bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Contact Roughness Measurement in Sub-Micron Range by Considering Depolarization Effects
Authors: Pöller Franziska , Salazar Bloise Félix , Jakobi Martin , Wang Shengjia , Dong Jie , Koch Alexander W.
Published: May 2019

The characteristics of a surface, particularly the roughness, play an important role in different fields of the industry and have to be considered to ensure quality standards. Currently, there are numerous sophisticated methods for measuring surface roughness but plenty of them cause long-term damage because they are in contact with the sample. This article presents a non-contact method to accurately determine small surface roughnesses resulting from the consideration of the depolarization effects caused by the rough surface. This technique can be applied as an extension in various roughness measurements and improves the approach of Chandley’s technique, which does not take into account the depolarization of the light scattered by the sample. The experimental setup and the measurements are easy to perform. The essential component is a quarter wave plate, which is incorporated into a Michelson interferometer. With the resulting two different contrasts and the recorded intensities of the sample and the reference mirror, the surface roughness can be estimated straightforwardly. This article details the theoretical approach, followed by the experimental results and the corresponding uncertainties. The experimental results are compared with Chandley’s method. In order to have reference roughness values of the samples, measurements with a stylus profilometer and with a confocal microscope are performed and compared.
Autonomous Visual Perception for Unmanned Surface Vehicle Navigation in an Unknown Environment
Authors: Zhan Wenqiang , Xiao Changshi , Wen Yuanqiao , Zhou Chunhui , Yuan Haiwen , Xiu Supu , Zhang Yimeng , Zou Xiong , Liu Xin , Li Qiliang
Published: May 2019

Robust detection and recognition of water surfaces are critical for autonomous navigation of unmanned surface vehicles (USVs), since any none-water region is likely an obstacle posing a potential danger to the sailing vehicle. A novel water region visual detection method is proposed in this paper. First, the input image pixels are clustered into different regions and each pixel is assigned a label tag and a confidence value by adaptive multistage segmentation algorithm. Then the resulting label map and associated confidence map are fed into a convolutional neural network (CNN) as training samples to train the network online. Finally, the online trained CNN is used to segment the input image again but with greater precision and stronger robustness. Compared with other deep-learning image segmentation algorithms, the proposed method has two advantages. Firstly, it dispenses with the need of manual labeling training samples which is a costly and painful task. Secondly, it allows real-time online training for CNN, making the network adaptive to the navigational environment. Another contribution of this work relates to the training process of neuro network. An effective network training method is designed to learn from the imperfect training data. We present the experiments in the lake with a various scene and demonstrate that our proposed method could be applied to recognize the water region in the unknown navigation environment automatically.
Dynamic Visual Measurement of Driver Eye Movements
Authors: Zhang Jin , Yang Ze , Deng Huaxia , Yu Huan , Ma Mengchao , Zhong Xiang
Published: May 2019

Vibrations often cause visual fatigue for drivers, and measuring the relative motion between the driver and the display is important for evaluating this visual fatigue. This paper proposes a non-contact videometric measurement method for studying the three-dimensional trajectories of the driver’s eyes based on stereo vision. The feasibility of this method is demonstrated by dynamic calibration. A high-speed dual-camera image acquisition system is used to obtain high-definition images of the face, and the relative trajectories between the eyes and the display are obtained by a set of robust algorithms. The trajectories of the eyes in three-dimensional space are then reconstructed during the vehicle driving process. This new approach provides three-dimensional information and is effective for assessing how vibration affects human visual performance.
UHF RFID Prototyping Platform for ISO 29167 Decryption Based on an SDR
Authors: Saxl Georg , Ferdik Manuel , Fischer Moritz , Maderboeck Martin , Ussmueller Thomas
Published: May 2019

Ultra high frequency radio frequency identification (UHF RFID) is becoming a key technology in the Internet of Things. It allows the implementation of batteryless and wireless nodes, including sensors and actuators. Due to its possible transmission range of >10 m and potential to carry critical information, security is a highly important topic. For this reason, the International Organization for Standardization has published several crypto suites for UHF RFID within the ISO-29167 standard in 2014. Recently, research has focused on implementing those encryption features on the transponder side. However, currently no crypto enabled UHF RFID readers are available. In order to cope with the rapid development in this field, ‘open’ and flexible readers based on software defined radios are needed. They make it possible to quickly adapt the protocol and to test new functionalities such as encryption. This paper deals with the first implementation of the ISO 29167-19 standardized RAMON decryption on a software defined radio. The programming of this hardware is done in LabVIEW which allows for controlling the built-in transceiver modules. However, first measurements show that the decryption takes 51 s. This is because LabVIEW is not suitable for handling very large numbers like they are utilized in cryptography. Because such a long processing time is not feasible in experiments nor in a real-life scenarios, this method is not suitable for a prototyping platform. Thus, a different approach is chosen to optimize the decryption processing time. LabVIEW still provides the framework for handling the protocol and controlling the transceivers, but the decryption is performed in a Java application. In that way, the entire decryption process takes only about 2.2 ms, which is 23,318 times faster than the implementation in LabVIEW. Thus, this new approach meets the necessary timing requirements and is suitable for realistic application scenarios. The shown method allows development and testing of new functionalities in UHF RFID systems but may also be employed in any application that require long processing times in LabVIEW. Furthermore, the implementation of decryption features is the first necessary step towards a fully compliant, crypto enabled interrogator for UHF RFID, featuring a high adaptability.
Self-Assembly of Functional Nucleic Acid-Based Colorimetric Competition Assay for the Detection of Immunoglobulin E
Authors: Lin Xuexia , Yu Caiyun , Lin Honggui , Wang Cui , Su Jianlong , Cheng Jie , Kankala Ranjith Kumar , Zhou Shu-Feng
Published: May 2019

In this work, we have developed a simple and rapid colorimetric assay for the detection of immunoglobulin E (IgE) using functional nucleic acids (FNAs) and a solid-phase competition enzyme-linked immunosorbent assay (ELISA). The FNAs including aptamer of recombinant IgE, G-quadruplex and its complementary fragments were immobilized on 96-well microplates to achieve recognition and detection of IgE in biological samples. The G-quadruplex DNAzyme catalyzed 2,2′-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS)-hemin-H2O2 system was used to improve the sensitivity of colorimetric assay. In the presence of IgE, the hairpin structure and G-quadruplex would be destroyed, resulting in the inactivation of DNAzyme and subsequent reduction of its absorbance. This cost-effective approach detected IgE in the linear range from 5.0 pg/mL to 500 ng/mL, with the limit of detection (LOD) of 2.0 pg/mL, under optimal conditions. Moreover, the developed method was successfully applied to the rapid detection of IgE in human urine, indicating a great potentiality of this approach in clinical diagnosis and other biomedical applications.
Design and Implementation of an Integrated IoT Blockchain Platform for Sensing Data Integrity
Authors: Hang Lei , Kim Do-Hyeun
Published: May 2019

With the rapid development of communication technologies, the Internet of Things (IoT) is getting out of its infancy, into full maturity, and tends to be developed in an explosively rapid way, with more and more data transmitted and processed. As a result, the ability to manage devices deployed worldwide has been given more and advanced requirements in practical application performances. Most existing IoT platforms are highly centralized architectures, which suffer from various technical limitations, such as a cyber-attack and single point of failure. A new solution direction is essential to enhance data accessing, while regulating it with government mandates in privacy and security. In this paper, we propose an integrated IoT platform using blockchain technology to guarantee sensing data integrity. The aim of this platform is to afford the device owner a practical application that provides a comprehensive, immutable log and allows easy access to their devices deployed in different domains. It also provides characteristics of general IoT systems, allows for real-time monitoring, and control between the end user and device. The business logic of the application is defined by the smart contract, which contains rules and conditions. The proposed approach is backed by a proof of concept implementation in realistic IoT scenarios, utilizing Raspberry Pi devices and a permissioned network called Hyperledger Fabric. Lastly, a benchmark study using various performance metrics is made to highlight the significance of the proposed work. The analysis results indicate that the designed platform is suitable for the resource-constrained IoT architecture and is scalable to be extended in various IoT scenarios.
Deep Autoencoder Neural Networks for Short-Term Traffic Congestion Prediction of Transportation Networks
Authors: Zhang Sen , Yao Yong , Hu Jie , Zhao Yong , Li Shaobo , Hu Jianjun
Published: May 2019

Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available online traffic service provider Washington State Department of Transportation. We then propose a deep autoencoder-based neural network model with symmetrical layers for the encoder and the decoder to learn temporal correlations of a transportation network and predicting traffic congestion. Our experimental results on the SATCS dataset show that the proposed DCPN model can efficiently and effectively learn temporal relationships of congestion levels of the transportation network for traffic congestion forecasting. Our method outperforms two other state-of-the-art neural network models in prediction performance, generalization capability, and computation efficiency.
A Novel Approach for Lidar-Based Robot Localization in a Scale-Drifted Map Constructed Using Monocular SLAM
Authors: Wang Su , Kobayashi Yukinori , Ravankar Ankit A. , Ravankar Abhijeet , Emaru Takanori
Published: May 2019

Scale ambiguity and drift are inherent drawbacks of a pure-visual monocular simultaneous localization and mapping (SLAM) system. This problem could be a crucial challenge for other robots with range sensors to perform localization in a map previously built by a monocular camera. In this paper, a metrically inconsistent priori map is made by the monocular SLAM that is subsequently used to perform localization on another robot only using a laser range finder (LRF). To tackle the problem of the metric inconsistency, this paper proposes a 2D-LRF-based localization algorithm which allows the robot to locate itself and resolve the scale of the local map simultaneously. To align the data from 2D LRF to the map, 2D structures are extracted from the 3D point cloud map obtained by the visual SLAM process. Next, a modified Monte Carlo localization (MCL) approach is proposed to estimate the robot’s state which is composed of both the robot’s pose and map’s relative scale. Finally, the effectiveness of the proposed system is demonstrated in the experiments on a public benchmark dataset as well as in a real-world scenario. The experimental results indicate that the proposed method is able to globally localize the robot in real-time. Additionally, even in a badly drifted map, the successful localization can also be achieved.
Convolutional Neural Networks Approach for Solar Reconstruction in SCAO Configurations
Authors: Suárez Gómez Sergio Luis , González-Gutiérrez Carlos , García Riesgo Francisco , Sánchez Rodríguez Maria Luisa , Iglesias Rodríguez Francisco Javier , Santos Jesús Daniel
Published: May 2019

Correcting atmospheric turbulence effects in light with Adaptive Optics is necessary, since it produces aberrations in the wavefront of astronomical objects observed with telescopes from Earth. These corrections are performed classically with reconstruction algorithms; between them, neural networks showed good results. In the context of solar observation, the usage of Adaptive Optics on solar differs from nocturnal operations, bringing up a challenge to correct the image aberrations. In this work, a convolutional approach is given to address this issue, considering SCAO configurations. A reconstruction algorithm is presented, “Shack-Hartmann reconstruction with deep learning on solar–prototype” (proto-HELIOS), to correct on fixed solar images, achieving an average 85.39% of precision in the reconstruction. Additionally, results encourage to continue working with these techniques to achieve a reconstruction technique for all the regions of the sun.
Particle Filtering for Localization of Broadband Sound Source Using an Ocean-Bottom Seismometer Sensor
Authors: Liu Yaqin , Zhang Haigang , Li Ziyang , Wang Xiaohan , Ma Jun
Published: May 2019

Passive source localization is a challenging task for one receiver, and the pressure sensor provides relatively simple information. An ocean-bottom seismometer (OBS) sensor placed on the seafloor surface can provide more information—not only pressure information, but also three-axis (x-, y-, and z-axis) velocity information at the seafloor interface. In this paper, an OBS sensor was used to estimate the position of the broadband sound source in a Pekeris shallow water waveguide with elastic bottom. As the dynamics that characterize ocean acoustic applications are inherently nonlinear, non-Gaussian, and non-stationary processes that quickly vary with space and time, sequential Bayesian filtering, such as particle filtering (PF), is able to adapt to these environmental changes. Simulation results show that the PF method with the vertical wave impedance (the ratio of the pressure and vertical particle velocity) in the frequency domain as a measurement vector is not affected by source depth and source spectrum information, making it more tolerant and more robust than that with pressure in positioning. Experimental data results verified the effectiveness of the PF method with the vertical wave impedance for the localization of the explosive source.
Soil Salinity Variations in an Irrigation Scheme during a Period of Extreme Dry and Wet Cycles
Authors: Chamaki Sheyda , Taghvaeian Saleh , Zhang Hailin , Warren Jason G.
Published: May 2019

Salinization of irrigated lands is a major challenge towards supplying required food and feed to meet the needs of an increasing global population. In this study, the changes in soil salinity and several other chemical properties were investigated in an irrigation scheme during a period that experienced severe drought followed by above-normal precipitation. Soil salinity, represented by the electrical conductivity (EC) of the saturated paste extract, decreased for the top layers and increased for the bottom layers during the study period, suggesting some level of leaching had occurred. However, the change in the average EC of top 1.5 m of the soil was not statistically significant. The change in exchangeable sodium percentage (ESP) was not significant over the study period either. In contrast, average pH and calcium concentrations increased and decreased significantly during the study period, respectively. EC and ESP data were used in soil classification. The percentage of all sampled sites classified as saline was 60 at the beginning of the dry–wet period, but dropped to 50% at the end of this period. All tested parameters were temporally stable, preserving their spatial rank during the study period.
Green Manure Planting Incentive Measures of Local Authorities and Farmers’ Perceptions of the Utilization of Rotation Fallow for Sustainable Agriculture in Guangxi, China
Authors: Ntakirutimana Leonard , Li Fuduo , Huang Xianlei , Wang Shu , Yin Changbin
Published: May 2019

Planting green manure in fallow croplands in winter can bring various economic and environmental benefits, including increased food production, carbon capture and sequestration, soil retention, sandstorm prevention, water retention, and provision of habitat for biodiversity. However, the increased production cost of planting green manure reduces farmers’ willingness to adopt this approach, which is unfavorable for its sustainability. This research aims to investigate the influence of instrumental variables on farmers’ perceptions of sustainable agriculture practices, especially the use of rotation fallow, and tries to understand the relationship between farmers’ perceptions of using rotation fallow and planting green manure under incentive measures adopted by local authorities in Guangxi Province, China. Using simultaneous equation models, the results show that subsidies and planting training were the most important drivers for restoring green manure planting in the target region. These incentive measures could be further enhanced as a priority to restore green manure planting. The study also finds that socioeconomic factors such as farmer’s income, area of farmland, and labor for agricultural production have a certain influence on planting green manure planting and on farmers’ perceptions of using rotation fallow as a form of sustainable agriculture practice.
The Enhancement of Lump Coal Percentage by High-Pressure Pulsed Hydraulic Fracturing for Sustainable Development of Coal Mines
Authors: Yan Hao , Zhang Jixiong , Zhou Nan , Chen Junli
Published: May 2019

The enhancement of lump coal percentage (LCP) is of great significance for most aging mines to achieve the production reduction and quality improvement. In order to enhance the LCP of hard coal seam in fully mechanized mining face and prolong the service life of aging mines, this paper puts forward the technological path of LCP enhancement using high-pressure pulsed hydraulic fracturing (HPPHF) based on the detailed analysis of the main factors controlling LCP. By analyzing the correlation between coal fracturing and LCP, the enhancement mechanism of LCP through HPPHF was concluded. Using the extended finite element method, a fluid–solid coupling numerical model of high-pressure pulsed water injection into coal seam was established, and effects of the fracturing method, pulse amplitude, pulse frequency, and water injection pressure on fracturing performance were assessed. Simulation results demonstrate that HPPHF can effectively reduce the required maximum pressure in fracturing, thus providing a higher percentage of coal lumps with lower energy consumption through the repeated pulsed loading of coal masses. Variations in pulsed pressure amplitude and frequency, as well as water injection pressure were positively correlated with fracturing performance. By their effect on the fracturing performance, we found that water injection pressure had the greatest influence, and the pulse amplitude and frequency had similar effects. At the same time, “high amplitude-high frequency” and “high amplitude-low frequency” had characteristics of short initiation time, large initiation pressure, but small fracture width, while “low amplitude-high frequency” and “low amplitude-low frequency” had characteristics of slow initiation speed, low initiation pressure, but large fracture width. Through the field test results in the fully mechanized mining face of Shichangwan Coal Mine, it was found that LCP with a diameter range of 13–100 mm was significantly enhanced by HPPHF. The present study is considered quite instrumental in providing a theoretical foundation for enhancing the LCP of hard coal seams and the sustainable development of coal mine enterprises.
Differential Game Analysis of Scientific Crowdsourcing on Knowledge Transfer
Authors: Wang Guohao , Yu Liying
Published: May 2019

Scientific crowdsourcing based on knowledge transfer between enterprises has drawn wide attention. This paper constructs the Stackelberg master–slave game model and the benefit sharing model. Through the model comparison and numerical simulation, the knowledge transfer behavior and the revenue distribution mechanism of crowdsourcing initiator and solver in the context of scientific crowdsourcing are studied. The research shows that the knowledge transfer quality and the crowdsourcing total revenue under the benefit sharing state are better than the Stackelberg master–slave game under the leadership of the crowdsourcing initiator and when the revenue distribution coefficient between the crowdsourcing initiator and solver is within a certain range. The final revenue for each party in the benefit sharing state is higher than the one in the Stackelberg master–slave game state. In addition, the research finds that the knowledge coupling degree between the initiator and the solver has a positive impact on knowledge transfer and crowdsourcing benefits. The conclusions of this paper provide a theoretical basis for enterprises, especially for large-scale high-tech business to business enterprises, to transfer knowledge and distribute revenue and eventually improve their scientific crowdsourcing quality.
Integrating Protein Quality and Quantity with Environmental Impacts in Life Cycle Assessment
Authors: Berardy Andrew , Johnston Carol S. , Plukis Alexandra , Vizcaino Maricarmen , Wharton Christopher
Published: May 2019

Life cycle assessment (LCA) evaluates environmental impacts of a product from material extraction through disposal. Applications of LCA in evaluating diets and foods indicate that plant-based foods have lower environmental impacts than animal-based foods, whether on the basis of total weight or weight of the protein content. However, LCA comparisons do not differentiate the true biological value of protein bioavailability. This paper presents a methodology to incorporate protein quality and quantity using the digestible indispensable amino acid score (DIAAS) when making comparisons using LCA data. The methodology also incorporates the Food and Drug Administration’s (FDA) reference amounts customarily consumed (RACCs) to best represent actual consumption patterns. Integration of these measures into LCA provides a mechanism to identify foods that offer balance between the true value of their protein and environmental impacts. To demonstrate, this approach is applied to LCA data regarding common protein foods’ global warming potential (GWP). The end result is a ratio-based score representing the biological value of protein on a GWP basis. Principal findings show that protein powders provide the best efficiency while cheeses, grains, and beef are the least efficient. This study demonstrates a new way to evaluate foods in terms of nutrition and sustainability.
Understanding the Spatial Agglomeration of Participation in Agri-Environmental Schemes: The Case of the Tuscany Region
Authors: Bartolini Fabio , Vergamini Daniele
Published: May 2019

Agri-environmental schemes (AESs) constitute one of the main agricultural policy instruments that address environmental objectives in the Common Agricultural Policy. However, in spite of a 20-year application window and large budgetary shares allocated by EU member states, several studies demonstrate lower-than-expected environmental impacts. The reasons for poor environmental outcomes are the lack of targeting, low participation rates, spatial heterogeneity, and information asymmetry between farmers and public administrators. This study comprehensively analyses the determinants of AES adoption while highlighting patterns of the spatial agglomeration of participation in organic and integrated production. For this, we combine the results of farm-level adoption analysis with a spatial analysis of the participation rate. The results show that both micro- and meso-level characteristics strongly impact AES participation. In fact, farm and household structure, quality of extension services, and territorial conditions all significantly affect AES adoption.
Do Controlling Shareholders Who Pledged Their Shares Affect Sustainable Development? An Investigation Based on the Perspective of Corporate Innovation
Authors: Ouyang Caiyue , Wang Xin , Xiong Jiacai
Published: May 2019

We examine the impact of share pledging (SP) on a firm’s innovation using a sample of Chinese firms. Our findings show that when controlling shareholders pledged their shares in personal loans, their firm’s innovation decreases. Our findings are robust for alternative metrics of innovation and SP. Additional analyses suggest that when controlling shareholders have little ownership or stock price volatility is high, the impact of SP on corporate innovation magnifies, presumably due to the high margin call risk of share against the pledged controlling shareholders. Overall, our study shows that the self-interest of controlling shareholders with pledged shares impedes corporate innovation, thereby impeding the sustainable development of society.
Internationalization Business Models and Patterns of SMEs and MNEs: A Qualitative Multi-Case Study in the Agrifood Sector
Authors: García-Álvarez de Perea Juan , Ramírez-García Carolina , Del Cubo-Molina Aida
Published: May 2019

Small- and Medium-sized Enterprises (SMEs) and Multinational Enterprises (MNEs) in the agri-food sector have been overcoming internationalization barriers. However, research is scarce, specifically to meet the Sustainable Development Goals, despite the importance of the sector. The main aim of our study is to explore the archetypes and internationalization pace of internationalized SMEs and MNEs in the agri-food sector, adopting an external perspective and an empirical approach. More particularly, the influence of the interaction of demand-side innovation and management control systems (MCSs) in companies in the industry is examined. A qualitative research design was developed in order to achieve an in-depth understanding of the contextual factors affecting international SMEs and MNEs in the agri-food sector. Semi-structured telephone interviews were conducted with three SME and three MNE managers. Our findings suggest that SMEs are not fundamentally different from MNEs—both types of organizations best fit the Casino model archetype. It was also found that strong competition helps the development of collaborative innovation, directing advancement toward fulfilling consumer demand. MCSs are neither communicating information nor managing perceived risks by creating trust and confidence; they are mostly used for diagnostic purposes, not substantially influencing the innovation process.
Expected Rural Wastewater Treatment Promoted by Provincial Local Discharge Limit Legislation in China
Authors: Wang Meishu , Gong Hui
Published: May 2019

Wastewater treatment in a rural region in China was undeveloped both in treatment capacity and legislation. The successful fast development of urban wastewater treatment plants (WWTPs) demonstrated the importance of legislation, including discharge limits. However, most provinces, with as high as 79.8% of the rural population in China, released no specific local discharge limits. Newly issued top-designed nationwide policy in September of 2018 by central China government required all provinces to issue their local rural wastewater discharge limits before June 2019. For the first time, this research analyzed the requirements of the newly issued policy and their inconsistence with several existing provincial limits. It proposed flexible principles for determination of discharge limits under various conditions to improve the rural residential environment as a whole. This study also proposed the use of the ratio between wastewater treatment cost and life expense to describe economic burden. Economic burden calculation for wastewater treatment in rural and urban regions was established respectively. Based on three conditions described in the new policy, the average burden for all urban residents was estimated as 0.122 ± 0.038% of the total life expense. In comparison, average nationwide rural burden was 0.087 ± 0.035% and 0.564 ± 0.196% for condition I (Total nitrogen(TN)/total phosphorus(TP) for resource recovery) and condition III (TN/TP for pollutant removal), respectively. It was also revealed that a stringent rural discharge limit lead to a Gini value as high as 0.38, indicting policy-related subsidies for rural residents should be carefully considered to ensure a balanced burden. Local discharge limit legislation and suitable financial policy is expected to promote rural wastewater treatment in China in the near future.
A Travel Behavior-Based Skip-Stop Strategy Considering Train Choice Behaviors Based on Smartcard Data
Authors: Lee Eun Hak , Lee Inmook , Cho Shin-Hyung , Kho Seung-Young , Kim Dong-Kyu
Published: May 2019

This study analyzes a skip-stop strategy considering four types of train choice behavior with smartcard data. The proposed model aims to minimize total travel time with realistic constraints such as facility condition, operational condition, and travel behavior. The travel time from smartcard data is decomposed by two distributions of the express trains and the local trains using a Gaussian mixture model. The utility parameters of the train choice model are estimated with the decomposed distribution using the multinomial logit model. The optimal solution is derived by a genetic algorithm to designate the express stations of the Bundang line in the Seoul metropolitan area. The results indicate the travel times of the transfer-based strategy and the high ridership-based strategy are estimated to be 21.2 and 19.7 min/person, respectively. Compared to the travel time of the current system, the transfer-based strategy has a 5.8% reduction and the high ridership-based strategy has a 12.2% reduction. For the travel behavior-based strategy, the travel time was estimated to be 18.7 minutes, the ratio of the saved travel time is 17.9%, and the energy consumption shows that the travel behavior-based strategy consumes 305,437 (kWh) of electricity, which is about 12.7% lower compared to the current system.
Do Bus Rapid Transit Systems Improve Accessibility to Job Opportunities for the Poor? The Case of Lima, Peru
Authors: Oviedo Daniel , Scholl Lynn , Innao Marco , Pedraza Lauramaria
Published: May 2019

Investments in public transit infrastructure in Latin America and the Caribbean often aim to reduce spatial and social inequalities by improving accessibility to jobs and other opportunities for vulnerable populations. One of the central goals of Lima’s Bus Rapid Transit (BRT) project was to connect low-income populations living in the peripheries to jobs in the city center, a policy objective that has not yet been evaluated. Building on secondary datasets of employment, household socio-demographics and origin–destination surveys before and after the BRT began operations, this paper examines the contribution of Lima’s BRT system to accessibility to employment in the city, particularly for low-income public transit users. We estimated the effects on potential accessibility to employment, comparing impacts on lower versus higher income populations, and assessed the changes in location-based accessibility to employment before (2004) and after implementation (2012) for treatment and comparison groups. We found that the BRT line reduced travel times for commuters to reach jobs, in comparison with traditional public transport in the city. However, the coverage of the BRT declines in areas with high concentrations of poor populations, limiting the equitability of accessibility improvements. The analysis by socioeconomic sub-groups found positive effects of the BRT system on accessibility for the higher income areas. Relative to the control group, accessibility increased in the 10-km boundary area of the BRT by 0.01, a seven percent increase relative to the treatment baseline accessibility index in the higher socioeconomic (SES) areas of the city. In contrast, in the areas with high concentrations of lower SES populations, the double difference estimate indicated an 11 percent decrease relative to the baseline accessibility index (0.09). We build on case-specific findings and international literature to reflect on policy avenues to include the poor in the mobility benefits of BRT systems. These measures include targeted fare subsidies for low-income groups, fare integration with other forms of public transport that reduce the cost of transfers, and the increase of coverage of the BRT through the integration of stations with non-motorized infrastructure.
Mean-Field Expansion, Regularization Issue, and Multi-Quark Functions in Nambu–Jona-Lasinio Model
Authors: Garibli Aydan A. , Jafarov Rauf G. , Rochev Vladimir E.
Published: May 2019

In this paper, the results of the investigation of multi-quark equations in the Nambu–Jona-Lasinio (NJL) model in the mean-field expansion are presented. The multi-quark functions have been considered up to the third order of expansion. One of the purposes of our computations is the study of corrections of higher orders to parameters of the model. The important problem of the application of the NJL model is regularization. We compare the NJL model with 4-dimensional cutoff regularization and the dimensionally analytical regularization. We also discuss so-called “predictive regularization” in the NJL model, and a modification of this regularization, which is free of the Landau pole, is proposed. To calculate the high-order corrections, we use the Legendre transform method in the framework of bilocal-source formalism, which allows one effectively to take into consideration the symmetry constraints. A generalization of the mean-field expansion for other types of multi-quark sources is also discussed.
Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis
Authors: Peter Stephan , Hölzer Martin , Lamkiewicz Kevin , di Fenizio Pietro Speroni , Al Hwaeer Hassan , Marz Manja , Schuster Stefan , Dittrich Peter , Ibrahim Bashar
Published: May 2019

Influenza A virus is recognized today as one of the most challenging viruses that threatens both human and animal health worldwide. Understanding the control mechanisms of influenza infection and dynamics is crucial and could result in effective future treatment strategies. Many kinetic models based on differential equations have been developed in recent decades to capture viral dynamics within a host. These models differ in their complexity in terms of number of species elements and number of reactions. Here, we present a new approach to understanding the overall structure of twelve influenza A virus infection models and their relationship to each other. To this end, we apply chemical organization theory to obtain a hierarchical decomposition of the models into chemical organizations. The decomposition is based on the model structure (reaction rules) but is independent of kinetic details such as rate constants. We found different types of model structures ranging from two to eight organizations. Furthermore, the model’s organizations imply a partial order among models entailing a hierarchy of model, revealing a high model diversity with respect to their long-term behavior. Our methods and results can be helpful in model development and model integration, also beyond the influenza area.
Effect of Cascading Reservoirs on the Flow Variation and Thermal Regime in the Lower Reaches of the Jinsha River
Authors: Long Lianghong , Ji Daobin , Liu Defu , Yang Zhengjian , Lorke Andreas
Published: May 2019

We analyzed the alteration of discharge and water temperature caused by two newly established reservoirs in the lower reaches of the Jinsha River. In comparison to longer-term observations from the pre-impoundment period, the seasonal flow variability was significantly affected by the larger, upstream-located Xiluodu reservoir, with higher discharge in spring and reduced discharge in summer. The smaller, downstream located Xiangjiaba reservoir did not contribute significantly to the total hydrological alteration caused by the reservoir cascade. Thermal stratification occurred in spring and summer in the Xiluodu reservoir, but was not observed in the Xiangjiaba reservoir. The vertical structure and seasonal dynamics of thermal stratification were mainly governed by the water temperature of the inflow and the depth of the water outlet. Despite the different thermal structure, both reservoirs reduced the amplitude of annual temperature variations and delayed the seasonal temperature cycle in the downstream river water. In contrast to discharge variation, thermal effects were cumulative along the cascading reservoirs. Homogenization and delay effects can be expected to increase further with the completion of ongoing reservoir construction upstream of the two studied reservoirs. Based on our findings, we discuss the larger-scale impacts of cascading hydropower developments and emphasize the need for taking water temperature and its variation into account when developing optimized operation or mitigation strategies for these systems.
MILP for Optimizing Water Allocation and Reservoir Location: A Case Study for the Machángara River Basin, Ecuador
Authors: Veintimilla-Reyes Jaime , De Meyer Annelies , Cattrysse Dirk , Tacuri Eduardo , Vanegas Pablo , Cisneros Felipe , Van Orshoven Jos
Published: May 2019

The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs.
Analysis and Projection of Flood Hazards over China
Authors: Liang Yulian , Wang Yongli , Zhao Yinjun , Lu Yuan , Liu Xiaoying
Published: May 2019

Floods have been experienced with greater frequency and more severity under global climate change. To understand the flood hazard and its variation in the future, the current and future flood hazards in the 21st century in China are discussed. Floods and their trends are assessed using the accumulation precipitation during heavy rainfall process (AP_HRP), which are calculated based on historical meteorological observations and the outputs of a global climate model (GCM) under three Representative Concentration Pathway (RCP) scenarios. The flood-causing HRPs counted by the flood-causing critical precipitation (the 60% fractile of AP_HRP) capture more than 70% of historical flood events. The projection results indicate that the flood hazards could increase under RCP4.5 and RCP8.5 and increase slightly under RCP2.6 during the 21st century (2011–2099). The spatial characteristics of flood hazards and their increasing trends under the three RCPs are similar in most areas of China. More floods could occur in southern China, including Guangdong, Hainan, Guangxi and Fujian provinces, which could become more serious in southeastern China and the northern Yunnan province. Construction of water conservancy projects, reservoir dredging, improvement of drainage and irrigation equipment and enhancement of flood control and storage capacity can mitigate the impacts of floods and waterlogging on agriculture.
Different Approaches to SCADA Data Completion in Water Networks
Authors: Marti-Puig Pere , Martí-Sarri Arnau , Serra-Serra Moisès
Published: May 2019

This work contributes to the techniques used for SCADA (Supervisory Control and Data Acquisition) system data completion in databases containing historical water sensor signals from a water supplier company. Our approach addresses the data restoration problem in two stages. In the first stage, we treat one-dimensional signals by estimating missing data through the combination of two linear predictor filters, one working forwards and one backwards. In the second stage, the data are tensorized to take advantage of the underlying structures at five minute, one day, and one week intervals. Subsequently, a low-range approximation of the tensor is constructed to correct the first stage of the data restoration. This technique requires an offset compensation to guarantee the continuity of the signal at the two ends of the burst. To check the effectiveness of the proposed method, we performed statistical tests by deleting bursts of known sizes in a complete tensor and contrasting different strategies in terms of their performance. For the type of data used, the results show that the proposed data completion approach outperforms other methods, the difference becoming more evident as the size of the bursts of missing data grows.
REQUIRED MATERIALS FOR EXPERTISE IN CASE OF RUNOVER ROLLING STOCK ON AN OBSTACLE
Authors:   A. Kuzyshyn; O. Kovalchuk
Published: May 2019

One of the tasks that are being solved during the forensic railway transport expertise is to investigate the actions and circumstances of a railway accident. After analyzing the state of traffic safety in the structure of Ukrzaliznytsia OJSC, the author found that in recent years the number of runover incidents of rolling stock on pedestrians and motor vehicles has increased significantly. This is primarily due to the non-observance of the “Rules of Conduct of Citizens in Railway Transport”. It was noted that when performing such railway transport expertise, the expert receives an incomplete amount of necessary information, which may be the result of incomplete research or the impossibility of giving an opinion on this railway accident. First of all, this is due to the fact that employees of the bodies of the Ministry of Internal Affairs when they are at the scene of a railroad accident have no special knowledge and cannot select the necessary information for the qualitative expertise.

And so, after conducting research, the author came to the conclusion that for a full and high-quality railway transport expertise in the event of rolling stock hitting an obstacle (vehicle or person), the expert needs to have the following list of documents and relevant data, namely: original speedometer module KKD-3 memory, registration tape CLUB-U; certificate on the provision of the train with VU-45 brakes; information on the type of track on which the railway accident occurred (link or continuous), the longitudinal profile and the plan of the section of the route on which the railway accident occurred; full-scale sheet form DU-1 for a freight train, and DU-1L – for the passenger; information on the permissible speed of movement in the area of the railway accident; warning on the train form DU-61; graphic reproduction of a clear situation of a railway accident with an indication of a specific stopping point of the train’s head, the location of the obstacle with reference to the picket column.

So, having received the necessary information in accordance with the list that is specified in this article, the expert can objectively and reliably assess the impact of the actions of each of the participants in this incident on the implementation of the mechanism of the railway accident as a whole.

Key words: forensic railway-transport expertise, rolling stock, runway, locomotive, track, obstacle.
Wellington e Napoleão: Representações Britânicas e Portuguesas no Romance e no Ecrã
Authors: Evans David , Gândara Terenas Gabriela , Lupi Bello Maria do Rosário
Published: May 2019

The primary aim of the present article is to analyse how the two opposing military leaders – Wellington and Napoleon – were portrayed in British and Portuguese novels and films. The article looks closely at the way British and Portuguese authors perceived the two
major figures of the Peninsular War, whilst examining, on the other hand, the way they were depicted in the cinema, contributing in this way, it is hoped, towards the reconstitution of a period of particular importance in Anglo-Portuguese relations. The first part of the study presents an overview of the way the War has been portrayed in Literature and the Cinema and the second looks closely at the many ways such narratives have depicted these great adversaries, two of the most remarkable figures of the nineteenth century.
O Movimento Sufragista Britânico na Imprensa Portuguesa (1908-1919)
Authors: Ferreira João Paulo
Published: May 2019

This paper analyses nine articles, written in the Portuguese press between 1908 and 1919, which focus on the activities of the British suffragette movement. The articles are taken from four contemporary periodicals: O Mundo, A Madrugada, A Mulher e a Criança and Alma Feminina. The first was a Republican daily newspaper, whilst the others were newspapers or magazines whose main purpose was the defence of women’s rights. The last of the four contains articles which were translated from the magazine Jus Suffragii and are analysed in this paper. Concepts such as imagology, reception theory, representation, propaganda and the polysystem theory were employed in the analysis of the articles. As different as the tactics of the Portuguese and British feminists were, the writers of the articles tended to consider all feminists as part of a single community who strived to defend basic human rights for women. Although an admiration for the suffragettes and their violent tactics transpires from the articles (which contrasts with the more passive attitude of Portuguese women), most of the writers were dismayed by the repression inflicted by the Police and the Government upon the suffragettes. This was due to the fact that the United Kingdom was considered to be a country
where the right of free speech was believed to be paramount. Hence, some of the articles stress the biased attitudes of British institutions against the suffragettes.
“And here’s to you, Mr. Robinson”: Para uma História do Sector Corticeiro Anglo-Português
Authors: Alarcão Miguel
Published: May 2019

In March 2010, while carrying out some research at the archives of the Portuguese Foreign Ministry, we came across, by sheer chance, with a few letters pertaining incidents from 1911. These documents, we believe, may be relevant to further studies on the industrial relationships between English employers and the Portuguese labour force in the cork trade soon after the Republican revolution (1910).