104 research outputs found
On the Expected Discounted Penalty Function for the Classical Risk Model with Potentially Delayed Claims and Random Incomes
We focus on the expected discounted penalty function of a compound Poisson risk model with random incomes and potentially delayed claims. It is assumed that each main claim will produce a byclaim with a certain probability and the occurrence of the byclaim may be delayed depending on associated main claim amount. In addition, the premium number process is assumed as a Poisson process. We derive the integral equation satisfied by the expected discounted penalty function. Given that the premium size is exponentially distributed, the explicit expression for the Laplace transform of the expected discounted penalty function is derived. Finally, for the exponential claim sizes, we present the explicit formula for the expected discounted penalty function
Aplicación web para mejorar control de pedidos del cliente del Chifa de Chong en Trujillo, 2023
El estudio tuvo como objetivo general mejorar el control de pedidos del cliente
en el Chifa de Chong Trujillo, 2023 con la implementación de un aplicativo web. El
tipo de investigación fue aplicada y de diseño pre experimental; como
instrumento se utilizaron las fichas de registro. Para el desarrollo de la
investigación se utilizó la metodología SCRUM Los resultados fueron un
aumento en el porcentaje de pedidos recibidos correctos del 46,7% al
83,3%, es decir, un incremento del 78,37%; un aumento en el porcentaje de
entregas perfectas del 68,9% al 88,9%, es decir, un incremento del 29,3%; una
disminución en el tiempo de tiempo promedio de organización de pedidos de una
media de 106,08 segundos a 50,02 segundos, es decir, una diferencia de 56,06
segundos. En conclusión, se logró mejorar el control de pedidos en la empresa
Chifa de Chong. Quedó demostrado una mejora en el porcentaje de pedidos
recibidos correctos, entregas perfectas y disminución del tiempo de organización
de pedidos
Fibroblast Growth Factor-10 (FGF-10) Mobilizes Lung-resident Mesenchymal Stem Cells and Protects Against Acute Lung Injury.
FGF-10 can prevent or reduce lung specific inflammation due to traumatic or infectious lung injury. However, the exact mechanisms are poorly characterized. Additionally, the effect of FGF-10 on lung-resident mesenchymal stem cells (LR-MSCs) has not been studied. To better characterize the effect of FGF-10 on LR-MSCs, FGF-10 was intratracheally delivered into the lungs of rats. Three days after instillation, bronchoalveolar lavage was performed and plastic-adherent cells were cultured, characterized and then delivered therapeutically to rats after LPS intratracheal instillation. Immunophenotyping analysis of FGF-10 mobilized and cultured cells revealed expression of the MSC markers CD29, CD73, CD90, and CD105, and the absence of the hematopoietic lineage markers CD34 and CD45. Multipotency of these cells was demonstrated by their capacity to differentiate into osteocytes, adipocytes, and chondrocytes. Delivery of LR-MSCs into the lungs after LPS injury reduced the inflammatory response as evidenced by decreased wet-to-dry ratio, reduced neutrophil and leukocyte recruitment and decreased inflammatory cytokines compared to control rats. Lastly, direct delivery of FGF-10 in the lungs of rats led to an increase of LR-MSCs in the treated lungs, suggesting that the protective effect of FGF-10 might be mediated, in part, by the mobilization of LR-MSCs in lungs
Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation
Two-tower models are a prevalent matching framework for recommendation, which
have been widely deployed in industrial applications. The success of two-tower
matching attributes to its efficiency in retrieval among a large number of
items, since the item tower can be precomputed and used for fast Approximate
Nearest Neighbor (ANN) search. However, it suffers two main challenges,
including limited feature interaction capability and reduced accuracy in online
serving. Existing approaches attempt to design novel late interactions instead
of dot products, but they still fail to support complex feature interactions or
lose retrieval efficiency. To address these challenges, we propose a new
matching paradigm named SparCode, which supports not only sophisticated feature
interactions but also efficient retrieval. Specifically, SparCode introduces an
all-to-all interaction module to model fine-grained query-item interactions.
Besides, we design a discrete code-based sparse inverted index jointly trained
with the model to achieve effective and efficient model inference. Extensive
experiments have been conducted on open benchmark datasets to demonstrate the
superiority of our framework. The results show that SparCode significantly
improves the accuracy of candidate item matching while retaining the same level
of retrieval efficiency with two-tower models. Our source code will be
available at MindSpore/models.Comment: Accepted by SIGIR 2023. Code will be available at
https://reczoo.github.io/SparCod
Nonisolated switching-capacitor-integrated three- port converters with seamless PWM/PFM modulation
Efficiency and power density of power converters for interfacing photovoltaic panels, energy storage components such as batteries, and loads in photovoltaic (PV) systems become more and more important. Compared with individual converter design for different terminals, power-integrated multiport converters shows obvious advantages in simplifying the system structure, reducing the component count, and improving the operation reliability. Originated from the high power-density switched capacitor topology, a nonisolated switching-capacitor-integrated three-port converter (SCI-TPC) is presented to achieve single-stage direct power conversion among three ports. In order to minimize the cross-regulation effect, pulse-width-modulation (PWM) and pulse-frequency-modulation (PFM) are adopted to realize the flexible power regulation and achieve power balance among three ports. Main operation modes, power flow distribution, and power transfer characteristic are analyzed. With the seamless PWM and PFM hybrid modulation, the current stress can be reduced and the overall conversion efficiency over a full operating range can be improved. Main experimental results are provided to validate the effectiveness of the proposed concept
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