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Neural network is a powerful learning paradigm for data feature learning in the era of big data. However, most neural network models are deterministic models that ignore the uncertainty of data. Fuzzy neural networks are proposed to address this problem. FDNN is a hierarchical deep neural network that derives information from both fuzzy and neural representations, the representations are then fused to form representation to be classified. FDNN perform well on uncertain data classification tasks. In this paper, we proposed a novel hierarchical fused quantum fuzzy neural network (HQFNN). Different from classical FDNN, HQFNN uses quantum neural networks to learn fuzzy membership functions in fuzzy neural network. We conducted simulated experiment on two types of datasets (Dirty-MNIST and 15-Scene), the results show that the proposed model can outperform several existing methods. In addition, we demonstrate the robustness of the proposed quantum circuit.

Machine learning (ML) has been used for many clinical decision-making processes and diagnostic procedures in bioinformatics applications. We examined eight algorithms, including linear discriminant analysis (LDA), logistic regression (LR), k-nearest neighbor (KNN), random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), Naïve Bayes classifier (NB), and artificial neural network (ANN) models, to evaluate their classification and prediction capabilities for four tissue types in Wolfiporia extensa using their monosaccharide composition profiles. All 8 ML-based models were assessed as exemplary models with AUC exceeding 0.8. Five models, namely LDA, KNN, RF, GBM, and ANN, performed excellently in the four-tissue-type classification (AUC > 0.9). Additionally, all eight models were evaluated as good predictive models with AUC value >0.8 in the three-tissue-type classification. Notably, all 8 ML-based methods outperformed the single linear discriminant analysis (LDA) plotting method. For large sample sizes, the ML-based methods perform better than traditional regression techniques and could potentially increase the accuracy in identifying tissue samples of W. extensa., QC 20230904

Wen Ting Zhu,1,* Xiang Feng Zeng,2,* Hua Yang,2 Meng Lei Jia,1 Wei Zhang,2 Wei Liu,2 Sheng Yao Liu3 1Department of Pharmacy, Biomedicine Research Center, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, People’s Republic of China; 2Department of Orthopedics, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, People’s Republic of China; 3Department of Orthopedics, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei Liu, Department of Orthopedics, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, People’s Republic of China, Email lwsurgery@163.com Sheng Yao Liu, Department of Orthopedics, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, People’s Republic of China, Email liushengyao12@163.comBackground: Osteosarcoma is a malignant bone tumor with a high rate of lung metastasis and mortality. It has been demonstrated that resveratrol can inhibit tumor proliferation and metastasis, but its application is limited due to poor water solubility and low bioavailability. In this study, we proposed to prepare folate-modified liposomes loaded with resveratrol to investigate its anti-osteosarcoma effect in vitro and in vivo.Methods: We prepared and characterized resveratrol liposomes modified with folate (denoted as, FA-Res/Lps). The effects of FA-Res/Lps on human osteosarcoma cell 143B proliferation, apoptosis, and migration were investigated by MTT, cell cloning, wound-healing assay, transwell, and flow cytometry. A xenograft tumor and lung metastasis model of osteosarcoma was constructed to study the therapeutic effects of FA-Res/Lps on the growth and metastasis of osteosarcoma in vivo.Resul

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24., Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE Xplore submission as part of WACV 2024

Sensor fusion is crucial for an accurate and robust perception system on autonomous vehicles. Most existing datasets and perception solutions focus on fusing cameras and LiDAR. However, the collaboration between camera and radar is significantly under-exploited. The incorporation of rich semantic information from the camera, and reliable 3D information from the radar can potentially achieve an efficient, cheap, and portable solution for 3D object perception tasks. It can also be robust to different lighting or all-weather driving scenarios due to the capability of mmWave radars. In this paper, we introduce the CRUW3D dataset, including 66K synchronized and well-calibrated camera, radar, and LiDAR frames in various driving scenarios. Unlike other large-scale autonomous driving datasets, our radar data is in the format of radio frequency (RF) tensors that contain not only 3D location information but also spatio-temporal semantic information. This kind of radar format can enable machine learning models to generate more reliable object perception results after interacting and fusing the information or features between the camera and radar.

Robust perception is a vital component for ensuring safe autonomous and assisted driving. Automotive radar (77 to 81 GHz), which offers weather-resilient sensing, provides a complementary capability to the vision- or LiDAR-based autonomous driving systems. Raw radio-frequency (RF) radar tensors contain rich spatiotemporal semantics besides 3D location information. The majority of previous methods take in 3D (Doppler-range-azimuth) RF radar tensors, allowing prediction of an object's location, heading angle, and size in bird's-eye-view (BEV). However, they lack the ability to at the same time infer objects' size, orientation, and identity in the 3D space. To overcome this limitation, we propose an efficient joint architecture called CenterRadarNet, designed to facilitate high-resolution representation learning from 4D (Doppler-range-azimuth-elevation) radar data for 3D object detection and re-identification (re-ID) tasks. As a single-stage 3D object detector, CenterRadarNet directly infers the BEV object distribution confidence maps, corresponding 3D bounding box attributes, and appearance embedding for each pixel. Moreover, we build an online tracker utilizing the learned appearance embedding for re-ID. CenterRadarNet achieves the state-of-the-art result on the K-Radar 3D object detection benchmark. In addition, we present the first 3D object-tracking result using radar on the K-Radar dataset V2. In diverse driving scenarios, CenterRadarNet shows consistent, robust performance, emphasizing its wide applicability.

Imidacloprid is one of the most used neonicotinoid insecticides all over the world and is considered as a contaminant of concern due to its high toxicity potential to aquatic organisms. However, the majority of the studies that have evaluated the effects of imidacloprid on aquatic organisms were conducted under temperate conditions. In the present study, a mesocosm experiment was conducted under sub-tropical conditions to assess the effects of imidacloprid on the structure (macroinvertebrates, zooplankton and phytoplankton) and functional endpoints of an aquatic ecosystem and to compare the results with similar temperate and (sub-)tropical mesocosm studies. Imidacloprid (0, 0.03, 0.3 and 3 µg/L) was applied to 13 mesocosms weekly over a period of 4 weeks, followed by a one month recovery period. At the community level a lowest NOECcommunity of 0.03 µg/L was calculated for the zooplankton, phytoplankton and macroinvertebrate communities. The highest sensitivity to imidacloprid (NOEC < 0.03 µg/L) were observed for Gerris sp., Diaptomus sp. and Brachionus quadridentatus. Imidacloprid induced population declines of the larger zooplankton species (Diaptomus sp. and Ostracoda) resulted in increased rotifer abundances and shifted the phytoplankton community to a graze resistant gelatinous cyanobacteria dominated ecosystem. These cyanobacteria blooms occurred at all different concentrations and could pose an important public health and environmental concern. Although there are some differences in species and community sensitivity between the present and the other (sub-)topical mesocosm studies, it can be observed that all show a similar general community response to imidacloprid. Under (sub-)tropical conditions, the toxic effects of imidacloprid occur at lower concentrations than found for temperate ecosystems.

The change in hypometabolism affects the regional links in the brain network. Here, to understand the underlying brain metabolic network deficits during the early stage and disease evolution of AD (Alzheimer disease), we applied correlation analysis to identify the metabolic connectivity patterns using 18F-FDG PET data for NC (normal control), sMCI (stable MCI), pMCI (progressive MCI) and AD, and explore the inter- and intra-hemispheric connectivity between anatomically-defined brain regions. Regions extracted from 90 anatomical structures were used to construct the matrix for measuring the inter- and intra-hemispheric connectivity. The brain connectivity patterns from the metabolic network show a decreasing trend of inter- and intra-hemispheric connections for NC, sMCI, pMCI and AD. Connection of temporal to the frontal or occipital regions is a characteristic pattern for conversion of NC to MCI, and the density of links in the parietal-occipital network is a differential pattern between sMCI and pMCI. The reduction pattern of inter and intra-hemispheric brain connectivity in the metabolic network depends on the disease stages, and is with a decreasing trend with respect to disease severity. Both frontal-occipital and parietal-occipital connectivity patterns in the metabolic network using 18F-FDG PET are the key feature for differentiating disease groups in AD.

The change in hypometabolism affects the regional links in the brain network. Here, to understand the underlying brain metabolic network deficits during the early stage and disease evolution of AD (Alzheimer disease), we applied correlation analysis to identify the metabolic connectivity patterns using 18F-FDG PET data for NC (normal control), sMCI (stable MCI), pMCI (progressive MCI) and AD, and explore the inter- and intra-hemispheric connectivity between anatomically-defined brain regions. Regions extracted from 90 anatomical structures were used to construct the matrix for measuring the inter- and intra-hemispheric connectivity. The brain connectivity patterns from the metabolic network show a decreasing trend of inter- and intra-hemispheric connections for NC, sMCI, pMCI and AD. Connection of temporal to the frontal or occipital regions is a characteristic pattern for conversion of NC to MCI, and the density of links in the parietal-occipital network is a differential pattern between sMCI and pMCI. The reduction pattern of inter and intra-hemispheric brain connectivity in the metabolic network depends on the disease stages, and is with a decreasing trend with respect to disease severity. Both frontal-occipital and parietal-occipital connectivity patterns in the metabolic network using 18F-FDG PET are the key feature for differentiating disease groups in AD.

Jen-Yang Tang,1,2 Tzu-Jung Yu,3 Li-Ching Lin,4–6 Sheng-Yao Peng,3 Chun-Lin Wang,7 Fu Ou-Yang,8,9 Yuan-Bin Cheng,10 Hsueh-Wei Chang9,11–131Department of Radiation Oncology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; 2Department of Radiation Oncology, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan; 3Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; 4Department of Radiation Oncology, Chi-Mei Foundation Medical Center, Tainan 71004, Taiwan; 5School of Medicine, Taipei Medical University, Taipei 11031, Taiwan; 6Department of Optometry, Chung Hwa University of Medical Technology, Tainan 71703, Taiwan; 7Bioresource Collection and Research Center, Food Industry Research and Development Institute, Hsinchu 30062, Taiwan; 8Division of Breast Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan; 9Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan; 10Graduate Institute of Natural Products, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; 11Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan; 12Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; 13Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung 80708, TaiwanIntroduction: The genus Nepenthes of the pitcher plants contains several natural and hybrid species that are commonly used in herbal medicine in several countries, but its possible use in cancer applications remains unknown as yet.Methods: In this study, we investigated the antioral cancer properties using ethyl acetate extracts of the Nepenthes hybrid (Nepenthes ventricosa x sibuyanensis), namely EANS. The bioactivity was detected by a MTS-based cell proliferation assay and flow cytom

Hepatitis C virus (HCV) encodes mechanisms to evade the multilayered antiviral actions of the host immune system. Great progress has been made in elucidating the strategies HCV employs to down-regulate interferon (IFN) production, impede IFN signaling transduction, and impair IFN-stimulated gene (ISG) expression. However, there is a limited understanding of the mechanisms governing how viral proteins counteract the antiviral functions of downstream IFN effectors due to the lack of an efficient approach to identify such interactions systematically. To study the mechanisms by which HCV antagonizes the IFN responses, we have developed a high-throughput profiling platform that enables mapping of HCV sequences critical for anti-IFN function at high resolution. Genome-wide profiling performed with a 15-nt insertion mutant library of HCV showed that mutations in the p7 region conferred high levels of IFN sensitivity, which could be alleviated by the expression of WT p7 protein. This finding suggests that p7 protein of HCV has an immune evasion function. By screening a liver-specific ISG library, we identified that IFI6-16 significantly inhibits the replication of p7 mutant viruses without affecting WT virus replication. In contrast, knockout of IFI6-16 reversed the IFN hypersensitivity of p7 mutant virus. In addition, p7 was found to be coimmunoprecipitated with IFI6-16 and to counteract the function of IFI6-16 by depolarizing the mitochondria potential. Our data suggest that p7 is a critical immune evasion protein that suppresses the antiviral IFN function by counteracting the function of IFI6-16.

Since the early 1990s, nations like the United Kingdom and the United States and multilateral organizations like UNESCO and OECD were looking forward to promoting the quality of education research and linking bridges among education research, education policies, and schooling. The principal investigator focuses on the issues associated with nongovernmental education research agencies with a goal to improve the construction of nongovernmental education research agencies in Taiwan. To overcome the research purposes we mentioned in the beginning, the researcher collects an extensive literature review related to education research agencies, education research policies, education research quality indicators, and schooling first. Moreover, the author aims at the issue related to nongovernmental education research agencies in eight case countries or international organizations to analyze the problems and struggles along with education research policies, education research quality indicators, and education practice via field study and in-depth interview data collection methods in each case country. Finally, the researcher juxtaposes and compares the development and models of nongovernmental research agencies in the world along with current issues in Taiwan. By conducting a series of focus group discussion panels on the issues of nongovernmental research agencies, the researcher reflects on the recent situation of nongovernmental research agencies with the interaction among education research, education research policies, education research quality indicators, and education practices, and provide some suggestions for future strategic plans on the development of nongovernmental research agencies and education research in Taiwan.

1. A filamentous fungus, Cunninghamella blakesleeana CGMCC 3.970, was applied as a microbial system to mimic mammalian metabolism of 4,5-dimethoxyl-canthin-6-one (1). Compound 1 belongs to canthin-6-one type alkaloids, which is a major bioactive constituent of a traditional Chinese medicine (the stems of Picrasma quassioides). 2. After 72 h of incubation in potato dextrose broth, 1 was metabolized to seven metabolites as follows: 4-methoxyl-5-hydroxyl-canthin-6-one (M1), 4-hydroxyl-5-methoxyl-canthin-6-one (M2), canthin-6-one (M3), canthin-6-one N-oxide (M4), 10-hydroxyl-4,5-dimethoxyl-canthin-6-one (M5), 1-methoxycarbonl-β-carboline (M6), and 4-methoxyl-5-O-β-D-glucopyranosyl-canthin-6-one (M7). 3. The structures of metabolites were determined using spectroscopic analyses, chemical methods, and comparison of NMR data with those of known compounds. Among them, M7 was a new compound. 4. The metabolic pathways of 1 were proposed, and the metabolic processes involved phase I (O-demethylation, dehydroxylation, demethoxylation, N-oxidation, hydroxylation, and oxidative ring cleavage) and phase II (glycosylation) reactions. 5. This was the first research on microbial transformation of canthin-6-one alkaloid, which could be a useful microbial model for producing the mammalian phase I and phase II metabolites of canthin-6-one alkaloids. 6. 1, M1−M5, and M7 are canthin-6-one alkaloids, whereas M6 belongs to β-carboline type alkaloids. The strain of Cunninghamella blakesleeana can supply an approach to transform canthin-6-one type alkaloids into β-carboline type alkaloids.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

UnlabelledPairing high-throughput sequencing technologies with high-throughput mutagenesis enables genome-wide investigations of pathogenic organisms. Knowledge of the specific functions of protein domains encoded by the genome of the hepatitis C virus (HCV), a major human pathogen that contributes to liver disease worldwide, remains limited to insight from small-scale studies. To enhance the capabilities of HCV researchers, we have obtained a high-resolution functional map of the entire viral genome by combining transposon-based insertional mutagenesis with next-generation sequencing. We generated a library of 8,398 mutagenized HCV clones, each containing one 15-nucleotide sequence inserted at a unique genomic position. We passaged this library in hepatic cells, recovered virus pools, and simultaneously assayed the abundance of mutant viruses in each pool by next-generation sequencing. To illustrate the validity of the functional profile, we compared the genetic footprints of viral proteins with previously solved protein structures. Moreover, we show the utility of these genetic footprints in the identification of candidate regions for epitope tag insertion. In a second application, we screened the genetic footprints for phenotypes that reflected defects in later steps of the viral life cycle. We confirmed that viruses with insertions in a region of the nonstructural protein NS4B had a defect in infectivity while maintaining genome replication. Overall, our genome-wide HCV mutant library and the genetic footprints obtained by high-resolution profiling represent valuable new resources for the research community that can direct the attention of investigators toward unidentified roles of individual protein domains.ImportanceOur insertional mutagenesis library provides a resource that illustrates the effects of relatively small insertions on local protein structure and HCV viability. We have also generated complementary resources, including a website (http://hangfei.bo

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

Previously unstudied dibenzoindolo[3,2-b]carbazoles have been prepared by two-directional, phase tag-assisted synthesis utilizing a connective-Pummerer cyclization and a SmI2-mediated tag cleavage-cyclization cascade. The use of a phase tag allows us to exploit unstable intermediates that would otherwise need to be avoided. The novel materials were characterized by X-ray, cyclic voltammetry, UV-vis spectroscopy, TGA, and DSC. Preliminary studies on the performance of OFET devices are also described.

UnlabelledPairing high-throughput sequencing technologies with high-throughput mutagenesis enables genome-wide investigations of pathogenic organisms. Knowledge of the specific functions of protein domains encoded by the genome of the hepatitis C virus (HCV), a major human pathogen that contributes to liver disease worldwide, remains limited to insight from small-scale studies. To enhance the capabilities of HCV researchers, we have obtained a high-resolution functional map of the entire viral genome by combining transposon-based insertional mutagenesis with next-generation sequencing. We generated a library of 8,398 mutagenized HCV clones, each containing one 15-nucleotide sequence inserted at a unique genomic position. We passaged this library in hepatic cells, recovered virus pools, and simultaneously assayed the abundance of mutant viruses in each pool by next-generation sequencing. To illustrate the validity of the functional profile, we compared the genetic footprints of viral proteins with previously solved protein structures. Moreover, we show the utility of these genetic footprints in the identification of candidate regions for epitope tag insertion. In a second application, we screened the genetic footprints for phenotypes that reflected defects in later steps of the viral life cycle. We confirmed that viruses with insertions in a region of the nonstructural protein NS4B had a defect in infectivity while maintaining genome replication. Overall, our genome-wide HCV mutant library and the genetic footprints obtained by high-resolution profiling represent valuable new resources for the research community that can direct the attention of investigators toward unidentified roles of individual protein domains.ImportanceOur insertional mutagenesis library provides a resource that illustrates the effects of relatively small insertions on local protein structure and HCV viability. We have also generated complementary resources, including a website (http://hangfei.bo

Previously unstudied dibenzoindolo[3,2-b]carbazoles have been prepared by two-directional, phase tag-assisted synthesis utilizing a connective-Pummerer cyclization and a SmI2-mediated tag cleavage-cyclization cascade. The use of a phase tag allows us to exploit unstable intermediates that would otherwise need to be avoided. The novel materials were characterized by X-ray, cyclic voltammetry, UV-vis spectroscopy, TGA, and DSC. Preliminary studies on the performance of OFET devices are also described.

This paper proposes a chaos-based analog-to-information conversion system for the acquisition and reconstruction of sparse analog signals. The sparse signal acts as an excitation term of a continuous-time chaotic system and the compressive measurements are performed by sampling chaotic system outputs. The reconstruction is realized through the estimation of the sparse coefficients with principle of chaotic parameter estimation. With the deterministic formulation, the analysis on the reconstructability is conducted via the sensitivity matrix from the parameter identifiability of chaotic systems. For the sparsity-regularized nonlinear least squares estimation, it is shown that the sparse signal is locally reconstructable if the columns of the sparsity-regularized sensitivity matrix are linearly independent. A Lorenz system excited by the sparse multitone signal is taken as an example to illustrate the principle and the performance., Comment: 36 pages,13 figures