Allocating Limited Resources to Protect a Massive Number of Targets using a Game Theoretic Model

Resource allocation is the process of optimizing the rare resources. In the area of security, how to allocate limited resources to protect a massive number of targets is especially challenging. This paper addresses this resource allocation issue by constructing a game theoretic model. A defender and an attacker are players and the interaction is formulated as a trade-off between protecting targets and consuming resources. The action cost which is a necessary role of consuming resource, is considered in the proposed model. Additionally, a bounded rational behavior model (Quantal Response, QR), which simulates a human attacker of the adversarial nature, is introduced to improve the proposed model. To validate the proposed model, we compare the different utility functions and resource allocation strategies. The comparison results suggest that the proposed resource allocation strategy performs better than others in the perspective of utility and resource effectiveness.Comment: 14 pages, 12 figures, 41 reference

DYNAMIC MONITORING OF HARVESTER WORKING PROGRESS BASED ON TRAVELING TRAJECTORY AND HEADER STATUS

ABSTRACT China's socialized service industry of agricultural machinery emerged as the times required, which resolved the institutional contradiction between small farm households and large-scale agriculture. However, as cross-operation harvesters are still monitored based on phone calls, the monitoring efficiency and real-time performance are relatively poor. To improve the dynamic monitoring accuracy of harvester working areas, we proposed a working progress monitoring method based on harvester traveling trajectory and header status identification. The position and gap bridge angle information of harvesters was synchronously acquired in real-time. The height of the header above ground was calculated to determine whether the harvester was harvesting on a valid trajectory. Finally, the valid trajectory of the harvester was selected for area calculation. Field experiments showed that the header heights at the working and non-working tracing points collected by the system were discretely distributed at intervals of [0m, 0.5m] and (0.5m, 2m), respectively. The working progress monitoring algorithm proposed in this paper effectively improved the monitoring accuracy of harvester working areas. The mean error between the working areas calculated with identifying the header status and the actual cultivated land area in the five test plots was 0.09 hm2, with a mean error rate of 3.10%, 8.59% lower than that without identifying the harvester header status

Performance Issue Identification in Cloud Systems with Relational-Temporal Anomaly Detection

Performance issues permeate large-scale cloud service systems, which can lead to huge revenue losses. To ensure reliable performance, it's essential to accurately identify and localize these issues using service monitoring metrics. Given the complexity and scale of modern cloud systems, this task can be challenging and may require extensive expertise and resources beyond the capacity of individual humans. Some existing methods tackle this problem by analyzing each metric independently to detect anomalies. However, this could incur overwhelming alert storms that are difficult for engineers to diagnose manually. To pursue better performance, not only the temporal patterns of metrics but also the correlation between metrics (i.e., relational patterns) should be considered, which can be formulated as a multivariate metrics anomaly detection problem. However, most of the studies fall short of extracting these two types of features explicitly. Moreover, there exist some unlabeled anomalies mixed in the training data, which may hinder the detection performance. To address these limitations, we propose the Relational- Temporal Anomaly Detection Model (RTAnomaly) that combines the relational and temporal information of metrics. RTAnomaly employs a graph attention layer to learn the dependencies among metrics, which will further help pinpoint the anomalous metrics that may cause the anomaly effectively. In addition, we exploit the concept of positive unlabeled learning to address the issue of potential anomalies in the training data. To evaluate our method, we conduct experiments on a public dataset and two industrial datasets. RTAnomaly outperforms all the baseline models by achieving an average F1 score of 0.929 and Hit@3 of 0.920, demonstrating its superiority

Lewis Y Promotes Growth and Adhesion of Ovarian Carcinoma-Derived RMG-I Cells by Upregulating Growth Factors

Lewis y (LeY) antigen is a difucosylated oligosaccharide carried by glycoconjugates on the cell surface. Overexpression of LeY is frequently observed in epithelial-derived cancers and has been correlated to the pathological staging and prognosis. However, the effects of LeY on ovarian cancer are not yet clear. Previously, we transfected the ovarian cancer cell line RMG-I with the α1,2-fucosyltransferase gene to obtain stable transfectants, RMG-I-H, that highly express LeY. In the present study, we examined the proliferation, tumorigenesis, adhesion and invasion of the cell lines with treatment of LeY monoclonal antibody (mAb). Additionally, we examined the expression of TGF-β1, VEGF and b-FGF in xenograft tumors. The results showed that the proliferation and adhesion in vitro were significantly inhibited by treatment of RMG-I-H cells with LeY mAb. When subcutaneously inoculated in nude mice, RMG-I-H cells produced large tumors, while mock-transfected cells RMG-I-C and the parental cells RMG-I produced small tumors. Moreover, the tumor formation by RMG-I-H cells was inhibited by preincubating the cells with LeY mAb. Notably, the expression of TGF-β1, VEGF and b-FGF all increased in RMG-I-H cells. In conclusion, LeY plays an important role in promoting cell proliferation, tumorigenecity and adhesion, and these effects may be related to increased levels of growth factors. The LeY antibody shows potential application in the treatment of LeY-positive tumors

Lewis y antigen promotes the proliferation of ovarian carcinoma-derived RMG-I cells through the PI3K/Akt signaling pathway

<p>Abstract</p> <p>Background</p> <p>Lewis y antigen is difucosylated oligosaccharide and is carried by glycoconjugates at cell surface. Elevated expression of Lewis y has been found in 75% of ovarian tumor, and the high expression level is correlated to the tumor's pathological staging and prognosis. This study was to investigate the effect and the possible mechanism of Lewis y on the proliferation of human ovarian cancer cells.</p> <p>Methods</p> <p>We constructed a plasmid encoding α1,2-fucosyltransferase (α1,2-FT) gene and then transfected it into ovarian carcinoma-derived RMG-I cells with lowest Lewis y antigen expression level. Effect of Lewis y on cell proliferation was assessed after transfection. Changes in cell survival and signal transduction were evaluated after α-L-fucosidase, anti-Lewis y antibody and phosphatidylinositol 3-kinase (PI3K) inhibitor treatment.</p> <p>Results</p> <p>Our results showed that the levels of α1,2-FT gene and Lewis y increased significantly after transfection. The cell proliferation of ovarian carcinoma-derived RMG-I cells sped up as the Lewis y antigen was increased. Both of α-L-fucosidase and anti-Lewis y antibody inhibited the cell proliferation. The phosphorylation level of Akt was apparently elevated in Lewis y-overexpressing cells and the inhibitor of PI3K, LY294002, dramatically inhibited the growth of Lewis y-overexpressing cells. In addition, the phosphorylation intensity and difference in phosphorylation intensity between cells with different expression of α1,2-FT were attenuated significantly by the monoantibody to Lewis y and by the PI3K inhibitor LY294002.</p> <p>Conclusions</p> <p>Increased expression of Lewis y antigen plays an important role in promoting cell proliferation through activating PI3K/Akt signaling pathway in ovarian carcinoma-derived RMG-I cells. Inhibition of Lewis y expression may provide a new therapeutic approach for Lewis y positive ovarian cancer.</p

Chemometrics-assisted identification of anti-inflammatory compounds from the green alga klebsormidium flaccidum var. Zivo

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The green alga Klebsormidium flaccidum var. zivo is a rich source of proteins, polyphenols, and bioactive small-molecule compounds. An approach involving chromatographic fractionation, anti-inflammatory activity testing, ultrahigh performance liquid chromatography-mass spectrometry profiling, chemometric analysis, and subsequent MS-oriented isolation was employed to rapidly identify its small-molecule anti-inflammatory compounds including hydroxylated fatty acids, chlorophyll-derived pheophorbides, carotenoids, and glycoglycerolipids. Pheophorbide a, which decreased intracellular nitric oxide production by inhibiting inducible nitric oxide synthase, was the most potent compound identified with an IC50 value of 0.24 µM in lipopolysaccharides-induced macrophages. It also inhibited nuclear factor kappaB activation with an IC50 value of 32.1 µM in phorbol 12-myristate 13-acetate-induced chondrocytes. Compared to conventional bioassay-guided fractionation, this approach is more efficient for rapid identification of multiple chemical classes of bioactive compounds from a complex natural product mixture

Metallic vanadium disulfide nanosheets as a platform material for multifunctional electrode applications

Nano-thick metallic transition metal dichalcogenides such as VS$_{2}$ are essential building blocks for constructing next-generation electronic and energy-storage applications, as well as for exploring unique physical issues associated with the dimensionality effect. However, such 2D layered materials have yet to be achieved through either mechanical exfoliation or bottom-up synthesis. Herein, we report a facile chemical vapor deposition route for direct production of crystalline VS$_{2}$ nanosheets with sub-10 nm thicknesses and domain sizes of tens of micrometers. The obtained nanosheets feature spontaneous superlattice periodicities and excellent electrical conductivities (~3$\times$10$^{3}$ S cm$^{-1}$), which has enabled a variety of applications such as contact electrodes for monolayer MoS$_{2}$ with contact resistances of ~1/4 to that of Ni/Au metals, and as supercapacitor electrodes in aqueous electrolytes showing specific capacitances as high as 8.6$\times$10$^{2}$ F g$^{-1}$. This work provides fresh insights into the delicate structure-property relationship and the broad application prospects of such metallic 2D materials.Comment: 23 pages, 5 figue

Value of loop electrosurgical excision procedure conization and imaging for the diagnosis of papillary squamous cell carcinoma of the cervix

BackgroundLoop electrosurgical excision procedure (LEEP) conization and hysterectomy are performed for some patients with papillary squamous cell carcinoma (PSCC), whereas only hysterectomy is performed for others. We aimed to determine the optimal management for PSCC.MethodsPatients diagnosed with PSCC by colposcopy-directed biopsy between June 2008 and January 2020 who underwent LEEP conization and hysterectomy or only hysterectomy at our hospital were enrolled. Results of cervical cytology, high-risk human papillomavirus testing, transvaginal sonography, pelvic magnetic resonance imaging, LEEP, hysterectomy, and pathology testing of colposcopy-directed biopsy samples were analyzed.ResultsA total of 379 women were diagnosed with PSCC by colposcopy-directed biopsy; 174 underwent LEEP before hysterectomy and 205 underwent only hysterectomy. Patients underwent and did not undergo LEEP were aged 47 ± 11 years and 52 ± 11 years, respectively. Among women who underwent LEEP, the agreement between LEEP and hysterectomy pathology was 85.1%. For women who underwent only hysterectomy, the agreement between preoperative clinical staging and pathological staging after hysterectomy was 82.4%. For patients with preoperative imaging indicative of malignancy, the accuracy of LEEP for diagnosing and staging PSCC was 88.5%, whereas for the hysterectomy-only group, it was 86.2%. For patients without malignancy detected with imaging, the accuracy of LEEP for diagnosing and staging PSCC was 81.6%; however, for those who did not undergo LEEP, it was 70.0%.ConclusionFor women diagnosed with PSCC by colposcopy-directed biopsy, LEEP conization is necessary for an accurate diagnosis when imaging does not indicate cancer; however, LEEP is not necessary when imaging indicates cancer