Neurogenic Inflammation of Guinea-Pig Bladder

Capsaicin, substance P, and ovalbumin, instilled into the bladders of naive and ovalbumin (OVA) sensitized guineapigs caused inflammation, as indicated by increased vascular permeability. Histological changes after exposure to these compounds progressed with time from intense vasodilatation to marginalization of granulocytes followed by interstitial migration of leukocytes. In vitro incubation of guinea-pig bladder tissue with substance P and ovalbumin stimulated release of prostaglandin D2 and leukotrienes. In vitro incubation of bladder tissue with capsaicin, OVA, prostaglandin D2, leukotriene C4, histamine, or calcium ionophore A-23587 all stimulated substance P release. These data suggest that bladder inflammation initiated by a variety of stimuli could lead to a cyclic pattern of release of inflammatory mediators and neuropeptides, which could result in amplification and persistence of cystitis after the inciting cause has subsided

Size versus truthfulness in the house allocation problem

We study the House Allocation problem (also known as the Assignment problem), i.e., the problem of allocating a set of objects among a set of agents, where each agent has ordinal preferences (possibly involving ties) over a subset of the objects. We focus on truthful mechanisms without monetary transfers for finding large Pareto optimal matchings. It is straightforward to show that no deterministic truthful mechanism can approximate a maximum cardinality Pareto optimal matching with ratio better than 2. We thus consider randomized mechanisms. We give a natural and explicit extension of the classical Random Serial Dictatorship Mechanism (RSDM) specifically for the House Allocation problem where preference lists can include ties. We thus obtain a universally truthful randomized mechanism for finding a Pareto optimal matching and show that it achieves an approximation ratio of eovere-1. The same bound holds even when agents have priorities (weights) and our goal is to find a maximum weight (as opposed to maximum cardinality) Pareto optimal matching. On the other hand we give a lower bound of 18 over 13 on the approximation ratio of any universally truthful Pareto optimal mechanism in settings with strict preferences. In the case that the mechanism must additionally be non-bossy, an improved lower bound of eovere-1 holds. This lower bound is tight given that RSDM for strict preference lists is non-bossy. We moreover interpret our problem in terms of the classical secretary problem and prove that our mechanism provides the best randomized strategy of the administrator who interviews the applicants

Online Assortment Optimization for Two-sided Matching Platforms

Motivated by online labor markets, we consider the online assortment optimization problem faced by a two-sided matching platform that hosts a set of suppliers waiting to match with a customer. Arriving customers are shown an assortment of suppliers, and may choose to issue a match request to one of them. After spending some time on the platform, each supplier reviews all the match requests she has received and, based on her preferences, she chooses whether to match with a customer or to leave unmatched. We study how platforms should design online assortment algorithms to maximize the expected number of matches in such two-sided settings. We establish that a simple greedy algorithm is 1/2-competitive against an optimal clairvoyant algorithm that knows in advance the full sequence of customers’ arrivals. However, unlike related online assortment problems, no randomized algorithm can achieve a better competitive ratio, even in asymptotic regimes. To advance beyond this general impossibility, we consider structured settings where suppliers’ preferences are described by the Multinomial Logit and Nested Logit choice models. We develop new forms of balancing algorithms, which we call preference-aware, that leverage structural information about suppliers’ choice models to design the associated discount function. In certain settings, these algorithms attain competitive ratios provably larger than the standard “barrier” of 1 − 1/e in the adversarial arrival model. Our results suggest that the shape and timing of suppliers’ choices play critical roles in designing online assortment algorithms for two-sided matching platforms

Experimental Analysis of IoT Networks Based on LoRa/LoRaWAN under Indoor and Outdoor EnvirMedusonments: Performance and Limitations

Nowadays, Internet of Things (IoT) has multiple applications in different fields. This concept allows physical devices to connect to the internet in order to establish a strong infrastructure that facilitates many device control and monitoring tasks. Low Power Wide Area (LPWA) communication protocols become widely used for IoT networks because of their low power consumption and the broad range communication. LPWA enables devices to transmit small amounts of data in a long distance. Among LPWA protocols, LoRa technology gained a lot of interest recently from the research community and many companies. LoRa is a long range and low power wireless communication technology regulated by the LoRaWAN standard. It can be o good candidate to deploy node network where long distance and extended battery life is required. A LoRaWAN architecture is deployed in a star-of-stars topology and based on a systematic evaluation of a long-term operation of the network monitoring. This works describes experimental results of testing LoRa in indoor and outdoor environments to understand how it works, evaluate its performance, and limitations. As expected, results show that LoRa performs better outdoor. It is also interesting to note that elevating the gateway in order to have a free line of sight with the IoT node, or close to it, increases the signal quality received by the end-node devices, and consequently, longer distances can be achieved

Cake Cutting Algorithms for Piecewise Constant and Piecewise Uniform Valuations

Cake cutting is one of the most fundamental settings in fair division and mechanism design without money. In this paper, we consider different levels of three fundamental goals in cake cutting: fairness, Pareto optimality, and strategyproofness. In particular, we present robust versions of envy-freeness and proportionality that are not only stronger than their standard counter-parts but also have less information requirements. We then focus on cake cutting with piecewise constant valuations and present three desirable algorithms: CCEA (Controlled Cake Eating Algorithm), MEA (Market Equilibrium Algorithm) and CSD (Constrained Serial Dictatorship). CCEA is polynomial-time, robust envy-free, and non-wasteful. It relies on parametric network flows and recent generalizations of the probabilistic serial algorithm. For the subdomain of piecewise uniform valuations, we show that it is also group-strategyproof. Then, we show that there exists an algorithm (MEA) that is polynomial-time, envy-free, proportional, and Pareto optimal. MEA is based on computing a market-based equilibrium via a convex program and relies on the results of Reijnierse and Potters [24] and Devanur et al. [15]. Moreover, we show that MEA and CCEA are equivalent to mechanism 1 of Chen et. al. [12] for piecewise uniform valuations. We then present an algorithm CSD and a way to implement it via randomization that satisfies strategyproofness in expectation, robust proportionality, and unanimity for piecewise constant valuations. For the case of two agents, it is robust envy-free, robust proportional, strategyproof, and polynomial-time. Many of our results extend to more general settings in cake cutting that allow for variable claims and initial endowments. We also show a few impossibility results to complement our algorithms.Comment: 39 page

Pareto Optimal Matchings in Many-to-Many Markets with Ties

We consider Pareto-optimal matchings (POMs) in a many-to-many market of applicants and courses where applicants have preferences, which may include ties, over individual courses and lexicographic preferences over sets of courses. Since this is the most general setting examined so far in the literature, our work unifies and generalizes several known results. Specifically, we characterize POMs and introduce the \emph{Generalized Serial Dictatorship Mechanism with Ties (GSDT)} that effectively handles ties via properties of network flows. We show that GSDT can generate all POMs using different priority orderings over the applicants, but it satisfies truthfulness only for certain such orderings. This shortcoming is not specific to our mechanism; we show that any mechanism generating all POMs in our setting is prone to strategic manipulation. This is in contrast to the one-to-one case (with or without ties), for which truthful mechanisms generating all POMs do exist

Systems biology approach for mapping the response of human urothelial cells to infection by Enterococcus faecalis

<p>Abstract</p> <p>Background</p> <p>To better understand the response of urinary epithelial (urothelial) cells to <it>Enterococcus faecalis</it>, a uropathogen that exhibits resistance to multiple antibiotics, a genome-wide scan of gene expression was obtained as a time series from urothelial cells growing as a layered 3-dimensional culture similar to normal urothelium. We herein describe a novel means of analysis that is based on deconvolution of gene variability into technical and biological components.</p> <p>Results</p> <p>Analysis of the expression of 21,521 genes from 30 minutes to 10 hours post infection, showed 9553 genes were expressed 3 standard deviations (SD) above the system zero-point noise in at least 1 time point. The asymmetric distribution of relative variances of the expressed genes was deconvoluted into technical variation (with a 6.5% relative SD) and biological variation components (>3 SD above the mode technical variability). These 1409 hypervariable (HV) genes encapsulated the effect of infection on gene expression. Pathway analysis of the HV genes revealed an orchestrated response to infection in which early events included initiation of immune response, cytoskeletal rearrangement and cell signaling followed at the end by apoptosis and shutting down cell metabolism. The number of poorly annotated genes in the earliest time points suggests heretofore unknown processes likely also are involved.</p> <p>Conclusion</p> <p><it>Enterococcus </it>infection produced an orchestrated response by the host cells involving several pathways and transcription factors that potentially drive these pathways. The early time points potentially identify novel targets for enhancing the host response. These approaches combine rigorous statistical principles with a biological context and are readily applied by biologists.</p

Sequential Deliberation for Social Choice

In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus. However, in instances where the underlying decision space is too large or complex for ordinal voting, standard voting methods of social choice may be impractical. How then can we design a mechanism - preferably decentralized, simple, scalable, and not requiring any special knowledge of the decision space - to reach consensus? We propose sequential deliberation as a natural solution to this problem. In this iterative method, successive pairs of agents bargain over the decision space using the previous decision as a disagreement alternative. We describe the general method and analyze the quality of its outcome when the space of preferences define a median graph. We show that sequential deliberation finds a 1.208- approximation to the optimal social cost on such graphs, coming very close to this value with only a small constant number of agents sampled from the population. We also show lower bounds on simpler classes of mechanisms to justify our design choices. We further show that sequential deliberation is ex-post Pareto efficient and has truthful reporting as an equilibrium of the induced extensive form game. We finally show that for general metric spaces, the second moment of of the distribution of social cost of the outcomes produced by sequential deliberation is also bounded

Proteome-level display by 2-dimensional chromatography of extracellular matrix-dependent modulation of the phenotype of bladder cancer cells

BACKGROUND: The extracellular matrix can have a profound effect upon the phenotype of cancer cells. Previous work has shown that growth of bladder cancer cells on a matrix derived from normal basement membrane suppresses many malignant features that are displayed when the cells are grown on a matrix that has been modified by malignant tumors. This work was undertaken to investigate proteome-level changes as determined by a new commercially available proteome display involving 2-dimensional chromatography for bladder cancer cells grown on different extracellular matrix preparations that modulate the expression of the malignant phenotype. RESULTS: Depending on the matrix, between 1300 and 2000 distinct peaks were detected by two-dimensional chromatographic fractionation of 2.1 – 4.4 mg of total cellular protein. The fractions eluting from the reversed-phase fractionation were suitable for mass spectrometric identification following only lyophilization and trypsin digestion and achieved approximately 10-fold higher sensitivity than was obtained with gel-based separations. Abundant proteins that were unique to cells grown on one of the matrices were identified by mass spectrometry. Following concentration, peaks of 0.03 AU provided unambiguous identification of protein components when 10% of the sample was analyzed, whereas peaks of 0.05 AU was approximately the lower limit of detection when the entire sample was separated on a gel and in-gel digestion was used. Although some fractions were homogeneous, others were not, and up to 3 proteins per fraction were identified. Strong evidence for post-translational modification of the unique proteins was noted. All 13 of the unique proteins from cells grown on Matrigel were related to MYC pathway. CONCLUSION: The system provides a viable alternative to 2-dimensional gel electrophoresis for proteomic display of biological systems. The findings suggest the importance of MYC to the malignant phenotype of bladder cancer cells