Signal Correction Research Articles

NLOS signal detection and correction for smartphone using convolutional neural network and variational mode decomposition in urban environment

NLOS signal detection and correction for smartphone using convolutional neural network and variational mode decomposition in urban environment

Damping Subsynchronous Oscillations Using a High Voltage Direct Current-Based Multi-Modal Damping Controller

Conventional series capacitors in transmission lines are of paramount importance for enhancing power transfer capability. However, the major drawback of series capacitors is the induced subsynchronous resonance phenomenon in power systems. This phenomenon affects nearby turbogenerator shafts and severely limits their reliability. Also, the controls of High Voltage Direct Current links are considered as a potential source of subsynchronous oscillations. This paper investigates the performance of a multimodal damping controller to stabilize unstable torsional modes in combination with a Power System Stabilizer for inertial mode damping. This research uses time-domain simulation-based multimodal damping controller design methods, namely the test signal and phase correction methods. These two methods involve injecting a test signal at a frequency of interest into the rectifier current control loop and measuring its phase difference with the electromagnetic torque, thus providing corresponding compensators to minimize the resulting angle. This work uses Power System Computer-Aided Design for time-domain simulation and Fast Fourier Transforms Analysis to conduct the phase correction method and verify controller performance.

Red light-green light: T-cell trafficking in cardiac and vascular inflammation.

Extravasation of T cells from the bloodstream into inflamed tissues requires interactions between T cells and vascular endothelial cells, a necessary step that allows T cells to exert their effector function during the immune response to pathogens and to sterile insults. This cellular cross talk involves adhesion molecules on both the vascular endothelium and the T cells themselves that function as receptor-ligand pairs to slow down circulating T cells. These will eventually extravasate into sites of inflammation when they receive the correct chemokine signals. Accumulation of T cells within the vascular wall can lead to vessel thickening and vascular disease, whereas T-cell extravasation into the myocardium often leads to cardiac chronic inflammation and adverse cardiac remodeling, hallmarks of heart failure. On the flip side, T-cell trafficking is required for pathogen clearance and to promote tissue repair after injury resulting from cardiac ischemia. Thus, a better understanding of the central players mediating these interactions may help develop novel therapeutics to modulate vascular and cardiac inflammation. Here, we review the most recent literature on pathways that regulate T-cell transendothelial migration, the last step leading to T-cell infiltration into tissues and organs in the context of vascular and cardiac inflammation. We discuss new potential avenues to therapeutically modulate these pathways to enhance or prevent immune cell infiltration in cardiovascular disease.

Micro-Raman Analysis of Sperm Cells on Glass Slide: Potential Label-Free Assessment of Sperm DNA toward Clinical Applications.

Routine assessment of sperm DNA integrity involves the time-consuming and complex process of staining sperm chromatin. Here, we report a Raman spectroscopy method combined with extended multiplicative signal correction (EMSC) for the extraction of characteristic fingerprints of DNA-intact and DNA-damaged sperm cells directly on glass slides. Raman results of sperm cell DNA integrity on glass substrates were validated one-to-one with clinical sperm cell staining. Although the overall Raman spectral pattern showed considerable similarity between DNA-damaged and DNA-intact sperm cells, differences in specific Raman spectral responses were observed. We then employed and compared multivariate statistical analysis based on principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. In comparison, the PLS-DA model showed relatively better results in terms of diagnostic sensitivity, specificity, and the classification rate between the sperm DNA damaged group and the DNA intact group. Our results demonstrate the potential of Raman based label-free DNA assessment of sperm cell on glass substrates as a simple method toward clinical applications.

NIR quantitative model trans-scale calibration from small scale to pilot scale via directed DOSC-SBC algorithm

In order to solve the problem of inapplicability of NIR quantitative models due to the large difference between the modeling samples and the samples to be tested, Directed DOSC-SBC（DDOSC-SBC）algorithm is proposed in this paper based on Direct Orthogonal Signal Correction combined with Slope/Bias Correction (DOSC-SBC) algorithm. To obtain the suitable spectral matrix transfer parameters for the test set during DDOSC spectral preprocessing, several representative test samples in the test set were selected, then the spectral systematic errors between the modeling set and the test set were corrected with the SBC method in order to realize the trans-scale prediction of the NIR quantitative model. NIR data and the critical quality attributes（CQAs）were detected in the small scale and pilot scale pharmaceutical process of the fluidized bed granulation of dextrin and water extraction of honeysuckle. After the small scale model was calibrated via the directed DOSC-SBC algorithm which was guided by representative pilot scale samples, the small scale model was able to predict the pilot scale test samples more accurately. The NIR quantitative model trans-scale calibration from small scale to pilot scale was also successfully realized with a RPD value higher than 3.5 and RSEP value lower than 10%. DDOSC-SBC algorithm is a successful model trans-scale calibrated method that can be applied to NIR real-time monitoring of CQAs in the preparation process of Chinese herbal medicine.

Respiratory frequency-tunable dynamic imaging for lung function: New exam method using chest X-ray cine imaging considering various respiratory diseases.

A convenient way to conduct pulmonary function tests while preventing infectious diseases was proposed, together with countermeasures for severe coronavirus disease 2019 (COVID-19). The correlation between diagnosis result and diagnosis result was examined for patients with mild chronic obstructive pulmonary disease (COPD) of the most abounding as a subject of spirometry, and the possibility of using this method as an alternative to spirometry was examined. This study was conducted in Kanagawa, Japan. Ten normal volunteers and 15 volunteers with mild COPD participated in this study. All images were taken by EXAVISTA (Hitachi, Japan) between October 2019 and February 2020. Continuous fluoroscopic images were taken in 12.5 frames per second for 10-20 s per subject. Images that do not adopt the automatic image processing of the equipment and only carry out the signal correction of each pixel were used for the analysis. The mean total dose for all volunteers was 0.2 mGy. There was no major discrepancy in the detection of lung field geometry, and no diagnostic problems were noted by the radiologist and physician. Existing X-ray cine imaging was used to extract frequency-tunable imaging. It is possible to identify abnormal regions on the images compared to spirometry, and it does not require maximum effort respiration; therefore, it is possible to perform a stable examination because the patient's physical condition and the ability of laboratory technicians on the day are less affected. This can also be used as a countermeasure in examining patients with infectious diseases. UMIN UMIN000043868.

Signal corrector and decoupling estimations for UAV control

AbstractFor a class of uncertain systems with large-error sensing, the low-order stable signal corrector and observer are presented for signal correction and uncertainty estimation according to completely decoupling estimation. The model-free signal corrector can reject the bounded stochastic disturbance/error in global position sensing, and system uncertainty can be estimated by the observer, even the existence of large disturbance in position sensing. Furthermore, a general form of signal corrector is given. The describing function method is used to analyse the robustness of the corrector in frequency domain, and the parameter selection rules are presented. The merits of the signal corrector includes its model free, gain-bounded stable structure, sufficient rejection of bounded stochastic disturbance/error in sensing and ease of parameters’ regulation. The corrector and observer are applied to a UAV navigation and control for large disturbance/error corrections in position/attitude angle and the uncertainties estimation in the UAV flight dynamics. The control laws are designed according to the correction-estimation results. Finally, experiments demonstrate the effectiveness of the proposed method.

Routine Processing and Automatic Detection of Volcanic Ground Deformation Using Sentinel-1 InSAR Data: Insights from African Volcanoes

Since the launch of Sentinel-1 mission, automated processing systems have been developed for near real-time monitoring of ground deformation signals. Here, we perform a regional analysis of 5 years over 64 volcanic centres located along the East African Rift System (EARS). We show that the correction of atmospheric signals for the arid and low-elevation EARS volcanoes is less important than for other volcanic environments. We find that the amplitude of the cumulative displacements exceeds three times the temporal noise of the time series (3σ) for 16 of the 64 volcanoes, which includes previously reported deformation signals, and two new ones at Paka and Silali volcanoes. From a 5-year times series, uncertainties in rates of deformation are ∼0.1 cm/yr, whereas uncertainties associated with the choice of reference pixel are typically 0.3–0.6 cm/yr. We fit the time series using simple functional forms and classify seven of the volcano time series as ‘linear’, six as ‘sigmoidal’ and three as ‘hybrid’, enabling us to discriminate between steady deformation and short-term pulses of deformation. This study provides a framework for routine volcano monitoring using InSAR on a continental scale. Here, we focus on Sentinel-1 data from the EARS, but the framework could be expanded to include other satellite systems or global coverage.

A Novel Method for the Background Signal Correction in SP-ICP-MS Analysis of the Sizes of Titanium Dioxide Nanoparticles in Cosmetic Samples.

We discuss the features involved in determining the titanium dioxide nanoparticle (TiO2NP) sizes in cosmetic samples via single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) in the millisecond-time resolution mode, and methods for considering the background signal. In the SP-ICP-MS determination of TiO2NPs in cosmetics, the background signal was recorded in each dwell time interval due to the signal of the Ti dissolved form in deionized water, and the background signal of the cosmetic matrix was compensated by dilution. A correction procedure for the frequency and intensity of the background signal is proposed, which differs from the known procedures due to its correction by the standard deviation above the background signal. Background signals were removed from the sample signal distribution using the deionized water signal distribution. Data processing was carried out using Microsoft Office Excel and SPCal software. The distributions of NP signals in cosmetic product samples were studied in the dwell time range of 4-20 ms. The limit of detection of the NP size (LODsize) with the proposed background signal correction procedure was 71 nm. For the studied samples, the LODsize did not depend on the threshold of the background signal and was determined by the sensitivity of the mass spectrometer.

Comparison of iCOR and Rayleigh atmospheric correction methods on Sentinel-3 OLCI images for a shallow eutrophic reservoir.

Remote sensing of inland waters is challenging, but also important, due to the need to monitor the ever-increasing harmful algal blooms (HABs), which have serious effects on water quality. The Ocean and Land Color Instrument (OLCI) of the Sentinel-3 satellites program is capable of providing images for the monitoring of such waters. Atmospheric correction is a necessary process in order to retrieve the desired surface-leaving radiance signal and several atmospheric correction methods have been developed through the years. However, many of these correction methods require programming language skills, or function as commercial software plugins, limiting their possibility of use by end users. Accordingly, in this study, the free SNAP software provided by the European Space Agency (ESA) was used to evaluate the possible differences between a partial atmospheric correction method accounting for Rayleigh scattering and a full atmospheric correction method (iCOR), applied on Sentinel-3 OLCI images of a shallow, highly eutrophic water reservoir. For the complete evaluation of the two methods, in addition to the comparison of the band reflectance values, chlorophyll (CHL) and cyanobacteria (CI) indices were also calculated and their values were intercompared. The results showed, that although the absolute values between the two correction methods did not coincide, there was a very good correlation between the two methods for both bands' reflectance (r>0.73) and the CHL and CI indices values (r>0.95). Therefore, since iCOR correction image processing time is 25 times longer than Rayleigh correction, it is proposed that the Rayleigh partial correction method may be alternatively used for seasonal water monitoring, especially in cases of long time-series, enhancing time and resources use efficiency. Further comparisons of the two methods in other inland water bodies and evaluation with in situ chlorophyll and cyanobacteria measurements will enhance the applicability of the methodology.

Heat-Shock Proteins.

Heat-shock proteins (HSPs), or stress proteins, are abundant and highly conserved, present in all organisms and in all cells. Selected HSPs, also known as chaperones, play crucial roles in folding and unfolding of proteins, assembly of multiprotein complexes, transport and sorting of proteins into correct subcellular compartments, cell-cycle control and signaling, and protection of cells against stress and apoptosis. More recently, HSPs have been shown to be key players in immune responses: during antigen presentation as well as cross-priming, they chaperone and transfer antigenic peptides to class I and class II molecules of the major histocompatibility complexes. In addition, extracellular HSPs can stimulate and cause maturation of professional antigen-presenting cells of the immune system, such as macrophages and dendritic cells. They also chaperone several toll-like receptors, which play a central role in innate immune responses. HSPs constitute a large family of proteins that are often classified based on their molecular weight as Hsp10, Hsp40, Hsp60, Hsp70, Hsp90, etc. This unit contains a table that lists common HSPs and summarizes their characteristics including (a) name, (b) subcellular localization, (c) known function, (d) chromosome assignment, (e) brief comments, and (f) references. © 2022 Wiley Periodicals LLC.

RF22 | PMON10 Exposure to a Real Life Environmental Chemical Mixture Alters the Metabolite Profile in the Plasma of Sheep: An Untargeted Metabolomics Study.

Abstract Humans are exposed to a mixture of endocrine disrupting chemicals (EDCs) in everyday life, believed to contribute to a range of non-communicable diseases. While the adverse health impacts of exposure to individual EDCs have been extensively investigated, studies on effects of real-world exposures characterized by chronic low doses of a mixture of chemicals, are only recently emerging. Biosolids derived from human wastes, exemplify both the array and dosage of chemicals humans are exposed to in real life and represents a novel model to investigate the risk posed by the EDCs. Previous studies in sheep have demonstrated aberrant reproductive and metabolic phenotypic effects in offsprings, as a result of maternal biosolid exposure. We hypothesize that EDC-mediated disruption in the maternal metabolic milieu is a potential mediator of the aberrant phenotypic outcomes in offsprings in the biosolid-exposure model. Recent untargeted metabolomic studies provide evidence of the technique's ability to unravel biomarkers of both exposure and effect by identifying the disrupted endogenous metabolite profile and xenobiotic mixture, respectively. In this study, we sought to identify biosolid exposure-induced maternal metabolic fingerprints that could influence fetal programming. Ewes were grazed on either organic fertilizer or biosolid-treated pastures from 1 month before mating until close to parturition. Plasma from blood samples collected on day 90 of the 147-day gestation period, from ewes carrying singleton pregnancies (Control n=15, Treatment n=15) were subjected to untargeted metabolomics using liquid chromatography-quadrupole time-of-flight mass spectrometry. Metabolites were identified by matching the retention time, mass and isotope profile to authentic standards or metabolome databases using Agilent's MassHunter Find by Molecular Feature workflow (v7.0). Untargeted metabolomics identified 1006 and 1295 annotated features from the negative and positive mode respectively. Principal component analysis and orthogonal signal correction partial least-squares discriminant analysis discriminated the metabolomes of control sheep and sheep grazed in biosolid-treated pasture. The key differential metabolites identified by variable importance in projection score primarily belonged to the super-class organic acids, fatty acids, benzenoids, glycerophospholipids and organoheterocyclic compounds. These differentially expressed metabolites are implicated in metabolic pathways including carnitine synthesis, alanine metabolism, glucose alanine cycle, phosphatidyl choline biosynthesis and glutathione metabolism. Some of the top differential metabolites- oleamide, pyroglutamic acid and 15-HETrE have been implicated in fetal development. Oleamide, an endocannabinoid, has growth inhibitory properties. 15-HETrE modulates arachidonic acid metabolism and upregulate PPARγ expression, which plays a pivotal role in fetal development and metabolic outcomes. These findings indicate that biosolids exposure results in alterations in the maternal metabolome which likely contributes to the aberrant phenotypic outcomes reported in offspring of biosolid-exposed mothers. This is the first study to apply metabolomics to validate the effect of real-life EDC exposure in sheep, a translationally relevant precocial model with a developmental trajectory similar to humans. Presentation: Sunday, June 12, 2022 1:00 p.m. - 1:05 p.m., Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Enhancing the flexibility and efficiency of a double-reheat coal-fired power unit by optimizing the steam temperature control: From simulation to application

Flexibility enhancement is crucial for thermal power plants to assist the power grid in accommodating the high penetration of intermittent renewable power. In this study, a new scheme for controlling the steam temperatures of a double-reheat coal-fired power unit is proposed. The scheme uses the leading signal correction of the low-temperature reheater for the control loop regulating the dampers fixed in the fuel gas ducts of the boiler. The scheme was tested using a dynamic model and applied to an in-service double-reheat coal-fired power plant. The results show that both flexibility and efficiency were enhanced when the new control scheme was adopted. The quantity of spray water for the secondary reheat steam could be reduced by 10 %–50 % during the peak-shaving transients with a load cycling rate in the range of 1 %–4 % rated power per minute. The average coal consumption rate decreased by 0.8–1.9 g kW−1h−1, which accounted for 0.29 %–0.69 % of the thermal efficiency of the power plant. The variation trends of the reheat steam temperatures became smooth, and the maximal measured metal temperature decreased by 12 °C. The results can guide the control optimization of modern peak-shaving power plants.

Femtosecond two-photon LIF imaging of atomic hydrogen in high-pressure methane-air flames

Atomic hydrogen (H) imaging studies in combustion systems have been limited thus far to atmospheric- or low-pressure flames. The commonly used excitation scheme for two-photon laser-induced fluorescence (TPLIF) of H involves 205-nm deep-ultra-violet (DUV) laser pulses generated using nanosecond (ns), picosecond (ps), or femtosecond (fs) laser systems. Ultrashort pulse, fs excitation schemes are more attractive because of the efficient two-photon excitation and interference-free kHz-rate imaging capability. In this work, we implemented a home-built, direct fourth harmonic generation (FHG) laser system to generate high-energy fs pulses for H imaging in CH4/air flames at pressures up to 10 bar. The high-energy FHG output was capable of overcoming transmission losses of DUV laser pulses through thick optical windows of the pressure vessel. Signal interferences such as photoionization, photolytic production, amplified spontaneous emission, and background chemiluminescence were avoided or minimized during data acquisition and subsequent data processing steps. A quadratic dependence of the H TPLIF signal on the laser energy was observed. The increase in the pressure from 1 to 10 bar showed a rapid decay of the fs H TPLIF signal although it should scale linearly with increasing H number density with pressure ideally at equilibrium conditions. Besides a detailed quenching correction, laser absorption and fluorescence signal trapping remain major issues at elevated pressures. The measured fluorescence signals are compared with the equilibrium H number densities and local H concentrations calculated using the Cantera (0D) and UNICORN (2D) flame codes, respectively, for a range of equivalence ratios, and possible reasons for discrepancies are discussed. Experimentally obtained 1D and 2D spatial distributions of H are well predicted by the UNICORN flame model. Steps towards quantitative single-shot H TPLIF imaging measurements in high-pressure flames are also discussed. Overall, the fs TPLIF imaging technique coupled with a high-efficiency home-built FHG system is a promising diagnostic approach for H imaging in high-pressure flames.

Observer-based adaptive ISMC for connected vehicles against cyber-attacks

This paper concentrates on decentralized variable structure adaptive integral sliding mode control (ISMC) for connected vehicles (CV) against cyber-attacks. First of all, a novel vehicle leader-follower model is established by jointly considering the cyber-attacks which involve replay attack and DoS attack simultaneously. Secondly, a decentralized control scheme is designed on the basis of the variable structure observer and adaptive integral sliding mode technique. The Lyapunov-Razumikhin method is adopted such that the state estimation error of CV system is asymptotically converged to zero, which can overcome the replay attack, DoS attack, and measurement delays, then a corrective signal is designed for the deception attack to eliminate the influence of deception attack on the CV system. Furthermore, the robust asymptotic stability of CV system is guaranteed by exploiting the emerging technique of robust control for time-delay systems. Meanwhile, the string stability of CV is guaranteed, even under the condition of heterogeneous vehicles. Finally, extensive simulations are conducted to verify the theoretical analysis and demonstrate the effectiveness and superiority of the proposed method.

The Evolutionary Dynamics of the Mitochondrial tRNA in the Cichlid Fish Family.

Simple SummaryCichlids are a unique example of fish diversity and species richness which have been explained by sympatric speciation at different freshwater sources in Africa. The mitochondria contribute to cell vitality by providing energy. It contains a circular genome with an established translation system that is spatially independent of the cytosolic counterpart. The current study aimed to investigate the evolutionary dynamics of the mitochondrial tRNA and its role in cichlids’ diversity. The available cichlid mitogenomes in the public database were filtered, in addition to newly sequenced accessions from a specific cichlid group known as the haplotilapiine lineage that is widely distributed in the Egyptian sector of the Nile River. Based on the comparative analysis of mitogenomic data, we identified 22 tRNA genes, in which a single gene was D-armless, while the cloverleaf secondary structure subdivided into stem-loop formations was predicted and used to define the levels of genetic divergence for the remained tRNAs. Peculiarly, in cichlids, the formation known as “T-arm” showed the lowest polymorphism levels among other structures in contrast to other organisms (e.g., scorpions). Comparing the whole family to the specific haplotilapiine lineage showed that the tryptophan tRNA was the most conserved tRNA, with signatures of possible purifying selection.The mitochondrial transfer RNA genes (tRNAs) attract more attention due to their highly dynamic and rapidly evolving nature. The current study aimed to detect and evaluate the dynamics, characteristic patterns, and variations of mitochondrial tRNAs. The study was conducted in two main parts: first, the published mitogenomic sequences of cichlids mt tRNAs have been filtered. Second, the filtered mitochondrial tRNA and additional new mitogenomes representing the most prevalent Egyptian tilapiine were compared and analyzed. Our results revealed that all 22 tRNAs of cichlids folded into a classical cloverleaf secondary structure with four domains, except for trnSGCU, missing the D domain in all cichlids. When consensus tRNAs were compared, most of the mutations were observed in the trnP at nucleotide levels (substitutions and indels), in contrast to trnLUAA. From a structural perspective, the anticodon loop and T-loop formations were the most conserved structures among all parts of the tRNA in contrast to the A-stem and D-loop formations. The trnW was the lowest polymorphic unneutral tRNA among all cichlids (both the family and the haplotilapiine lineage), in contrast with the neutral trnD that was extremely polymorphic among and within the haplotilapiine lineage species compared to other cichlids species. From a phylogenetic perspective, the trnC was extremely hypervariable and neutral tRNA in both haplotilapiine lineage and cichlids but was unable to report correct phylogenetic signal for the cichlids. In contrast to trnI and trnY, less variable neutral tRNAs that were able to cluster the haplotilapiine lineage and cichlids species as previously reported. By observing the DNA polymorphism in the coding DNA sequences (CDS), the highest affected amino acid by non-synonymous mutations was isoleucine and was equally mutated to valine and vice versa; no correlation between mutations in CDS and tRNAs was statistically found. The current study provides an insight into the mitochondrial tRNA evolution and its effect on the cichlid diversity and speciation model at the maternal level.

METHOD OF IMPROVING THE ACCURACY OF NAVIGATION MEMS DATA PROCESSING OF UAV INERTIAL NAVIGATION SYSTEM

Context. Modern theory and practice of preparation and conduct of hostilities on land, at sea, in the air, and recently in cyberspace dictates the relentless modernization of military equipment. The development of fundamentally new weapons is carried out considering one of the main requirements – maximum automation of operational processes, which allows combatants to distance themselves from each other as much as possible.
 Among the newest models of armaments on the battlefield, due to the predominantly positional nature of the armed confrontation, unmanned aerial vehicles (UAVs) have become virtually indispensable due to their own multitasking. One of the ways to increase the efficiency of UAVs on the battlefield is to increase the level of technical perfection of flight control systems.
 Creating new approaches to the design of unmanned aerial vehicle navigation systems, in particular, based on a platformless inertial navigation system is an urgent task that will provide automatic control of the UAV flight route in the absence of corrective signals from the global satellite navigation system.
 Objective. The purpose of this work is to develop a method for improving the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter.
 This method will increase the speed of data processing of navigation parameters and the accuracy of determining the positioning parameters in the space of the UAV through the use of an advanced Madgwik filter.
 The paper shows the developed block diagram of MEMS PINS filtration on the basis of the improved Madgwik filter, the detailed mathematical description of filtration processes is carried out.
 This method was tested experimentally in the MATLAB software environment using a real set of data collected during the flight of the UAV.
 Method. To achieve this goal, the following methods were used: intelligent systems, theory of automatic control, pseudo-spectral method; methods based on genetic algorithm and fuzzy neural network apparatus.
 Results. A method for improving the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter has been developed. The possibility of practical application of the obtained results and in comparison, with traditional methods is investigated. An experiment was performed in the MatLab software environment, and a comparison was made with the method of processing navigation data based on the Madgwik filter and the Kalman filter.
 Conclusions. The developed method of increasing the accuracy of MEMC navigation data processing of an inertial navigation system of an unmanned aerial vehicle based on an advanced Madgwik filter shows an advantage over known methods in the absence of corrective signals from the global satellite navigation system for accuracy and speed of navigation data processing.

Large-scale top-down proteomics of the Arabidopsis thaliana leaf and chloroplast proteomes.

We present a large-scale top-down proteomics (TDP) study of plant leaf and chloroplast proteins, achieving the identification of over 4700 unique proteoforms. Using capillary zone electrophoresis coupled with tandem mass spectrometry analysis of offline size-exclusion chromatography fractions, we identify 3198 proteoforms for total leaf and 1836 proteoforms for chloroplast, with 1024 and 363 proteoforms having post-translational modifications, respectively. The electrophoretic mobility prediction of capillary zone electrophoresis allowed us to validate post-translational modifications that impact the charge state such as acetylation and phosphorylation. Identified modifications included Trp (di)oxidation events on six chloroplast proteins that may represent novel targets of singlet oxygen sensing. Furthermore, our TDP data provides direct experimental evidence of the N- and C-terminal residues of numerous mature proteoforms from chloroplast, mitochondria, endoplasmic reticulum, and other sub-cellular localizations. With this information, we suggest true transit peptide cleavage sites and correct sub-cellular localization signal predictions. This large-scale analysis illustrates the power of top-down proteoform identification of post-translational modifications and intact sequences that can benefit our understanding of both the structure and function of hundreds of plant proteins.

Single Point Failure Free Interleaved Synchronous Buck Converter for Microsatellite Electrolysis Propulsion

This article describes the design and implementation of a dc–dc converter used to power a microsatellite on-board electrolyzer. The proposed topology is a four-phase interleaved synchronous buck converter with output current control. The proposed converter is single point failure free (SPFF), so in case of any individual component failure, the functionality of the system is not compromised. SPFF operation is achieved using individual protections in each buck phase, redundant output current control, and redundant clock systems. Besides, analog majority voter circuits are used to select the correct control signal after any failure and to isolate it. Detailed mathematical analysis and circuit design are presented. Furthermore, a 40-W prototype has been implemented to validate the concept. Experimental results presented show the correct performance of the system in every case and its fault tolerant capability. In addition, the ac behavior and stability of the system have been studied and verified under the full range of possible operating conditions. Finally, efficiency measurements are presented.

TransDSSL: Transformer Based Depth Estimation via Self-Supervised Learning

Recently, transformers have been widely adopted for various computer vision tasks and show promising results due to their ability to encode long-range spatial dependencies in an image effectively. However, very few studies on adopting transformers in self-supervised depth estimation have been conducted. When replacing the CNN architecture with the transformer in self-supervised learning of depth, we encounter several problems such as problematic multi-scale photometric loss function when used with transformers and, insufficient ability to capture local details. In this letter, we propose an attention-based decoder module, Pixel-Wise Skip Attention (PWSA), to enhance fine details in feature maps while keeping global context from transformers. In addition, we propose utilizing self-distillation loss with single-scale photometric loss to alleviate the instability of transformer training by using correct training signals. We demonstrate that the proposed model performs accurate predictions on large objects and thin structures that require global context and local details. Our model achieves state-of-the-art performance among the self-supervised monocular depth estimation methods on KITTI and DDAD benchmarks.