Internal versus External Replacement of Mutual Fund Managers

I use a unique dataset of 1,808 mutual fund manager replacements to study the determinants and the subsequent impact of the choice between hiring the successor from within (internal hire) and outside (external hire) the fund family. I find that fund families prefer to replace their top performers with internal hires and bottom performers with external hires. External hires demonstrate superior ability to turn around bottom performing funds, but exhibit inferior ability to maintain the record of top performing funds. I find no cross-sectional difference in post-replacement performance between internal and external successors, indicating fund families, in general, make their replacement decisions optimally. I do, however, find that funds that deviate from the optimal decision have subsequent sub-par performance. Overall, the evidence suggests that portfolio managers play a pivotal role in determining mutual fund performance

Managerial multitasking in the mutual fund industry

We examine the determinants and consequences of mutual fund managers simultaneously managing multiple funds. Well-performing managers multitask by taking over poorly performing funds or launching new funds. Subsequent to multitasking, funds run by managers prior to multitasking (i.e., incumbent funds) experience performance deterioration while the performance of the acquired funds improves. Multitasking increases the assets of fund companies but results in a wealth transfer from shareholders of the incumbent funds to those of the funds the managers take over. Multitasking arrangements are terminated when investors recognize the associated agency problem and withdraw their capital from the incumbent funds

Taxonomy-Based Pruning in Generalized Frequent Itemsets Mining

The original purpose of data mining is for analysis of supermarket transaction data. Now with the rapid development in business, industry and science, data mining is used in lots of domains, so mining interesting information from large database becomes more important. Data mining includes two main parts: frequent itemsets mining and association rules mining. And frequent itemsets mining plays an essential role between them. Our thesis is focused on frequent itemsets mining. Previous studies on frequent itemsets mining is at single or multiple concept level, however, mining frequent itemsets at flexible multiple concept level may help finding more specific and useful information from huge data. In this thesis, four methods are introduced for mining frequent itemsets at flexible multiple level by extension of Apriori and Eclat algorithms. We also implement two algorithms for frequent pairs mining. We draw some conclusions about which method is suitable for which distributions of data

A Systematic Review on Different Treatment Methods of Bone Metastasis from Cancers

Background and objective Skeletal metastase is one of the most common complications related to advanced cancer. The aim of this study is to analyze the effectiveness and safety of radiotherapy plus intravenous bisphosphonates versus radiotherapy alone for treating bone metastasis. Methods We searched the Cochrane Library, PubMed, EMBASE, CBM, CNKI and VIP, as well as the reference lists of reports and reviews. The quality of included trials was evaluated by the Cochrane Handbook. Data were extracted and evaluated by two reviewers independently. The Cochrane Collaboration’s Rev-Man 5.0 was used for data analysis. Results Twenty-two trials involving 1 585 patients were included. Compared with radiotherapy alone, radiotherapy plus intravenous bisphosphonates was more effective in total effective rate of pain relive (RR=1.21, 95%CI: 1.13-1.30, P < 0.001), average abated time (WMD=16.00, 95%CI: 10.12-21.88, P < 0.001), and quality of life (RR=1.25, 95%CI: 1.08-1.45, P=0.003, with significant differences. Side effects have no significant differences between the two groups except fever (RR=5.61, 95%CI: 3.11-10.13, P < 0.001). Conclusion Current evidence supports more effective of radiotherapy plus intravenous bisphosphonates for bone metastases. The combine treatment is safe and effective

CrossFusion: Interleaving Cross-modal Complementation for Noise-resistant 3D Object Detection

The combination of LiDAR and camera modalities is proven to be necessary and typical for 3D object detection according to recent studies. Existing fusion strategies tend to overly rely on the LiDAR modal in essence, which exploits the abundant semantics from the camera sensor insufficiently. However, existing methods cannot rely on information from other modalities because the corruption of LiDAR features results in a large domain gap. Following this, we propose CrossFusion, a more robust and noise-resistant scheme that makes full use of the camera and LiDAR features with the designed cross-modal complementation strategy. Extensive experiments we conducted show that our method not only outperforms the state-of-the-art methods under the setting without introducing an extra depth estimation network but also demonstrates our model's noise resistance without re-training for the specific malfunction scenarios by increasing 5.2\% mAP and 2.4\% NDS

Divalent cations activate TRPV1 through promoting conformational change of the extracellular region

Divalent cations Mg and Ba selectively and directly potentiate transient receptor potential vanilloid type 1 heat activation by lowering the activation threshold into the room temperature range. We found that Mg potentiates channel activation only from the extracellular side; on the intracellular side, Mg inhibits channel current. By dividing the extracellularly accessible region of the channel protein into small segments and perturbing the structure of each segment with sequence replacement mutations, we observed that the S1-S2 linker, the S3-S4 linker, and the pore turret are all required for Mg potentiation. Sequence replacements at these regions substantially reduced or eliminated Mg-induced activation at room temperature while sparing capsaicin activation. Heat activation was affected by many, but not all, of these structural alternations. These observations indicate that extracellular linkers and the turret may interact with each other. Site-directed fluorescence resonance energy transfer measurements further revealed that, like heat, Mg also induces structural changes in the pore turret. Interestingly, turret movement induced by Mg precedes channel activation, suggesting that Mg-induced conformational change in the extracellular region most likely serves as the cause of channel activation instead of a coincidental or accommodating structural adjustment

Achieving Energy-Efficient Uplink URLLC with MIMO-Aided Grant-Free Access

The optimal design of the energy-efficient multiple-input multiple-output (MIMO) aided uplink ultra-reliable low-latency communications (URLLC) system is an important but unsolved problem. For such a system, we propose a novel absorbing-Markov-chain-based analysis framework to shed light on the puzzling relationship between the delay and reliability, as well as to quantify the system energy efficiency. We derive the transition probabilities of the absorbing Markov chain considering the Rayleigh fading, the channel estimation error, the zero-forcing multi-user-detection (ZF-MUD), the grant-free access, the ACK-enabled retransmissions within the delay bound and the interactions among these technical ingredients. Then, the delay-constrained reliability and the system energy efficiency are derived based on the absorbing Markov chain formulated. Finally, we study the optimal number of user equipments (UEs) and the optimal number of receiving antennas that maximize the system energy efficiency, while satisfying the reliability and latency requirements of URLLC simultaneously. Simulation results demonstrate the accuracy of our theoretical analysis and the effectiveness of massive MIMO in supporting large-scale URLLC systems.Comment: 14 pages, 9 figures, accepted to appear on IEEE Transactions on Wireless Communications, Aug. 202