Extracellular Vesicles: Messengers of p53 in Tumor–Stroma Communication and Cancer Metastasis

Tumor progression to a metastatic and ultimately lethal stage relies on a tumor-supporting microenvironment that is generated by reciprocal communication between tumor and stromal host cells. The tumor–stroma crosstalk is instructed by the genetic alterations of the tumor cells—the most frequent being mutations in the gene Tumor protein p53 (TP53) that are clinically correlated with metastasis, drug resistance and poor patient survival. The crucial mediators of tumor–stroma communication are tumor-derived extracellular vesicles (EVs), in particular exosomes, which operate both locally within the primary tumor and in distant organs, at pre-metastatic niches as the future sites of metastasis. Here, we review how wild-type and mutant p53 proteins control the secretion, size, and especially the RNA and protein cargo of tumor-derived EVs. We highlight how EVs extend the cell-autonomous tumor suppressive activity of wild-type p53 into the tumor microenvironment (TME), and how mutant p53 proteins switch EVs into oncogenic messengers that reprogram tumor–host communication within the entire organism so as to promote metastatic tumor cell dissemination.     

Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans

A mobile robot exploring an unknown environment has no absolute frame of reference for its position, other than features it detects through its sensors. Using distinguishable landmarks is one possible approach, but it requires solving the object recognition problem. In particular, when the robot uses two-dimensional laser range scans for localization, it is difficult to accurately detect and localize landmarks in the environment (such as corners and occlusions) from the range scans.In this paper, we develop two new iterative algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment, that avoid the above problems. The first algorithm is based on matching data points with tangent directions in two scans and minimizing a distance function in order to solve the displacement between the scans. The second algorithm establishes correspondences between points in the two scans and then solves the point-to-point least-squares problem to compute the relative pose of the two scans. Our methods work in curved environments and can handle partial occlusions by rejecting outliers.     

Minimizing information disclosure to third parties in social login platforms

Over the past few years, a large and ever increasing number of Web sites have incorporated one or more social login platforms and have encouraged users to log in with their Facebook, Twitter, Google, or other social networking identities. Research results suggest that more than two million Web sites have already adopted Facebook’s social login platform, and the number is increasing sharply. Although one might theoretically refrain from such social login features and cross-site interactions, usage statistics show that more than 250 million people might not fully realize the privacy implications of opting-in. To make matters worse, certain Web sites do not offer even the minimum of their functionality unless users meet their demands for information and social interaction. At the same time, in a large number of cases, it is unclear why these sites require all that personal information for their purposes. In this paper, we mitigate this problem by designing and developing a framework for minimum information disclosure in social login interactions with third-party sites. Our example case is Facebook, which combines a very popular single sign-on platform with information-rich social networking profiles. Whenever users want to browse to a Web site that requires authentication or social interaction using a Facebook identity, our system employs, by default, a Facebook session that reveals the minimum amount of information necessary. Users have the option to explicitly elevate that Facebook session in a manner that reveals more or all of the information tied to their social identity. This enables users to disclose the minimum possible amount of personal information during their browsing experience on third-party Web sites.     

Distributed computing on oriented anonymous hypercubes with faulty components

We give efficient algorithms for distributed computation on oriented, anonymous, asynchronous hypercubes with possible faulty components (i.e. processors and links) and deterministic processors. Initially, the processors know only the size of the network and that they are inter-connected in a hypercube topology. Faults may occur only before the start of the computation (and that despite this the hypercube remains a connected network). However, the processors do not know where these faults are located. As a measure of complexity we use the total number of bits transmitted during the execution of the algorithm and we concentrate on giving algorithms that will minimize this number of bits. The main result of this paper is an algorithm for computing Boolean functions on anonymous hypercubes with bit cost , where is the number of faulty components (i.e. links plus processors), is the number of links which are either faulty, or non-faulty but adjacent to faulty processors, and is the diameter of the hypercube with faulty components. Received: October 1992 / Accepted: April 2001     

Public-Private Partnerships in the Water Sector

Abstract

Types of partnerships between public and private companies in water and sewage services are evaluated on the basis of the economic efficiency of the scheme for each partner. Modeling of public-private partnerships involves the formulation of a contract prototype, which determines the roles, functions, and responsibilities as well as the allocation of costs and revenues for each partner. Alternative water management scenarios are used to identify the investments required for meeting the projected demand for water and sewage services. Investment and operational costs as well as revenues from water and sewage services are estimated according to the allocation defined in the contract prototype. The economic efficiency of the scheme is assessed through a cost benefit analysis for each partner. The evaluation of different water management scenarios indicates that, for the Cyclades Islands, Greece, there is a substantial water market where several forms of partnerships could be attractive for both the public and the private sectors. Such partnerships include, among others, lease purchase, temporary privatization, built operate transfer (BOT), and built own operate transfer (BOOT). These forms of public-private partnerships could also be successful in similar regions where significant improvements and expansion of the infrastructure is required while access to the required funds and expertise is restricted for small public water companies.     

Improving the performance of passive network monitoring applications with memory locality enhancements

Passive network monitoring is the basis for a multitude of systems that support the robust, efficient, and secure operation of modern computer networks. Emerging network monitoring applications are more demanding in terms of memory and CPU resources due to the increasingly complex analysis operations that are performed on the inspected traffic. At the same time, as the traffic throughput in modern network links increases, the CPU time that can be devoted for processing each network packet decreases. This leads to a growing demand for more efficient passive network monitoring systems in which runtime performance becomes a critical issue.In this paper we present locality buffering, a novel approach for improving the runtime performance of a large class of CPU and memory intensive passive monitoring applications, such as intrusion detection systems, traffic characterization applications, and NetFlow export probes. Using locality buffering, captured packets are being reordered by clustering packets with the same port number before they are delivered to the monitoring application. This results in improved code and data locality, and consequently, in an overall increase in the packet processing throughput and decrease in the packet loss rate. We have implemented locality buffering within the widely used libpcap packet capturing library, which allows existing monitoring applications to transparently benefit from the reordered packet stream without modifications. Our experimental evaluation shows that locality buffering improves significantly the performance of popular applications, such as the Snort IDS, which exhibits a 21% increase in the packet processing throughput and is able to handle 67% higher traffic rates without dropping any packets.     

Stability of the spectral responsivity of cryogenically cooled InSb infrared detectors

The spectral responsivity of two cryogenically cooled InSb detectors was observed to drift slowly with time. The origin of these drifts was investigated and was shown to occur due to a water-ice thin film that was deposited onto the active areas of the cold detectors. The presence of the ice film (which is itself a dielectric film) modifies the transmission characteristics of the antireflection coatings deposited on the active areas of the detectors, thus giving rise to the observed drifts. The magnitude of the drifts was drastically reduced by evacuating the detector dewars while baking them at 50 degrees C for approximately 48 h. All InSb detectors have antireflection coatings to reduce the Fresnel reflections and therefore enhance their spectral responsivity. This work demonstrates that InSb infrared detectors should be evacuated and baked at least annually and in some cases (depending on the quality of the dewar and the measurement uncertainty required) more frequently. These observations are particularly relevant to InSb detectors mounted in dewars that use rubber O rings since the ingress of moisture was found to be particularly serious in this type of dewar.     

Distributed algorithms for barrier coverage using relocatable sensors

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within \(\varTheta (n^2)\) steps with the barrier fully covered, while the constant-memory algorithm is shown to take \(\varTheta (n)\) steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires \(\varOmega (n)\) steps on some inputs, our second algorithm is asymptotically optimal.