Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Complexity of Nash Equilibria and Other Fixed Points (Extended Abstract)

We reexamine, what it means to compute Nash equilibria and, more, generally, what it means to compute a fixed point of a given Brouwer function, and we investigate the complexity of the associated problems. Specifically, we study the complexity of the following problem: given a finite game, Gamma, with 3 or more players, and given epsiv > 0, compute a vector x' (a mixed strategy profile) that is within distance e (say in t^) of some (exact) Nash equilibrium. We show that approximation of an (actual) Nash equilibrium for games with 3 players, even to within any non-trivial constant additive factor epsiv < 1/2 in just one desired coordinate, is at least as hard as the long standing square-root sum problem, as well as more general arithmetic circuit decision problems, and thus that even placing the approximation problem in NP would-resolve a major open problem in the complexity of numerical computation. Furthermore, we show that the (exact or approximate) computation of Nash equilibria for 3 or more players is complete for the class of search problems, which we call FIXP, that can be cast as fixed point computation problems for functions represented by algebraic circuits (straight line programs) over basis {+, *, -, /, max, min}, with rational constants. We show that the linear fragment of FIXP equals PPAD. Many problems in game theory, economics, and probability theory, can be cast as fixed point problems for such algebraic functions. We discuss several important such problems: computing the value of Shapley's stochastic games, and the simpler games of Condon, extinction probabilities of branching processes, termination probabilities of stochastic context-free grammars, and of Recursive Markov Chains. We show that for some of them, the approximation, or even exact computation, problem can be placed-in PPAD, while for others, they are at least as hard as the square-root sum and arithmetic circuit decision problems.
Economie d’avant garde

Social norms are inuenced by the technological environment that a society faces. Behavioral modes reect purposive decision making by individuals, given the environment they live in. Thus, as technology changes, so might social norms. There were big changes in social norms during the 20th century, especially in sexual mores. In 1900 only six percent of unwed females engaged in premarital sex. Now, three quarters do. It is argued here that this was the result of technological improvement in contraceptives, which lowered the cost of premarital sex. The evolution from an abstinent to a promiscuous society is studied using an equilibrium matching model. Keywords: Social change; the sexual revolution; technological progress in contraceptives; bilaterial search. JEL Classi cation Nos: E1, J1, O3 "Social Change" is the title of a classic book by the great sociologist William F. Ogburn. Updates are available at http://www.econ.rochester.edu/Faculty/GreenwoodPapers/sc.pdf yDepartment of Economics, University of Rochester, Rochester, NY 14627-0156. zDepartment of Economics, Pennsylvania State University, 619 Kern Graduate Building, University Park, PA 16802-3306. Why is there so much social change today, and why was there so little in ancient times? The most probable answer, the result of quite extensive study, is mechanical invention and scienti c discovery. There is no doubt that useful inventions and researches cause social changes. Steam and steel were major forces in developing our extensive urban life. Gunpowder inuenced the decline of feudalism. The discovery of seed-planting destroyed the hunting cultures and brought a radically new form of social life. The automobile is helping to create the metropolitan community. Small inventions, likewise, have far-reaching effects. The coin-in-the-slot device changes the range and nature of salesmanship, radically a¤ects di¤erent businesses, and creates unemployment. The e¤ects of the invention of contraceptives on population and social institutions is so vast as to defy human estimation. It is obvious, then, that social changes are caused by inventions. William F. Ogburn (1936, pp. 1-2)
Sustained Water Loss in California's Mountain Ranges During Severe Drought From 2012 to 2015 Inferred From GPS

Drought struck California during 7 of the 9 years from 2007 to 2015, reducing the state's available water resources. Pumping of Central Valley groundwater has produced spectacular land subsidence. Uplift of the adjacent Sierra Nevada mountains has been proposed to be either tectonic uplift or solid Earth's elastic response to unloading of Central Valley groundwater. We find that of the 24 mm of uplift of the Sierra Nevada from October 2011 to October 2015, just 5 mm is produced by Central Valley groundwater loss, less than 2 mm is tectonic uplift, and 17 mm is solid Earth's elastic response to water loss in the Sierra Nevada. We invert GPS vertical displacements recording solid Earth's elastic response to infer changes in water storage across the western U.S. from January 2006 to October 2017. We find water changes to be sustained over periods of drought or heavy precipitation: the Sierra Nevada lost 15 ± 19 km3 of water during drought from October 2006 to October 2009, gained 18 ± 14 km3 of water during heavy precipitation from October 2009 to October 2011, and lost 45 ± 21 km3 of water during severe drought from October 2011 to October 2015 (95% confidence limits). Such large changes are not in hydrology models: snow accumulation in October is negligible and long‐term soil moisture change is small. We infer that there must be large loss of either deep soil moisture or groundwater in river alluvium and in crystalline basement in the Sierra Nevada. The results suggest there to be parching of water in the ground during the summer of years of drought and seeping of melting snow into the Sierra Nevada in the spring of years of heavy precipitation.
Epidemic Algorithms for Reliable Multicasting in Ad Hoc Networks

existence depend on the nodes forming them. Thus, services and applications designed for ad hoc networks should adapt to this dynamic and distributed environment. In particular, multicast algorithms having reliability and scalability requirements should abstain from centralized approaches. We aspire to define a reliable and scalable multicast protocol for ad hoc networks. Our target is to utilize epidemic techniques for this purpose. In this paper, we present a brief survey of epidemic algorithms for reliable multicasting in ad hoc networks, and describe formulations and analytical results for simple epidemics. Then, P2P anti-entropy algorithm for content distribution and our prototype simulation model are described together with our initial results demonstrating the behavior of the algorithm.
On the list and bounded distance decodibility of Reed-Solomon codes

For an error-correcting code and a distance bound, the list decoding problem is to compute all the codewords within a given distance to a received message. The bounded distance decoding problem is to find one codeword if there is at least one codeword within the given distance, or to output the empty set if there is not. Obviously the bounded distance decoding problem is not as hard as the list decoding problem. For a Reed-Solomon code [n, k]/sup q/, a simple counting argument shows that for any integer 0 < g < n, there exists at least one Hamming ball of radius n - g, which contains at least (/sup n//sub g/)/q/sup g-k/ many codewords. Let g(n, k, q) be the smallest positive integer g such that (/sup n//sub g/)/q/sup g-k/ < 1. One knows that k /spl les/ g(n, k, q) /spl les/ /spl radic/nk /spl les/ n. For the distance bound up to n- /spl radic/nk;, it is well known that both the list and bounded distance decoding can be solved efficiently. For the distance bound between n - /spl radic/nk and n - g(n, k, q), we do not know whether the Reed-Solomon code is list, or bounded distance decodable, nor do we know whether there are polynomially many codewords in all balls of the radius. It is generally believed that the answers to both questions are no. There are public key cryptosystems proposed recently, whose security is based on the assumptions. In this paper, we prove: (1) List decoding can not be done for radius n - g(n, k: q) or larger, otherwise the discrete logarithm over F/sub qg(m, k, q)-k/ is easy. (2) Let h and g be positive integers satisfying q /spl ges/ max(g/sup 2/, (h-l)/sup 2+/spl epsiv//) and g /spl ges/ (4//spl epsiv/ + 2)(h + 1) for a constant /spl epsiv/ > 0. We show that the discrete logarithm problem over F/sub qh/ can be efficiently reduced by a randomized algorithm to the bounded distance decoding problem of the Reed-Solomon code [q, g - h]/sub q/ with radius q - g. These results show that the decoding problems for the Reed-Solomon code are at least as hard as the discrete logarithm problem over finite fields. The main tools to obtain these results are an interesting connection between the problem of list-decoding of Reed-Solomon code and the problem of discrete logarithm over finite fields, and a generalization of Katz's theorem on representations of elements in an extension finite field by products of distinct linear factors.
Provisioning of VoIP Services for Mobile Subscribers Using WiFi Access Network

This article proposes a solution for two issues in current communications. Firstly, that IMS suffers from client inexistence. Secondly, that mobile operators want to give the subscriber a possibility to access their VoIP network and efficiently cover special areas like airports. To address these problems, we have developed a novel service architecture, which allows 2G subscribers access to a SIP based VoIP network via WiFi complying security standards. User authentication and authorization is based on the EAP- SIM algorithm. Integrity and confidentiality is provided by IPSec connection established using parameters derived from authentication triplets. Consequently, all security-related issues can be performed exclusively using the subscriber identity module (SIM). We have tested and verified the proposed architecture with a mobile phone and have proven the correctness of our approach. The main drawback that remains is the difficulty of IPSec implementation that can be bypassed by a special application.
Learning in Online Auctions ?

We consider the problem of revenue maximization in online auctions, that is, auctions in which bids are received and dealt with one-by-one. In this paper, we demonstrate that results from online learning can be usefully applied in this context, and we derive a new auction for digital goods that achieves a constant competitive ratio with respect to the optimal (offline) fixed price revenue. This substantially improves upon the best previously known competitive ratio for this problem of O(exp( √ log log h)) [4]. We also apply our techniques to the related problem of designing online posted price mechanisms, in which the seller declares a price for each of a series of buyers, and each buyer either accepts or rejects the good at that price. Despite the relative lack of information in this setting, we show that online learning techniques can be used to obtain results for online posted price mechanisms which are similar to those obtained for online auctions. Portions of this work appeared as an extended abstract in Proceedings of SODA’03 [5]. Email addresses: avrim@cs.cmu. edu (Avrim Blum), vijayk@amazon.com (Vijay Kumar), atri@cs.utexas. edu (Atri Rudra), felix@cs.berkeley. edu (Felix Wu). 1 Supported in part by National Science Foundation grants CCR-0105488 and IIS0121678. 2 Work done while the author was at IBM India Research Lab, New Delhi, India. 3 Supported in part by National Science Foundation ITR grant CCR-0121555. Preprint submitted to Elsevier Science 16 September 2003
Organic matter and meiobenthos in submarine canyons of the Iberian continental margin

Abundance of metazoan meiofauna and foraminifera, and biomass and community structure of nematodes were investigated in benthic zones along the Nazaré Canyon and adjacent continental slope in relation to concentration of organic matter and its suitability as a food source for the meiobenthos. The Nazaré canyon sediments were richer in organic carbon (Corg), total nitrogen, and phytopigments compared to the adjacent open slope. In addition, phytodetritus was fresher in the canyon sediment than on the slope (higher chlorophyll a: phaeopigments). Nevertheless, the abundance of polychaetes, copepods, bivalves, nematodes, total metazoans, and nematode biomass were not always higher in the canyon than on the adjacent open slope. Lower densities occurred in the upper and middle canyon, and living benthic foraminifers were significantly more abundant on the adjacent slope. The stations in the upper and middle canyon contained infinitesimal numbers of foraminifers. Reduced diversity and evenness and high K-dominance of the nematode assemblages in the upper part of the canyon indicated environmental stress, perhaps related to high Corg content
Bioinformatics Original Paper Reliable Prediction of Drosha Processing Sites Improves Microrna Gene Prediction

Motivation: Mature microRNAs (miRNAs) are processed from long hairpin transcripts. Even though it is only the first of several steps, the initial Drosha processing defines the mature product and is characteristic for all miRNA genes. Methods that can separate between true and false processing sites are therefore essential to miRNA gene discovery. Results: We present a classifier that predicts 5 0 Drosha processing sites in hairpins that are candidate miRNAs. The classifier, called Microprocessor SVM, correctly predicts the processing site for 50% of known human 5 0 miRNAs, and 90% of its predictions are within two nucleotides of the true site. Another classifier that is trained on the output from the Microprocessor SVM outperforms existing methods for prediction of unconserved miRNAs. Reanalysis of characteristics and supporting evidence for a set of newly annotated miRNAs shows that some miRNAs may be misannotated. This suggests that expressed hairpins should not be annotated as miRNAs until they are verified to be Drosha and Dicer substrates.
Thermodynamic Analysis of Wind Energy Systems

This chapter studies the efficiency performance of wind energy systems evaluated by energy and exergy analyses. The theories of energy and exergy analyses along with efficiency calculation for horizontal-axis wind turbines (WTs) are provided by a lucid explanation. A 1.5 MW WT is selected for the thermodynamic analysis using reanalyzed meteorological data retrieved from the National Aeronautics and Space Administration's (NASA) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), data set. Matlab scripts are developed to calculate the energy and exergy efficiencies using the MERRA-2 data set. The energy efficiency presents higher magnitude than the exergy efficiency based on the theoretical derivation and the calculated time series of efficiencies. Comparison of impacts of four meteorological variables (wind speed, pressure, temperature, and humidity ratio) on WT efficiencies shows that although wind speed dominates the turbine's efficiency performance, other meteorological variables also play important roles. In addition, uncertainties of the meteorological variables are represented by the best-fit distributions, which are critically important for evaluating the reliability of wind power performance considering realistic meteorological uncertainty.
Quantitative prediction of repaglinide-rifampicin complex drug interactions using dynamic and static mechanistic models: Delineating differential CYP3A4 induction and OATP1B1 inhibition potential of rifampicin

Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate to hepatic uptake transporter, organic anion transporting polypeptide (OATP)1B1. The purpose of this study is to predict the “dosing-time” dependent pharmacokinetic interactions of repaglinide with rifampicin, using mechanistic models. In vitro hepatic transport of repaglinide, characterized using sandwich-cultured human hepatocytes, and intrinsic metabolic parameters were used to build a dynamic whole-body physiologically-based pharmacokinetic (PBPK) model. The PBPK model adequately described repaglinide plasma concentration-time profiles; and successfully predicted area under the plasma concentration-time curve ratios of repaglinide (within ±25% error), dosed (staggered 0-24h) after rifampicin treatment, when primarily considering induction of CYP3A4 and reversible inhibition of OATP1B1 by rifampicin. Further, a static mechanistic “extended net-effect” model incorporating transport and metabolic disposition parameters of repaglinide and interaction potency of rifampicin was devised. Predictions based on the static model are similar to that observed in the clinic (average error ~19%), as well as similar to the PBPK model predictions. Both the models suggested that the combined effect of increased gut extraction and decreased hepatic uptake caused minimal repaglinide systemic exposure change when repaglinide is dosed simultaneously or 1h after the rifampicin dose. On the other hand, isolated induction effect as a result of temporal separation of the two drugs translated to ~5-fold reduction in repaglinide systemic exposure. In conclusion, both dynamic and static mechanistic models are instrumental in delineating the quantitative contribution of transport and metabolism in the dosing-time dependent repaglinide-rifampicin interactions.
Co-Parsing with Competitive Models

We present an asymmetric approach to a run-time combination of two parsers where one component serves as a predictor to the other one. Predictions are integrated by means of weighted constraints and therefore are subject to preferential decisions. Previously, the same architecture has been successfully used with predictors providing partial or inferior information about the parsing problem. It has now been applied to a situation where the predictor produces exactly the same type of information at a fully competitive quality level. Results show that the combined system outperforms its individual components, even though their performance in isolation is already fairly high.
Simplifying credit scoring rules using LVQ + PSO

One of the key elements in the banking industry rely on the appropriate selection of customers. In order to manage credit risk, banks dedicate special efforts in order to classify customers according to their risk. The usual decision making process consists in gathering personal and financial information about the borrower. Processing this information can be time consuming, and presents some difficulties due to the heterogeneous structure of data. We offer in this paper an alternative method that is able to classify customers' profiles from numerical and nominal attributes. The key feature of our method, called LVQ+PSO, is the finding of a reduced set of classifying rules. This is possible, due to the combination of a competitive neural network with an optimization technique. These rules constitute a predictive model for credit risk approval. The reduced quantity of rules makes this method not only useful for credit officers aiming to make quick decisions about granting a credit, but also could act as borrower's self selection. Our method was applied to an actual database of a credit consumer financial institution in Ecuador. We obtain very satisfactory results. Future research lines are exposed.
Protection from Distributed Denial of Service Attack Using History-based IP Filtering

In this paper, we intr oducea practical schemeto defendagainstDistrib utedDenialof Service(DDoS)attacksbasedon IP sourceaddressfiltering . The edgerouter keepsa history of all the legitimate IP addresseswhich havepreviously appeared in the network. When the edgerouter is overloaded,this history is used to decidewhether to admit an incoming IP packet. Unlik e other proposalsto defendagainstDDoSattacks,our schemeworks well during highly-distrib uted DDoS attacks, i.e., fr om a large number of sources.We presentseveral heuristic methodsto make the IP addressdatabaseaccurateand robust, and we presentexperimental resultsthat demonstratethe effectivenessof our schemein defendingagainsthighly-distrib uted DDoSattacks.
Modeling the Martian dust cycle, 1. Representations of dust transport processes

[1] A dust transport scheme has been developed for a general circulation model of the Martian atmosphere. This enables radiatively active dust transport, with the atmospheric state responding to changes in the dust distribution via atmospheric heating, as well as dust transport being determined by atmospheric conditions. The scheme includes dust lifting, advection by model winds, atmospheric mixing, and gravitational sedimentation. Parameterizations of lifting initiated by (1) near-surface wind stress and (2) convective vortices known as dust devils are considered. Two parameterizations are defined for each mechanism and are first investigated offline using data previously output from the non-dust-transporting model. The threshold-insensitive parameterizations predict some lifting over most regions, varying smoothly in space and time. The threshold-sensitive parameterizations predict lifting only during extreme atmospheric conditions (such as exceptionally strong winds), so lifting is rarer and more confined to specific regions and times. Wind stress lifting is predicted to peak during southern summer, largely between latitudes 15° and 35°S, with maxima also in regions of strong slope winds or thermal contrast flows. These areas are consistent with observed storm onset regions and dark streak surface features. Dust devil lifting is also predicted to peak during southern summer, with a moderate peak during northern summer. The greatest dust devil lifting occurs in early afternoon, particularly in the Noachis, Arcadia/Amazonis, Sirenum, and Thaumasia regions. Radiatively active dust transport experiments reveal strong positive feedbacks on lifting by near-surface wind stress and negative feedbacks on lifting by dust devils.
Integrating Omics Data

Recent genome-wide studies revealed that the human genome encodes over 10,000 long non-coding RNAs (lncRNAs) with little protein-coding capacity. Growing evidence suggests that many lncRNAs may have important functions in complex diseases and are potentially a new class of therapeutic targets for treating complex disease. In contrast to the fast pace of cataloguing lncRNAs in the human genome, the function of the vast majority of lncRNAs remain unknown. In this chapter, we described data integration strategies for identifying lncRNA that are associated with cancer subtypes and clinical prognosis, and predicted those that are potential drivers of cancer progression
COMPARISON AND COMBINATIO FEATURES IN A HYBRID H RECOGNITION S

Recently, the advantages of the spectral parameters obtained by frequency filtering (FF) of the logarithmic filter bank energies (logFBEs) have been reported. These parameters, which are frequency derivatives of the logFBEs, lie in the frequency domain, and have shown good recognition performance with respect to the conventional mel-frequency cepstral coefficients (MFCC) for HMM systems. In this paper, the FF features are compared with the MFCCs and the Rasta-PLP features in the framework of a hybrid HMM/MLP recognition system, for both clean and noisy speech. Taking advantage of the ability of the hybrid system to deal with correlated features, the inclusion of the second frequency derivatives and the raw logFBEs as additional features is proposed. Furthermore, in order to enhance the robustness of these features in noisy conditions, they are combined with the Rasta temporal filtering approach. Finally, a study of the FF in the framework of multistream processing is presented. From the experimental tests, it appears that the new spectral parameters and the tested combinations yield an enhanced recognition performance.