Convergence properties of a family of inexact Levenberg-Marquardt methods

We present a family of inexact Levenberg-Marquardt (LM) methods for the nonlinear equations which takes more general LM parameters and perturbation vectors. We derive an explicit formula of the convergence order of these inexact LM methods under the H$\mathrm{\ddot{o}}$derian local error bound condition and the H$\mathrm{\ddot{o}}$derian continuity of the Jacobian. Moreover, we develop a family of inexact LM methods with a nonmonotone line search and prove that it is globally convergent. Numerical results for solving the linear complementarity problem are reported

A Nonsecosteroidal Vitamin D Receptor Modulator Ameliorates Experimental Autoimmune Encephalomyelitis without Causing Hypercalcemia

Vitamin D receptor (VDR) agonists are currently the agents of choice for the treatment of psoriasis, a skin inflammatory indication that is believed to involve an autoimmune component. 1,25-dihydroxyvitamin D3 [1,25-(OH)2D3], the biologically active metabolite of vitamin D, has shown efficacy in animal autoimmune disease models of multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, and type I diabetes. However, the side effect of 1,25-(OH)2D3 and its synthetic secosteroidal analogs is hypercalcemia, which is a major impediment in their clinical development for autoimmune diseases. Hypercalcemia develops as a result of the action of VDR agonists on the intestine. Here, we describe the identification of a VDR modulator (VDRM) compound A that was transcriptionally less active in intestinal cells and as a result exhibited less calcemic activity in vivo than 1,25-(OH)2D3. Cytokine analysis indicated that the VDRM not only modulated the T-helper cell balance from Th1 to Th2 effector function but also inhibited Th17 differentiation. Finally, we demonstrate that the oral administration of compound A inhibited the induction and progress of experimental autoimmune encephalomyelitis in mice without causing hypercalcemia

IL-21 promotes myocardial ischaemia/reperfusion injury through the modulation of neutrophil infiltration.

BACKGROUND AND PURPOSE: The immune system plays an important role in driving the acute inflammatory response following myocardial ischaemia/reperfusion injury (MIRI). IL-21 is a pleiotropic cytokine with multiple immunomodulatory effects, but its role in MIRI is not known. EXPERIMENTAL APPROACH: Myocardial injury, neutrophil infiltration and the expression of neutrophil chemokines KC (CXCL1) and MIP-2 (CXCL2) were studied in a mouse model of MIRI. Effects of IL-21 on the expression of KC and MIP-2 in neonatal mouse cardiomyocytes (CMs) and cardiac fibroblasts (CFs) were determined by real-time PCR and ELISA. The signalling mechanisms underlying these effects were explored by western blot analysis. KEY RESULTS: IL-21 was elevated within the acute phase of murine MIRI. Neutralization of IL-21 attenuated myocardial injury, as illustrated by reduced infarct size, decreased cardiac troponin T levels and improved cardiac function, whereas exogenous IL-21 administration exerted opposite effects. IL-21 increased the infiltration of neutrophils and increased the expression of KC and MIP-2 in myocardial tissue following MIRI. Moreover, neutrophil depletion attenuated the IL-21-induced myocardial injury. Mechanistically, IL-21 increased the production of KC and MIP-2 in neonatal CMs and CFs, and enhanced neutrophil migration, as revealed by the migration assay. Furthermore, we demonstrated that this IL-21-mediated increase in chemokine expression involved the activation of Akt/NF-κB signalling in CMs and p38 MAPK/NF-κB signalling in CFs. CONCLUSIONS AND IMPLICATIONS: Our data provide novel evidence that IL-21 plays a pathogenic role in MIRI, most likely by promoting cardiac neutrophil infiltration. Therefore, targeting IL-21 may have therapeutic potential as a treatment for MIRI. LINKED ARTICLES: This article is part of a themed section on Spotlight on Small Molecules in Cardiovascular Diseases. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.8/issuetoc

Rate-invariant analysis of covariance trajectories

Statistical analysis of dynamic systems, such as videos and dynamic functional connectivity, is often translated into a problem of analyzing trajectories of relevant features, particularly covariance matrices. As an example, in video-based action recognition, a natural mathematical representation of activity videos is as parameterized trajectories on the set of symmetric, positive-definite matrices (SPDMs). The variable execution-rates of actions, implying arbitrary parameterizations of trajectories, complicates their analysis and classification. To handle this challenge, we represent covariance trajectories using transported square-root vector fields (TSRVFs), constructed by parallel translating scaled-velocity vectors of trajectories to their starting points. The space of such representations forms a vector bundle on the SPDM manifold. Using a natural Riemannian metric on this vector bundle, we approximate geodesic paths and geodesic distances between trajectories in the quotient space of this vector bundle. This metric is invariant to the action of the reparameterization group, and leads to a rate-invariant analysis of trajectories. In the process, we remove the parameterization variability and temporally register trajectories during analysis. We demonstrate this framework in multiple contexts, using both generative statistical models and discriminative data analysis. The latter is illustrated using several applications involving video-based action recognition and dynamic functional connectivity analysis

PA-YOLO-Based Multifault Defect Detection Algorithm for PV Panels

In recent years, solar photovoltaic (PV) energy, as a clean energy source, has received widespread attention and experienced rapid growth worldwide. However, the rapid growth of PV power deployment also brings important challenges to the maintenance of PV panels, and in order to solve this problem, this paper proposes an innovative algorithm based on PA-YOLO. First, we propose to use PA-YOLO’s asymptotic feature pyramid network (AFPN) instead of YOLOv7’s backbone network to support direct interactions of nonadjacent layers and avoid large semantic gaps between nonadjacent layers. For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. Finally, we propose a customized convolutional block equipped with an EMA mechanism to enhance the perceptual and expressive capabilities of the model. Experimental results on the dataset show that our proposed model achieves excellent performance with an average accuracy (mAP) of 94.5%, which is 6.8% higher than YOLOv7. In addition, our algorithm also succeeds in drastically reducing the model size from 71.3 MB to 48.4 MB, which well demonstrates the effectiveness of the model

Photopatternable Magnetic Hollowbots by Nd-Fe-B Nanocomposite for Potential Targeted Drug Delivery Applications

In contrast to traditional drug administration, targeted drug delivery can prolong, localize, target and have a protected drug interaction with the diseased tissue. Drug delivery carriers, such as polymeric micelles, liposomes, dendrimers, nanotubes, and so on, are hard to scale-up, costly, and have short shelf life. Here we show the novel fabrication and characterization of photopatternable magnetic hollow microrobots that can potentially be utilized in microfluidics and drug delivery applications. These magnetic hollowbots can be fabricated using standard ultraviolet (UV) lithography with low cost and easily accessible equipment, which results in them being easy to scale up, and inexpensive to fabricate. Contact-free actuation of freestanding magnetic hollowbots were demonstrated by using an applied 900 G external magnetic field to achieve the movement control in an aqueous environment. According to the movement clip, the average speed of the magnetic hollowbots was estimated to be 1.9 mm/s

Simultaneous improvement of strength and ductility in ZK60 magnesium alloy by constructing the bimodal grain structure

In this study, the microstructure and mechanical properties of the commercial magnesium (Mg) ZK60 alloy were conducted to promote the application of Mg alloys. Scanning electron microscopy, tensile and compression tests, electron back scattering diffraction, transmission electron microscope and visco-plasticity self-consistent methods were employed to analyze the microstructure evolution and the strengthening and toughening mechanisms. By direct extrusion in the as-cast state, a bimodal microstructure was obtained, and the mechanical properties were enhanced. The ZK60 alloy, with a bimodal grain structure, exhibited a good combination of strength and ductility. The tensile yield strength (TYS), ultimate tensile strength (UTS), compressive yield strength (CYS) and fracture elongation (FE) reached 272 MPa, 347 MPa, 289 MPa, and 36.2%, respectively. Compared with the traditional extrusion ZK60 alloy, the increment in TYS, UTS, CYS, and FE was 15 MPa, 31 MPa, 25 MPa and 8.6%, respectively. The formation of the bimodal structure in the ZK60-CE sample is attributed to the combination of the PSN and Zener pinning effects. The improvement in strength is mainly attributed to the residual dislocations in the un-DRXed grains and the good ductility is ascribed to the activation of the non-basal slip. This study provides a low-cost and efficient strategy for the preparation of the bimodal structure by regulating the pre-extrusion microstructure to improve mechanical properties