bluuebunny/crossref_metadata_2025 huggingface dataset:
Designing on the Basis of Recycling-Metallurgy Possibilities: Material-Specific Rules and Standards for “Anti-Dissipative” Products
Authors: Schoch Konrad , Liedtke Christa , Bienge Katrin
Published: January 2021

The demand for metals from the entire periodic table is currently increasing due to the ongoing digitalization. However, their use within electrical and electronic equipment (EEE) poses problems as they cannot be recovered sufficiently in the end-of-life (EoL) phase. In this paper, we address the unleashed dissipation of metals caused by the design of EEE for which no globally established recycling technology exists. We describe the European Union’s (EU) plan to strive for a circular economy (CE) as a political response to tackle this challenge. However, there is a lack of feedback from a design perspective. It is still unknown what the implications for products would be if politics were to take the path of a CE at the level of metals. To provide clarification in this respect, a case study for indium is presented and linked to its corresponding recycling-metallurgy of zinc and lead. As a result, a first material-specific rule on the design of so-called “anti-dissipative” products is derived, which actually supports designing EEE with recycling in mind and represents an already achieved CE on the material level. In addition, the design of electrotechnical standardization is being introduced. As a promising tool, it addresses the multi-dimensional problems of recovering metals from urban ores and assists in the challenge of enhancing recycling rates. Extending the focus to other recycling-metallurgy besides zinc and lead in further research would enable the scope for material-specific rules to be widened.
Mapping Large-Scale Mangroves along the Maritime Silk Road from 1990 to 2015 Using a Novel Deep Learning Model and Landsat Data
Authors: Guo Yujuan , Liao Jingjuan , Shen Guozhuang
Published: January 2021

Mangroves are important ecosystems and their distribution and dynamics can provide an understanding of the processes of ecological change. Meanwhile, mangroves protection is also an important element of the Maritime Silk Road (MSR) Cooperation Project. Large amounts of accessible satellite remote sensing data can provide timely and accurate information on the dynamics of mangroves, offering significant advantages in space, time, and characterization. In view of the capability of deep learning in processing massive data in recent years, we developed a new deep learning model—Capsules-Unet, which introduces the capsule concept into U-net to extract mangroves with high accuracy by learning the spatial relationship between objects in images. This model can significantly reduce the number of network parameters to improve the efficiency of data processing. This study uses Landsat data combined with Capsules-Unet to map the dynamics of mangrove changes over the 25 years (1990–2015) along the MSR. The results show that there was a loss in the mangrove area of 1,356,686 ha (about 21.5%) between 1990 and 2015, with anthropic activities such as agriculture, aquaculture, tourism, urban development, and over-development appearing to be the likely drivers of this decline. This information contributes to the understanding of ecological conditions, variability characteristics, and influencing factors along the MSR.
A Remote Sensing-Based Assessment of Water Resources in the Arabian Peninsula
Authors: Wehbe Youssef , Temimi Marouane
Published: January 2021

A better understanding of the spatiotemporal distribution of water resources is crucial for the sustainable development of hyper-arid regions. Here, we focus on the Arabian Peninsula (AP) and use remotely sensed data to (i) analyze the local climatology of total water storage (TWS), precipitation, and soil moisture; (ii) characterize their temporal variability and spatial distribution; and (iii) infer recent trends and change points within their time series. Remote sensing data for TWS, precipitation, and soil moisture are obtained from the Gravity Recovery and Climate Experiment (GRACE), the Tropical Rainfall Measuring Mission (TRMM), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), respectively. The study relies on trend analysis, the modified Mann–Kendall test, and change point detection statistics. We first derive 10-year (2002–2011) seasonal averages from each of the datasets and intercompare their spatial organization. In the absence of large-scale in situ data, we then compare trends from GRACE TWS retrievals to in situ groundwater observations locally over the subdomain of the United Arab Emirates (UAE). TWS anomalies vary between −6.2 to 3.2 cm/month and −6.8 to −0.3 cm/month during the winter and summer periods, respectively. Trend analysis shows decreasing precipitation trends (−2.3 × 10−4 mm/day) spatially aligned with decreasing soil moisture trends (−1.5 × 10−4 g/cm3/month) over the southern part of the AP, whereas the highest decreasing TWS trends (−8.6 × 10−2 cm/month) are recorded over areas of excessive groundwater extraction in the northern AP. Interestingly, change point detection reveals increasing precipitation trends pre- and post-change point breaks over the entire AP region. Significant spatial dependencies are observed between TRMM and GRACE change points, particularly over Yemen during 2010, revealing the dominant impact of climatic changes on TWS depletion.
Efficient Hybrid Supervision for Instance Segmentation in Aerial Images
Authors: Chen Linwei , Fu Ying , You Shaodi , Liu Hongzhe
Published: January 2021

Instance segmentation in aerial images is of great significance for remote sensing applications, and it is inherently more challenging because of cluttered background, extremely dense and small objects, and objects with arbitrary orientations. Besides, current mainstream CNN-based methods often suffer from the trade-off between labeling cost and performance. To address these problems, we present a pipeline of hybrid supervision. In the pipeline, we design an ancillary segmentation model with the bounding box attention module and bounding box filter module. It is able to generate accurate pseudo pixel-wise labels from real-world aerial images for training any instance segmentation models. Specifically, bounding box attention module can effectively suppress the noise in cluttered background and improve the capability of segmenting small objects. Bounding box filter module works as a filter which removes the false positives caused by cluttered background and densely distributed objects. Our ancillary segmentation model can locate object pixel-wisely instead of relying on horizontal bounding box prediction, which has better adaptability to arbitrary oriented objects. Furthermore, oriented bounding box labels are utilized for handling arbitrary oriented objects. Experiments on iSAID dataset show that the proposed method can achieve comparable performance (32.1 AP) to fully supervised methods (33.9 AP), which is obviously higher than weakly supervised setting (26.5 AP), when using only 10% pixel-wise labels.
An Accurate GEO SAR Range Model for Ultralong Integration Time Based on mth-Order Taylor Expansion
Authors: Zhou Binbin , Qi Xiangyang , Zhang Heng
Published: January 2021

As the Geosynchronous Earth Orbital Synthetic Aperture Radar (GEO SAR) allows a wide area viewing combined with a short revisit cycle, it is suitable for many applications that require high timeliness, such as natural disaster monitoring, weather supervision, and military reconnaissance. However, the ultralong integration time and the invalidation of “stop-and-go” assumption caused by the raise of orbital height also greatly increase the difficulty of signal processing. In this paper, a generalized method for calculating the accurate propagation distance between a GEO satellite and a target with ultralong integration time is proposed. This range model is mainly composed of an accurate pulse transmitting distance and an error compensation term for “stop-and-go” assumption failure. The transmitting distance is obtained by Taylor expansion, and the specific derivation process of the general formula of the mth-order expansion is given, in this paper. As for the compensation term, this is achieved by approximately calculating the pulse receiving distance based on twice Taylor expansion, the first expansion is for fast-time and the other is for slow-time. Finally, a series of simulation experiments were conducted to verify the effectiveness and superiority of this new range model for an ultralong integration time.
User-Cell Association for Security and Energy Efficiency in Ultra-Dense Heterogeneous Networks
Authors: Marabissi Dania , Mucchi Lorenzo , Morosi Simone
Published: January 2021

The last decades have been characterized by an exponential increase in digital services. The demand is foreseen to further increase in the next years, and mobile networks will have to mandatorily supply connections to enable digital services with very different requirements, from ultra high speed to ultra low latency. The deployment and the coexistence of cells of different size, from femto to macro, will be one of the key elements for providing such pervasive wireless connection: the ultra dense networks (UDN) paradigm. How to associate users and base stations is one of the most investigated research topics. Many criteria can be drawn, from minimization of power consumption to optimization of throughput. In this paper we propose a new utility to optimize two of the most important features of future mobile connection: security and energy consumption. By using our utility it is possible to jointly select the base station to be activated in a UDN, and associate users to the base stations with the aim of maximizing the secure throughput by spending the minimum energy. Moreover, we propose a heuristic that allows to achieve performance very close to the optimal one with reduced complexity. Effectiveness of the proposed approach is proved by means of comparison with benchmark approaches.
Registering Unmanned Aerial Vehicle Videos in the Long Term
Authors: Lemaire Pierre , Crispim-Junior Carlos Fernando , Robinault Lionel , Tougne Laure
Published: January 2021

Unmanned aerial vehicles (UAVs) have become a very popular way of acquiring video within contexts such as remote data acquisition or surveillance. Unfortunately, their viewpoint is often unstable, which tends to impact the automatic processing of their video flux negatively. To counteract the effects of an inconsistent viewpoint, two video processing strategies are classically adopted, namely registration and stabilization, which tend to be affected by distinct issues, namely jitter and drifting. Following our prior work, we suggest that the motion estimators used in both situations can be modeled to take into account their inherent errors. By acknowledging that drifting and jittery errors are of a different nature, we propose a combination that is able to limit their influence and build a hybrid solution for jitter-free video registration. In this work, however, our modeling was restricted to 2D-rigid transforms, which are rather limited in the case of airborne videos. In the present paper, we extend and refine the theoretical ground of our previous work. This addition allows us to show how to practically adapt our previous work to perspective transforms, which our study shows to be much more accurate for this problem. A lightweight implementation enables us to automatically register stationary UAV videos in real time. Our evaluation includes traffic surveillance recordings of up to 2 h and shows the potential of the proposed approach when paired with background subtraction tasks.
Performance Evaluation of Attribute-Based Encryption in Automotive Embedded Platform for Secure Software Over-The-Air Update
Authors: La Manna Michele , Treccozzi Luigi , Perazzo Pericle , Saponara Sergio , Dini Gianluca
Published: January 2021

This paper aims to show that it is possible to improve security for over the air update functionalities in an automotive scenario through the use of a cryptographic scheme, called “Attribute-Based-Encryption” (ABE), which grants confidentiality to the software/firmware update done Over The Air (OTA). We demonstrate that ABE is seamlessly integrable into the state of the art solutions regarding the OTA update by showing that the overhead of the ABE integration in terms of computation time and its storage is negligible w.r.t. the other overheads that are introduced by the OTA process, also proving that security can be enhanced with a minimum cost. In order to support our claim, we report the experimental results of an implementation of the proposed ABE OTA technique on a Xilinx ZCU102 evaluation board, which is an automotive-oriented HW/SW platform that is equipped with a Zynq UltraScale+ MPSoC chip that is representative of the computing capability of real automotive Electronic Control Units (ECUs).
Hybrid Carbon Microfibers-Graphite Fillers for Piezoresistive Cementitious Composites
Authors: Birgin Hasan Borke , D’Alessandro Antonella , Laflamme Simon , Ubertini Filippo
Published: January 2021

Multifunctional structural materials are very promising in the field of engineering. Particularly, their strain sensing ability draws much attention for structural health monitoring applications. Generally, strain sensing materials are produced by adding a certain amount of conductive fillers, around the so-called “percolation threshold”, to the cement or composite matrix. Recently, graphite has been found to be a suitable filler for strain sensing. However, graphite requires high amounts of doping to reach percolation threshold. In order to decrease the amount of inclusions, this paper proposes cementitious materials doped with new hybrid carbon inclusions, i.e., graphite and carbon microfibers. Carbon microfibers having higher aspect ratio than graphite accelerate the percolation threshold of the graphite particles without incurring into dispersion issues. The resistivity and strain sensitivity of different fibers’ compositions are investigated. The electromechanical tests reveal that, when combined, carbon microfibers and graphite hybrid fillers reach to percolation faster and exhibit higher gauge factors and enhanced linearity.
Building Trust for Smart Connected Devices: The Challenges and Pitfalls of TrustZone
Authors: Koutroumpouchos Nikolaos , Ntantogian Christoforos , Xenakis Christos
Published: January 2021

TrustZone-based Trusted Execution Environments (TEEs) have been utilized extensively for the implementation of security-oriented solutions for several smart intra and inter-connected devices. Although TEEs have been promoted as the starting point for establishing a device root of trust, a number of published attacks against the most broadly utilized TEE implementations request a second view on their security. The aim of this research is to provide an analytical and educational exploration of TrustZone-based TEE vulnerabilities with the goal of pinpointing design and implementation flaws. To this end, we provide a taxonomy of TrustZone attacks, analyze them, and more importantly derive a set of critical observations regarding their nature. We perform a critical appraisal of the vulnerabilities to shed light on their underlying causes and we deduce that their manifestation is the joint effect of several parameters that lead to this situation. The most important ones are the closed implementations, the lack of security mechanisms, the shared resource architecture, and the absence of tools to audit trusted applications. Finally, given the severity of the identified issues, we propose possible improvements that could be adopted by TEE implementers to remedy and improve the security posture of TrustZone and future research directions.
A Novel Simplified System to Estimate Lower-Limb Joint Moments during Sit-to-Stand
Authors: Hwang Seoyoon , Choi Seoyoung , Lee Yang-Soo , Kim Jonghyun
Published: January 2021

To provide effective diagnosis and rehabilitation, the evaluation of joint moments during sit-to-stand is essential. The conventional systems for the evaluation, which use motion capture cameras, are quite accurate. However, the systems are not widely used in clinics due to their high cost, inconvenience, and the fact they require lots of space. To solve these problems, some studies have attempted to use inertial sensors only, but they were still inconvenient and inaccurate with asymmetric weight-bearing. We propose a novel joint moment estimation system that can evaluate both symmetric and asymmetric sit-to-stands. To make a simplified system, the proposal is based on a kinematic model that estimates segment angles using a single inertial sensor attached to the shank and a force plate. The system was evaluated with 16 healthy people through symmetric and asymmetric weight-bearing sit-to-stand. The results showed that the proposed system (1) has good accuracy in estimating joint moments (root mean square error < 0.110 Nm/kg) with high correlation (correlation coefficient > 0.99) and (2) is clinically relevant due to its simplicity and applicability of asymmetric sit-to-stand.
Visualization Method for the Cell-Level Vesicle Transport Using Optical Flow and a Diverging Colormap
Authors: Lee Seohyun , Kim Hyuno , Higuchi Hideo , Ishikawa Masatoshi
Published: January 2021

Elucidation of cell-level transport mediated by vesicles within a living cell provides key information regarding viral infection processes and also drug delivery mechanisms. Although the single-particle tracking method has enabled clear analysis of individual vesicle trajectories, information regarding the entire cell-level intracellular transport is hardly obtainable, due to the difficulty in collecting a large dataset with current methods. In this paper, we propose a visualization method of vesicle transport using optical flow, based on geometric cell center estimation and vector analysis, for measuring the trafficking directions. As a quantitative visualization method for determining the intracellular transport status, the proposed method is expected to be universally exploited in various biomedical cell image analyses.
Finger-Vein Recognition Using Heterogeneous Databases by Domain Adaption Based on a Cycle-Consistent Adversarial Network
Authors: Noh Kyoung Jun , Choi Jiho , Hong Jin Seong , Park Kang Ryoung
Published: January 2021

The conventional finger-vein recognition system is trained using one type of database and entails the serious problem of performance degradation when tested with different types of databases. This degradation is caused by changes in image characteristics due to variable factors such as position of camera, finger, and lighting. Therefore, each database has varying characteristics despite the same finger-vein modality. However, previous researches on improving the recognition accuracy of unobserved or heterogeneous databases is lacking. To overcome this problem, we propose a method to improve the finger-vein recognition accuracy using domain adaptation between heterogeneous databases using cycle-consistent adversarial networks (CycleGAN), which enhances the recognition accuracy of unobserved data. The experiments were performed with two open databases—Shandong University homologous multi-modal traits finger-vein database (SDUMLA-HMT-DB) and Hong Kong Polytech University finger-image database (HKPolyU-DB). They showed that the equal error rate (EER) of finger-vein recognition was 0.85% in case of training with SDUMLA-HMT-DB and testing with HKPolyU-DB, which had an improvement of 33.1% compared to the second best method. The EER was 3.4% in case of training with HKPolyU-DB and testing with SDUMLA-HMT-DB, which also had an improvement of 4.8% compared to the second best method.
Shape-Sensing of Beam Elements Undergoing Material Nonlinearities
Authors: Savino Pierclaudio , Gherlone Marco , Tondolo Francesco , Greco Rita
Published: January 2021

The use of in situ strain measurements to reconstruct the deformed shape of structures is a key technology for real-time monitoring. A particularly promising, versatile and computationally efficient method is the inverse finite element method (iFEM), which can be used to reconstruct the displacement field of beam elements, plate and shell structures from some discrete strain measurements. The iFEM does not require the knowledge of the material properties. Nevertheless, it has always been applied to structures with linear material constitutive behavior. In the present work, advances are proposed to use the method also for concrete structures in civil engineering field such as bridges normally characterized by material nonlinearities due to the behavior of both steel and concrete. The effectiveness of iFEM, for simply supported reinforced concrete beam and continuous beams with load conditions that determine the yielding of reinforcing steel, is studied. In order to assess the influence on displacements and strains reconstructions, different measurement stations and mesh configurations are considered. Hybrid procedures employing iFEM analysis supported by bending moment-curvature relationship are proposed in case of lack of input data in plastic zones. The reliability of the results obtained is tested and commented on to highlight the effectiveness of the approach.
Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App
Authors: Lozano Domínguez José Manuel , Mateo Sanguino Tomás de J.
Published: January 2021

Improving road safety through artificial intelligence is now crucial to achieving more secure smart cities. With this objective, a mobile app based on the integration of the smartphone sensors and a fuzzy logic strategy to determine the pedestrian’s crossing intention around crosswalks is presented. The app developed also allows the calculation, tracing and guidance of safe routes thanks to an optimization algorithm that includes pedestrian areas on the paths generated over the whole city through a cloud database (i.e., zebra crossings, pedestrian streets and walkways). The experimentation carried out consisted in testing the fuzzy logic strategy with a total of 31 volunteers crossing and walking around a crosswalk. For that, the fuzzy logic approach was subjected to a total of 3120 samples generated by the volunteers. It has been proven that a smartphone can be successfully used as a crossing intention detector system with an accuracy of 98.63%, obtaining a true positive rate of 98.27% and a specificity of 99.39% according to a receiver operating characteristic analysis. Finally, a total of 30 routes were calculated by the proposed algorithm and compared with Google Maps considering the values of time, distance and safety along the routes. As a result, the routes generated by the proposed algorithm were safer than the routes obtained with Google Maps, achieving an increase in the use of safe pedestrian areas of at least 183%.
Predicting Cyanobacterial Blooms Using Hyperspectral Images in a Regulated River
Authors: Ahn Jung Min , Kim Byungik , Jong Jaehun , Nam Gibeom , Park Lan Joo , Park Sanghyun , Kang Taegu , Lee Jae-Kwan , Kim Jungwook
Published: January 2021

Process-based modeling for predicting harmful cyanobacteria is affected by a variety of factors, including the initial conditions, boundary conditions (tributary inflows and atmosphere), and mechanisms related to cyanobacteria growth and death. While the initial conditions do not significantly affect long-term predictions, the initial cyanobacterial distribution in water is particularly important for short-term predictions. Point-based observation data have typically been used for cyanobacteria prediction of initial conditions. These initial conditions are determined through the linear interpolation of point-based observation data and may differ from the actual cyanobacteria distribution. This study presents an optimal method of applying hyperspectral images to establish the Environmental Fluid Dynamics Code-National Institute of Environment Research (EFDC-NIER) model initial conditions. Utilizing hyperspectral images to determine the EFDC-NIER model initial conditions involves four steps that are performed sequentially and automated in MATLAB. The EFDC-NIER model is established using three grid resolution cases for the Changnyeong-Haman weir section of the Nakdong River Basin, where Microcystis dominates during the summer (July to September). The effects of grid resolution on (1) water quality modeling and (2) initial conditions determined using cumulative distribution functions are evaluated. Additionally, the differences in Microcystis values are compared when applying initial conditions using hyperspectral images and point-based evaluation data. Hyperspectral images allow detailed initial conditions to be applied in the EFDC-NIER model based on the plane-unit cyanobacterial information observed in grids, which can reduce uncertainties in water quality (cyanobacteria) modeling.
Implementation of an Online Auditory Attention Detection Model with Electroencephalography in a Dichotomous Listening Experiment
Authors: Baek Seung-Cheol , Chung Jae Ho , Lim Yoonseob
Published: January 2021

Auditory attention detection (AAD) is the tracking of a sound source to which a listener is attending based on neural signals. Despite expectation for the applicability of AAD in real-life, most AAD research has been conducted on recorded electroencephalograms (EEGs), which is far from online implementation. In the present study, we attempted to propose an online AAD model and to implement it on a streaming EEG. The proposed model was devised by introducing a sliding window into the linear decoder model and was simulated using two datasets obtained from separate experiments to evaluate the feasibility. After simulation, the online model was constructed and evaluated based on the streaming EEG of an individual, acquired during a dichotomous listening experiment. Our model was able to detect the transient direction of a participant’s attention on the order of one second during the experiment and showed up to 70% average detection accuracy. We expect that the proposed online model could be applied to develop adaptive hearing aids or neurofeedback training for auditory attention and speech perception.
Binary Amplitude Reflection Gratings for X-ray Shearing and Hartmann Wavefront Sensors
Authors: Goldberg Kenneth A. , Wojdyla Antoine , Bryant Diane
Published: January 2021

New, high-coherent-flux X-ray beamlines at synchrotron and free-electron laser light sources rely on wavefront sensors to achieve and maintain optimal alignment under dynamic operating conditions. This includes feedback to adaptive X-ray optics. We describe the design and modeling of a new class of binary-amplitude reflective gratings for shearing interferometry and Hartmann wavefront sensing. Compact arrays of deeply etched gratings illuminated at glancing incidence can withstand higher power densities than transmission membranes and can be designed to operate across a broad range of photon energies with a fixed grating-to-detector distance. Coherent wave-propagation is used to study the energy bandwidth of individual elements in an array and to set the design parameters. We observe that shearing operates well over a ±10% bandwidth, while Hartmann can be extended to ±30% or more, in our configuration. We apply this methodology to the design of a wavefront sensor for a soft X-ray beamline operating from 230 eV to 1400 eV and model shearing and Hartmann tests in the presence of varying wavefront aberration types and magnitudes.
A Statistical Approach to Analyzing Engineering Estimates and Bids
Authors: Farshidpour Roshanak , Negoro Kiana , Tehrani Fariborz M.
Published: January 2021

This paper introduces a methodology to assess the accuracy of engineering estimates in relation to the final project cost. The objective of this assessment is to develop a comprehensive approach towards obtaining a more reliable estimate of the project cost. This approach relies on the review of a synthesis of literature, which provides a basis for determining key components in the estimation of the capital cost of a project. A systematic review of existing data for selected projects was obtained as well. Employed data cover sampled public transportation projects to maintain existing infrastructure within selected geographical location and specified time. Enhanced analysis of existing data through statistical models was employed to indicate potential measures for prevention of errors in the estimate due to uncertainties in the time, cost, and method of construction. The comparison of results with similar findings from past research shows the effectiveness of presented methodologies and opportunities to enhance statistical analyses of bids and engineering estimates. Conclusions enable project managers to address uncertainties in the bidding process and enhance financial sustainability of projects within specific programs.
Assessing and Predicting the Impact of Multi-Scenario Land Use Changes on the Ecosystem Service Value: A Case Study in the Upstream of Xiong’an New Area, China
Authors: Wang Zhiyin , Cao Jiansheng
Published: January 2021

The evaluation of ecosystem service value has become the basis of ecological protection, ecological regionalization, and ecological compensations. Land use changes have taken place due to several natural and anthropogenic reasons, significantly influencing the ecosystem services value (ESV). In this study, we used an interactive coupling model that simulates future land use changes and the equivalent coefficient table method to predict and evaluate the ecosystem service value in the upstream of Xiong’an New Area in 2035, and we quantitatively calculated the impact of land use changes on the ecosystem service value under four future scenarios. The results indicate that from 2015 to 2035, the ecosystem service value in the production scenario and life scenario decreased significantly by CNY 1635.39 million and 561.95 million, respectively, and the areas where the ESV decreased mainly appeared in river banks and surrounding areas of towns. The conversion of forest land to cultivated land and the conversion of grassland to construction land are the main reasons for the reduction of the ecosystem service value in the production scenario and life scenario, respectively. The ecosystem service value in the ecological scenario increased significantly by CNY 2550.59 million, and the conversion of grassland to waters is the main reason for the increase in ecosystem service value, with a contribution rate of 73.89%. Moreover, due to the trade-off between ecosystem services, the overall change of ecosystem service value in the current scenario is not obvious. In conclusion, strictly controlling the scale of construction land, strengthening the management and protection of water resources, and expanding the afforestation scale may improve the ecosystem service value of the upstream Xiong’an New Area in the future.
How to Achieve Positive Energy Districts for Sustainable Cities: A Proposed Calculation Methodology
Authors: Gabaldón Moreno Andrea , Vélez Fredy , Alpagut Beril , Hernández Patxi , Sanz Montalvillo Cecilia
Published: January 2021

In this paper, a methodology for calculating the energy balance at the district level and energy performance of those districts aspiring to become a Positive Energy District (PED) is proposed. PEDs are understood as districts that achieve a positive energy balance on an annual basis by means of exporting more energy than is consumed within their limits. The main issue to standardize the concept, besides which characteristics should be considered, is that current standards to calculate an energy balance are not applied at the district level. This paper reviews the current standards and adapts them to propose an energy balance calculation methodology. Calculation of an energy balance at the district level is complex since it includes several parameters, such as which loads (or elements) should be included, which renewable energy technologies should be considered on-site production, and which primary energy factors should be used. The proposed methodology is thought to help cities at the design stage of a district and to evaluate its annual energy balance. The methodology is performed in eight steps, and all the needed assumptions that affect the calculation of the annual energy balance are discussed in each step.
Analyzing Urban Public Policies of the City of Ensenada in Mexico Using an Attractive Land Footprint Agent-Based Model
Authors: Sandoval-Félix Javier , Castañón-Puga Manuel , Gaxiola-Pacheco Carelia Guadalupe
Published: January 2021

The Urban Development Plan of the city of Ensenada, México (UDPE) states four major strategic projects, one of which mandates to “Acquire and enable new land reserves and expand opportunities for economic and social development.” This is of vital importance given the large number of vacant lots that perforates the urban surface in contrast to the physical limitations of growth demarcated by hill areas of a steep slope, which forces a sustainable use of the land. These are important growth challenges, affecting aspects such as the real estate market, in particular, that related to industrial activities, which has not matured due to outdated planning practice, resulting in industrial sprawl. This paper shows an institutional effort to analyze the UDPE from a Complex Systems approach with an Agent-Based Model, adapting Peter Allen’s concept of Structural Attractor. This attraction results from an agglomeration of UDPE’s regulatory attributes and real estate investor’s land-acquisition criteria that affects the spatial behavior of vacant land that is attractive for industrial activity. Unlike physical land uses, these attractive zones emerge, grow, move, diminish, and emerge again over time in the form of Attractive Land Footprints. Understanding these phenomena is vital for local policymakers. The findings indicate that the current Urban Plan is ill-suited regarding current industry development expectations. The model also showed unexpected roles played by population density, road network, and residential land use in Attractive Land Footprint dynamics, acting as a thought-provoking process for policymakers and real estate investors, as it helped them to understand Ensenada’s industry phenomena.
Potential for Sustainable Development in the Southeastern Spanish Region of Guadix
Authors: Álvarez-Lorente Tamara , Entrena-Durán Francisco
Published: January 2021

The Southeastern Spanish Region of Guadix is a mainly agrarian territory located in the Granada province, which is in demographic decline and has low economic dynamism. Reversing such a difficult socioeconomic situation requires the implementation of policies capable of promoting demographic revitalization and fruitfully exploiting potential for sustainable development in the zone. Such policies must be based on an appropriate diagnosis of the existing problems. In order to provide elements to make said diagnosis, this research combines the use of quantitative and qualitative methods. Quantitatively, the evolution of demographic dynamics in the region have been analyzed, as well as its levels of occupation, education, its economic situation, or its environmental conditions. In this regard, correlation analysis, factorial analysis, and clustering have been completed with the aim of revealing internal territorial imbalances. A series of qualitative interviews with key actors has also been conducted. Finally, given the little success of development programs applied to date, among other things, it is concluded that a greater involvement of local actors in said programs is needed. Thus, these actors have to be involved in development policies, which in turn must take into account the socioeconomic, cultural, environmental, and geological resources available in the area.
Hadron–Quark Phase Transition in the SU (3) Local Nambu–Jona-Lasinio (NJL) Model with Vector Interaction
Authors: Alaverdyan Grigor
Published: January 2021

We study the hadron–quark hybrid equation of state (EOS) of compact-star matter. The Nambu–Jona-Lasinio (NJL) local SU (3) model with vector-type interaction is used to describe the quark matter phase, while the relativistic mean field (RMF) theory with the scalar-isovector δ-meson effective field is adopted to describe the hadronic matter phase. It is shown that the larger the vector coupling constant GV, the lower the threshold density for the appearance of strange quarks. For a sufficiently small value of the vector coupling constant, the functions of the mass dependence on the baryonic chemical potential have regions of ambiguity that lead to a phase transition in nonstrange quark matter with an abrupt change in the baryon number density. We show that within the framework of the NJL model, the hypothesis on the absolute stability of strange quark matter is not realized. In order to describe the phase transition from hadronic matter to quark matter, Maxwell’s construction is applied. It is shown that the greater the vector coupling, the greater the stiffness of the EOS for quark matter and the phase transition pressure. Our results indicate that the infinitesimal core of the quark phase, formed in the center of the neutron star, is stable.
Unpaired Image Denoising via Wasserstein GAN in Low-Dose CT Image with Multi-Perceptual Loss and Fidelity Loss
Authors: Yin Zhixian , Xia Kewen , He Ziping , Zhang Jiangnan , Wang Sijie , Zu Baokai
Published: January 2021

The use of low-dose computed tomography (LDCT) in medical practice can effectively reduce the radiation risk of patients, but it may increase noise and artefacts, which can compromise diagnostic information. The methods based on deep learning can effectively improve image quality, but most of them use a training set of aligned image pairs, which are difficult to obtain in practice. In order to solve this problem, on the basis of the Wasserstein generative adversarial network (GAN) framework, we propose a generative adversarial network combining multi-perceptual loss and fidelity loss. Multi-perceptual loss uses the high-level semantic features of the image to achieve the purpose of noise suppression by minimizing the difference between the LDCT image and the normal-dose computed tomography (NDCT) image in the feature space. In addition, L2 loss is used to calculate the loss between the generated image and the original image to constrain the difference between the denoised image and the original image, so as to ensure that the image generated by the network using the unpaired images is not distorted. Experiments show that the proposed method performs comparably to the current deep learning methods which utilize paired image for image denoising.
Influence of Mach Number of Main Flow on Film Cooling Characteristics under Supersonic Condition
Authors: Zhang Bo , Chen Yuan-Xiang , Wang Zhi-guo , Li Ji-Quan , Ji Hong-hu
Published: January 2021

The flow and heat transfer characteristics of a film jet inclined to different supersonic situations with a varying Mach number of the main flow were numerically investigated. In supersonic situations, complicated waves are generated by the obstacle of the film jet. In this work, extra pressure is exerted onto the film jet, causing better film attachment to the wall. The strengthening of attachment decreases mixing between the main flow and film jet, causing better film cooling. We observed multi-interfacial layered structures caused by the film jet under the complicated effect of shock waves. At the interfaces of the film jet and shock waves, additional pressure is exerted on the film towards the wall. The pressure increases as the Mach number of the main flow increases and contributes to the increased adhesion of the gas film, which causes the cooling enhancement under a supersonic condition. In the vicinity of the film hole exit, a local low pressure region is formed under the influence of the supersonic main flow. An aerodynamic convergent–divergent state was formed in the film hole, devastating the state of supersonic congestion of the film hole and further enhancing the film cooling effect.
Implementing a Symmetric Lightweight Cryptosystem in Highly Constrained IoT Devices by Using a Chaotic S-Box
Authors: Alshammari Badr M. , Guesmi Ramzi , Guesmi Tawfik , Alsaif Haitham , Alzamil Ahmed
Published: January 2021

In the Internet of Things (IoT), a lot of constrained devices are interconnected. The data collected from those devices can be the target of cyberattacks. In this paper, a lightweight cryptosystem that can be efficiently implemented in highly constrained IOT devices is proposed. The algorithm is mainly based on Advanced Encryption Standard (AES) and a new chaotic S-box. Since its adoption by the IEEE 802.15.4 protocol, AES in embedded platforms have been increasingly used. The main cryptographic properties of the generated S-box have been validated. The randomness of the generated S-box has been confirmed by the NIST tests. Experimental results and security analysis demonstrated that the cryptosystem can, on the one hand, reach good encryption results and respects the limitation of the sensor’s resources, on the other hand. So the proposed solution could be reliably applied in image encryption and secure communication between networked smart objects.
A Self-Assembling Ferritin Nanoplatform for Designing Classical Swine Fever Vaccine: Elicitation of Potent Neutralizing Antibody
Authors: Zhao Zekai , Chen Xinghua , Chen Yibao , Li Hui , Fang Kui , Chen Huanchun , Li Xiangmin , Qian Ping
Published: January 2021

Protein-based self-assembling nanoplatforms exhibit superior immunogenicity compared with soluble antigens. Here, we present a comprehensive vaccine strategy for displaying classical swine fever virus (CSFV) E2 glycoprotein on the surface of ferritin (fe) nanocages. An E2-specific blocking antibody assay showed that the blocking rates in pE2-fe/Gel02 (84.3%) and a half-dose cohort of E2-fe/Gel02 (81.9%) were significantly higher (p < 0.05) than that in a ferritin-free cohort of pE2/Gel02 (62.7%) at 21 days post immunization (dpi) in vivo. Furthermore, quantitation of neutralizing potency revealed that a highly significant difference (p < 0.001) was observed between the pE2-fe/Gel02 cohort (1:32, equivalent to live-attenuated strain C at 1:32) and the pE2/Gel02 cohort (1:4) at 21 dpi. Moreover, the innate immune cytokines of IL-4 and IFN-γ activated by the half-dose (20 μg) cohort of E2-fe/Gel02 were equivalent to those elicited by the full dose (40 μg) of purified E2 in the pE2/Gel02 cohort at most time points. In conclusion, we successfully obtained an antigen-displaying E2-ferritin nanoplatform and confirmed high ferritin-assisted humoral and cellular immunities. Our results provided a novel paradigm of self-assembling nanovaccine development for the defense and elimination of potentially pandemic infectious viral pathogens.
Contributo da formação MRMI para a organização da resposta em situações de exceção
Authors: Vale Luís , Faria Rui
Published: January 2021

A catástrofe natural que assolou o arquipélago da Madeira em 2010 evidenciou a necessidade de várias instituições da Região procurar uma formação reconhecida internacionalmente no Ensino e Treino em Catástrofe. Essa formação veio da Escandinávia, Medical Response to Major Incidents – MRMI, criada pelo Prof. Sten Lennquist, ex-Presidente da ESTES, sociedade europeia onde está subsidiado o Board Internacional do MRMI. Na Madeira, um grupo de médicos e enfermeiros do SESARAM fazem a formação em 2010 e procuram desde logo alargar o leque de formadores na área, a nível regional e nacional, sendo hoje o grupo de instrutores constituído por profissionais de diversas áreas do socorro, reconhecidos internacionalmente. Com uma periodicidade bi-anual e com várias deslocações ao Continente e Açores, de norte a sul, num total de 21 cursos, mais de 1500 agentes de várias entidades da resposta, das mais variadíssimas áreas profissionais, tiveram formação em catástrofe, procurando-se munir estes profissionais de conhecimentos básicos a aplicar na resposta multidisciplinar desejada em situações de exceção. O lema “Treinar mais, para fazer melhor” é uma verdade indiscutível, na tentativa de todos usarem uma mesma linguagem no manuseio da Catástrofe, tornando assim o MRMI numa possível metodologia de Treino, adotada a nível regional e nacional, na sua perfeita simbiose com a política de socorro nacional.
Uma visão global sobre a gestão do risco de cheias torrenciais na Madeira. Perspetivas e desafios
Authors: Lopes Sérgio
Published: January 2021

O presente capítulo consiste numa tentativa de apresentar uma revisão do processo de gestão do risco de aluviões na Ilha da Madeira, onde as bacias hidrográficas são muito suscetíveis a uma mistura de processos hidrogeomorfológicos complexos, marcados pela formação de escoamento turbulento, com origem nos ribeiros de montanha. O Plano de Gestão de Riscos de Inundações, que está em vigor desde 2017, preconiza um conjunto vasto de medidas de redução do risco, algumas das quais implementadas nos anos subsequentes à aluvião de fevereiro de 2010, e sustentadas no Estudo de Avaliação do Risco de Aluvião (Almeida et al., 2010). Destaca-se a importância de adotar uma estratégia de gestão integrada do risco, que requer coordenação e vigilância constante, num processo de incorporação de medidas não estruturais e estruturais. As primeiras englobam medidas de conservação e uso do solo, o ordenamento do território e a implementação de sistemas tanto de prevenção, como de alerta e de seguros (Ramos, 2009), ao passo que as medidas estruturais correspondem a intervenções de engenharia de controlo dos processos de produção, transporte e deposição da carga sólida transportada pelos cursos de água, mencionando-se a regularização fluvial nas áreas urbanas e a construção de barreiras descontínuas de retenção do caudal sólido grosseiro nos cursos de água principais. Os programas de povoamento e repovoamento florestal nas cabeceiras das bacias, não só favorecem a conservação do solo, mas também, representam uma medida estruturante para a sustentabilidade da bacia hidrográfica. Nesta perspetiva de gestão integrada deve ser dada igual importância a outros aspetos, designadamente: a) sensibilização e educação da população para a redução do risco de catástrofe; b) manutenção dos programas de monitorização das condições de funcionamento das bacias hidrográficas de maior vulnerabilidade; c) a investigação e o aprofundamento dos conhecimentos sobre as aluviões. Neste contexto, considera-se importante desenvolver uma metodologia de coordenação regional da estratégia de gestão do risco, a aplicar nos projetos e organizações, não apenas para responder às catástrofes de cheia, mas sobretudo para as antecipar.
Vjera i pastoral
Authors: Čondić Alojzije
Published: January 2021

U osnovne pastoralne izazove koje nameće sekularizacija ulazi vjerska ravnodušnost, odnosno smanjenje vjerskoga života i nedostatka osjećaja crkvenosti. Ako se uzme da je vjera put kojim se može spasiti, onda se vjera i njezina primjena u životu odnosi na bît Crkve i njezina poslanja. Sukladno tomu pisac, teološko-pastoralnim načinom evanđeoske prosudbe, na temelju znanstvenih istraživanja, povezuje odnos vjere i pastorala u crkvenom životu, u Europi i Hrvat­skoj, a potom govori o uzrocima i razlozima smanjenja vjere i crkvenosti. Raščlanjujući kulturno surječje hrvatskoga društva i pastoralni rad, govori o vjeri kao milosnom daru, za koji treba stvarati plemenito ozračje, da bi se što plodonosnije umnožila u vjernicima. Potom autor predlaže pastoralne smjernice o nužnosti pastoralne metanoje i načinu produbljenja vjere i crkvenosti.