The huge size of online social networks (OSNs) makes it prohibitively expensive to precisely measure any properties which require the knowledge of the entire graph. To estimate the size of an OSN, i.e., the number of users an OSN has, this paper introduces two estimators using widely available OSN functionalities/services. The first estimator is a maximum likelihood estimator (MLE) based on uniform sampling. An O(logn) algorithm is developed to solve the estimator, which is 70 times faster than the naive linear probing algorithm in our experiments. The second estimator is based on random walkers and we generalize it to estimate other graph properties. In-depth evaluations are conducted on six real OSNs to show the bias and variance of these two estimators. Our analysis addresses the challenges and pitfalls when developing and implementing such estimators for OSNs.

Extensive research has been conducted on top of online social networks (OSNs), while little attention has been paid to the data collection process. Due to the large scale of OSNs and their privacy control policies, a partial data set is often used for analysis. The data set analyzed is decided by many factors including the choice of seeds, node selection algorithms, and the sample size. These factors may introduce biases and further contaminate or even skew the results. To evaluate the impact of different factors, this paper examines the OSN graph crawling problem, where the nodes are OSN users and the edges are the links (or relationship) among these users. More specifically, by looking at various factors in the crawling process, the following problems are addressed in this paper:* Efficiency: How fast different crawlers discover nodes/links;* Sensitivity: How different OSNs and the number of protected users affect crawlers;* Bias: How major graph properties are skewed.To the best of our knowledge, our simulations on four real world online social graphs provide the first in-depth empirical answers to these questions.

Intravenous (iv) injection of secretin activates neurons in brain areas controlling autonomic function and emotion. Peripheral administration of secretin inhibits gastric functions through a central mechanism that is mediated by vagal dependant pathways. We investigated whether the vagus nerve is involved in intraperitoneal (ip) injection of secretin-induced brain neuronal activation in conscious rats as monitored by Fos immunohistochemistry. Secretin (40 or 100 microgram/kg, ip, -90 min) induced a linear dose-related increase in the number of Fos positive neurons in the central nucleus of the amygdala (CeA), and a plateau Fos response in the area postrema (AP), nucleus tractus solitarii (NTS), locus coeruleus (LC), Barrington's nucleus (Bar), external lateral subnucleus of parabrachial nucleus (PBel) and arcuate nucleus (Arc), and at the highest dose, in the dorsal motor nucleus of the vagus (DMV) compared with ip injection of vehicle. Double immunohistochemistry in the NTS showed that a substantial number of neurons activated by secretin (40 microgram/kg, ip) are tyrosine hydroxylase positive. Subdiaphragmatic vagotomy (-7 days) abolished Fos expression-induced by ip secretin (40 microgram/kg) in the NTS, DMV, LC, Bar, PBel and CeA, while a significant rise in the AP was maintained. In contrast, capsaicin (-10 days) did not influence the Fos induction in the above nuclei. Quantitative real-time polymerase chain reaction (PCR) and reverse transcription PCR showed that secretin receptor mRNA is expressed in the nodose ganglia and levels were higher in the right compared to the left ganglion. These results indicate that peripheral secretin activates catecholaminergic NTS neurons as well as neurons in pontine and limbic nuclei regulating autonomic functions and emotion through vagal dependent capsaicin resistant pathways. Secretin injected ip may signal to the brain by interacting with secretin receptors on vagal afferent as well as on AP neurons outside the blood brain barrier.

To protect user privacy in the search engine context, most current approaches, such as private information retrieval and privacy preserving data mining, require a server-side deployment, thus users have little control over their data and privacy. In this paper we propose a user-side solution within the context of keyword based search. We model the search privacy threat as an information inference problem and show how to inject noise into user queries to minimize privacy breaches. The search privacy breach is measured as the mutual information between real user queries and the diluted queries seen by search engines. We give the lower bound for the amount of noise queries required by a perfect privacy protection and provide the optimal protection given the number of noise queries. We verify our results with a special case where the number of noise queries is equal to the number of user queries. The simulation result shows that the noise given by our approach greatly reduces privacy breaches and outperforms random noise. As far as we know, this work presents the first theoretical analysis on user side noise injection for search privacy protection.

A partial equilibrium model of stochastic crop production is used to analyze the environmental impacts of popular subsidized crop insurance programs. Land use is unchanged only when an actuarially fair, perfectly separating insurance contract is offered. For the more typical pooling equilibrium contracts, however, land with a minimum quality that is stricly lower than the minimum quality without insurance will be added to production. In such cases, the environment will be adversely effected. If economically marginal land is also environmentally marginal, pooling crop insurance policies disproportionately contribute to the degradation of the environment. Popular subsidies merely exacerbate the problem.

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A new long-wavelength vertical-cavity surface-emitting laser structure is described that utilizes AlGaAs-GaAs mirrors bonded to AlInGaAs-InP quantum wells with an intracavity buried tunnel junction. This structure offers complete wavelength flexibility in the 1250-1650 nm fiber communication bands and reduces the high free-carrier losses and bonded junction voltage drops in previous devices. The intracavity contacts electrically bypass the bonded junctions to reduce threshold voltage. N-type current spreading layers and undoped AlGaAs mirrors minimize optical losses. This has enabled 134 degreesC maximum continuous-wave lasing temperature, 2-mW room-temperature continuous-wave single-mode power, and 1-mW single-mode power at 80 degreesC, in various devices in the 1310-1340 nm wavelength range.