bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges of Managing Maritime Cultural Heritage in Asia in the Face of Climate Change
Authors: Daly Patrick , Feener R. Michael , Ishikawa Noboru , Mujah Ibrahim , Irawani Maida , Hegyi Alexandru , Baranyai Krisztina , Majewski Jedrzej , Horton Benjamin
Published: May 2022

Changing weather patterns, increasing frequency and intensity of natural hazards, and rising sea levels associated with global climate change have the potential to threaten cultural heritage sites worldwide. This is especially the case for maritime heritage sites located in the low-lying coastal and delta regions of Asia. Maritime heritage can reflect both highly localized cultural products based on the coupling of people and maritime environments and the historic footprints of complex maritime networks that connect people, ideas, and material over vast distances, creating unique cultural spheres. Furthermore, maritime heritage sites potentially serve as or contain records of how past societies have been impacted by and adapted to past environmental stress. Therefore, their degradation threatens local/regional/global cultural patrimony as well as evidence of human resilience and fragility in the face of environmental change. This makes a strong case for urgent preservation. However, the possible damage caused by climate change and the scale of vulnerable maritime heritage pose seemingly insurmountable challenges. In this paper, we present the ways in which maritime heritage sites across Asia are vulnerable to environmental stresses, such as changing sea levels, coastal erosion, flooding, and storm surges. Our objective is to draw upon our experience documenting endangered cultural heritage across South and Southeast Asia to illustrate that there are unique conceptual and practical characteristics of maritime heritage that complicate effective management and conservation efforts on the scale required to prevent massive loss by climate change. We conclude by stressing the need to reconceptualize debates about the custody and stewardship of maritime heritage and the urgency of employing a wide range of innovative preservation solutions to ensure maritime patrimony is not lost to the rising tides.
Effects of Additive and Roasting Processes on Nitrogen Removal from Aluminum Dross
Authors: Lv Shuai-Shuai , Zhang Yu , Ni Hong-Jun , Wang Xing-Xing , Wu Wei-Yang , Lu Chun-Yu
Published: May 2022

Taking high nitrogen aluminum dross as the research object, the effects of the additives sodium carbonate and cryolite and the roasting process on the denitrification effect of aluminum dross were studied. The principle of additive denitrification was studied by XRD, SEM and TG-DSC. The experimental results show that sodium carbonate and cryolite can quickly reduce the content of aluminum nitride in aluminum dross. The optimum denitrification process parameters were also obtained simultaneously. When the mass ratio of cryolite to aluminum dross was 0.4, the roasting temperature was 900 °C, and the roasting time was 3 h, the denitrification degree could reach 96.19%. When the mass ratio of sodium carbonate to aluminum dross was 0.8, the roasting temperature was 1000 °C, and the roasting time was 4 h, the denitrification degree could reach 91.32%. This study provides a reference for the non-harmful treatment of high nitrogen aluminum dross.
Nanofluid Structural Forces Alter Solid Wetting, Enhancing Oil Recovery
Authors: Wu Pingkeng , Nikolov Alex D. , Wasan Darsh T.
Published: May 2022

Nanofluids have attracted significant research interest for their promising application in enhanced oil recovery. One striking feature leading to the outstanding efficiency of nanofluids in enhanced oil recovery is the structure of nanoparticles, which induces oscillatory structural forces in the confined space between fluid–fluid interfaces or air–liquid and liquid–solid interfaces. To promote the understanding of the oscillatory structural forces and their application in enhanced oil recovery, we reviewed the origin and theory of the oscillatory structural forces, factors affecting their magnitude, and the experimental techniques demonstrating their impacts on enhanced oil recovery. We also reviewed the methods, where the benefits of nanofluids in enhanced oil recovery provided by the oscillatory structural forces are directly manifested. The oscillatory structural forces promote the wetting and spreading of nanofluids on solid surfaces, which ultimately enhances the separation of oil from the reservoir. Some imbibition tests demonstrated as much as 50% increased oil recovery, compared to the cases where the oscillatory structural forces were absent.
Improved Bidirectional GAN-Based Approach for Network Intrusion Detection Using One-Class Classifier
Authors: Xu Wen , Jang-Jaccard Julian , Liu Tong , Sabrina Fariza , Kwak Jin
Published: May 2022

Existing generative adversarial networks (GANs), primarily used for creating fake image samples from natural images, demand a strong dependence (i.e., the training strategy of the generators and the discriminators require to be in sync) for the generators to produce as realistic fake samples that can “fool” the discriminators. We argue that this strong dependency required for GAN training on images does not necessarily work for GAN models for network intrusion detection tasks. This is because the network intrusion inputs have a simpler feature structure such as relatively low-dimension, discrete feature values, and smaller input size compared to the existing GAN-based anomaly detection tasks proposed on images. To address this issue, we propose a new Bidirectional GAN (Bi-GAN) model that is better equipped for network intrusion detection with reduced overheads involved in excessive training. In our proposed method, the training iteration of the generator (and accordingly the encoder) is increased separate from the training of the discriminator until it satisfies the condition associated with the cross-entropy loss. Our empirical results show that this proposed training strategy greatly improves the performance of both the generator and the discriminator even in the presence of imbalanced classes. In addition, our model offers a new construct of a one-class classifier using the trained encoder–discriminator. The one-class classifier detects anomalous network traffic based on binary classification results instead of calculating expensive and complex anomaly scores (or thresholds). Our experimental result illustrates that our proposed method is highly effective to be used in network intrusion detection tasks and outperforms other similar generative methods on two datasets: NSL-KDD and CIC-DDoS2019 datasets.
Twist Angle-Dependent Interlayer Exciton in MoS2 Bilayers Revealed by Room-Temperature Reflectance
Authors: Xiong Lei , Tang Tianhong , Fan Xiaoyue , Liu Haiyang , Zhu Peng , Zhang Xiaolan , Qiao Wei , Wang Qinsheng , Wang Zhiwei , Niu Binghui , Wang Gang
Published: May 2022

In 2H stacking bilayer MoS2, the exciton with an interlayer nature has been evidenced due to the hybridization of hole states among both layers. The transition energy of this interlayer exciton is located between the A and B excitons. In this work, we investigate the evolution of optical properties in stacking MoS2 bilayers with the twisted angles ranging from 0° to 60°, especially focusing on the interlayer exciton. The clear modulations of the exciton responses are observed by the room-temperature reflectance. The interlayer exciton transition is observed in the artificial stacking bilayer MoS2 with the twisted angle around 60°. We found that the interlayer exciton is very sensitive to the twisted angle. Once the stacking angle deviates the 2H stacking by a few degrees, the interlayer transition is quenched. This is due to the bilayer symmetry and interlayer coupling of this unique system.
Metal-Organic Framework vs. Coordination Polymer—Influence of the Lanthanide on the Nature of the Heteroleptic Anilate/Terephtalate 3D Network
Authors: Oggianu Mariangela , Manna Fabio , Ashoka Sahadevan Suchithra , Avarvari Narcis , Abhervé Alexandre , Mercuri Maria Laura
Published: May 2022

Metal-organic frameworks (MOFs), whose definition has been regularly debated, are a sub-class of coordination polymers (CPs) which may feature both an overall 3D architecture and some degree of porosity. In this context, MOFs based on lanthanides (Ln-MOFs) could find many applications due to the combination of sorption properties and magnetic/luminescent behaviors. Here we report rare examples of 3D Ln-CPs based on anilate linkers, obtained under solvothermal conditions using a heteroleptic strategy. The three compounds of formula [Yb2(μ-ClCNAn)2(μ-F4BDC)(H2O)4]·(H2O)3 (1), [Er2(μ-ClCNAn)2(μ-F4BDC)(H2O)4]·(H2O)4 (2) and [Eu2(μ-ClCNAn)2(μ-F4BDC)(H2O)6] (3) have been characterized by single-crystal X-ray diffraction, thermogravimetric analysis, and optical measurements. Structural characterization revealed that compounds 1 and 2 present an interesting MOF architecture with extended rectangular cavities which are only filled with water molecules. On the other hand, compound 3 shows a much more complex topology with no apparent cavities. We discuss here the origins of such differences and highlight the crucial role of the Ln(III) ion nature for the topology of the CP. Compounds 1 and 2 now offer a playground to investigate the possible synergy between gas/solvent sorption and magnetic/luminescent properties of Ln-MOFs.
Wideband Collinear Phase Matching in Cubic Semiconductors via the Linear Electro-Optic Effect: A Theoretical Study
Authors: Zhong Kai , Li Fangjie , Qiao Hongzhan , Zhang Xianzhong , Xu Degang , Yao Jianquan
Published: May 2022

In order to achieve collinear phase-matched nonlinear optical frequency conversion in cubic crystals, a novel method to induce and modulate the birefringence based on the linear electro-optic effect was studied. Taking terahertz generation with ZnTe and CdTe crystals of the 4¯3m point group as an example, an external electric field provided the freedom to realize perfect phase matching (PM) in a wide bandwidth up to 2 THz for difference frequency generation, with monochromatic optical waves at around 800 nm and 1010 nm, respectively. Theoretical simulations showed that such a method helps to extend the terahertz frequency, enhance the conversion efficiency, and alleviate the limitation on the pump wavelength, which is highly favorable for nonlinear optical uses of cubic crystals. Simultaneous wideband terahertz generation pumped by ultrashort laser pulses via optical rectification or difference frequency mixing was also discussed, indicating that an electric field can be used to modulate the PM characteristics without changing the group velocity-matching condition. Tuning the nonlinear interaction by an applied voltage is fast, robust, and convenient compared to other approaches. In addition, the linear electro-optic effect can make the nonlinear crystal a compact and high-speed terahertz amplitude modulator, which has great potential in radar, communication, imaging, etc.
Processes of the Reliability and Degradation Mechanism of High-Power Semiconductor Lasers
Authors: Song Yue , Lv Zhiyong , Bai Jiaming , Niu Shen , Wu Zibo , Qin Li , Chen Yongyi , Liang Lei , Lei Yuxin , Jia Peng , Shan Xiaonan , Wang Lijun
Published: May 2022

High-power semiconductor lasers have attracted widespread attention because of their small size, easy modulation, and high conversion efficiency. They play an important role in national economic construction and national defense construction, including free-space communication; industrial processing; and the medical, aerospace, and military fields, as well as other fields. The reliability of high-power semiconductor lasers is the key point of the application system. Higher reliability is sought in the military defense and aerospace fields in particular. Reliability testing and failure analysis help to improve the performance of high-power semiconductor lasers. This article provides a basis for understanding the reliability issues of semiconductor lasers across the whole supply chain. Firstly, it explains the failure modes and causes of failure in high-power semiconductor lasers; this article also summarizes the principles and application status of accelerated aging experiments and lifetime evaluation; it also introduces common techniques used for high-power semiconductor laser failure analysis, such as the electron beam-induced current (EBIC) technique and the optical beam-induced current (OBIC) technique, etc. Finally, methods used to improve the reliability of high-power semiconductor lasers are proposed in terms of the preparation process, reliability screening, and method application.
Bias-Voltage Dependence of Tunneling Decay Coefficient and Barrier Height in Arylalkane Molecular Junctions with Graphene Contacts as a Protecting Interlayer
Authors: Im Kyungjin , Seo Dong-Hyoup , Song Hyunwook
Published: May 2022

We studied a molecular junction with arylalkane self-assembled monolayers sandwiched between two graphene contacts. The arrangement of graphene-based molecular junctions provides a stable device structure with a high yield and allows for extensive transport measurements at 78 K. We observed a temperature-independent current density–voltage (J–V) characteristic and the exponential dependency of the current density on the molecular length, proving that the charge transport occurs by non-resonant tunneling through the molecular barrier. Based on the Simmons model, the bias-voltage dependence of the decay coefficient and barrier height was extracted from variable-length transport characterizations. The J–V data measured were simulated by the Simmons model, which was modified with the barrier lowering induced by the bias voltage. Indeed, there isno need for adjustable fitting parameters. The resulting simulation was in remarkable consistency with experimental measurements over a full bias range up to |V| ≤ 1.5 V for the case of graphene/arylalkane/graphene heterojunctions. Our findings clearly showed the demonstration of stable and reliable molecular junctions with graphene contacts and their intrinsic charge transport characteristics, as well as justifying the application of the voltage-induced barrier lowering approximation to the graphene-based molecular junction.
Full-Length Transcriptome Sequencing Analysis and Characterization of Gene Isoforms Involved in Flavonoid Biosynthesis in the Seedless Kiwifruit Cultivar ‘Chengxiang’ (Actinidia arguta)
Authors: Jia Yun , Wu Yong-Peng , Wang Feng-Wei , Zhang Lei , Yu Gang , Wang Ya-Ling , Zhang Ying
Published: May 2022

Kiwifruit an important horticultural crop that is widely cultivated and is known as the king of fruits. Recently, a new seedless kiwifruit cultivar, ‘Chengxiang’ (Actinidia arguta), was discovered by field transplantation. It exhibited distinguishable characteristics such as parthenocarpy, and a unique flavor and appearance when compared to other cultivated type. Flavonoids are known to play an important role in fertility and parthenocarpy in plants. However, the genes responsible for flavonoid biosynthesis in seedless kiwifruit remain largely unknown. Especially, chalcone synthase (CHS), as a key enzyme catalyzing the first committed step in the flavonoid pathway, remains a mystery. In this study, we combined a full-length transcriptome survey by PacBio single-molecule real-time (SMRT) sequencing, CHS gene family analysis, and analysis of the gene expression involved in flavonoid pathways to further enhance the understanding of parthenocarpy. Based on SMRT, we obtained 80,615 high-quality full-length consensus transcripts. In total, 52,406 (90.79%) transcripts were functionally annotated, and more than 80% of the transcripts were longer than 1Kb. Among them, 39,117 (74.64%) transcripts were assigned to GO terms, the majority of which were associated with the cell (19,089, 48.80%) and metabolic process (19,859, 50.77%). Furthermore, 25,289 (48.26%) transcripts were mapped into 129 KEGG pathways. We identified the majority of putative genes as being involved in the flavonoid biosynthesis pathway, including 14 key enzyme gene families, such as CHS, chalcone isomerase (CHI), flavonol synthase (FLS), and so on. Moreover, we also identified 13 CHS genes and characterized the CHS gene family in seedless kiwifruit. We further evaluated the expression pattern of 10 flavonoid-related key enzyme genes in flowers using quantitative real-time PCR. This is the first time that the full-length transcriptome have been studied in seedless kiwifruit, and the findings enhance our understanding the molecular mechanisms of parthenocarpy.
A Socioeconomic Dataset of the Risk Associated with the 1% and 0.2% Return Period Stillwater Flood Elevation under Sea-Level Rise for the Northern Gulf of Mexico
Authors: Del Angel Diana , Yoskowitz David , Bilskie Matthew , Hagen Scott
Published: May 2022

Storm surge flooding can cause significant damage to coastal communities. In addition, coastal communities face an increased risk of coastal hazards due to sea-level rise (SLR). This research developed a dataset to communicate the socioeconomic consequences of flooding within the 1% and 0.2% Annual Exceedance Probability Floodplain (AEP) under four SLR scenarios for the Northern Gulf of Mexico region. Assessment methods primarily used HAZUS-MH software, a GIS-based modeling tool developed by the Federal Emergency Management Agency in the United States, to estimate natural disasters’ physical, economic, and social impacts. This dataset consists of 29 shapefiles containing seven different measures of storm surge inundation impacts under SLR (including building damage, displaced people and shelter needs, road exposure, essential facilities, wastewater treatment plants, bridges, and vehicle damage). The data is publicly available under the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC).
Segmentation of Dental Restorations on Panoramic Radiographs Using Deep Learning
Authors: Rohrer Csaba , Krois Joachim , Patel Jay , Meyer-Lueckel Hendrik , Rodrigues Jonas Almeida , Schwendicke Falk
Published: May 2022

Convolutional Neural Networks (CNNs) such as U-Net have been widely used for medical image segmentation. Dental restorations are prominent features of dental radiographs. Applying U-Net on the panoramic image is challenging, as the shape, size and frequency of different restoration types vary. We hypothesized that models trained on smaller, equally spaced rectangular image crops (tiles) of the panoramic would outperform models trained on the full image. A total of 1781 panoramic radiographs were annotated pixelwise for fillings, crowns, and root canal fillings by dental experts. We used different numbers of tiles for our experiments. Five-times-repeated three-fold cross-validation was used for model evaluation. Training with more tiles improved model performance and accelerated convergence. The F1-score for the full panoramic image was 0.7, compared to 0.83, 0.92 and 0.95 for 6, 10 and 20 tiles, respectively. For root canals fillings, which are small, cone-shaped features that appear less frequently on the radiographs, the performance improvement was even higher (+294%). Training on tiles and pooling the results thereafter improved pixelwise classification performance and reduced the time to model convergence for segmenting dental restorations. Segmentation of panoramic radiographs is biased towards more frequent and extended classes. Tiling may help to overcome this bias and increase accuracy.
Concordance between SIVA, IVAN, and VAMPIRE Software Tools for Semi-Automated Analysis of Retinal Vessel Caliber
Authors: Mautuit Thibaud , Cunnac Pierre , Cheung Carol Y. , Wong Tien Y. , Hogg Stephen , Trucco Emanuele , Daien Vincent , MacGillivray Thomas J. , Labarère José , Chiquet Christophe
Published: May 2022

We aimed to compare measurements from three of the most widely used software packages in the literature and to generate conversion algorithms for measurement of the central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) between SIVA and IVAN and between SIVA and VAMPIRE. We analyzed 223 retinal photographs from 133 human participants using both SIVA, VAMPIRE and IVAN independently for computing CRAE and CRVE. Agreement between measurements was assessed using Bland–Altman plots and intra-class correlation coefficients. A conversion algorithm between measurements was carried out using linear regression, and validated using bootstrapping and root-mean-square error. The agreement between VAMPIRE and IVAN was poor to moderate: The mean difference was 20.2 µm (95% limits of agreement, LOA, −12.2–52.6 µm) for CRAE and 21.0 µm (95% LOA, −17.5–59.5 µm) for CRVE. The agreement between VAMPIRE and SIVA was also poor to moderate: the mean difference was 36.6 µm (95% LOA, −12.8–60.4 µm) for CRAE, and 40.3 µm (95% LOA, 5.6–75.0 µm) for CRVE. The agreement between IVAN and SIVA was good to excellent: the mean difference was 16.4 µm (95% LOA, −4.25–37.0 µm) for CRAE, and 19.3 µm (95% LOA, 0.09–38.6 µm) for CRVE. We propose an algorithm converting IVAN and VAMPIRE measurements into SIVA-estimated measurements, which could be used to homogenize sets of vessel measurements obtained with different software packages.
A Machine Learning Approach to Screen for Otitis Media Using Digital Otoscope Images Labelled by an Expert Panel
Authors: Sandström Josefin , Myburgh Hermanus , Laurent Claude , Swanepoel De Wet , Lundberg Thorbjörn
Published: May 2022

Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning would be valuable for this prevalent disease. This study investigated the performance of a convolutional neural network in screening for otitis media using digital otoscopic images labelled by an expert panel. Methods: Five experienced otologists diagnosed 347 tympanic membrane images captured with a digital otoscope. Images with a majority expert diagnosis (n = 273) were categorized into three screening groups Normal, Pathological and Wax, and the same images were used for training and testing of the convolutional neural network. Expert panel diagnoses were compared to the convolutional neural network classification. Different approaches to the convolutional neural network were tested to identify the best performing model. Results: Overall accuracy of the convolutional neural network was above 0.9 in all except one approach. Sensitivity to finding ears with wax or pathology was above 93% in all cases and specificity was 100%. Adding more images to train the convolutional neural network had no positive impact on the results. Modifications such as normalization of datasets and image augmentation enhanced the performance in some instances. Conclusions: A machine learning approach could be used on digital otoscopic images to accurately screen for otitis media.
Pulmonary Veins Morphometric Characteristics and Spatial Orientation Influence on Its Cryoballoon Isolation Results
Authors: Mamchur Sergey , Chichkova Tatiana , Khomenko Egor , Kokov Alexander
Published: May 2022

The aim of this paper is to evaluate the effect of pulmonary vein (PV) morphometric characteristics and spatial orientation on the results of cryoballoon ablation (CBA). Methods: A randomized, prospective, single-center controlled study was conducted, enrolling 230 patients with drug-refractory atrial fibrillation (AF). We compared procedural and long-term outcomes in patients who underwent their first procedure of pulmonary vein isolation (PVI) for AF with either radiofrequency ablation (RFA) (n = 108) or CBA (n = 122) and assessed their interaction with the different pattern of PV anatomy, morphometric characteristics, and spatial orientation. The primary efficacy endpoint was any documented atrial arrhythmia recurrence (AF, atrial flutter, or atrial tachycardia) lasting over 30 s during a 12-month follow-up after a 90-day blanking period and discontinuation of antiarrhythmic drugs. The procedure’s endpoint was the achievement of PVI. Before the intervention, all patients underwent computed tomography (CT) to assess the PV anatomical variant, maximum and minimum diameters of the PV’s ostia, their cross-sectional area, orifice ovality index, and PV tilt angles. Results: The mean follow-up period was 14 months (12; 24). Long-term efficacy in the cryoablation group was 78.8% and in the RFA group—83.3% (OR = 0.74; 95% CI 0.41–1.3; p = 0.31). The RFA results did not depend on PV anatomy. The «difficult» occlusion of the right inferior PV (RIPV) occurred in 12 patients and was associated with a more horizontal PV position in the frontal plane; the mean tilt angle was −15.2 ± 6.2° versus −26.5 ± 6.3° in the absence of technical difficulties (p = 0.0001). In 11 cases (9%), during ablation of the right superior PV (RSPV), phrenic nerve injury (PNI) occurred and was associated with the maximum and minimum RSPV diameter, 20.0–20.4 mm (OR = 13.2; 95% CI: 4.7–41.9, p < 0.05) and 17.5–20 mm (OR = 12.5; 95% CI 3.4–51, p < 0.05), respectively. Patients with arrhythmia recurrence were characterized by significantly larger diameters and ovality of the left superior PV (LSPV). The spatial orientation of the PV does not affect the long-term results of cryoablation. Conclusion: Preprocedural evaluation of PV morphology and orientation using cardiac CT might help choose the optimal technology for the individual patient.
Are Vaccinations Alone Enough to Curb the Dynamics of the COVID-19 Pandemic in the European Union?
Authors: Miłobędzki Paweł
Published: May 2022

I use the data on the COVID-19 pandemic maintained by Our Word in Data to estimate a nonstationary dynamic panel exhibiting the dynamics of confirmed deaths, infections and vaccinations per million population in the European Union countries in the period of January–July 2021. Having the data aggregated on a weekly basis I demonstrate that a model which allows for heterogeneous short-run dynamics and common long-run marginal effects is superior to that allowing only for either homogeneous or heterogeneous responses. The analysis shows that the long-run marginal death effects with respect to confirmed infections and vaccinations are positive and negative, respectively, as expected. Since the estimate of the former effect compared to the latter one is about 71.67 times greater, only mass vaccinations can prevent the number of deaths from being large in the long-run. The success in achieving this is easier for countries with the estimated large negative individual death effect (Cyprus, Denmark, Ireland, Portugal, Estonia, Lithuania) than for those with the large but positive death effect (Bulgaria, Hungary, Slovakia). The speed of convergence to the long-run equilibrium relationship estimates for individual countries are all negative. For some countries (Bulgaria, Denmark, Estonia, Greece, Hungary, Slovakia) they differ in the magnitude from that averaged for the whole EU, while for others (Croatia, Ireland, Lithuania, Poland, Portugal, Romania, Spain), they do not.
Progressive Training Technique with Weak-Label Boosting for Fine-Grained Classification on Unbalanced Training Data
Authors: Jin Yuhui , Wang Zuyun , Liao Huimin , Zhu Sainan , Tong Bin , Yin Yu , Huang Jian
Published: May 2022

In practical classification tasks, the sample distribution of the dataset is often unbalanced; for example, this is the case in a dataset that contains a massive quantity of samples with weak labels and for which concrete identification is unavailable. Even in samples with exact labels, the number of samples corresponding to many labels is small, resulting in difficulties in learning the concepts through a small number of labeled samples. In addition, there is always a small interclass variance and a large intraclass variance among categories. Weak labels, few-shot problems, and fine-grained analysis are the key challenges affecting the performance of the classification model. In this paper, we develop a progressive training technique to address the few-shot challenge, along with a weak-label boosting method, by considering all of the weak IDs as negative samples of every predefined ID in order to take full advantage of the more numerous weak-label data. We introduce an instance-aware hard ID mining strategy in the classification loss and then further develop the global and local feature-mapping loss to expand the decision margin. We entered the proposed method into the Kaggle competition, which aims to build an algorithm to identify individual humpback whales in images. With a few other common training tricks, the proposed approach won first place in the competition. All three problems (weak labels, few-shot problems, and fine-grained analysis) exist in the dataset used in the competition. Additionally, we applied our method to CUB-2011 and Cars-196, which are the most widely-used datasets for fine-grained visual categorization tasks, and achieved respective accuracies of 90.1% and 94.9%. This experiment shows that the proposed method achieves the optimal effect compared with other common baselines, and verifies the effectiveness of our method. Our solution has been made available as an open source project.
A Simplified Hard-Switching Loss Model for Fast-Switching Three-Level T-Type SiC Bridge-Legs
Authors: Cittanti Davide , Gammeter Cristoph , Huber Jonas , Bojoi Radu , Kolar Johann W.
Published: May 2022

Hard-switching losses in three-level T-type (3LTT) bridge-legs cannot be directly estimated from datasheet energy loss curves, which are given for symmetric two-level half-bridge configurations only. The commutations in a 3LTT bridge-leg occur between semiconductors with different blocking voltages and/or current ratings, and involve a third semiconductor device in the switching transition, which contributes additional capacitive losses. This paper, therefore, describes a simplifed approach to estimate a lower bound for the hard-switching losses of 3LTT bridge-legs (note that the approach is applicable to other three-level topolgies as well). In view of the very fast switching speeds of wide-bandgap semiconductors, the model neglects voltage/current overlap losses and considers only the dominating charge-related loss contributions (semiconductor output capacitances, body diode reverse-recovery charge), thus requiring minimal information from datasheets. A direct experimental verification with an 800 V DC-link 3LTT bridge-leg (1200 V and 650 V SiC MOSFETs) operating with output currents up to 25 A confirms the good accuracy of the simplified switching-loss model.
Analysis of a User Interface Based on Multimodal Interaction to Control a Robotic Arm for EOD Applications
Authors: Goyzueta Denilson V. , Guevara M. Joseph , Montoya A. Andrés , Sulla E. Erasmo , Lester S. Yuri , L. Pari , C. Elvis Supo
Published: May 2022

A global human–robot interface that meets the needs of Technical Explosive Ordnance Disposal Specialists (TEDAX) for the manipulation of a robotic arm is of utmost importance to make the task of handling explosives safer, more intuitive and also provide high usability and efficiency. This paper aims to evaluate the performance of a multimodal system for a robotic arm that is based on Natural User Interface (NUI) and Graphical User Interface (GUI). The mentioned interfaces are compared to determine the best configuration for the control of the robotic arm in Explosive Ordnance Disposal (EOD) applications and to improve the user experience of TEDAX agents. Tests were conducted with the support of police agents Explosive Ordnance Disposal Unit-Arequipa (UDEX-AQP), who evaluated the developed interfaces to find a more intuitive system that generates the least stress load to the operator, resulting that our proposed multimodal interface presents better results compared to traditional interfaces. The evaluation of the laboratory experiences was based on measuring the workload and usability of each interface evaluated.
Template-Based Semi-Formal Approach to Robust Equivalence Checking
Authors: Wang Qinhao , Fujita Masahiro
Published: May 2022

In order to ensure the correct behaviors and that bugs have not entered the design, equivalence checking technology plays an important role in VLSI design. In this paper, we propose a new template-based, semi-formal equivalence checking method for C-based system design and Register Transfer Level (RTL)/netlist implementation design, whose internal structures can be very different. Staring with a C-based description as a specification, we first randomly generate a set of templates. Each template has one or a small number of missing sentences based on the original C description. Many sets of mutants can be represented by these templates, using symbolic constants, variables, and operators. The process of finding those missing portions can be formulated as a Quantified Boolean Formula (QBF) problem. Then, based on the counter-example guided method, by simulating only the implementation, the templates can be refined. Since the templates are generated from the original C description, their structures are very similar to each other. With the original C description as a specification, we can simulate or formally check the equivalence between the refined template and the original C description, thereby indirectly achieving the equivalence checking of the C-based systems design and RTL/netlist implementation design. The experimental results on several practical examples demonstrate the effectiveness of the proposed method.
Study on Gibbs Optimization-Based Resource Scheduling Algorithm in Data Aggregation Networks
Authors: Ding Sheng , Du Huazheng , Xia Na , Li Shaojie , Yu Yongtang
Published: May 2022

In data aggregation networks (WSNs, ad hoc, mesh, etc.), it is key to schedule the network resources, such as channels and TDMA time slots, to minimize the communication conflict and optimize the network data-gathering performance. In this paper, the resources scheduling problem is formulated as a vertex coloring problem in graph theory. Then, a multi-channel TDMA scheduling algorithm based on the Gibbs optimization is proposed. By defining the Gibbs energy expression according to the objective function of the problem, the joint probability of channel and time slot can be computed for the optimized selection of channels and time slots. This algorithm is low-complexity and its convergence performance can be proven. Experiments with different network parameters demonstrate that the proposed algorithm can reduce the communication conflict, improve the network throughput, and effectively reduce the network transmission delay and scheduling length for the data aggregation networks.
Research on Interference Coordination Optimization Strategy for User Fairness in NOMA Heterogeneous Networks
Authors: Yu Zhihao , Hou Jia
Published: May 2022

In order to comprehensively improve the performance of edge users in heterogeneous cellular networks and the fairness of network users, a downlink interference coordination optimization strategy in heterogeneous cellular networks with non-orthogonal multiple access (NOMA) based on the cell range expansion (CRE) and the almost blank subframe (ABS) technology is proposed. Different from the traditional interference coordination strategy, a NOMA user pairing scheme combined with ABS technology and a dynamic NOMA power allocation scheme are designed to maximize the network fairness based on the optimized throughput of the edge users. The simulation results show that the proposed optimization strategy can balance the performance of network users more effectively to improve the throughput of edge users and network fairness than other NOMA user pairing and power allocation algorithms without the complexity being increased.
Vibration Suppression of Hub Motor-Air Suspension Vehicle
Authors: Jiang Hong , Wu Chuqi , Chen Bo
Published: May 2022

Aiming at the negative vibration effect caused by the increased unsprung mass of the hub motor-air suspension (HM-AS) vehicle and the unbalanced magnetic force (UMF) of the hub motor, a linear quadratic regulator (LQR) air suspension control strategy based on a genetic algorithm is proposed. Considering the coupling effect of road surface excitation and UMF, the model of the HM-AS vehicle is established. Then, according to optimal control theory and the genetic algorithm, the LQR controller is designed to suppress the vibration of the HM-AS vehicle, and the weight matrix of the LQR controller is optimized through the genetic algorithm. The simulation results show that the proposed LQR control strategy effectively improves the ride comfort and motor safety of the HM-AS vehicle.
New Integrated Energy Solution Idealization: Hybrid for Renewable Energy Network (Hy4REN)
Authors: Ramos Helena M. , Vargas Brandon , Saldanha João Roquette
Published: May 2022

A review of different energy components is detailed, as a baseline of fundamentals for the new integrated energy concept idealization. This innovative solution is a Hybrid for Renewable Energy Network (Hy4REN) based on well-studied elements to produce the best final solution. This proposal has the objective of improving energy system sustainability, facing fossil fuel and climate change restrictions, and increasing energy network flexibility. The most mature energy storage technology, pumped hydropower energy storage (PHES), is used to support both the grid connection and stand-alone modes, as an integrated hybrid energy system. The hybrid system idealization is modular and scalable, with a complementary nature among several renewables, using sea water in offshore mode to build an integrated solution. By evaluating a variety of energy sources, complemented with economic analysis, the benefits associated are evidenced using this sustainable methodology based only on renewable sources. Combined production of hydropower, using sea water, with pumped storage and water hammer events to create potential energy to supply hydropower in a water loop cycle, without consuming electrical energy, is explored. Other renewable sources are also integrated, such as floating solar PV energy and an oscillating water column (OWC) with coupled air-venting Wells and wind turbines, all integrated into the Hy4REN device. This complementarity of available sources allows us to improve energy storage flexibility and addresses the energy transition toward net-zero carbon emissions, inducing significant improvements in the sustainability of the energy network as a whole.
Evaluating the Transition of the European Union Member States towards a Circular Economy
Authors: Nazarko Joanicjusz , Chodakowska Ewa , Nazarko Łukasz
Published: May 2022

This paper presents the assessment of the European Union member states in terms of the circular economy (CE) targets, using a combination of the Data Envelopment Analysis (DEA) method and factor analysis. This approach fills in the existing knowledge gap by providing an innovative methodology of an objectivised comparative evaluation of the degree of implementation of the CE principles by the EU countries. Assessing countries’ performance in achieving the goals of the circular economy is a challenge due to the lack of a generally accepted methodology, the multitude of indicators, and the insufficient data. Countries may be compared in a narrow way, according to single indicators, but a more holistic synthetic assessment of countries is also needed to determine their position against each other. In such cases, DEA may be successfully used. The study resulted in the identification of two clusters of countries with similar profiles of relative efficiency in the CE goals’ implementation. It was concluded that the position of a particular country in achieving the CE aims was strongly correlated its GDP per capita. Moreover, factor analysis showed that many CE indicators are strongly correlated with each other and may be aggregated into five meta-indicators (factors): Recycling rate of general waste, Waste production, Jobs and investments, Recycling rate of special waste, and Circular material use rate. In addition to simple rankings and indication of benchmarks, the article offers a novel concept of technology competitors which was used to group units competing for positions in the ranking.
Collapse Mechanism of Transmission Tower Subjected to Strong Wind Load and Dynamic Response of Tower-Line System
Authors: Li Junkuo , Gao Fan , Wang Lihuan , Ren Yaning , Liu Chuncheng , Yang Aiquan , Yan Zhao , Jiang Tao , Li Chengbo
Published: May 2022

Transmission towers are prone to collapse under strong wind load, resulting in significant economic losses. In order to investigate the collapse mechanism and failure modes of the transmission tower under strong wind load and whether the wind vibration factor can greatly reflect the increasing effect of the fluctuating wind, the finite element method (FEM) is utilized to analyze the ultimate bearing capacity of a typical 220 kV transmission tower. The results show that the collapse of the tower under strong wind loads is usually due to the buckling of the leg members. When the reference wind speed is equal to 27 m/s, a small part of the main leg members reaches their yield strength, while the diagonal members are still in the elastic range, and the deformation of the transmission tower is unapparent at this wind speed. When reference wind speed is equal or greater than 30 m/s, the growing variety of main legs is totally into the plastic yield stage, and the overall deformation of this tower is visible. Therefore, the transmission tower is collapsed due to the large deformation caused by the elastic-plastic buckling of leg members. Based on the aforementioned study, a finite element model involving three transmission towers and four span transmission lines is established to analyze the dynamic response of the tower-line system below fluctuating wind. Results show that the wind-induced coefficients designed by current code not only notably satisfy the stress response of tower components subjected to fluctuating wind loads in the elastic phase but also accurately assess the collapse displacement of the transmission tower. The increasing effect of displacement on the top tower under fluctuating wind, unfortunately, could not considerably reply with the investigated factor, and the load-carrying capacity of the transmission tower in the plastic phase can be overestimated by static calculation results.
A Flexible Deep Learning Method for Energy Forecasting
Authors: Taleb Ihab , Guerard Guillaume , Fauberteau Frédéric , Nguyen Nga
Published: May 2022

Load prediction with higher accuracy and less computing power has become an important problem in the smart grids domain in general and especially in demand-side management (DSM), as it can serve to minimize global warming and better integrate renewable energies. To this end, it is interesting to have a general prediction model which uses different standard machine learning models in order to be flexible enough to be used in different regions and/or countries and to give a prediction for multiple days or weeks with relatively good accuracy. Thus, we propose in this article a flexible hybrid machine learning model that can be used to make predictions of different ranges by using both standard neural networks and an automatic process of updating the weights of these models depending on their past errors. The model was tested on Mayotte Island and the mean absolute percentage error (MAPE) obtained was 1.71% for 30 min predictions, 3.5% for 24 h predictions, and 5.1% for one-week predictions.
Review of Electric Vehicle Charger Cybersecurity Vulnerabilities, Potential Impacts, and Defenses
Authors: Johnson Jay , Berg Timothy , Anderson Benjamin , Wright Brian
Published: May 2022

Worldwide growth in electric vehicle use is prompting new installations of private and public electric vehicle supply equipment (EVSE). EVSE devices support the electrification of the transportation industry but also represent a linchpin for power systems and transportation infrastructures. Cybersecurity researchers have recently identified several vulnerabilities that exist in EVSE devices, communications to electric vehicles (EVs), and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. The potential impact of attacks on these systems stretches from localized, relatively minor effects to long-term national disruptions. Fortunately, there is a strong and expanding collection of information technology (IT) and operational technology (OT) cybersecurity best practices that may be applied to the EVSE environment to secure this equipment. In this paper, we survey publicly disclosed EVSE vulnerabilities, the impact of EV charger cyberattacks, and proposed security protections for EV charging technologies.
Life Cycle Based Climate Emissions of Charcoal Conditioning Routes for the Use in the Ferro-Alloy Production
Authors: Surup Gerrit , Kaffash Hamideh , Ma Yan , Trubetskaya Anna , Pettersen Johan , Tangstad Merete
Published: May 2022

Renewable reductants are intended to significantly reduce CO2 emissions from ferro-alloy production, e.g., by up to 80% in 2050 in Norway. However, charcoals provide inferior properties compared to fossil fuel-based reductants, which can hamper large replacement ratios. Therefore, conditioning routes from coal beneficiation was investigated to improve the inferior properties of charcoal, such as mechanical strength, volatile matter, CO2 reactivity and mineral matter content. To evaluate the global warming potential of renewable reductants, the CO2 emissions of upgraded charcoal were estimated by using a simplified life cycle assessment, focusing on the additional emissions by the energy demand, required chemicals and mass loss for each process stage. The combination of ash removal, briquetting and high-temperature treatment can provide a renewable coke with superior properties compared to charcoal, but concomitantly decrease the available biomass potential by up to 40%, increasing the CO2-based global warming potential of industrial produced charcoal to ≈500 kg CO2-eq. t−1 FC. Based on our assumptions, CO2 emissions from fossil fuel-based reductants can be reduced by up to 85%. A key to minimizing energy or material losses is to combine the pyrolysis and post-treatment processes of renewable reductants to upgrade industrial charcoal on-site at the metallurgical plant. Briquetting showed the largest additional global warming potential from the investigated process routes, whereas the high temperature treatment requires a renewable energy source to be sustainable.
Activities Related to an Electromobility Strategy as a Part of Low Carbon Energy Transition: A Survey in Polish Communes
Authors: Trębecki Jacek , Przybylska Joanna , Rydzak Waldemar , Sellitto Miguel Afonso , Oleśków-Szłapka Joanna
Published: May 2022

The aim of this article is to diagnose the situation of electromobility in local government units of Polish municipalities. Besides the main features of the communes, the issue of type of strategy that is being built was raised, what are the trends in this respect, and how public transport fits into them? The empirical basis was a survey conducted in 2020 using the CAWI (computer assisted web interview) method, covering all 2477 communes in Poland. Responses were received from 2230 municipalities (90% response rate). Based on the statistical analysis, the main conclusion is that rural communes are less willing to implement the electromobility strategy, but if they decide to do so, they develop long-term strategies. Another conclusion is that the amount of budget revenue per capita does not affect decisions on building an electromobility strategy. Also, a general tendency in Poland is an increase in the propensity to invest in electromobility, mainly in infrastructure for users, compared to public transport and electric buses. The main implication of the study is that Polish public authorities now have background information regarding the theme that can be useful in developing guidelines for local electromobility strategy implementation.