11 research outputs found
Three essays in corporate finance
Full text linkThe first essay, the Financial Consequences of Customer Satisfaction: Evidence from Yelp Ratings and SBA Loans, demonstrates the financial and real consequences of customer satisfaction using a novel and comprehensive Yelp dataset. I show that Yelp ratings are significant indicators of business outcomes in a regression discontinuity design setting. A one-half star increase in Yelp ratings leads to a higher probability of receiving SBA loans, better loan terms, and better loan performance. The results are more pronounced when banks have less information about the borrowers. Yelp ratings become less effective when using repeated loan transactions. Lastly, higher Yelp ratings lead to increases in consumer demand and the likelihood of subsequent business opening.
In the second essay, Are Open Market Share Repurchase Programs Really Flexible, I show that open market share repurchase programs are not as flexible as expected, utilizing the financial crisis and predetermined variation in program ending dates. Firms with share repurchase programs ending after December 2007 cut real activities more than otherwise similar firms with programs ending before December 2007. The effects are more pronounced in firms that do not depend on banks, without long-term analyst coverage, without credit ratings, and with no new debt or equity issuance. The freed-up capital indeed goes toward share repurchase programs: firms buyback on average 84% of the predetermined amount of the shares.
The third essay, ''Trading'' Political Favors:Evidence from the Impact of the STOCK Act, demonstrates the tacit benefits that accrue to both politicians and the firms to which they are connected through stock ownership. Specifically, we show strong evidence that politicians use private information and political favors for financial gains from stock investments in their personal portfolios, and that these favors have a real impact on the value and economic outcomes of the firms in which they invest. To do so, we assemble the stock ownership and trading data for all members of the U. S. Congress from 2010 to 2013 and use the passage of the Stop Trading on Congressional Knowledge (STOCK) Act in 2012 as an experiment to examine changes in politicians' trading performance as well as in firm value and outcomes. We find that prior to the STOCK Act, members of the Congress earn significant abnormal returns on their stock trades, and an increase in their holdings of a firm's stock positively predicts the firm's likelihood of being acquired as well as its revenue and earnings surprises. After the passage of the Act, politicians exhibit no such informational advantage in trading or outperformance. On the firms' side, we show that companies with politician ownership on average lose 1.4% in value during the three-day window around the Act's passage, while firms not owned by politicians experience no abnormal returns. Correspondingly, after the Act's passage, these politician-owned firms lose a significant amount of procurement contracts and government grants and become less likely to be selected by the government into high-profile trade missions compared to during the pre-Act period. We find that these mutual benefits are particularly pronounced for politicians who are powerful and firms that are politically active.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-08-01The student, Ruidi Huang, accepted the attached license on 2019-07-01 at 02:17.The student, Ruidi Huang, submitted this Dissertation for approval on 2019-07-01 at 02:22.This Dissertation was approved for publication on 2019-07-02 at 17:15.DSpace SAF Submission Ingestion Package generated from Vireo submission #14114 on 2019-11-26 at 14:00:40Made available in DSpace on 2019-11-26T20:58:35Z (GMT). No. of bitstreams: 3
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High-throughput neuron fluorescence imaging through artificial intelligence
No full textFluorescence image analysis is a commonly used method in biological image processing. In practice, different dyes correspond to different staining structures inside the cell. It is difficult for us to manually analyze and correlate images, as it is a tedious process and image interpretation is subjective from person to person.
Deep learning has proven to be successful in image classification field. In recent years, it has been widely used in the field of biological image analysis. This project will start from the processing of fluorescence image to tuning parameter of designed convolution neural network. The goal of this project is to build a deep learning model to classify different types of neuron cells for biomedical detection.Master of Science (Signal Processing
Air entrainment and free-surface fluctuations in A-type hydraulic jumps with an abrupt drop
No full textIn high dam construction projects in China, stilling basin design with an abrupt bottom drop is sometimes introduced to reduce the bottom velocity and pressure loads by generating A-type hydraulic jumps. Although the stilling basin design is not new, A-type hydraulic jumps have not been studied taking into account the air entrainment and evolution of internal air–water flow structures. This paper presents an experimental study of self-aerated A-type jumps in terms of bubble transport and free-surface fluctuations over the bottom drop. Four Froude numbers from 4.1 to 10.3 are tested for three drop heights, in addition to the flat-bottom case. Compared to the classic hydraulic jumps, A-jumps are observed with longer jump lengths and weaker free-surface fluctuations. The downward deflection of the jet-shear flow and formation of a bottom roller in the step cavity require a modification to the analytical expression of velocity and void fraction distributions. The relationship between the bubble diffusivity and jump spreading rate differs from that in classic hydraulic jumps, suggesting a faster expansion of the bubble diffusion layer than the turbulent shear flow downstream of the drop, especially for large drop heights. At large approach velocities, the reattachment of the deflected jet-shear flow to the lowered bed may cause a local rise in bubble counts downstream the bottom roller. Further increase in drop height results in a W-jump with overwhelming bottom roller over the surface roller and an arced surface jet, which is beyond the scope of this study.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
Does ethical leadership boost nurses’ patient‐oriented organizational citizenship behaviours? A cross‐sectional study
No full textLearning from past bids to participate strategically in day-ahead electricity markets
Full text linkWe consider the process of bidding by electricity suppliers in a day-ahead market context, where each supplier bids a linear non-decreasing function of her generating capacity with the goal of maximizing her individual profit given other competing suppliers' bids. Based on the submitted bids, the market operator schedules suppliers to meet demand during each hour and determines hourly market clearing prices. Eventually, this game-theoretic process reaches a Nash equilibrium when no supplier is motivated to modify her bid. However, solving the individual profit maximization problem requires information of rivals' bids, which are typically not available. To address this issue, we develop an inverse optimization approach for estimating rivals' production cost functions given historical market clearing prices and production levels. We then use these functions to bid strategically and compute Nash equilibrium bids. We present numerical experiments illustrating our methodology, showing good agreement between bids based on the estimated production cost functions with the bids based on the true cost functions. We discuss an extension of our approach that takes into account network congestion resulting in location-dependent pricesFirst author draf
AutoBench: Automatic Testbench Generation and Evaluation Using LLMs for HDL Design
Full text linkIn digital circuit design, testbenches constitute the cornerstone of simulation-based hardware verification. Traditional methodologies for testbench generation during simulation-based hardware verification still remain partially manual, resulting in inefficiencies in testing various scenarios and requiring expensive time from designers. Large Language Models (LLMs) have demonstrated their potential in automating the circuit design flow. However, directly applying LLMs to generate testbenches suffers from a low pass rate. To address this challenge, we introduce AutoBench, the first LLM-based testbench generator for digital circuit design, which requires only the description of the design under test (DUT) to automatically generate comprehensive testbenches. In AutoBench, a hybrid testbench structure and a self-checking system are realized using LLMs. To validate the generated testbenches, we also introduce an automated testbench evaluation framework to evaluate the quality of generated testbenches from multiple perspectives. Experimental results demonstrate that AutoBench achieves a 57% improvement in the testbench pass@1 ratio compared with the baseline that directly generates testbenches using LLMs. For 75 sequential circuits, AutoBench successfully has a 3.36 times testbench pass@1 ratio compared with the baseline. The source codes and experimental results are open-sourced at this link: https://github.com/AutoBench/AutoBenc
OplixNet: Towards Area-Efficient Optical Split-Complex Networks with Real-to-Complex Data Assignment and Knowledge Distillation
Full text linkHaving the potential for high speed, high throughput, and low energy cost,
optical neural networks (ONNs) have emerged as a promising candidate for
accelerating deep learning tasks. In conventional ONNs, light amplitudes are
modulated at the input and detected at the output. However, the light phases
are still ignored in conventional structures, although they can also carry
information for computing. To address this issue, in this paper, we propose a
framework called OplixNet to compress the areas of ONNs by modulating input
image data into the amplitudes and phase parts of light signals. The input and
output parts of the ONNs are redesigned to make full use of both amplitude and
phase information. Moreover, mutual learning across different ONN structures is
introduced to maintain the accuracy. Experimental results demonstrate that the
proposed framework significantly reduces the areas of ONNs with the accuracy
within an acceptable range. For instance, 75.03% area is reduced with a 0.33%
accuracy decrease on fully connected neural network (FCNN) and 74.88% area is
reduced with a 2.38% accuracy decrease on ResNet-32.Comment: Accepted by Design Automation and Test in Europe (DATE) 202
The impact of altered dietary adenine concentrations on the gut microbiota in Drosophila
Full text linkThe gut microbiota influences host metabolism and health, impacting diseases. Research into how diet affects gut microbiome dynamics in model organisms is crucial but underexplored. Herein, we examined how dietary adenine affects uric acid levels and the gut microbiota over five generations of Drosophila melanogaster. Wild-type W1118 flies consumed diets with various adenine concentrations (GC: 0%, GL: 0.05%, and GH: 0.10%), and their gut microbiota were assessed via Illumina MiSeq sequencing. Adenine intake significantly increased uric acid levels in the GH group > the GC group. Despite no significant differences in the alpha diversity indices, there were significant disparities in the gut microbiota health index (GMHI) and dysbiosis index (MDI) among the groups. Adenine concentrations significantly altered the diversity and composition of the gut microbiota. High adenine intake correlated with increased uric acid levels and microbial population shifts, notably affecting the abundances of Proteobacteria and Firmicutes. The gut microbiota phenotypes included mobile elements, gram-positive bacteria, biofilm-forming bacteria, and gram-negative bacteria. The significantly enriched KEGG pathways included ageing, carbohydrate metabolism, and the immune system. In conclusion, adenine intake increases uric acid levels, alters gut microbiota, and affects KEGG pathways in Drosophila across generations. This study highlights the impact of dietary adenine on uric acid levels and the gut microbiota, providing insights into intergenerational nutritional effects
Review on laser directed energy deposited aluminum alloys
No full textLightweight aluminum (Al) alloys have been widely used in frontier fields like aerospace and automotive industries, which attracts great interest in additive manufacturing (AM) to process high-value Al parts. As a mainstream AM technique, laser-directed energy deposition (LDED) shows good scalability to meet the requirements for large-format component manufacturing and repair. However, LDED Al alloys are highly challenging due to their inherent poor printability (e.g. low laser absorption, high oxidation sensitivity and cracking tendency). To further promote the development of LDED high-performance Al alloys, this review offers a deep understanding of the challenges and strategies to improve printability in LDED Al alloys. The porosity, cracking, distortion, inclusions, element evaporation and resultant inferior mechanical properties (worse than laser powder bed fusion) are the key challenges in LDED Al alloys. Processing parameter optimizations, in-situ alloy design, reinforcing particle addition and field assistance are the efficient approaches to improving the printability and performance of LDED Al alloys. The underlying correlations between processes, alloy innovation, characteristic microstructures, and achievable performances in LDED Al alloys are discussed. The benchmark mechanical properties and primary strengthening mechanism of LDED Al alloys are summarized. This review aims to provide a critical and in-depth evaluation of current progress in LDED Al alloys. Future opportunities and perspectives in LDED high-performance Al alloys are also outlined
Dan bu zi you neng ji suan yu Gaosi jia su fen zi dong li xue de kai fa yu ying yong ji xi bao mo yu na mi zuan shi de xiang hu zuo yong zhi lian xu jian mo
No full textM.Phil.In the thesis, a single-step free energy calculation and an enhanced sampling method, namely VSS and GaMD, are discussed. Additionally, I discuss the ability of prickly nanodiamond inducing pores on membrane investigated by continuum modelling calculation.Gaussian accelerated molecular dynamics (GaMD) is an enhanced sampling technique that improves conformational sampling without the need to predefine a set of collective variables. Accurate free energy reweighting is guaranteed by the harmonic boost potential which is built automatically from the probability distribution statistics of the system potential. We have implemented GaMD in NAMD, a popular scalable molecular dynamics simulation software, and validated the method on three model systems: alanine dipeptide, the chignolin fast-folding protein and the M3 muscarinic G protein-coupled receptor (GPCR). The reweighted free energy profiles agree well with results from traditional long-timescale molecular dynamics.Virtual Substitution Scan (VSS) toolkit is a VMD plugin which reuses plain MD simulation trajectories to perform single-step free energy perturbation (sFEP) calculations. sFEP is a promising method to calculate the binding free energy change when a ligand is alchemically transformed into one with moderate difference. We have shown that, with a carefully chosen scheme, sFEP can produce reasonably accurate result compared with multi-step FEP (mFEP) calculations. However, an unexpected error was found when using sFEP to compute the free energy change of transforming a benzene into an anisole or a methylaniline. We show that such exception arose from insufficient bond angle sampling. To tackle the problem, we update our VSS toolkit to sample different bond angles and improved the performance.Creating a chemically inert nanocarrier to send macromolecules into the cell interior is an important topic in drug and biolabel delivery. An efficient nanocarrier not only should deliver macromolecules into the cell by endocytosis, but also escape from the endosome to release the macromolecules into cytosol from vesicles. Recent experimental study reports that prickly nanodiamonds could rupture the endosomal membrane much better than rounded nanoparticles(NPs), making it a nice candidate for drug delivery. We built a model to explain the phenomenon by energetic considerations and quantify the criteria for which a NP can induce a pore in membranes. Using the model, we evaluated the most probable pore states and wrapping states for NPs of different size, sharpness, and adhesion strength. The effect on how each property of the NP affects its chance to pierce a pore is discussed in detail.在此論文中，我們將討論兩個由我們研發的程式插件：一為增強取樣方法GaMD，二為單步自由能計算VSS。其後，我們將討論如何使用連續模型能量計算，來探究尖銳的納米粒子刺穿細胞膜的能力。Gaussian accelerated molecular dynamics(GaMD)是一種增強取樣的技術，它不需要使用者預先定義一組集體變量，就可以改進構象取樣。程式會自動收集系統勢能的概率分佈，自動構建出一個符合諧波分佈的提升勢能，由此保證自由能權重調整的精確性。我們在NAMD（一種流行的分子動力模擬並行軟件）中實施了GaMD，並利用了三個具代表性的系統來驗證這個方法，分別為：丙氨酸二肽、快速折疊蛋白chignolin和M3毒蕈鹼G蛋白偶聯受體(GPCR)。其自由能經過重新加權後，與傳統的長時間分子動力學(MD)模擬結果吻合。Virtual Substitution Scan(VSS)工具包是一個VMD插件，它可以重用一般的MD模擬軌跡來執行單步自由能微擾(sFEP)計算。sFEP常用於計算配體煉金術式轉化時所需的自由能差，當轉變不太大的時候，它是一種有效的自由能差計算方法。我們早前已證明瞭，只要小心選擇計算方法，sFEP亦可達至多步自由能微擾(mFEP)的精準度。然而，當計算苯轉化為苯甲醚或甲基苯胺的自由能差時，sFEP出現了意料之外的誤差。我們發現，這異常狀況是源於對鍵角的取樣不足。為瞭解決這個問題，我們更新了我們的VSS工具包，讓其可以對不同鍵角進行取樣，從而改善了它的準確性。如何建造化學惰性的納米載體運送大分子進入細胞內部，是藥物傳遞和生物標籤傳遞的重要課題。有效的納米載體不僅要協助大分子通過胞吞作用進入細胞，還要破壞內體膜，使大分子能逃出囊泡，到達細胞溶質。最近有實驗研究指出，尖銳的納米鑽石可以刺破囊泡膜，有望能發展成新的藥物遞送載體，而其表現與圓潤的納米粒子(NP)產生明顯對比。為瞭解釋有關現象，我們構建了一個模型，通過能量計算來量化刺穿薄膜的標準。我們會比較不同尺寸、銳度和粘附強度的NP，計算出每個NP自由能最低的包裹狀態以及破孔大小。另外，我們亦會詳細討論如果NP的不同物理性質改變時，將如何影響其刺穿薄膜的能力。Pang, Yui Tik = 單步自由能計算與高斯加速分子動力學的開發與應用及細胞膜與納米鑽石的相互作用之連續建模 / 彭睿迪.Thesis M.Phil. Chinese University of Hong Kong 2017.Includes bibliographical references (leaves 60-68).Abstracts also in Chinese.Title from PDF title page (viewed on 10, February, 2020).Pang, Yui Tik = Dan bu zi you neng ji suan yu Gaosi jia su fen zi dong li xue de kai fa yu ying yong ji xi bao mo yu na mi zuan shi de xiang hu zuo yong zhi lian xu jian mo / Peng Ruidi
