga , Corsini Emanuela
Published: August 2019

THP-1 cells express high levels of native functional nucleotide-binding oligomerization domain 1 (NOD1), NOD2, and Toll-like receptor 4 (TLR4) receptors, and have often been used for investigating the immunomodulatory effects of small molecules. We postulated that they would represent an ideal cell-based model for our study, the aim of which was to develop a new in vitro tool for functional characterization of NOD antagonists. NOD antagonists were initially screened for their effect on NOD agonist-induced interleukin-8 (IL-8) release. Next, we examined the extent to which the selected NOD antagonists block the NOD-TLR4 synergistic crosstalk by measuring the effect of NOD antagonism on tumor necrosis factor-α (TNF-α) secretion from doubly activated THP-1 cells. Overall, the results obtained indicate that pro-inflammatory cytokine secretion from THP-1 provides a valuable, simple and reproducible in vitro tool for functional characterization of NOD antagonists.