Rational approximation solution of the fractional Sharma–Tasso–Olever equation

AbstractIn the paper, we implement relatively new analytical techniques, the variational iteration method, the Adomian decomposition method and the homotopy perturbation method, for obtaining a rational approximation solution of the fractional Sharma–Tasso–Olever equation. The three methods in applied mathematics can be used as alternative methods for obtaining an analytic and approximate solution for different types of differential equations. In these schemes, the solution takes the form of a convergent series with easily computable components. The numerical results demonstrate the significant features, efficiency and reliability of the three approaches

Expression and role of fibroblast activation protein-alpha in microinvasive breast carcinoma

<p>Abstract</p> <p>Background</p> <p>Diagnosis of ductal carcinoma in situ (DCIS) in breast cancer cases is challenging for pathologist due to a variety of in situ patterns and artefacts, which could be misinterpreted as stromal invasion. Microinvasion is detected by the presence of cytologically malignant cells outside the confines of the basement membrane and myoepithelium. When malignant cells invade the stroma, there is tissue remodeling induced by perturbed stromal-epithelial interactions. Carcinoma-associated fibroblasts (CAFs) are main cells in the microenvironment of the remodeled tumor-host interface. They are characterized by the expression of the specific fibroblast activation protein-alpha (FAP-α), and differ from that of normal fibroblasts exhibiting an immunophenotype of CD34. We hypothesized that staining for FAP-α may be helpful in determining whether DCIS has microinvasion.</p> <p>Methods</p> <p>349 excised breast specimens were immunostained for smooth muscle actin SMA, CD34, FAP-α, and Calponin. Study material was divided into 5 groups: group 1: normal mammary tissues of healthy women after plastic surgery; group 2: usual ductal hyperplasia (UDH); group 3: DCIS without microinvasion on H & E stain; group 4: DCIS with microinvasion on H & E stain (DCIS-MI), and group 5: invasive ductal carcinoma (IDC). A comparative evaluation of the four immunostains was conducted.</p> <p>Results</p> <p>Our results demonstrated that using FAP-α and Calponin adjunctively improved the sensitivity of pathological diagnosis of DCIS-MI by 11.29%, whereas the adjunctive use of FAP-α and Calponin improved the sensitivity of pathological diagnosis of DCIS by 13.6%.</p> <p>Conclusions</p> <p>This study provides the first evidence that immunostaining with FAP-α and Calponin can serve as a novel marker for pathologically diagnosing whether DCIS has microinvasion.</p

Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation

Deep reinforcement learning (DRL) has been proven its efficiency in capturing users' dynamic interests in recent literature. However, training a DRL agent is challenging, because of the sparse environment in recommender systems (RS), DRL agents could spend times either exploring informative user-item interaction trajectories or using existing trajectories for policy learning. It is also known as the exploration and exploitation trade-off which affects the recommendation performance significantly when the environment is sparse. It is more challenging to balance the exploration and exploitation in DRL RS where RS agent need to deeply explore the informative trajectories and exploit them efficiently in the context of recommender systems. As a step to address this issue, We design a novel intrinsically ,otivated reinforcement learning method to increase the capability of exploring informative interaction trajectories in the sparse environment, which are further enriched via a counterfactual augmentation strategy for more efficient exploitation. The extensive experiments on six offline datasets and three online simulation platforms demonstrate the superiority of our model to a set of existing state-of-the-art methods

The CXC chemokine cCAF stimulates precocious deposition of ECM molecules by wound fibroblasts, accelerating development of granulation tissue

BACKGROUND: During wound repair, fibroblasts orchestrate replacement of the provisional matrix formed during clotting with tenascin, cellular fibronectin and collagen III. These, in turn, are critical for migration of endothelial cells, keratinocytes and additional fibroblasts into the wound site. Fibroblasts are also important in the deposition of collagen I during scar formation. The CXC chemokine chicken Chemotactic and Angiogenic Factor (cCAF), is highly expressed by fibroblasts after wounding and during development of the granulation tissue, especially in areas where extracellular matrix (ECM) is abundant. We hypothesized that cCAF stimulates fibroblasts to produce these matrix molecules. RESULTS: Here we show that this chemokine can stimulate precocious deposition of tenascin, fibronectin and collagen I, but not collagen III. Studies in culture and in vivo show that tenascin stimulation can also be achieved by the N-terminal 15 aas of the protein and occurs at the level of gene expression. In contrast, stimulation of fibronectin and collagen I both require the entire molecule and do not involve changes in gene expression. Fibronectin accumulation appears to be linked to tenascin production, and collagen I to decreased MMP-1 levels. In addition, cCAF is chemotactic for fibroblasts and accelerates their migration. CONCLUSIONS: These previously unknown functions for chemokines suggest that cCAF, the chicken orthologue of human IL-8, enhances healing by rapidly chemoattracting fibroblasts into the wound site and stimulating them to produce ECM molecules, leading to precocious development of granulation tissue. This acceleration of the repair process may have important application to healing of impaired wounds

The Composite Face Effect Between Young and Older Chinese Adults Remains Stable

Holistic face perception is often considered to be a cornerstone of face processing. However, the development of the ability to holistically perceive faces in East Asian individuals is unclear. Therefore, we measured and compared holistic face processing in groups of Chinese children, young adults, and older adults by employing the complete composite face paradigm. The results demonstrate a similar magnitude of the composite effect in all three groups although face recognition performance in the task was better in young adults than in the two other groups. These findings suggest that holistic face perception in Eastern individuals is stable from late childhood to at least age 60, whereas face memory may be subject to later development and earlier decline.Peer Reviewe

Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models

Factor models have been widely used in practice. However, an undesirable feature of a high dimensional factor model is that the model has too many parameters. An effective way to address this issue, proposed in a seminar work by Tsai and Tsay (2010), is to decompose the loadings matrix by a high-dimensional known matrix multiplying with a low-dimensional unknown matrix, which Tsai and Tsay (2010) name constrained factor models. This paper investigates the estimation and inferential theory of constrained factor models under large-N and large-T setup, where N denotes the number of cross sectional units and T the time periods. We propose using the quasi maximum likelihood method to estimate the model and investigate the asymptotic properties of the quasi maximum likelihood estimators, including consistency, rates of convergence and limiting distributions. A new statistic is proposed for testing the null hypothesis of constrained factor models against the alternative of standard factor models. Partially constrained factor models are also investigated. Monte carlo simulations confirm our theoretical results and show that the quasi maximum likelihood estimators and the proposed new statistic perform well in finite samples. We also consider the extension to an approximate constrained factor model where the idiosyncratic errors are allowed to be weakly dependent processes

A finite control set model predictive control method for matrix converter with zero common-mode voltage

In this paper a finite control set model predictive control method is presented that eliminates the common-mode voltage at the output of a matrix converter. In the predictive control process only the rotating vectors are selected to generate the output voltage and the input current in order to remove the common mode voltage. In addition, a modified four-step commutation strategy is proposed to eliminate common-mode voltage spikes caused by the conventional four-step commutation strategy based on the current direction. The proposed method reduces the computational complexity greatly compared with the enhanced space vector modulation with rotating vectors. The feasibility and operation of the proposed method are verified using experimental results. The resulting common-mode voltage is near to zero with good quality input and output converter waveforms