Constrained variational-hemivariationalinequalities on nonconvex star-shaped sets

In this paper, we study a class of constrained variational–hemivariational inequality problems with nonconvex sets which are star-shaped with respect to a certain ball in a reflexive Banach space. The inequality is a fully nonconvex counterpart of the variational–hemivariational inequality of elliptic type since it contains both, a convex potential and a locally Lipschitz one. Two new results on the existence of a solution are proved by a penalty method applied to a variational–hemivariational inequality penalized by the generalized directional derivative of the distance function of the constraint set. In the first existence theorem, the strong monotonicity of the governing operator and a relaxed monotonicity condition of the Clarke subgradient are assumed. In the second existence result, these two hypotheses are relaxed and a suitable hypothesis on the upper semicontinuity of the operator is adopted. In both results, the penalized problems are solved by using the Knaster, Kuratowski, and Mazurkiewicz (KKM) lemma. For a suffciently small penalty parameter, the solution to the penalized problem solves also the original one. Finally, we work out an example on the interior and boundary semipermeability problem that ilustrate the applicability of our results

Kernel methods for time series data

Kernel methods are powerful learning techniques with excellent generalization capability. This thesis develops three advanced approaches within the generic SVM framework in the application domain of time series data. The first contribution presents a new methodology for incorporating privileged information about the future evolution of time series, which is only available in the training phase. The task is prediction of the ordered categories of future time series movements. This is implemented by directly extending support vector ordinal regression with implicit constraints to leaning using privileged information paradigm. The second contribution demonstrates a novel methodology of constructing efficient kernels for time series classification problems. These kernels are constructed by representing each time series through a linear readout model from a high dimensional state space model with a fixed deterministically constructed dynamic part. Learning is then performed in the linear readout model space. Finally, in the same context, we introduce yet another novel time series kernel by co-learning the dynamic part and a global metric in the linear readout model space, encouraging time series from the same class to be represented by close model representations, while model representations of time series from different classes to be well-separated

Genome-wide characterization of the PP2C gene family in peanut (Arachis hypogaea L.) and the identification of candidate genes involved in salinity-stress response

Plant protein phosphatase 2C (PP2C) play important roles in response to salt stress by influencing metabolic processes, hormone levels, growth factors, etc. Members of the PP2C family have been identified in many plant species. However, they are rarely reported in peanut. In this study, 178 PP2C genes were identified in peanut, which were unevenly distributed across the 20 chromosomes, with segmental duplication in 78 gene pairs. AhPP2Cs could be divided into 10 clades (A-J) by phylogenetic analysis. AhPP2Cs had experienced segmental duplications and strong purifying selection pressure. 22 miRNAs from 14 different families were identified, targeting 57 AhPP2C genes. Gene structures and motifs analysis exhibited PP2Cs in subclades AI and AII had high structural and functional similarities. Phosphorylation sites of AhPP2C45/59/134/150/35/121 were predicted in motifs 2 and 4, which located within the catalytic site at the C-terminus. We discovered multiple MYB binding factors and ABA response elements in the promoter regions of the six genes (AhPP2C45/59/134/150/35/121) by cis-elements analysis. GO and KEGG enrichment analysis confirmed AhPP2C-A genes in protein binding, signal transduction, protein modification process response to abiotic stimulus through environmental information processing. Based on RNA-Seq data of 22 peanut tissues, clade A AhPP2Cs showed a varying degree of tissue specificity, of which, AhPP2C35 and AhPP2C121 specifically expressed in seeds, while AhPP2C45/59/134/150 expressed in leaves and roots. qRT-PCR indicated that AhPP2C45 and AhPP2C134 displayed significantly up-regulated expression in response to salt stress. These results indicated that AhPP2C45 and AhPP2C134 could be candidate PP2Cs conferring salt tolerance. These results provide further insights into the peanut PP2C gene family and indicate PP2Cs potentially involved in the response to salt stress, which can now be further investigated in peanut breeding efforts to obtain cultivars with improved salt tolerance

Hashimoto's Encephalopathy and Seizure Disorders

Hashimoto's encephalopathy (HE) is a rare, clinically heterogeneous condition associated with positive thyroid autoantibodies. It is increasingly recognized as an important and treatable cause of autoimmune encephalopathy. Thyroid-associated antibodies such as thyroperoxidase (TPO) antibody, thyroglobulin (TG) antibody, and thyrotropin receptor (TR) antibody were found in HE patients with seizure disorders. Although antithyroid antibodies are required for the diagnosis of HE, their role in the pathogenesis of HE remains uncertain. Instead of playing a key role in the pathophysiology processes of HE, it is suggested that thyroid-associated antibodies are hallmarks of HE. Seizure disorders were found in approximately two-thirds of HE patients, and common anticonvulsant therapy alone is usually ineffective. Some patients did not respond to any antiepileptic drugs. The use of immunotherapy can effectively control seizure disorders. Electroencephalography and imaging findings are not specific to HE patients and can also be seen in other causes of encephalopathies. However, the prognosis in the majority of patients with HE was usually good if it is diagnosed and treated correctly

Application and Curative Effect of Micro-implant Anchorage in Orthodontics

Purpose: To explore and analyze the curative effects of micro - implant anchorages in orthodontics.Methods: A retrospective analysis of 65 patients undergoing orthodontic treatment in Department of Stomatology, Binzhou Medical University Hospital, Shandong, China was carried out. Thirty four cases in the treatment group were treated with a micro-implant as the anchorage, while 31 cases of the control group were treated with a palatal bar and facebow as the anchorage, and the curative results of the two groups were then compared.Results: After a 13-month treatment, both anchorages were clinically effective, but the micro-implant anchorage showed higher efficacy. Measurement indices for the test group, including sella-nasion - A point (SNA) angle (- 1.88 ± 0.71), sella-nasion-B point (SNB) angle (1.39 ± 0.42), A point - nasion - B point (ANB) angle (- 2.40 ± 0.83), upper central incisor - lower central incisor (U1 - L1) angle (25.79 ± 5.90), upper central incisor - sella - nasion (U1 - SN) angle (- 10.13 ± 3.68), lower central incisor – mandibular plane (L1 - MP) angle (- 4.22 ± 0.45), upper central incisor - nasion - A point (U1 - NA) angle (- 1.32 ± 1.35) and lower central incisor - nasion - B point (L1 - NB) angle (- 1.32 ± 1.35) of the test group were significantly different those of the control group Overbite (OB), overjet (OJ), intercanine width and the width of the first molars of treatment and control groups were also remarkably). Moreover, micro-implant was observed to be more stable during treatment.Conclusion: Compared with traditional anchorages, micro-implants possess the advantages of slighter trauma, simpler operation, more reliable curative effect and high stability.Keywords: Micro-implant anchorage, Orthodontics, Facebow anchorage, Oral medicine, Clinical efficac