Discrete Modulation Research Articles

Influence of realistic EV fleet response with power and energy controllers in an EV-wind virtual power plant

To facilitate the integration of volatile renewable energy sources (RES), electric vehicle (EV) fleets are considered valuable flexibility assets. With their storage capability, they can contribute to compensating for fluctuations and providing balancing support when integrated in a virtual power plant (VPP). This paper investigates the response of an EV fleet to wind power fluctuations by accounting for non-synchronized activation time and discrete modulation of the charging current. The influence of the EV fleet response is further investigated comparing a power-based controller with an energy-based one. Results show that a realistic EV fleet response affects the VPP output more when a power controller is considered. A discrete modulation of the EV charging current can cause oscillations, which would not occur with a linear modulation. Positively, the influence of a non-synchronized EV activation time is negligible for both controllers, proving that a synchronized activation time can be assumed during similar studies. Despite the equality from a mathematical perspective, the hourly VPP energy production when an EV fleet is controlled with a power controller does not correspond to when an energy controller is adopted.

Implementation of modified switching table for direct power control of shunt active power filter

ABSTRACT The direct power control (DPC) technique has been proposed as an alternative method to sophisticated current control techniques in order to synthesise the instantaneous active and reactive powers fed by the inverter into the grid. The method selects the voltage vector of the inverter based on the quantised values of the instantaneous active and reactive power errors and thereby controls the power exchange between inverter and the Point of Common Coupling (PCC) directly. The method has better dynamic performance, an inherent decoupling of active and reactive powers and robustness against parameter variations. However, the application of DPC to shunt active power filter (SAPF) requires high sampling frequency in the digital controller and at the same time suffers from the issue of the large variation in the switching frequency. This work proposes implementation of a modified switching table of DPC using multisector Discrete Space Vector Modulation(DSVM) concept for the SAPF to alleviate the problem of high sampling frequency requirement and variation in switching frequency and reduce burden on the controller. The performance of the method is evaluated in MATLAB Simulink® environment, verified with 2 kVA laboratory prototype under various load conditions and compared with constant switching frequency-predictive deadbeat DPC method.

Performance analysis of continuous-variable quantum key distribution using non-Gaussian states

In this study, we analyze the efficiency of a protocol with discrete modulation of continuous variable non-Gaussian states, the coherent states having one photon added and then one photon subtracted (PASCS). We calculate the secure key generation rate against collective attacks using the fact that Eve's information can be bounded based on the protocol with Gaussian modulation, which in turn is unconditionally secure. Our results for a four-state protocol show that the PASCS always outperforms the equivalent coherent states protocol under the same environmental conditions. Interestingly, we find that for the protocol using discrete-modulated PASCS, the noisier the line, the better will be its performance compared to the protocol using coherent states. Thus, our proposal proves to be advantageous for performing quantum key distribution in non-ideal situations.

Experimental study on underwater continuous-variable quantum key distribution with discrete modulation.

We experimentally demonstrated the feasibility of an underwater continuous-variable quantum key distribution (CV-QKD) system based on four-state protocol, which is promising to guarantee the unconditionally secure underwater wireless optical communication. CV-QKD parameter estimation is performed after transmitting quantum coherent signal from Alice to Bob through a water tank. The secure key rate under collective attack of the demonstrated CV-QKD system is estimated as 22.9 kbits/s at a channel loss of 12.4 dB. In addition, the performance is also investigated with various water types and the maximum underwater transmission distance of the demonstrated CV-QKD system is estimated as 148.7 m in the pure sea water.

Even sampling photonic-integrated interferometric array for synthetic aperture imaging.

To improve the effectiveness of spatial spectrum sampling for the photonic-integrated interferometric imaging, an array forming scheme is proposed with evenly distributed interferometric baselines, which is referred to as the even sampling photonic-integrated interferometric array (ESPIA). The subaperture array of ESPIA is configured as equi-spaced concentric rings. The subaperture beams are coupled and transmitted to the photonic integrated circuit through fiber optic channels and paired into baselines by the interferometric beam combination. The characteristics of ESPIA are analyzed with the discrete modulation transfer function (D-MTF) and multi-resolution mutual information (MR-MI). The simulation results show that it can realize the even sampling coverage of spatial spectrum effectively. With the same scale of synthetic aperture and subaperture array, it can also improve the capabilities of information acquisition for the interferometric array.

Study of differential proteomics in granulosa cells of premature ovarian insufficiency (POI) and the roles and mechanism of RAC1 in granulosa cells

In the present study, we focused on characterizing the proteome in granulosa cells in patients with biochemical premature ovarian insufficiency (bPOI) in order to identify differential proteins and investigate the fundamental mechanisms of POI. A total of 2688 proteins were identified based on the data-independent acquisition method, and 70 differentially expressed proteins were significant. Bioinformatic analyses, including gene expression pattern analysis, gene ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Search Tool for the Retrieval of Interacting Genes/Proteins analysis, revealed discrete modules and the underlying molecular mechanisms in bPOI. Importantly, we observed that Ras-related C3 botulinum toxin substrate 1 (RAC1) was downregulated in the granulosa cells of bPOI. Low expression of RAC1 may affect the development process of POI by affecting the proliferation, apoptosis, and hormone synthesis of granulosa cells. Downregulation of RAC1 expression in the KGN and COV434 cells inhibited cell proliferation, blocked cells in the G1/G0 phase, and promoted apoptosis. Western blot results showed that β-catenin and cyclin D1 in the KGN and COV434 cells transfected with RAC1-siRNA were downregulated, while P21 and Bax were upregulated. Knocking down RAC1 in the KGN cells or adding the RAC1 enzyme inhibitor to the human luteinized granulosa cells (hLGC) inhibited the synthesis of E2, and the expression of aromatase and follicle-stimulating hormone receptor (FSHR) was reduced.

Topologically semisimple and topologically perfect topological rings

Extending the Wedderburn-Artin theory of (classically) semisimple associative rings to the realm of topological rings with right linear topology, we show that the abelian category of left contramodules over such a ring is split (equivalently, semisimple) if and only if the abelian category of discrete right modules over the same ring is split (equivalently, semisimple). Our results in this direction complement those of Iovanov-Mesyan-Reyes. An extension of the Bass theory of left perfect rings to the topological realm is formulated as a list of conjecturally equivalent conditions, many equivalences and implications between which we prove. In particular, all the conditions are equivalent for topological rings with a countable base of neighborhoods of zero and for topologically right coherent topological rings. Considering the rings of endomorphisms of modules as topological rings with the finite topology, we establish a close connection between the concept of a topologically perfect topological ring and the theory of modules with perfect decomposition. Our results also apply to endomorphism rings and direct sum decompositions of objects in certain additive categories more general than the categories of modules; we call them topologically agreeable categories. We show that any topologically agreeable split abelian category is Grothendieck and semisimple. We also prove that a module $\Sigma$-coperfect over its endomorphism ring has a perfect decomposition provided that either the endomorphism ring is commutative or the module is countably generated, partially answering a question of Angeleri Hugel and Saorin.

Настенный газовый конвекционный котел с атмосферной горелкой двойной модуляции

Introduction. Apartment heating requires the thermal capacity of no more than 1.0–2.5 kW; hot water preparation needs 15–25 kW. Convection gas boilers cannot operate efficiently, if a change in the range of smooth modulation reaches 20 times. Discrete modulation is triggered in the heating mode, which is also accompanied by a substantial increase in greenhouse gas emissions and a sharp decline in energy efficiency. The heating of such premises requires heat generators operating in the two ranges of thermal capacity. Materials and methods. The author analyzes the operation of a wall-mounted convection gas boiler with an atmospheric burner equipped with a three-section manifold that ensures a smooth modulation range of 2.4–6 kW, when the boiler is in the heating mode, and the modulation range of 15–24 kW, when the boiler is in the hot water supply mode (HWS). Results. The author made boiler efficiency diagrams for the heating and HWS modes during the steady boiler operation; the author also made boiler diagrams for discrete modulation modes and the regular on-off switching of the boiler. A direct method, that entailed the study of the flow rates of gas and heat conductor, as well as the boiler inlet and outlet temperatures, was employed to find the energy efficiency values. Conclusions. The use of conventional wall-mounted gas convection boilers as a source of heating for the 60 m2 premises entails discrete capacity modulation, that causes a substantial reduction in the energy efficiency of a heating system and rises greenhouse gas emissions. The application of efficiency indicators to different modes of operation of boilers does not convey the real mode of operation of a boiler during the heating period, since it entails a substantial overestimation, while wall-mounted convection boilers, having atmospheric burners with two ranges of smooth modulation, ensure highly efficient apartment heating.

Experimental demonstration of high-rate discrete-modulated continuous-variable quantum key distribution system.

A high-rate continuous-variable quantum key distribution (CV-QKD) system based on high-order discrete modulation is experimentally investigated. With the help of the novel system scheme, effective digital signal processing (DSP) algorithms and advanced analytical security proof methods, the transmission results of 5.059 km, 10.314 km, 24.490 km, and 50.592 km are achieved for 1 GBaud optimized quantum signals. Correspondingly, the asymptotic secret key rates (SKRs) are 292.185 Mbps, 156.246 Mbps, 50.491 Mbps, and 7.495 Mbps for discrete Gaussian (DG) 64QAM, and 328.297 Mbps, 176.089 Mbps, 51.304 Mbps, and 9.193 Mbps for DG 256QAM, respectively. Under the same parameters, the achieved SKRs of DG 256QAM is almost same as ideal Gaussian modulation. In this case, the demonstrated high-rate discrete-modulated CV-QKD system has the application potential for high-speed security communication under tens of kilometers.

Computational fluid dynamics simulation and experimental investigation of a thermoelectric system for predicting influence of applied voltage and cooling water on cooling performance

PurposeThe purpose of this paper is to experimentally and numerically investigate the cooling performance of the air-to-water thermoelectric cooling system under different working conditions.Design/methodology/approachAn air-to-water thermoelectric cooling system was designed and manufactured according to the principle of discrete binary thermoelectric Peltier modules, and the thermal performance, heat transfer rate and average COP values were examined at different cooling water temperatures and voltages applied. Additionally, numerical simulations were performed by computational fluid dynamics approach to investigate the temperature distribution and airflow structure inside the cooling chamber.FindingsAnalyses were performed using experimental tests and numerical methods. It was concluded that, by decreasing the cooling water temperature from 20 to 5 °C, the average COP increases about 36%. The voltage analysis showed that the efficiency of the system does not always increase as the voltage rises; more importantly, the optimum voltage is different and depends on whether it is desired to increase COP or increase the cooling rate.Originality/valueIn the studies published in the field of thermoelectric cooling systems, little attention has been paid to the voltage applied and its relationship to other operating conditions. In most cases, the tests are performed at a constant voltage. In this study, several options, including applied voltage and cooling water temperature, were considered simultaneously and their effects on performance have been tested. It was found that under such studies, optimization work should be done to evaluate maximum performance in different working conditions.

Proton radiography using discrete range modulation method – A Monte Carlo study

The advantage of proton therapy is the Bragg peak, but its range uncertainties can also lead to a certain dose deviation. This uncertainty can be reduced by using proton radiography to determine the water equivalent path length (WEPL). In this study, a discrete range modulation (DRM) method is introduced and its image quality compared with that of the previously reported continuous range modulation (CRM) method. MCNPX2.7.0 was used to simulate parallel proton beams with energies from 70 to 230 MeV at 2.5 MeV/step. In the DRM method, the WEPL can be related to R80 using the relationship between the proton energy and energy deposition at 80% of the fall-off (E80). For the CRM method, a dose gradient plan was created to estimate the relationship between WEPL and accumulated dose. DRM and CRM were compared using four different phantoms. For the slab, CIRS 062M head and cake phantoms, DRM had a good agreement with the theoretic WEPL: within 2 mm or 1%, and with a standard deviation of less than 0.5 mm. For the sphere phantom, DRM can achieve a GammapRG passing rate of 0.999, passing the criteria of a WEPL deviation of less than 2 mm and a distance-to-agreement of less than 3 mm. Proton radiographs made by the DRM method are more accurate and precise than those made by CRM. Two algorithms are proposed to solve the range mixing problems. DRM can also save unnecessary doses that do not contribute to imaging.

Model Predictive Control for PMSM Based on Discrete Space Vector Modulation with RLS Parameter Identification

Model Predictive Control (MPC) based on Discrete Space Vector Modulation (DSVM) has the advantages of simple mathematical model and fast dynamic response. It is widely used in permanent magnet synchronous motor (PMSM). Additionally, the control performance of DSVM-MPC is influenced by the accuracy of motor parameters and the select speed of optimal voltage vector. In order to identify motor parameters accurately, model predictive control for PMSM based on discrete space vector modulation with recursive least squares (RLS) parameter identification is proposed in this paper. Additionally, a method to preselect candidate voltage vectors is proposed to select the optimal voltage vector more quickly. The simulation model of RLS-DSVM-MPC is established to simulate the influence of different parameters on PMSM performance. The simulation results show that model predictive control for PMSM based on discrete space vector modulation with RLS parameter identification has a better control performance than that of without RLS parameter identification.

Novel Stilbene-Nitroxyl Hybrid Compounds Display Discrete Modulation of Amyloid Beta Toxicity and Structure.

Several neurodegenerative diseases are driven by misfolded proteins that assemble into soluble aggregates. These “toxic oligomers” have been associated with a plethora of cellular dysfunction and dysregulation, however the structural features underlying their toxicity are poorly understood. A major impediment to answering this question relates to the heterogeneous nature of the oligomers, both in terms of structural disorder and oligomer size. This not only complicates elucidating the molecular etiology of these disorders, but also the druggability of these targets as well. We have synthesized a class of bifunctional stilbenes to modulate both the conformational toxicity within amyloid beta oligomers (AβO) and the oxidative stress elicited by AβO. Using a neuronal culture model, we demonstrate this bifunctional approach has the potential to counter the molecular pathogenesis of Alzheimer’s disease in a powerful, synergistic manner. Examination of AβO structure by various biophysical tools shows that each stilbene candidate uniquely alters AβO conformation and toxicity, providing insight towards the future development of structural correctors for AβO. Correlations of AβO structural modulation and bioactivity displayed by each provides insights for future testing in vivo. The multi-target activity of these hybrid molecules represents a highly advantageous feature for disease modification in Alzheimer’s, which displays a complex, multifactorial etiology. Importantly, these novel small molecules intervene with intraneuronal AβO, a necessary feature to counter the cycle of dysregulation, oxidative stress and inflammation triggered during the earliest stages of disease progression.

SCELT (symbolic computation aided eigenvalue and linear code for tokamaks): A full MHD eigenvalue code in toroidal geometry developed with the use of a symbolic computation technique

In this work, we report the construction of an eigenvalue computer code largely in C++ language, SCELT, by using the symbolic computation technique for the first time to solve the linearized single fluid magnetohydrodynamic (MHD) eigenvalue problem in toroidal geometry. A symbolic vector analysis module is developed to function the automatic derivation of the tedious linearized full MHD equations in the magnetic flux coordinate system. Furthermore, another module is developed to implement the automatic numerical discretization. These two modules dramatically reduce the human workload and obviate the possibility of a mistake during code development. The tools provide a means of constructing matrices from differential operations and can be used for (generalized) linear problems, such as source driven and eigenvalue problems. Demo uses of both the symbolic vector analysis module and automatic numerical discretization module, such as the Poisson equation and tokamak equilibrium equation, are presented to demonstrate their advantages and potential broad applications. The full MHD eigenvalue code developed with these two modules is verified by the internal kink mode and tearing mode tests. Program summaryProgram Title: SCELT (Symbolic Computation aided Eigenvalue and Linear code for Tokamaks)CPC Library link to program files:https://doi.org/10.17632/35h3xmc28k.1Licensing provisions: GNU General Public License 3.0Programming language: C++, MATLABExternal routines/libraries:• EIGEN (https://eigen.tuxfamily.org/index.php?title=Main_Page)Nature of problem: The eigenvalue full MHD model determines a wide range of physical phenomena arising from the basic destabilizing forces, which are of considerable both fundamental and practical importance for magnetic fusion plasmas. From the viewpoint of physics, solving the model is equivalent to finding the spectrum of the system, and for realistic tokamak geometry, it becomes possible only with the help of computer simulation. From the viewpoint of mathematics, it is actually a problem of solving a set of partial differential equations in a general curvilinear coordinate system.Solution method: Different from the conventional method, a symbolic vector analysis module using the symbolic computation technique is developed to conduct the automatic expansion of the full MHD equations in the magnetic flux coordinate system. In addition, an automatic numerical discretization module is developed to automatically implement the numerical discretization. Facilitated by the two modules, the coefficients of the matrices of the eigenvalue equation will be automatically generated and passed to the linear eigenvalue solver (eig function of MATLAB). The eigenvalues and eigenvectors are resolved by the solver.Additional comments including restrictions and unusual features: As originally motivated by the development of an eigenvalue full MHD code, a symbolic vector analysis module by using symbolic computation technique and a closely related automatic numerical discretization module are developed and directly applied to physics code development for the first time at least in the fusion field. Many (generalized) linear physics problems can benefit from the standalone or integrated application of these two modules. The tokamak equilibrium and eigenvalue MHD problems presented in the paper can be considered two important and practical examples.

Electrostatic Discharge Sensing of Concentric Circles of Poly2 with Different Potentials and Discrete High-voltage P-well Modulation on Circular Ultrahigh-voltage N-channel Laterally Diffused MOSFET Devices

Electrostatic Discharge Sensing of Concentric Circles of Poly2 with Different Potentials and Discrete High-voltage P-well Modulation on Circular Ultrahigh-voltage N-channel Laterally Diffused MOSFET Devices

580-nm-thick vertical-structure light-emitting diode for visible light communication

Visible light communication (VLC) is a key technology for 6G. Here, we propose, fabricate, and characterize a vertical-structure light-emitting diode (VSLED) to manage the dilemma of both power and speed for VLCs. Ultrathin VSLED architecture offers the unique features of decreasing the RC time constant for increasing modulation bandwidth and reducing confined optical modes inside the diode for enhancing light extraction. A 580-nm-thick VSLED with a dominant emission wavelength of 427.8 nm is implemented on a 2-in. metal-based bonded III-nitride-on-silicon wafer. Based on a bit-loading discrete multitone modulation scheme, we establish a visible light communication system using 1 × 1 mm2 VSLED, which can achieve a data transmission rate of 608 Mbps at a baud rate of 200 MBaud.

An RNA-sequencing transcriptome of the rodent Schwann cell response to peripheral nerve injury

BackgroundThe important contribution of glia to mechanisms of injury and repair of the nervous system is increasingly recognized. In stark contrast to the central nervous system (CNS), the peripheral nervous system (PNS) has a remarkable capacity for regeneration after injury. Schwann cells are recognized as key contributors to PNS regeneration, but the molecular underpinnings of the Schwann cell response to injury and how they interact with the inflammatory response remain incompletely understood.MethodsWe completed bulk RNA-sequencing of Schwann cells purified acutely using immunopanning from the naïve and injured rodent sciatic nerve at 3, 5, and 7 days post-injury. We used qRT-PCR and in situ hybridization to assess cell purity and probe dataset integrity. Finally, we used bioinformatic analysis to probe Schwann cell-specific injury-induced modulation of cellular pathways.ResultsOur data confirm Schwann cell purity and validate RNAseq dataset integrity. Bioinformatic analysis identifies discrete modules of genes that follow distinct patterns of regulation in the 1st days after injury and their corresponding molecular pathways. These findings enable improved differentiation of myeloid and glial components of neuroinflammation after peripheral nerve injury and highlight novel molecular aspects of the Schwann cell injury response such as acute downregulation of the AGE/RAGE pathway and of secreted molecules Sparcl1 and Sema5a.ConclusionsWe provide a helpful resource for further deciphering the Schwann cell injury response and a depth of transcriptional data that can complement the findings of recent single cell sequencing approaches. As more data become available on the response of CNS glia to injury, we anticipate that this dataset will provide a valuable platform for understanding key differences in the PNS and CNS glial responses to injury and for designing approaches to ameliorate CNS regeneration.

Hide and seek with quantum resources: new and modified protocols for quantum steganography

Steganography is the science of hiding and communicating a secret message by embedding it in an innocent looking text such that the eavesdropper is unaware of its existence. Previously, attempts were made to establish steganography using quantum key distribution (QKD). Recently, it has been shown that such protocols are vulnerable to a certain steganalysis attack that can detect the presence of the hidden message and suppress the entire communication. In this work, we elaborate on the vulnerabilities of the original protocol which make it insecure against this detection attack. Further, we propose a novel steganography protocol using discrete modulation continuous variable QKD that eliminates the threat of this detection-based attack. Deriving from the properties of our protocol, we also propose modifications in the original protocol to dispose of its vulnerabilities and make it insusceptible to steganalysis.

Costas DFC-Based Random Stepped Wideband Waveform for Interference Countermeasure in SAR Imagery

Interference in SAR imagery will induce false targets or form a mask in specific areas to prevent accurate scene assessment. Traditional anti-jamming methods based on waveform agility require a trade-off between anti-jamming performance and imaging quality in waveform design. In this paper, we proposed a SAR ECCM scheme including a Costas DFC-based random stepped wideband waveform and corresponding imaging processing method. The waveform exhibits high flexibility against forwarding interference due to the decomposition of a wideband signal into multiple pulses with different Costas discrete frequency encoding, carrier frequency and phase modulation. Furthermore, the combination of FCDC and the imaging processing successfully overcomes the Doppler sensitivity of the proposed waveform. Extensive simulations confirmed the superiority of this waveform and processing method under different interference strategies.

Automated machine learning for secure key rate in discrete-modulated continuous-variable quantum key distribution

Continuous-variable quantum key distribution (CV QKD) with discrete modulation has attracted increasing attention due to its experimental simplicity, lower-cost implementation and compatibility with classical optical communication. Correspondingly, some novel numerical methods have been proposed to analyze the security of these protocols against collective attacks, which promotes key rates over one hundred kilometers of fiber distance. However, numerical methods are limited by their calculation time and resource consumption, for which they cannot play more roles on mobile platforms in quantum networks. To improve this issue, a neural network model predicting key rates in nearly real time has been proposed previously. Here, we go further and show a neural network model combined with Bayesian optimization. This model automatically designs the best architecture of neural network computing key rates in real time. We demonstrate our model with two variants of CV QKD protocols with quaternary modulation. The results show high reliability with secure probability as high as 99.15% - 99.59%, considerable tightness and high efficiency with speedup of approximately 107 in both cases. This inspiring model enables the real-time computation of unstructured quantum key distribution protocols' key rate more automatically and efficiently, which has met the growing needs of implementing QKD protocols on moving platforms.