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Sixth generation promises to have a variety of applications, as well as network entities, in terms of power, range, data rates, latency, and propagation environment. The overall heterogeneity of the network poses significant challenges in terms of physical (PHY) layer design. This article first identifies some of the areas where the 5G multinumerology orthogonal frequency division multiplexing (OFDM) falls short before discussing the possible approaches toward PHY design. In particular, we discuss a backward-compatible, forward-looking, and extendable PHY layer framework that can be extended as new requirements arise to enable a graceful and sustainable network evolution. This is illustrated with a simple case study, where users with different requirements are allowed to use the same time-frequency (T-F) resources in a cohesive manner. The article concludes with the discussion of some critical research problems/areas pertaining to the said framework. [ABSTRACT FROM AUTHOR]

This letter reports a SnS2 and ZnO nanocomposite (NC) prepared by dispersion method. The nanocomposite shows promising characteristics for optoelectronic application. SnS2:ZnO NC shows a wide absorption spectrum covering ultraviolet (UV)-visible-near infrared (NIR) regions. Hence, using the proposed nanocomposite a broadband photodetector with a structure comprising Al/ SnS2:ZnO/PEDOT:PSS/ Indium Tin Oxide (ITO) is fabricated. At a bias voltage of 1 V, the measured responsivity values (A/W) of the proposed device are 140.41, 848.63, and 1094.48 at 350 nm (UV), 750 nm (visible) and 900 nm (NIR), respectively. [ABSTRACT FROM AUTHOR]

Aspects are opinion targets to extract in aspect-based sentiment analysis. While existing methods can already produce satisfactory extraction results, they suffer when faced with compound aspect terms, typically phrase-level aspect terms that have inner structure and occur infrequently in the training set. This issue can be mainly attributed to the scarcity of training examples targeting compound aspect terms and by the neglect of the syntactic structure of a sentence in the modeling process. In this article, we aim to cope with compound aspect extraction by a two-stage hybrid approach. First, we introduce a conditional generation method for data augmentation in a masked sequence-to-sequence framework, which is controllable to preserve original aspects while generating a new sentence. Second, we propose a constituency lattice structure that is induced from the constituency-based parse tree of a sentence. Experimental results on two review datasets show that this approach can greatly improve the effect of compound aspect extraction. [ABSTRACT FROM AUTHOR]

This work presents the impact of barrier spacer on the structural and optical properties of strain-coupled Stranski-Krastanov (SK) on Sub Monolayer (SML) quantum dot (QD) heterostructures. Various ternary and quaternary materials have been employed as the barrier layer of SK-SML QD heterostructures. In the coupled SK-SML QDs, the residual strain propagates from the SML seed layer towards the top SK dots, introducing defects and dislocations. After employing the ternary (GaAs1-ySby) and quaternary (InxAl0.21Ga1-.0.21-xAs and In0.18Ga0.82As1-ySby) materials, the residual strain reduces, reducing the defects which thereby helps in increasing the crystalline quality of the heterostructure. Nextnano software has been used to compute the structures' strain, energy band profile, probability density functions, and emission wavelength. Two strain components, viz. hydrostatic as well as biaxial strain, have been computed and compared for all the heterostructures to understand the distribution of the strain profile. The emission wavelength is red-shifted for the SK-SML QD heterostructures with ternary and quaternary materials as a barrier layer as compared to that of the GaAs barrier. Moreover, type-I and II energy band profiles are observed for Sb-based barrier material, appropriate for various optoelectronic applications. This is a comparative study of SK-SML QDs with various barrier materials helps minimize the strain and defects and improve the device performance. [ABSTRACT FROM AUTHOR]

One of the significant post-quantum cryptographic candidates is the NTRU public key cryptosystem. It operates on polynomial rings, where the parameter largely determines the security of the system. Although NTRU is being studied currently, it has a long and well-established history. There are several lattice-based attacks on NTRU-like systems that exploit the special structures of the rings used in these systems. The aim of this paper is to analyze the original NTRU, NTRU Encrypt, and NTRU Primes encryption schemes by structuring their common elements and showing the strongest hybrid attack using both lattice reduction and meet-in-the-middle (MITM) search on them. Furthermore, it is noted that, ignoring a polynomial factor of the not-well-studied cost of Block Korkin-Zolotarev (BKZ) algorithm, we estimate the security of the construction of encryption keys and show that by balancing lattice reduction costs and a MITM search cost, one can achieve better performance than using any of these methods on their own. Unlike previous studies, we found the way to ignore polynomial impact 22-24 from BKZ loops with multiple shortest vector problem (SVP) and the factor of 27 was omitted from the cost of one step in guessing the SVP.

Several cryptosystems based on the Ring Learning with Errors (RLWE) problem have been proposed within the NIST post-quantum cryptography standardization process, e.g., NewHope. Furthermore, there are systems like Kyber which are based on the closely related MLWE assumption. Both previously mentioned schemes result in a non-zero decryption failure rate (DFR). The combination of encryption and decryption for these kinds of algorithms can be interpreted as data transmission over a noisy channel. To the best of our knowledge this paper is the first work that analyzes the capacity of this channel. We show how to modify the encryption schemes such that the input alphabets of the corresponding channels are increased. In particular, we present lower bounds on their capacities which show that the transmission rate can be significantly increased compared to standard proposals in the literature. Furthermore, under the common assumption of stochastically independent coefficient failures, we give lower bounds on achievable rates based on both the Gilbert-Varshamov bound and concrete code constructions using BCH codes. By means of our constructions, we can either increase the total bitrate (by a factor of 1.84 for Kyber and by factor of 7 for NewHope) while guaranteeing the same DFR or for the same bitrate, we can significantly reduce the DFR for all schemes considered in this work (e.g., for NewHope from 2−216 to 2−12769). [ABSTRACT FROM AUTHOR]

The past 50 years witnessed the inventions of more than one thousand power electronic topologies. However, we still lack a common standard to compare and classify various topologies. Moreover, topologies are often created through intuition rather than systematic approaches. The intuition of voltage and current sharing, along with modularity and scalability, gives rise to cascaded-bridge and multi-parallleled converters, respectively. Nevertheless, power converters with both high-voltage and large-current capabilities are still obscure yet important. This article first investigates the symmetries of circuit topologies through group theory. Notably, symmetries lie in twofold—individual modules and connections. Symmetries not only help to classify topologies but also play an important role in the creation of new topologies. Based on wallpaper groups, this article proposes the lattice converters, which readily scale to manage high voltages and large currents. The proposed lattice converters benefit from 1) modularity and scalability, 2) boundless current and voltage ratings, 3) multiple input/output ports, 4) sensorless voltage balancing, 5) high power quality, and 6) flexible control. Simulation and experimental results demonstrate the effectiveness and superiority of the proposed theory and lattice converters. [ABSTRACT FROM AUTHOR]

We study the list decodability of different ensembles of codes over the real alphabet under the assumption of an omniscient adversary. It is a well-known result that when the source and the adversary have power constraints $P $ and $N $ respectively, the list decoding capacity is equal to $\frac {1}{2}\log \frac {P}{N}$. Random spherical codes achieve constant list sizes, and the goal of the present paper is to obtain a better understanding of the smallest achievable list size as a function of the gap to capacity. We show a reduction from arbitrary codes to spherical codes, and derive a lower bound on the list size of typical random spherical codes. We also give an upper bound on the list size achievable using nested Construction-A lattices and infinite Construction-A lattices. We then define and study a class of infinite constellations that generalize Construction-A lattices and prove upper and lower bounds for the same. Other goodness properties such as packing goodness and AWGN goodness of infinite constellations are proved along the way. Finally, we consider random lattices sampled from the Haar distribution and show that if a certain conjecture that originates in analytic number theory is true, then the list size grows as a polynomial function of the gap-to-capacity. [ABSTRACT FROM AUTHOR]

DNA nanostructures offer promising applications, particularly in the biomedical domain, as they can be used for targeted drug delivery, construction of nanorobots, or as a basis for molecular motors. One of the most prominent techniques for assembling these structures is DNA origami. Nowadays, desktop applications are used for the in silico design of such structures. However, as such structures are often spatially complex, their assembly and analysis are complicated. Since virtual reality (VR) was proven to be advantageous for such spatial-related tasks and there are no existing VR solutions focused on this domain, we propose Vivern, a VR application that allows domain experts to design and visually examine DNA origami nanostructures. Our approach presents different abstracted visual representations of the nanostructures, various color schemes, and an ability to place several DNA nanostructures and proteins in one environment, thus allowing for the detailed analysis of complex assemblies. We also present two novel examination tools, the Magic Scale Lens and the DNA Untwister, that allow the experts to visually embed different representations into local regions to preserve the context and support detailed investigation. To showcase the capabilities of our solution, prototypes of novel nanodevices conceptualized by our collaborating experts, such as DNA-protein hybrid structures and DNA origami superstructures, are presented. Finally, the results of two rounds of evaluations are summarized. They demonstrate the advantages of our solution, especially for scenarios where current desktop tools are very limited, while also presenting possible future research directions. [ABSTRACT FROM AUTHOR]

In this sequel to our previous article (Cordero et al., 2020) on general inference systems for reasoning with if–then dependencies, we study transformations of if–then rules to semantically equivalent collections of if–then rules suitable to solve several problems related to reasoning with data dependencies. We work in a framework of general lattice-based if–then rules whose semantics is parameterized by systems of isotone Galois connections. This framework allows us to obtain theoretical insight as well as algorithms on a general level and observe their special cases by choosing various types of parameterizations. This way, we study methods for automated reasoning with different types of if–then rules in a single framework that covers existing as well as novel types of rules. Our approach supports a large family of if–then rules, including fuzzy if–then rules with various types of semantics. The main results in this article include new observations on the syntactic inference of if–then rules, complete collections of rules, reduced normal forms of collections of rules, and automated reasoning methods. We demonstrate the generality of the framework and the results by examples of their particular cases focusing on fuzzy if–then rules. [ABSTRACT FROM AUTHOR]

Uncertainties are widespread in real-world situations. In the existing studies, the uncertainties expressed by the agents engaged in a conflict situation have been extensively investigated. However, to what extent these agents can be trusted is often ignored and seldom taken into account. In this article, to manage these two sides of uncertainties, we propose a mathematical framework for multilevel conflict analysis from an outsider's perspective. Concretely, in order to indicate the analysis levels and manage the conflict situation with an extent-intent view, we resort to fuzzy formal concept analysis. At first, we explain what is multilevel data analysis. After that, based on fuzzy concept lattices, we present a general framework for multilevel conflict analysis and a method for computing the maximal coalitions and minimum conflict sets. And then, we describe how to update conflict analysis results when increasing analysis levels. Experimental analysis demonstrates that managing two sides of uncertainties can bring much more conflict resolution, and increasing analysis levels is helpful for postponing decision making and bringing more economical conflict resolutions. Finally, case studies are made to show the application of multilevel conflict analysis model and some interesting findings are obtained. Specifically, once the cost of increasing analysis levels is taken into consideration, it is interesting to choose the optimal analysis level for making the most economic decision. The main contribution of this study is the model of multilevel conflict analysis based on fuzzy concept lattices, which can incorporate the uncertainties of two sides. [ABSTRACT FROM AUTHOR]

We report the fabrication of a crystalline $\varepsilon $ -Ga2O3 epilayer on a diamond substrate as deep ultraviolet photodetectors for high-temperature operation. Despite their large lattice mismatch, we achieve high quality growth of $\varepsilon $ -Ga2O3 films on diamond that exhibit a single out-of-plane orientation. A metal-semiconductor-metal photodetector is fabricated based on the crystalline $\varepsilon $ -Ga2O3/diamond heterostructure, which exhibits a high photo-to-dark current ratio of ${3.67}\times {10}^{{6}}$ under 254 nm light illumination at the bias of 20 V, a UV/visible rejection ratio of 259, and fast rise (decay) time of 0.323 (0.171) s at room temperature. Furthermore, thanks to the high crystalline film quality, the device responsivity decreases by only 2/3, and the rise (decay) time is 0.325 (0.539) s when the photodetector is operated up to a high temperature of 473 K. This study explores an effective heterostructure design for the application of deep ultraviolet photodetectors at high temperatures. [ABSTRACT FROM AUTHOR]

Infinite periodic arrays of antennas that can be individually described by means of spherical modes are analyzed starting from the generalized scattering matrix (GSM) of an isolated element. After computing the GSM of an isolated element with the finite-element method (FEM), a fast postprocessing can be carried out to calculate the response of the element in an infinite array environment by using addition theorems for spherical modes. For this purpose, an efficient computation of lattice sums of spherical harmonics is used. The main advantage of this method is that the antenna is analyzed only once whatever the array lattice or scan angle. In addition, fast frequency analysis can be performed since the starting point is the computation of the isolated antenna with the FEM, which is suitable for fast frequency sweep. The active reflection coefficient and the embedded radiation pattern of the infinite periodic array are calculated for several examples to show the capabilities of the proposed method. [ABSTRACT FROM AUTHOR]

We demonstrate the first recurrent neural network architecture for learning signal temporal logic (TL) formulas, and present the first systematic comparison of formula inference methods. Legacy systems embed much expert knowledge which is not explicitly formalized. There is great interest in learning formal specifications that characterize the ideal behavior of such systems—that is, formulas in TL that are satisfied by the system’s output signals. Such specifications can be used to better understand the system’s behavior and improve the design of its next iteration. Previous inference methods either assumed certain formula templates, or did a heuristic enumeration of all possible templates. This work proposes a neural network architecture that infers the formula structure via gradient descent, eliminating the need for imposing any specific templates. It combines the learning of formula structure and parameters in one optimization. Through systematic comparison, we demonstrate that this method achieves similar or better misclassification rates (MCRs) than enumerative and lattice methods. We also observe that different formulas can achieve similar MCR, empirically demonstrating the under-determinism of the problem of TL inference. [ABSTRACT FROM AUTHOR]

Learning and identifying key concepts from past fault records are essential for us to understand the causes of these faults, which lay the foundation for the fault diagnosis and prognosis. At present, faults in many fields (e.g., rail, automobile, and smart grid) are recorded in textual form. Due to the lack of effective mining and analysis tools, latent information in the massive textual data (text records) has not been fully unearthed. In this paper, a novel Adversarial Training-based Lattice LSTM model called AT-Lattice is proposed to address this problem. In this model, the Named Entity Recognition (NER) is achieved by Lattice LSTM and Conditional Random Field (CRF), where the Lattice LSTM is used to provide sequence information between words, and the CRF is used to get the final entity prediction result. In addition, the Chinese Word Segmentation (CWS) task is introduced to conduct the adversarial training with the NER task. The framework of the adversarial training is able to make full use of the boundary information and filter out the noise caused by the introduced CWS task. More importantly, extensive experiments are conducted on five different train fault datasets collected by a rail transit company. The results demonstrate that the proposed model outperforms the state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

In the information age, image processing technologies play a vital role in the field of industrial engineering. In this article, a novel spline scheme called the hierarchical polishing splines algorithm is proposed, and it is applied to the field of computed tomography (CT) image reconstruction of coronavirus disease 2019 (COVID-19). The proposed algorithm defines a set of control lattices, wherein the density of lattice points in these control lattice ranges from coarse to fine in order, and the final applied function is produced by adding the functions derived from every control lattices. In order to demonstrate the performance of the proposed algorithm, some CT images from COVID-19 patients are selected. The experimental results show that the reconstructed COVID-19 CT images by using the proposed algorithm have good quality when compared with some widely used approaches. In addition, this article also applies the proposed algorithm to reconstruct the infected regions derived from COVID-19 CT images, and the results also show that the proposed algorithm is more efficient than others. Besides, the applicability of the proposed algorithm is discussed, wherein the COVID-19 severity is estimated based on the reconstructed COVID-19 CT images, and the applicability analysis shows that the use of the proposed algorithm to reconstruct COVID-19 CT images can help to achieve more accurate severity assessment of COVID-19 in a certain extent. [ABSTRACT FROM AUTHOR]

Liang et al. in 2000 defined interval type-2 fuzzy sets (IT2FSs), which constitute a subset of type-2 fuzzy sets. While the membership degrees in the former are functions from [0, 1] to [0, 1] (fuzzy truth values), the membership degrees in IT2FSs only take their values in $\lbrace {\text{0}},{\text{1}}\rbrace$. Although all the initial work on IT2FSs involved convex membership degrees only, in 2015, Bustince et al. began the study on IT2FSs in general, including certain sets with nonconvex membership degrees. However, these are obviously early stages, with a lot of open problems regarding the theoretical structure of IT2FSs. For example, as far as we know, no negation operator has been obtained in this context. Therefore, it seems appropriate to continue with the study started in previous papers, delving deeper into the properties and operations of IT2FSs. Consequently, this work studies the structure of the set of functions from [0, 1] to $\lbrace {\text{0}},{\text{1}}\rbrace$ (expanding the set considered by Bustince et al.), from which we have removed the constant function $\mathbf{0}$ , to offer a different study to the one carried out by Walker and Walker. More specifically, we consider join and meet operations, partial order derived from each one, and the negation operators in that set. Among other results, we provide new characterizations of join and meet operations and of partial orders on the set of functions from [0, 1] to $ \lbrace {\text{0}},{\text{1}} \rbrace $ ; we also present the first negation operators on this set. [ABSTRACT FROM AUTHOR]

Photonic crystals (PhCs) are periodically structured dielectric materials that have attracted significant research interest in the last two decades for their ability to slow down the group velocity of a propagating pulse envelope with promising sensing applications. This review article discusses the properties of 2-D PhCs including the slow-light phenomenon, bandgap generation, and application of these properties for gas and liquid sensing. Waveguide generation by introducing defects with light guiding and confinement is discussed. In addition, for 2-D PhC line waveguides, a comprehensive review on the slow-light principle and phenomenon of slow-light enhanced sensing for gases and liquids is discussed. 1-D and 3-D PhCs are also reviewed for bandgap generation and defects in PhCs along with present fabrication challenges and future trends. Our study highlights an increase in the detection capabilities of PhC-based sensors paving way for high-sensitivity detectors with applications in ubiquitous monitoring of gases and liquids. [ABSTRACT FROM AUTHOR]

We present the design and experimental validation of wideband dual-circularly-polarized (dual-CP) reflect-arrays (RAs) based on dual-functional-layered unit cells with independent control of circular polarizations. The proposed dual-CP RA cells comprise a circular polarization selective surface (CPSS) on the top based on a bandwidth-enhanced dual-meandered Pierrot structure that implements polarization selection of CP waves and a reflective half-wave plate (HWP) on the bottom. The dual-CP phase delay of the RA cells relies on the Berry-phase (BP) dictated by the rotation of the CPSS and HWP elements for achieving reflective beamforming of CP waves of opposite handedness. The diffractive properties of an infinite periodic gradient array of the dual-CP RA cells in a triangular lattice are investigated, which numerically verifies the dual-CP anomalous reflection capability. Two proof-of-concept RAs operating at X-band are designed, fabricated, and characterized. By replacing only the bottom functional layer of the RA, symmetrical and asymmetrically distributed dual-CP beams can be obtained. A measured peak gain of higher than 23.5 dBic is achieved, with a joint bandwidth of 11% for an axial ratio < 2 dB and a gain variation < 1 dB. The improved bandwidth performance, high-resolution BP compensation, and printed manufacturing process without using any metallic cavities make the demonstrated CPSS-based dual-CP RAs promising candidates for wireless and satellite communications. [ABSTRACT FROM AUTHOR]

Safe autonomous navigation is an essential and challenging problem for robots operating in highly unstructured or completely unknown environments. Under these conditions, not only robotic systems must deal with limited localization information but also their maneuverability is constrained by their dynamics and often suffers from uncertainty. In order to cope with these constraints, this article proposes an uncertainty-based framework for mapping and planning feasible motions online with probabilistic safety guarantees. The proposed approach deals with the motion, probabilistic safety, and online computation constraints by: 1) incrementally mapping the surroundings to build an uncertainty-aware representation of the environment and 2) iteratively (re)planning trajectories to goal that is kinodynamically feasible and probabilistically safe through a multilayered sampling-based planner in the belief space. In-depth empirical analyses illustrate some important properties of this approach, namely: 1) the multilayered planning strategy enables rapid exploration of the high-dimensional belief space while preserving asymptotic optimality and completeness guarantees and 2) the proposed routine for probabilistic collision checking results in tighter probability bounds in comparison to other uncertainty-aware planners in the literature. Furthermore, real-world in-water experimental evaluation on a nonholonomic torpedo-shaped autonomous underwater vehicle and simulated trials in an urban environment on an unmanned aerial vehicle demonstrate the efficacy of the method and its suitability for systems with limited onboard computational power. Note to Practitioners—Emergent robotic applications require operating in previously unmapped scenarios. This article presents a unified mapping–planning strategy that enables robots to navigate autonomously and safely in harsh environments. [ABSTRACT FROM AUTHOR]

We present a numerical approach for analysing simultaneous amplification and compression of a chirped hyperbolic secant soliton using a tapered Yb-doped photonic crystal fiber (PCF) based self-similar compressor. Theoretical studies reveal the conservation of input soliton during the amplification process due to self-similar property, which in turn helps for high quality compression of amplified soliton. In order to satisfy the self-similar condition, we note that the Yb-doped fiber should exhibit a decreasing group velocity dispersion (GVD). Such a constraint is met using a tapered PCF in our work, which is modeled using a fully vectorial effective index method (FVEIM). Influence of spatial and spectral dependent gain, saturation energy, amplified spontaneous emission (ASE), dispersion and nonlinearity on pulse propagation are analyzed using the combined solution of dynamic rate equations (DRE) and the generalized nonlinear Schrödinger equation (GNLSE). Numerical outcomes upon solving the aforementioned equations show that a 1 ps pulse is compressed down to a pulsewidth of 55.4 fs with a peak power of 1.03 kW in a total fiber length of $L=2.5$ m and taper ratio of 2.34. Overall quality of the compression scheme is evidenced by a relatively high compression factor (Fc) = 18.12, and low percentage of pedestal energy ($PE$) = 10.95 % [ABSTRACT FROM AUTHOR]

In this article, sinusoidal functions are introduced to a discrete map for hyperchaos generation and attractor self-reproduction. The constructed map shares a unique structure with controllable symmetry and conditional symmetry, which exhibits compound lattice dynamics, including 1-D and 2-D attractor growth. The direction of attractor growth can be controlled under polarity balance. STM32-based circuit realization verifies the results with numerical simulation and theoretical analysis. A pseudorandom number generator is built finally based on the newly proposed hyperchaotic map proving the high performance in application. [ABSTRACT FROM AUTHOR]

Trivalent Al3+-doped samples of magnetite (Alx ${\mathrm {Fe}}_{3-x}\text{O}$ 4, $0.01\le x \le1.0$) were produced by wet chemical method. The X-ray diffraction studies confirmed the formation of a single-phase inverse spinel-type structure. Particles having spherical morphology and size range lying between 4 and 25 nm were observed during transmission electron microscopic investigation. Magnetic measurement displayed increase in saturation magnetization with a maximum value of ~62 $\text{A}\cdot \text{m}$ 2/kg for $x =0.1$ , and thereafter, it started decreasing with increased concentration of Al. The temperature during magnetic hyperthermia got stabilized near therapeutic range (~315 K) for the samples such as $x =0.01$ , 0.5, 0.7, and 1.0 at various external alternating current magnetic fields. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs), as promising components of the sustainable and eco-friendly transportation systems, are being widely adopted to reduce the consumption of fossil fuel and pollution of environments. EVs are usually equipped with wireless modules to support the vehicle to vehicle communications, by which an electric vehicular network (EVN) is formed. In EVN, some EVs are with insufficient battery energy and may exhaust the battery energy before arriving at their destinations, and these EVs are referred to as IEVs. More seriously, IEVs probably cannot find any fixed charging facilities nearby. With the development of mobile charging technology, some movable charging stations (MCSs) are deployed into EVN, and MCSs can actively navigate to charge IEVs. In this paper, an assignment rescheduling mechanism of movable charging stations (ARMM) is proposed, where the MCS assignments are dynamically rescheduled. In ARMM, in order to reduce the charging expenses of IEVs and enhance the proportion of charged IEVs, the assigned IEVs of some MCSs could be switched to other MCSs, while the charging positions of MCSs are selected by minimizing the charging expenses of IEVs and are dynamically altered. Besides, the incentives of assigned IEVs to reduce the charging expenses of unassigned IEVs are proven. Simulation results demonstrate the preferable performance of ARMM, i.e. ARMM can reduce the charging expenses of IEVs and enhance the proportion of charged IEVs effectively. [ABSTRACT FROM AUTHOR]

Real-time semantic segmentation, which aims to achieve high segmentation accuracy at real-time inference speed, has received substantial attention over the past few years. However, many state-of-the-art real-time semantic segmentation methods tend to sacrifice some spatial details or contextual information for fast inference, thus leading to degradation in segmentation quality. In this paper, we propose a novel Deep Multi-branch Aggregation Network (called DMA-Net) based on the encoder-decoder structure to perform real-time semantic segmentation in street scenes. Specifically, we first adopt ResNet-18 as the encoder to efficiently generate various levels of feature maps from different stages of convolutions. Then, we develop a Multi-branch Aggregation Network (MAN) as the decoder to effectively aggregate different levels of feature maps and capture the multi-scale information. In MAN, a lattice enhanced residual block is designed to enhance feature representations of the network by taking advantage of the lattice structure. Meanwhile, a feature transformation block is introduced to explicitly transform the feature map from the neighboring branch before feature aggregation. Moreover, a global context block is used to exploit the global contextual information. These key components are tightly combined and jointly optimized in a unified network. Extensive experimental results on the challenging Cityscapes and CamVid datasets demonstrate that our proposed DMA-Net respectively obtains 77.0% and 73.6% mean Intersection over Union (mIoU) at the inference speed of 46.7 FPS and 119.8 FPS by only using a single NVIDIA GTX 1080Ti GPU. This shows that DMA-Net provides a good tradeoff between segmentation quality and speed for semantic segmentation in street scenes. [ABSTRACT FROM AUTHOR]

The performance of symbol detection in multiple-input multiple-output (MIMO) systems is largely determined by the achievable diversity order. The inter antenna interference (IAI), however, can limit detectors’ ability to take full advantage of diversity. This occurs because off-diagonal channel coefficients of the MIMO channel matrix are not mutually orthogonal. Nevertheless, this can be mitigated with the aid of lattice reduction (LR), which aims to increase the orthogonality among these coefficients. We propose a LR aided probability data association (PDA) detector that achieves a similar diversity order to that of the optimum detector but with significant less computational complexity. [ABSTRACT FROM AUTHOR]

Metal halides have been demonstrated to be promising candidates for X-ray detectors. However, its large leakage current caused by the severe ion migration and intrinsic defect substantially degrades device performance. In this work, an asymmetric BA2CsPb2I7-CsPbI3 planar heterojunction X-ray detector is designed to suppress the leakage current. Both experimental and theoretical calculations demonstrate that: 1) enlarged ion migration energy (0.80 eV) and conductivity mutation at the interface ensure stable baseline and suppress leakage current; 2) CsPbI3 ensures effective absorption of X-ray, while BA2CsPb2I7 induces larger bulk resistance, which is expected to achieve higher photocurrent and lower dark current. Finally, the obtained X-ray detector exhibits negligible baseline drift, faster response, and smaller leakage current compared to the CsPbI3 counterparts. Specifically, the device exhibits a detection limit of $0.092 ~\mu $ Gy $_{air}$ /s, and the CsPbI3-based device was $2.63 ~\mu $ Gy $_{air}$ /s. [ABSTRACT FROM AUTHOR]

This article proposes an original structure of evanescent quadridge antenna (EQA) to conceive dual-polarized full-metal front-ends that can be used in active antennas (AAs) with wide field-of-view (FoV). An original design methodology is here proposed that allows to induce radiation from subwavelength squared apertures based on the use of evanescent and quadridge waveguides. The proposal is illustrated by means of a design with 4.5% bandwidth providing dual-circular polarization (CP) with good performance up to 50°-scanning even in the diagonal plane. For comparison purposes, a metallic benchmark is also proposed, which is based on the use of classical quadridge horns. Such comparative analysis allows to understand the superior performance of the proposed concept and its main advantage: it allows to avoid the excitation of the first high order mode in the squared quadridge aperture. The excitation of such spurious mode in the antenna is explained in terms of simple equivalent circuit models characterizing the aperture periodic discontinuity. [ABSTRACT FROM AUTHOR]

A partitioning scheme based on Penrose-inspired subarrays is proposed for wide-scan planar phased arrays. The regular triangular lattice adopted for the arrangement of the antenna elements is organized into irregularly shaped tiles that exploit the properties offered by the Penrose tessellation. The novel array architecture ensures a remarkable reduction of the transmit/receive modules without harming the scan angle range and peak sidelobe level thanks to the optimization based on the Pareto front that is able to tackle conflicting objectives. The performance of the proposed approach is assessed in different scenarios and proves the robustness and flexibility of the new tiling architecture. Moreover, a thorough analysis is carried out to highlight the unique feature of the partition scheme of offering a noteworthy reduction in energy consumption. [ABSTRACT FROM AUTHOR]

This article presents the coupled electrothermal simulation results of single event burnout (SEB) in power diode with field limiting rings termination structure. Two different hardening techniques of low carrier lifetime control and introducing the buffer layer are investigated comparatively in both the radiation tolerance improvement and the electrical performance degradation. Our simulations reveal that a significant reduction in the carrier lifetime is needed for the hardening of the power diode using only the carrier lifetime control method. However, the sharp increases in the forward voltage drop and the leakage current at the lower carrier lifetime make this hardening technique unacceptable. On the contrary, the addition of the buffer layer is able to improve the safe operating area under the heavy ion irradiation even up to the breakdown voltage, while the breakdown characteristics and the leakage current are kept unchanged and the increases in the forward voltage drop and the reverse recovery charge can be well controlled. In conclusion, adding a buffer layer is considered a superior and promising hardening technique. [ABSTRACT FROM AUTHOR]

Frenkel pair (FP) formation at HfO2/Ti interface and oxygen vacancy interaction with the filament in HfO2/Ti-based resistive random access memory (ReRAM) are the important mechanisms in the ReRAM operations. In this article, the formation barriers, ${E}_{A}$ , and formation energies of ${V}_{O}/{O}_{i}$ FP across the HfO2/Ti interface with and without preexisting vacancy are calculated using the ab initio tool under zero external electric field. It is found that both the formation barrier and energy can be increased or decreased due to a preexisting oxygen vacancy. The spread of the effect increases inversely with the distance between the FP and the preexisting vacancy. A compact model is then proposed. The parallel migration barrier of an oxygen vacancy at the nearest and the second nearest neighbors (NNs) of a filament is also studied. It is found that the second NN has the lowest barrier due to its ability to retain a +2 charge state. The merging and dissolution of an oxygen vacancy with a filament (equivalent to perpendicular migration) is found to have a similar behavior that +2 states enhance the interaction. It is found that the fourfold coordinated oxygens (4C) and threefold coordinated oxygens (3C) filaments behave similarly during dissolution. However, 4C and 3C filaments prefer merging with 4C and 3C vacancy, respectively. The barrier of merging a +2 4C vacancy with a 4C filament is only 0.56 eV. The data and model obtained from this study may be used to implement device-level simulators, such as kinetic Monte Carlo (KMC) simulators, for ReRAM. [ABSTRACT FROM AUTHOR]

We consider the problem of representation learning for graph data. Given images are special cases of graphs with nodes lie on 2D lattices, graph embedding tasks have a natural correspondence with image pixel-wise prediction tasks such as segmentation. While encoder-decoder architectures like U-Nets have been successfully applied to image pixel-wise prediction tasks, similar methods are lacking for graph data. This is because pooling and up-sampling operations are not natural on graph data. To address these challenges, we propose novel graph pooling and unpooling operations. The gPool layer adaptively selects some nodes to form a smaller graph based on their scalar projection values. We further propose the gUnpool layer as the inverse operation of the gPool layer. Based on our proposed methods, we develop an encoder-decoder model, known as the graph U-Nets. Experimental results on node classification and graph classification tasks demonstrate that our methods achieve consistently better performance than previous models. Along this direction, we extend our methods by integrating attention mechanisms. Based on attention operators, we proposed attention-based pooling and unpooling layers, which can better capture graph topology information. The empirical results on graph classification tasks demonstrate the promising capability of our methods. [ABSTRACT FROM AUTHOR]

The nonionizing energy loss (NIEL) concept, introduced more than 40 years ago, is still used to characterize the damage generated by different particles and $\gamma $ -rays. Its continuing relevance is due to the experimentally established scaling in the creation rate of defects by radiation of different types. NIEL calculations are quite simple, based on classical physics. We thus name them classical NIEL, NIELc. Their calculation depends on an $a$ priori known $E_{d}$ -displacement threshold energy in monoatomic materials. For the compound semiconductor materials studied here, Ga $X$ and In $X$ , where $X$ are the cations N, P, As, Sb, the experimental $E_{d}$ values vary over a wide range and only approximate values for NIELc can be calculated. Thanks to some recent studies carried out using the molecular dynamic (MD) method, the NIEL values were estimated using atomic scale calculations. Consequently, we can now compare NIELc with more precise data. These data also include the “dynamic” behavior of the NIEL, which is related to the annealing of the damage (like Frenkel pair recombination) and the generation of extended crystalline defects. The NIEL calculated using the MD method is referred to in the literature as NIELeff. A detailed comparison between NIELc and NIELeff as a function of electron and proton energies is made here. It shows that the difference between the two quantities is not large and cannot influence the dependence of NIEL on temperature and different radiation types. Both yield similar results in calculating the effect of displacement damage. As an additional use of NIELc, we analyze its application to estimate the relative tolerance of the different members of the Ga $X$ and In $X$ families to radiation defects as a function of particle energies. [ABSTRACT FROM AUTHOR]

The magnetization stability of a YBCO superconductor was numerically studied using the Monte Carlo method. The magnetization-reversal loops of samples with various pinning configurations (periodic and random) were calculated as well as minor loops caused by field inhomogeneities. Hysteresis energy losses were estimated via areas bounded by the minor loops at different temperatures. Samples providing a balance between the critical current, pinning properties, and energy losses, were identified. Among the considered distributions, the homogeneous (periodic) defect configurations showed the highest efficiency. [ABSTRACT FROM AUTHOR]

MnxAl100-x and MnyGe100−y alloy epitaxial films of 20 nm thickness are prepared on Cr(001) single-crystal underlayers at 300 °C by varying the Mn content, $x$ or $y$ , from 0 to 100 at. %. The formation of crystallographic phase is systematically investigated as a function of composition by reflection high-energy electron and X-ray diffractions. The phases in MnxAl100−x and MnyGe100−y films are determined to vary in the orders of $A 1=> L 1_{0} + A 12=> L 1_{0} => A 2=> A12$ and $A 4=> tP => cP => D 0_{22} => A12$ with increasing the Mn content, respectively. Metastable fct-based ordered $L1$ 0 phase is formed in the MnxAl100−x films with $x $ = 50– $65. L1$ 0 single phase is obtained at an Mn-rich composition of $x $ = 58, whereas bcc-based disordered $A12$ and $A2$ phases are, respectively, involved at the $L1$ 0 stoichiometric composition of $x $ = 50 and at a more Mn-rich composition of $x $ = 65. Employment of a slight Mn-rich composition stabilizes $L1$ 0 phase. On the other hand, metastable fct-based ordered $D0$ 22 phase is formed in the MnyGe100−y films with $y$ = 60– $75. D0$ 22 single phase is obtained in the range from the stoichiometric composition of $y$ = 75 to a slightly Mn-poor composition of $y $ = 68. The $c$ -axis orientation is normal to the film surface for both $L1$ 0 and $D0$ 22 crystals. The present study has clarified the crystal structure and growth of MnxAl100−x and MnyGe100−y films for the respective full compositional ranges and has shown that control of the composition is important to obtain $L1$ 0 and $D0$ 22 ordered Mn-based alloy films with perpendicular magnetic anisotropies. [ABSTRACT FROM AUTHOR]

In the process of NIST postquantum cryptography standardization, module lattice-based Dilithium has been chosen as one of the three third-round finalists for digital signature schemes. More evaluations of its implementation efficiency on different platforms are required for further competition. In this article, we present an efficient implementation of Dilithium on a field-programmable gate array (FPGA) system-on-chip (SoC) platform. To achieve a high computation speed, we design a hardware architecture to perform the main body of the algorithm, and the preprocessing and postprocessing steps are accomplished by the processor. For the hardware architecture, we take some optimizations on the most time-consuming operations, that is, polynomial multiplication, hashing, and sampling. Polynomial multiplications are accelerated by the radix-4 number theoretic transform (NTT) architecture with a conflict-free memory mapping scheme. A fast modular multiplication on the Dilithium modulus is proposed to support the underlying calculations. For hashing and sampling, we design a multipurpose hashing unit and a compact sampling unit. The cooperative work of the two units accelerates the sampling process significantly. We implement the Key Generation, Signing, and Verification algorithms of the round-3 Dilithium at all three security levels on the Xilinx Zynq-7000 platform. Compared with existing software/hardware codesign for Dilithium on a similar platform, our design achieves about $17\times $ and $40\times $ improvements in performance for the Signing and Verification algorithms, respectively, at the cost of about $7.8\times $ more look up table (LUT) resources. [ABSTRACT FROM AUTHOR]

This article continues the theoretical study of weighted structures in mathematical fuzzy logic focusing on the finite model theory of fuzzy logics valued on arbitrary finite $\mathrm{MTL}$ -chains. We show that for any first-order (or infinitary with finitely many variables) formula $\varphi$ , there is a truth-value that $\varphi$ takes almost surely in every finite many-valued model and such that every other truth-value is almost surely not taken. This generalizes a theorem in the fuzzy setting due to Robert Kosik and Christian G. Fermüller. [ABSTRACT FROM AUTHOR]

Granularrules have been extensively used for classification in fuzzy datasets to promote the advancement of artificial intelligence. However, due to the diversity of data types, how to improve the readability of the extracted granular rules while ensuring efficiency is always a challenge. Since granular reduct in granular computing (GrC) can simplify real complex problem and dataset, this article carries out granular rule learning from the perspective of granular reduct by taking formal concept analysis (FCA)-based GrC method as a framework. Specifically, for achieving classification task, we first propose a method to update the granular reduct, and then explore the updating mechanism of fuzzy granular rule in a reduced dataset. Second, a novel fuzzy rule-based classification model named FRCM is presented for fuzzy granular rule learning. In order to verify the effectiveness of the proposed model, some numerical experiments for incremental learning and fuzzy rule mining are conducted to demonstrate that FRCM can achieve the state-of-the-art classification performance. [ABSTRACT FROM AUTHOR]

The aggregate signature is a special signature mode widely used in the wireless medical sensor network. The aggregate signature can reduce bandwidth and storage space in this sensor network by aggregating multiple signatures from different signers into a short signature. Traditional aggregate signature protocols based on the discrete logarithm problem and the great integer factorization problem cannot resist quantum attacks. In this article, we propose a new noninteractive identity-based aggregate signature protocol from lattices. We prove that the proposed protocol is secure in the quantum random oracle model. Additionally, the performance of the proposed protocol is much better than most previous protocols according to our experiment. Meanwhile, the size of the aggregate signature in our protocol is a logarithmic function of the number of signatures being aggregated. [ABSTRACT FROM AUTHOR]

Achieving broadband angular selectivity has been attracting much interest from both scientists and engineers in recent years. Previous experimental demonstrations have been limited to the $p$ -polarized incidence. Here, we propose a universal approach to achieve polarization-independent broadband angular selectivity by introducing electrically and magnetically anisotropic diamagnetic medium into multiple 1-D photonic crystal stacks. Such stacks have a broadband angular photonic bandgap for both $s$ - and $p$ -polarized waves. The anisotropic diamagnetic medium is artificially constructed with periodically arranged close metallic ring arrays, which exhibits a negligible frequency dispersion in an ultrawide band. As a proof of principle, one stack of photonic structures for the normal-incidence-selective case is fabricated and measured in the microwave region. The proposed approach is simple, robust, and scalable from near-zero frequencies to terahertz frequencies, showing promising practical applications such as spatial filters and anti-jamming communications. [ABSTRACT FROM AUTHOR]

In this communication, a novel metasurface with multiple unit cells of different thicknesses based on optimized multielement phase cancellation (OMEPC) is proposed for extremely wideband, omnidirectional, and polarization-independent radar cross section (RCS) reduction under wide-angle oblique incidence. Omnidirectional characteristic refers to the capability of RCS reduction under all azimuth angles ($\varphi ^{i}$) at certain elevation angles ($\theta ^{i}$). The equivalent circuit model of the square patch unit cell is analyzed under both normal and oblique incidences. Unit cells of multiple thicknesses are adopted to solve the in-phase reflection at certain frequencies. The scattered fields of the proposed multiple-element metasurface under different frequencies, polarizations, and incident angles are jointly optimized and simultaneously suppressed by OMEPC. When the range of incident angles is increased from 0° to 40°, the proposed multiple-element metasurface can achieve the 10 dB specular RCS reduction from 7.34 to 64.85 GHz with a ratio bandwidth of 8.84:1 for both TE and TM polarizations, and the 8 dB RCS reduction bandwidth is approximately 6.76–83.70 GHz. The measurement results are in agreement with the theoretical analysis and simulation results. [ABSTRACT FROM AUTHOR]

In this study, Pre-diagnosis of degraded aluminum indium gallium phosphide (AlInGaP) light-emitting diodes (LEDs) that were soaked in liquid nitrogen (LN2) was performed. To visualize the early deterioration of LED emission, a combination of material, electrical, optical, and computer-aided machine-vision analysis of LED failure spots on the surface was examined. Results indicate that several small failure spots, which can be identified by the MATLAB processed emission images and surface roughness variation, can be found. Furthermore, LN2 soaking induced some local damages inside the device that penetrate the multiple-quantum well. The decrease of current and luminescence intensity also reflects the gradual degradation of the device after being soaked in LN2. This integrated analysis and Pre-diagnosis of the degraded device provided early screening of LED failure spots and real-time inspection during operations. [ABSTRACT FROM AUTHOR]

In this article, we have evaluated the merits of monolithically cointegrated alternate channel complementary metal-oxide-semiconductor (CMOS) device architecture, utilizing tensile strained germanium ($\boldsymbol {\varepsilon }$ -Ge) for the p-channel FinFET and variable indium (In) compositional InxGa1-xAs ($0.10\le {x} \le0.53$) for the n- channel FinFET. The device simulation models were calibrated using the experimental results of Ge and InGaAs FinFETs and subsequently transferred to the cointegrated Ge and InxGa1-x As structure while keeping the device simulation parameters fixed. The device parameters, such as ${V}_{\text {T}}$ , ${I}_{\text {on}}$ , ${I}_{\text {off}}$ , and subthreshold-swing (SS), were determined for identical fin dimensions for n- and p-channel FinFETs as a function of In composition that alters the tensile strain in Ge. These parameters are controllable during the heteroepitaxial growth by varying In composition in InxGa1-xAs. $\boldsymbol {\varepsilon }$ -Ge p-FinFET is shown to be superior in terms of SS and ${I}_{\text {on}}/{I}_{\text {off}}$ ratio compared with other competing architectures. The cointegrated architecture of CMOS inverter exhibited an optimum performance over a range of In compositions from 20% to 40% while driving fan-out fan-out 1 (FO-1) and FO-4 load configurations. In addition, the CMOS inverter with symmetric rise and fall times as well as noise-immune functionality demonstrated 150 GHz of operating frequency with 30-nW total power dissipation at 20% In composition, and hence a superior power-delay-product comparable with International Technology Roadmap for Semiconductors (ITRS) standards. Moreover, the three-stage CMOS ring oscillator performance was evaluated with various In compositions to be stable and power efficient. Thus, the cointegrated approach has a potential to: 1) simplify large-scale CMOS integration and 2) be compatible with optoelectronic materials. [ABSTRACT FROM AUTHOR]

We propose a new STAckable Recurrent cell (STAR) for recurrent neural networks (RNNs), which has fewer parameters than widely used LSTM [16] and GRU [10] while being more robust against vanishing or exploding gradients. Stacking recurrent units into deep architectures suffers from two major limitations: (i) many recurrent cells (e.g., LSTMs) are costly in terms of parameters and computation resources; and (ii) deep RNNs are prone to vanishing or exploding gradients during training. We investigate the training of multi-layer RNNs and examine the magnitude of the gradients as they propagate through the network in the ”vertical” direction. We show that, depending on the structure of the basic recurrent unit, the gradients are systematically attenuated or amplified. Based on our analysis we design a new type of gated cell that better preserves gradient magnitude. We validate our design on a large number of sequence modelling tasks and demonstrate that the proposed STAR cell allows to build and train deeper recurrent architectures, ultimately leading to improved performance while being computationally more efficient. [ABSTRACT FROM AUTHOR]

This paper deals with hardware implementations for lattice-based cryptography. Various CPA and CCA secure algorithms for LWE, RLWE and MLWE problems have been studied, parallelized, implemented and compared on FPGA using high-level synthesis. The impact of PRNG choices on the implementations performances and costs is also evaluated. HLS allows us to compare various sets of algorithms, architectures and parameters with a reduced design effort. Our results are often similar to state-of-the-art for various speed and cost trade-offs. Sometimes we obtain better results thanks to the exploration of numerous architecture and algorithm optimizations. [ABSTRACT FROM AUTHOR]

Nitride based light emitting diodes (LEDs) have demonstrated very high efficiency in the blue and green wavelength ranges. For full color LED based displays, efficient and small sized devices emitting in the three primary colors - red, green and blue are required. While phosphide based red LEDs are highly efficient, high surface recombination velocities limit their scaling to small dimensions. Nitride emitters can be scaled to smaller sizes, however for longer emission wavelength such as yellow, orange, and red, the indium content in the active region of the devices needs to be >30%. Due to the large lattice mismatch between GaN and InN, the needed high indium content introduces a large strain in the structure, often resulting in poor material quality. Recently, a novel technique to mitigate this lattice mismatch induced strain was demonstrated with the use of compliant porous GaN underlayer based substrates. In our previous reports, we have discussed the surface morphology, strain state evolution and device demonstrations using these substrates, however a detailed discussion regarding the pore cross-sections and dislocation propagation for each generation of these porous GaN substrates was yet to be reported. In this work, we will discuss the cross-sectional transmission electron microscopy (TEM) results of these substrates across multiple stages of the substrate technology development. [ABSTRACT FROM AUTHOR]

Since the initial proposal in 1999 by Noda et al., photonic crystal surface emitting lasers (PCSELs) have shown to achieve large area, coherent lasing with a narrow, single mode beam. Owing to their unique orthogonal electrical/optical cavity scheme, PCSELs have emerged as one of the most promising platforms for high power diode lasers. In this paper, we report the performance trade-offs and challenges in power scaling, modal competition, and charge injection control. To address these challenges, we investigate the electrical and optical performances of PCSELs under high-power operation. Heterostructure designs with electron block layers were incorporated for efficient and balanced electrical charge injection. Symmetry breaking strategy was introduced in the photonic crystal design to engineer the in-plane momentum dependent quality factor (Q(k)) for mode discrimination and single mode operation. The impact of electrode designs was also investigated to achieve large area uniform charge injection. Simulation results of these designs indicate promising solutions and improved performances for large-area high-power and single-mode PCSEL operations. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS-MPC) strategies for power conversion devices benefit from extending the prediction horizon length. Solving this problem relies on the definition of the underlying integer least-squares problem. Sphere decoding algorithm (SDA) has been extensively used in previous works as an approach to solve this problem. In this article, a parallel and fully scalable K-best SDA hardware design is proposed as an alternative. The K-best SDA establishes a different breadth-first search strategy, which addresses some of the main drawbacks of the SDA. Through experimental tests based on an uninterruptible power supply, the K-best SDA performance for long prediction horizon FCS-MPC is assessed and verified. Results demonstrate key beneficial aspects through which the K-best SDA is capable of rendering an improved control performance when compared to the conventional SDA. [ABSTRACT FROM AUTHOR]

The nearest lattice point problem in $\mathbb {R}^{n}$ is formulated in a distributed network with $n$ nodes. The objective is to minimize the probability that an incorrect lattice point is found, subject to a constraint on inter-node communication. Algorithms with a single as well as an unbounded number of rounds of communication are considered for the case $n=2$. For the algorithm with a single round, expressions are derived for the error probability as a function of the total number of communicated bits. We observe that the error exponent depends on the lattice structure and that zero error requires an infinite number of communicated bits. In contrast, with an infinite number of allowed communication rounds, the nearest lattice point can be determined without error with a finite average number of communicated bits and a finite average number of rounds of communication. In two dimensions, the hexagonal lattice, which is most efficient for communication and compression, is found to be the most expensive in terms of communication cost. [ABSTRACT FROM AUTHOR]

Metastable $\alpha '$ -Fe-N (12 at% N) and $\alpha '$ -Fe-C (12 at% C) are unique materials with a magnetocrystalline constant $K_{1}$ of + $5\times10$ 6 and $- 7\times10$ 6 erg/cm3, respectively, according to measurements based on thin films. Therefore, co-addition $\alpha ''$ -Fe $_{16}X_{2}$ ($X $ = N, C) particles are attractive as potential new soft magnetic materials because their magnetocrystalline constant can be varied by manipulating their N and C concentrations. However, introducing C interstitially into $\alpha $ -Fe particles by the carbonization process using a C-containing gas such as CO gas is difficult because the equilibrium phase Fe3C is easily generated. Therefore, we investigated various reaction routes of nitridation and carbonization, along with various C-containing gases, to prepare co-addition $\alpha ''$ -Fe16(N, C)2 particles. We obtained $\alpha ''$ -Fe16(N, C)2 particles using a route in which $\alpha $ -Fe was obtained by reduction of Fe3O4 particles, followed by nitridation to $\alpha ''$ -Fe16N2 and subsequent carbonization to $\alpha ''$ -Fe16(N, C)2. The amount of C particles after carbonization was measured to be 0.8 wt% (3.6 at%). This gas–solid reaction process based on the concept of using $\alpha ''$ -Fe16N2 as a material with an expanded $\alpha $ -Fe lattice is a useful method for the co-addition of interstitial N and C. [ABSTRACT FROM AUTHOR]