Incentive Contracting versus Ownership Reforms: Evidence from China's Township and Village Enterprises

We use a unique data set to study the implications of introducing managerial incentives and, in addition to incentives, better defined ownership for a firm's financial performance. The data set traces the ten-year history of 80 Chinese rural enterprises, known as township and village enterprises. During this period, these originally (mostly) community owned, local government controlled socialist collective firms were first allowed to introduce managerial incentive contracts and then to change to ownership forms of more clearly defined income and control rights. The study finds that introducing managerial incentives had a positive but statistically insignificant effect on these firms' performance measured by accounting return on assets or return on equity. It also finds that the performance is significantly better under ownership forms of better-defined rights than under community ownership even when the latter is supplemented with managerial incentive contracts. The findings shed lights on some important theoretical and policy issues.http://deepblue.lib.umich.edu/bitstream/2027.42/39749/3/wp365.pd

A Framework for Specifying and Monitoring User Tasks

Knowledge about user task execution can help systems better reason about when to interrupt users. To enable recognition and forecasting of task execution, we develop a novel framework for specifying and monitoring user task sequences. For task specification, our framework provides an XML-based language with tags inspired by regular expressions. For task monitoring, our framework provides an event handler that manages events from any instrumented application and a monitor that observes a user's transitions within and among specified tasks. The monitor supports multiple active tasks and multiple instances of the same task. The use of our framework will enable systems to consider a user's position within a task model when reasoning about when to interrupt

Reconstruction of Gravitational Lensing Using WMAP 7-Year Data

Gravitational lensing by large scale structure introduces non-Gaussianity into the Cosmic Microwave Background and imprints a new observable, which can be used as a cosmological probe. We apply a four-point estimator to the Wilkinson Microwave Anisotropy Probe (WMAP) 7-year coadded temperature maps alone to reconstruct the gravitational lensing signal. The Gaussian bias is simulated and subtracted, and the higher order bias is investigated. We measure a gravitational lensing signal with a statistical amplitude of $\mathcal {C}$ = $1.27\pm 0.98$ using all the correlations of the W- and V-band Differencing Assemblies (DAs). We therefore conclude that WMAP 7-year data alone, can not detect lensing.Comment: 10 pages, 10 figure

Sherlock: Scalable Fact Learning in Images

We study scalable and uniform understanding of facts in images. Existing visual recognition systems are typically modeled differently for each fact type such as objects, actions, and interactions. We propose a setting where all these facts can be modeled simultaneously with a capacity to understand unbounded number of facts in a structured way. The training data comes as structured facts in images, including (1) objects (e.g., $$), (2) attributes (e.g.,$$), (3) actions (e.g., $$), and (4) interactions (e.g.,$$). Each fact has a semantic language view (e.g., $$) and a visual view (an image with this fact). We show that learning visual facts in a structured way enables not only a uniform but also generalizable visual understanding. We propose and investigate recent and strong approaches from the multiview learning literature and also introduce two learning representation models as potential baselines. We applied the investigated methods on several datasets that we augmented with structured facts and a large scale dataset of more than 202,000 facts and 814,000 images. Our experiments show the advantage of relating facts by the structure by the proposed models compared to the designed baselines on bidirectional fact retrieval.Comment: Jan 7 Updat

Incentive Contracting versus Ownership Reforms: Evidence from China's Township and Village Enterprises

We use a unique data set to study the implications of introducing managerial incentives and, in addition to incentives, better defined ownership for a firm's financial performance. The data set traces the ten-year history of 80 Chinese rural enterprises, known as township and village enterprises. During this period, these originally (mostly) community owned, local government controlled socialist collective firms were first allowed to introduce managerial incentive contracts and then to change to ownership forms of more clearly defined income and control rights. The study finds that introducing managerial incentives had a positive but statistically insignificant effect on these firms' performance measured by accounting return on assets or return on equity. It also finds that the performance is significantly better under ownership forms of better-defined rights than under community ownership even when the latter is supplemented with managerial incentive contracts. The findings shed lights on some important theoretical and policy issues. Classification-JEL:

Developing Security for E-Commerce Applications: A Teaching Case

The number of severe computer security breaches in e-commerce applications has been on the increase over the last few years. This has become one of the biggest security problems in recent years. Although there are tools to build e-commerce application firewalls to alert and prevent intruder attacks, these tools are not trivial to install (they are not plug-and-play). Internet intruders can create havoc and produce catastrophe results by exploiting weaknesses in e- commerce applications. Therefore, developers of e-commerce web sites have to incorporate ways to systematically identify and eliminate vulnerabilities in the EC applications to enhance their security. This paper describes how Microsoft ASP.Net can be used to assist students in exploring ways to increase the security of EC applications

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.This work was supported by the National Institutes of Health, R01GM103502-05 to CD, ZH and DS. Partial support was also provided by grants from the Office of Science (BER), U.S. Department of Energy (DE-SC0004962), the Joslin Diabetes Center (Pilot & Feasibility grant P30 DK036836), the Army Research Office under MURI award W911NF-12-1-0390, National Institutes of Health (1RC2GM092602-01, R01GM089978 and 5R01DE024468), NSF (1457695), and Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS), Purchase Request No. HR0011515303, Program Code: TRS-0 Issued by DARPA/CMO under Contract No. HR0011-15-C-0091. Funding for open access charge: National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. (R01GM103502-05 - National Institutes of Health; 1RC2GM092602-01 - National Institutes of Health; R01GM089978 - National Institutes of Health; 5R01DE024468 - National Institutes of Health; DE-SC0004962 - Office of Science (BER), U.S. Department of Energy; P30 DK036836 - Joslin Diabetes Center; W911NF-12-1-0390 - Army Research Office under MURI; 1457695 - NSF; HR0011515303 - Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS); HR0011-15-C-0091 - DARPA/CMO; National Institutes of Health)Published versio