Does ESPN’s Total Quarterback Rating Help Explain an NFL Team’s Probability of Winning?

The purpose of this study is to examine the relationship between an NFL quarterback’s Total Quarterback Rating (TQR) and his team’s prospect of winning games. We use a binary-logit model to estimate the marginal effects of TQR on the probability of winning, controlling for teams’ power rankings and home-field advantage. We find that a 5-point improvement in the TQR score would lead to a 2% increase in the probability of winning the game. Our results suggest that NFL coaches could see an increase in the probability of winning through the improvement of their quarterbacks’ performance. This model can also be used to predict the outcome of NFL games in the coming seasons

(EMC)-M-3: Improving Energy Efficiency via Elastic Multi-Controller SDN in Data Center Networks

Energy consumed by network constitutes a significant portion of the total power budget in modern data centers. Thus, it is critical to understand the energy consumption and improve the power efficiency of data center networks (DCNs). In doing so, one straightforward and effective way is to make the size of DCNs elastic along with traffic demands, i.e., turning off unnecessary network components to reduce the energy consumption. Today, software defined networking (SDN), as one of the most promising solutions for data center management, provides a paradigm to elastically control the resources of DCNs. However, to the best of our knowledge, the features of SDN have not been fully leveraged to improve the power saving, especially for large-scale multi-controller DCNs. To address this problem, we propose (EMC)-M-3, a mechanism to improve DCN\u27s energy efficiency via the elastic multi-controller SDN. In (EMC)-M-3, the energy optimizations for both forwarding and control plane are considered by utilizing SDN\u27s fine-grained routing and dynamic control mapping. In particular, the flow network theory and the bin-packing heuristic are used to deal with the forwarding plane and control plane, respectively. Our simulation results show that E3MC can achieve more efficient power management, especially in highly structured topologies such as Fat-Tree and BCube, by saving up to 50% of network energy, at an acceptable level of computation cost

MicroRNA-186 suppresses cell proliferation and metastasis in bladder cancer

Purpose: Bladder cancer (BCa) is a common malignancy in the urinary system. This study aims to explore the role of miR-186 in BCa tumorigenesis. Methods: The expression of miR-186 and ADAMTS12 in clinical BCa tissues and cell lines was detected. BCa cell lines T24, 5637 and EJ were used to transfect miR-186 mimics or inhibitors. Luciferase reporter gene detection confirmed the correlation between miR-186 and ADAMTS12. MTT method and flow cytometry were used to detect cell viability and apoptosis. Cell migration and invasion ability was detected by transwell assay. The protein level of ADAMTS12, β-catenin, GSK-3β and p-GSK-3β was determined using western blot analysis. Results: MiR-186 was negatively correlated with the expression of ADAMTS12 in BCa tissues. Further research confirmed that ADAMTS12 is the direct target of miR-186. In addition, overexpression of miR-186 down-regulated the expression of ADAMTS12,inhibiting cell viability and apoptosis, while knockout of miR-186 led to the opposite result. miR-186 also inhibits the phosphorylation of GSK-3 β and β-catenin without changing the total GSK-3β level. Our study shows that miR-186 has a negative regulatory effecton the expression of ADAMTS12 in clinical specimens and in vitro. miR-186 can inhibit the proliferation and invasion of BCa cells. Conclusions: miR-186 has the potential to be used as a biomarker in the early detection of BCa. Keywords: Purpose: Bladder cancer (BCa) is a common malignancy in the urinary system. This study aims to explore the role of miR-186 in BCatumorigenesis.Methods: The expression of miR-186 and ADAMTS12 in clinical BCa tissues and cell lines was detected. BCa cell lines T24, 5637 andEJ were used to transfect miR-186 mimics or inhibitors. Luciferase reporter gene detection confirmed the correlation between miR-186 and ADAMTS12. MTT method and flow cytometry were used to detect cell viability and apoptosis. Cell migration and invasionability was detected by transwell assay. The protein level of ADAMTS12, β-catenin, GSK-3β and p-GSK-3β was determined usingwestern blot analysis.Results: MiR-186 was negatively correlated with the expression of ADAMTS12 in BCa tissues. Further research confirmed thatADAMTS12 is the direct target of miR-186. In addition, overexpression of miR-186 down-regulated the expression of ADAMTS12,inhibiting cell viability and apoptosis, while knockout of miR-186 led to the opposite result. miR-186 also inhibits the phosphorylationof GSK-3 β and β-catenin without changing the total GSK-3β level. Our study shows that miR-186 has a negative regulatory effecton the expression of ADAMTS12 in clinical specimens and in vitro. miR-186 can inhibit the proliferation and invasion of BCa cells.Conclusions: miR-186 has the potential to be used as a biomarker in the early detection of BCa.Keywords: miR-186; ADAMTS12; bladder cancer; proliferation; metastasis biomarker

When Social Influence Meets Item Inference

Research issues and data mining techniques for product recommendation and viral marketing have been widely studied. Existing works on seed selection in social networks do not take into account the effect of product recommendations in e-commerce stores. In this paper, we investigate the seed selection problem for viral marketing that considers both effects of social influence and item inference (for product recommendation). We develop a new model, Social Item Graph (SIG), that captures both effects in form of hyperedges. Accordingly, we formulate a seed selection problem, called Social Item Maximization Problem (SIMP), and prove the hardness of SIMP. We design an efficient algorithm with performance guarantee, called Hyperedge-Aware Greedy (HAG), for SIMP and develop a new index structure, called SIG-index, to accelerate the computation of diffusion process in HAG. Moreover, to construct realistic SIG models for SIMP, we develop a statistical inference based framework to learn the weights of hyperedges from data. Finally, we perform a comprehensive evaluation on our proposals with various baselines. Experimental result validates our ideas and demonstrates the effectiveness and efficiency of the proposed model and algorithms over baselines.Comment: 12 page

5-(4-Chloro­benz­yl)-1H-tetra­zole

In the title compound, C8H7ClN4, the phenyl and tetra­zole rings are inclined at a dihedral angle of 67.52 (6)°. In the crystal, mol­ecules are linked by an N—H⋯N hydrogen bond into a chain structure along [010]. π–π inter­actions with centroid–centroid distances of 3.526 (1) Å between adjacent tetra­zole rings further link the chains, forming a ribbon structure

2-(4-Chloro­phen­yl)acetamide

In the title compound, C8H8ClNO, the acetamide group is twisted out the benzene plane with a dihedral angle of 83.08 (1)°. In the crystal, mol­ecules are linked by N—H⋯O hydrogen bonds, forming layers parallel to the ab plane