Compressive Sensing Based on HQS for Image reconstruction

This work solves the image distortion problem caused by the noise generated during the sampling and reconstruction process, a compressive sensing algorithm based on half quadratic splitting (CS-HQS) is proposed to reconstruct images in this paper. For the part dominated by error terms, the regularization term is introduced and the second-order momentum adaptive gradient descent method is used to get the auxiliary variables. For the part dominated by the sparse prior of compressive sensing, the Bayesian maximum posterior inference is used to get the sparse coeffi cient. The combination of the two methods not only avoids the generation of random noise, but also enhances the stability of the model. The experimental results demonstrate that the strong robustness of the proposed algorithm

Systemic robustness: a mean-field particle system approach

This paper is concerned with the problem of budget control in a large particle system modeled by stochastic differential equations involving hitting times, which arises from considerations of systemic risk in a regional financial network. Motivated by Tang and Tsai (Ann. Probab., 46(2018), pp. 1597{1650), we focus on the number or proportion of surviving entities that never default to measure the systemic robustness. First we show that both the mean-field particle system and its limiting McKean-Vlasov equation are well-posed by virtue of the notion of minimal solutions. We then establish a connection between the proportion of surviving entities in the large particle system and the probability of default in the limiting McKean-Vlasov equation as the size of the interacting particle system N tends to infinity. Finally, we study the asymptotic efficiency of budget control in different economy regimes: the expected number of surviving entities is of constant order in a negative economy; it is of order of the square root of N in a neutral economy; and it is of order N in a positive economy where the budget's effect is negligible.Comment: 33 page

Coverage Goal Selector for Combining Multiple Criteria in Search-Based Unit Test Generation

Unit testing is critical to the software development process, ensuring the correctness of basic programming units in a program (e.g., a method). Search-based software testing (SBST) is an automated approach to generating test cases. SBST generates test cases with genetic algorithms by specifying the coverage criterion (e.g., branch coverage). However, a good test suite must have different properties, which cannot be captured using an individual coverage criterion. Therefore, the state-of-the-art approach combines multiple criteria to generate test cases. Since combining multiple coverage criteria brings multiple objectives for optimization, it hurts the test suites' coverage for certain criteria compared with using the single criterion. To cope with this problem, we propose a novel approach named \textbf{smart selection}. Based on the coverage correlations among criteria and the subsumption relationships among coverage goals, smart selection selects a subset of coverage goals to reduce the number of optimization objectives and avoid missing any properties of all criteria. We conduct experiments to evaluate smart selection on $400$ Java classes with three state-of-the-art genetic algorithms under the $2$-minute budget. On average, smart selection outperforms combining all goals on $65.1\%$ of the classes having significant differences between the two approaches. Secondly, we conduct experiments to verify our assumptions about coverage criteria relationships. Furthermore, we experiment with different budgets of $5$, $8$, and $10$ minutes, confirming the advantage of smart selection over combining all goals.Comment: arXiv admin note: substantial text overlap with arXiv:2208.0409

Pathologically Activated Neuroprotection via Uncompetitive Blockade of \u3cem\u3eN\u3c/em\u3e-Methyl-d-aspartate Receptors with Fast Off-rate by Novel Multifunctional Dimer Bis(propyl)-cognitin

Uncompetitive N-methyl-d-aspartate (NMDA) receptor antagonists with fast off-rate (UFO) may represent promising drug candidates for various neurodegenerative disorders. In this study, we report that bis(propyl)-cognitin, a novel dimeric acetylcholinesterase inhibitor and γ-aminobutyric acid subtype A receptor antagonist, is such an antagonist of NMDA receptors. In cultured rat hippocampal neurons, we demonstrated that bis(propyl)-cognitin voltage-dependently, selectively, and moderately inhibited NMDA-activated currents. The inhibitory effects of bis(propyl)-cognitin increased with the rise in NMDA and glycine concentrations. Kinetics analysis showed that the inhibition was of fast onset and offset with an off-rate time constant of 1.9 s. Molecular docking simulations showed moderate hydrophobic interaction between bis(propyl)-cognitin and the MK-801 binding region in the ion channel pore of the NMDA receptor. Bis(propyl)-cognitin was further found to compete with [3H]MK-801 with a Ki value of 0.27 μm, and the mutation of NR1(N616R) significantly reduced its inhibitory potency. Under glutamate-mediated pathological conditions, bis(propyl)-cognitin, in contrast to bis(heptyl)-cognitin, prevented excitotoxicity with increasing effectiveness against escalating levels of glutamate and much more effectively protected against middle cerebral artery occlusion-induced brain damage than did memantine. More interestingly, under NMDA receptor-mediated physiological conditions, bis(propyl)-cognitin enhanced long-term potentiation in hippocampal slices, whereas MK-801 reduced and memantine did not alter this process. These results suggest that bis(propyl)-cognitin is a UFO antagonist of NMDA receptors with moderate affinity, which may provide a pathologically activated therapy for various neurodegenerative disorders associated with NMDA receptor dysregulation

Functional evaluation of constructed pseudo-endogenous microRNA-targeted myocardial ultrasound nanobubble

BackgroundStem cell transplantation is one of the treatment methods for acute myocardial infarction (AMI). MicroRNA-1 contributes to the study of the essential mechanisms of stem cell transplantation for treating AMI by targeted regulating the myocardial microenvironment after stem cell transplantation at the post-transcriptional level. Thus, microRNA-1 participates in regulating the myocardial microenvironment after stem cell transplantation, a promising strategy for the Stem cell transplantation treatment of AMI. However, the naked microRNA-1 synthesized is extremely unstable and non-targeting, which can be rapidly degraded by circulating RNase. Herein, to safely and effectively targeted transport the naked microRNA-1 synthesized into myocardial tissue, we will construct pseudo-endogenous microRNA-targeted myocardial ultrasound nanobubble pAd-AAV-9/miRNA-1 NB and evaluate its characteristics, targeting, and function.MethodsThe pAd-AAV-9/miRNA-1 gene complex was linked to nanobubble NBs by the “avidin-biotin bridging” method to prepare cardiomyocyte-targeted nanobubble pAd-AAV-9/miRNA-1 NB. The shape, particle size, dispersion, and stability of nanobubbles and the connection of pAd-AAV-9/miRNA-1 gene complex to nanobubble NB were observed. The virus loading efficiency was determined, and the myocardium-targeting imaging ability was evaluated using contrast-enhanced ultrasound imaging in vivo. The miRNA-1 expression level in myocardial tissue and other vital organs ex vivo of SD rats was considered by Q-PCR. Also, the cytotoxic effects were assessed.ResultsThe particle size of NBs was 504.02 ± 36.94 nm, and that of pAd-AAV-9/miRNA-1 NB was 568.00 ± 37.39 nm. The particle size and concentration of pAd-AAV-9/miRNA-1 NBs did not change significantly within 1 h at room temperature (p > 0.05). pAd-AAV-9/miRNA-1 NB had the highest viral load rate of 86.3 ± 2.2% (p < 0.05), and the optimum viral load was 5 μL (p < 0.05). pAd-AAV-9/miRNA-1 NB had good contrast-enhanced ultrasound imaging in vivo. Quantitative analysis of miRNA-1 expression levels in vital organs ex vivo of SD rats by Q-PCR showed that pAd-AAV-9/miRNA-1 NB targeted the myocardial tissue. Q-PCR indicated that the expression level of miRNA-1 in the myocardium of the pAd-AAV-9/miRNA-1 NB + UTMD group was significantly higher than that of the pAd-AAV-9/miRNA-1 NB group (p < 0.05). pAd-AAV-9/miRNA-1 NB had no cytotoxic effect on cardiomyocytes (p > 0.05).ConclusionThe pAd-AAV-9/miRNA-1 NB constructed in this study could carry naked miRNA-1 synthesized in vitro for targeted transport into myocardial tissue successfully and had sound contrast-enhanced imaging effects in vivo

Coverage goal selector for combining multiple criteria in search-based unit test generation

Unit testing is critical to the software development process, ensuring the correctness of basic programming units in a program (e.g., a method). Search-based software testing (SBST) is an automated approach to generating test cases. SBST generates test cases with genetic algorithms by specifying the coverage criterion (e.g., branch coverage). However, a good test suite must have different properties, which cannot be captured using an individual coverage criterion. Therefore, the state-of-the-art approach combines multiple criteria to generate test cases. Since combining multiple coverage criteria brings multiple objectives for optimization, it hurts the test suites’ coverage for certain criteria compared with using the single criterion. To cope with this problem, we propose a novel approach named smart selection . Based on the coverage correlations among criteria and the subsumption relationships among coverage goals, smart selection selects a subset of coverage goals to reduce the number of optimization objectives and avoid missing any properties of all criteria. We conduct experiments to evaluate smart selection on 400 Java classes with three state-of-the-art genetic algorithms under the 2-minute budget. On average, smart selection outperforms combining all goals on 65.1% of the classes having significant differences between the two approaches. Secondly, we conduct experiments to verify our assumptions about coverage criteria relationships. Furthermore, we assess the coverage performance of smart selection under varying budgets of 5, 8, and 10 minutes and explore its effect on bug detection, confirming the advantage of smart selection over combining all goals

Prime-boost vaccination of mice and rhesus macaques with two novel adenovirus vectored COVID-19 vaccine candidates.

ABSTRACTCOVID-19 vaccines are being developed urgently worldwide. Here, we constructed two adenovirus vectored COVID-19 vaccine candidates of Sad23L-nCoV-S and Ad49L-nCoV-S carrying the full-length gene of SARS-CoV-2 spike protein. The immunogenicity of two vaccines was individually evaluated in mice. Specific immune responses were observed by priming in a dose-dependent manner, and stronger responses were obtained by boosting. Furthermore, five rhesus macaques were primed with 5 × 109 PFU Sad23L-nCoV-S, followed by boosting with 5 × 109 PFU Ad49L-nCoV-S at 4-week interval. Both mice and macaques well tolerated the vaccine inoculations without detectable clinical or pathologic changes. In macaques, prime-boost regimen induced high titers of 103.16 anti-S, 102.75 anti-RBD binding antibody and 102.38 pseudovirus neutralizing antibody (pNAb) at 2 months, while pNAb decreased gradually to 101.45 at 7 months post-priming. Robust T-cell response of IFN-γ (712.6 SFCs/106 cells), IL-2 (334 SFCs/106 cells) and intracellular IFN-γ in CD4+/CD8+ T cell (0.39%/0.55%) to S peptides were detected in vaccinated macaques. It was concluded that prime-boost immunization with Sad23L-nCoV-S and Ad49L-nCoV-S can safely elicit strong immunity in animals in preparation of clinical phase 1/2 trials