Miracle-dz/UniFAR-FTUs huggingface dataset:
Indirect Fitness Benefits Enable the Spread of Host Genes Promoting Costly Transfer of Beneficial Plasmids

Bacterial genes that confer crucial phenotypes, such as antibiotic resistance, can spread horizontally by residing on mobile genetic elements (MGEs). Although many mobile genes provide strong benefits to their hosts, the fitness consequences of the process of transfer itself are less clear. In previous studies, transfer has been interpreted as a parasitic trait of the MGEs because of its costs to the host but also as a trait benefiting host populations through the sharing of a common gene pool. Here, we show that costly donation is an altruistic act when it spreads beneficial MGEs favoured when it increases the inclusive fitness of donor ability alleles. We show mathematically that donor ability can be selected when relatedness at the locus modulating transfer is sufficiently high between donor and recipients, ensuring high frequency of transfer between cells sharing donor alleles. We further experimentally demonstrate that either population structure or discrimination in transfer can increase relatedness to a level selecting for chromosomal transfer alleles. Both mechanisms are likely to occur in natural environments. The simple process of strong dilution can create sufficient population structure to select for donor ability. Another mechanism observed in natural isolates, discrimination in transfer, can emerge through coselection of transfer and discrimination alleles. Our work shows that horizontal gene transfer in bacteria can be promoted by bacterial hosts themselves and not only by MGEs. In the longer term, the success of cells bearing beneficial MGEs combined with biased transfer leads to an association between high donor ability, discrimination, and mobile beneficial genes. However, in conditions that do not select for altruism, host bacteria promoting transfer are outcompeted by hosts with lower transfer rate, an aspect that could be relevant in the fight against the spread of antibiotic resistance.
Noise robust hands-free speech recognition using microphone array and Kalman filter as front-end system of conversational TV

In this paper, we investigate hands-free speech recognition as front-end system of conversational TV. The conversational TV is one of machine conversation systems to retrieve the interesting information by inquiring it to the TV. To realize the natural machine conversation without consciousness of microphone, hands-free speech recognition is required. In the hands-free speech recognition system, the directions of the arriving signal are estimated by using a microphone array and the desired signal is enhanced by beam forming. Then, the user utterance section is detected automatically from continuously observed signal. Furthermore, by applying the noise reduction and noise adaptation, the enhanced speech signal is recognized accurately.
Strong wavevector dependence of hole transport in heterostructures

Heterostructures such as resonant tunneling diodes, quantum well photodetectors and lasers, and cascade lasers break the symmetry of the crystalline lattice. Such break in lattice symmetry causes a strong interaction of heavy-, lightand split-off hole bands. A resonant tunneling diode is used as a vehicle to study hole transport in heterostructures including the subband dispersion transverse to the main transport direction. Four key findings are demonstrated: (1) the heavy and light hole interaction is shown to be strong enough to result in dominant current flow off the 0 zone center (more holes flow through the structure at an angle than straight through), (2) explicit inclusion of the transverse momentum in the current integration is needed, (3) most of the current flow is due to injection from heavy holes in the emitter, and (4) the dependence on the angle φ of the transverse momentum k is weak. Two bandstructure models are utilized to demonstrate the underlying physics: (1) independent/uncoupled heavy-, lightand split-off bands, and (2) second-nearest neighbor sp3s* tight-binding model. Current–voltage ( I –V) simulations including explicit integration of the total energy E, transverse momentum |k| and transverse momentum angle φ are analyzed. An analytic formula for the current density J(k) as a function of transverse momentumk is derived and utilized to explain the three independent mechanisms that generate off-zone-center current flow: (1) nonmonotonic (electron-like) hole dispersion, (2) different quantum well and emitter effective masses, and (3) momentum-dependent quantum well coupling strength. The analytic expression is also used to generate a complete I –V characteristic that compares well to the full numerical solution. The Fermi level and temperature dependence on the I –V is examined. Finally a simulation is compared to experimental data. c © 2001 Academic Press
A Test of Efficiency for the S&P Index Option Market Using Variance Forecasts

To forecast future option prices, autoregressive models of implied volatility derived from observed option prices are commonly employed [see Day and Lewis (1990), and Harvey and Whaley (1992)]. In contrast, the ARCH model proposed by Engle (1982) models the dynamic behavior in volatility, forecasting future volatility using only the return series of an asset. We assess the performance of these two volatility prediction models from S&P 500 index options market data over the period from September 1986 to December 1991 by employing two agents who trade straddles, each using one of the two different methods of forecast. Straddle trading is employed since a straddle does not need to be hedged. Each agent prices options according to her chosen method of forecast, buying (selling) straddles when her forecast price for tomorrow is higher (lower) than today's market closing price, and at the end of each day the rates of return are computed. We find that the agent using the GARCH forecast method earns greater profit than the agent who uses the implied volatility regression (IVR) forecast model. In particular, the agent using the GARCH forecast method earns a profit in excess of a cost of $0.25 per straddle with the near-the-money straddle trading.
Online hot selling period and its impact on e-retailer’s pricing strategies

The express delivery industry is often overloaded in some hot online selling seasons, which causes consumers’ dissatisfaction. Under such a circumstance, the e-retailer can utilise two opposite strategies, i.e. to set-up either a low price with a pre-announced markdown pricing (PMDP) strategy, or a high price with a pre-announced markup pricing (PMUP) strategy for the hot selling period. As both the prices and the express service quality are different between the regular period and the hot selling period, consumers can strategically choose their purchase time, which will in turn influences the e-retailer’s pricing strategy. To investigate under what condition one pricing strategy will dominate the other, we propose a two period pricing model in which the selling season are divided into regular and hot selling period, and all consumers are assumed to be strategic. The e-retailer determines the prices over the two kinds of periods to maximise its profit. The comparison shows that a PMUP (resp. PMDP) strategy is preferred when the overloading degree in the hot selling period is slight (resp. heavy). Furthermore, we extend our model by incorporating the competition of traditional retailers.
Location disambiguation for geo-tagged images

In this poster, we address the problem of location disambiguation for geotagged Web photo resources. We propose an approach for analyzing and partitioning large geotagged photo collections using geographic and semantic information. By organizing the dataset in a structural scheme, we resolve the location ambiguity and clutter problem yield by massive volume of geotagged photos.
On the resilience of P2P-based botnet graphs

P2P botnets represent another escalation level in the race of arms between criminals and the research community. By utilizing a distributed P2P architecture they are resilient against random failures and attacks and overcome the limitations of a central command and control server. For this reason, it is important to monitor them to gather information for potential takedown attempts. In this paper, we introduce our high-frequency crawling tool Strobo-Crawler that can carry out a fine-grained node enumeration. Furthermore, we propose mechanisms to derive accurate snapshots of the botnet graph on the basis of restricted monitoring data. We applied Strobo-Crawler in a two week crawling campaign in the P2P botnets Sality and ZeroAccess and describe the results along with a careful evaluation of our graph reconstruction. Furthermore, we provide a thorough analysis of the resulting botnet graphs and also provide these graphs to the public. Our results indicate that they are highly resilient against node churn, but also against targeted attacks. Bots are highly interconnected and the graphs are characterized by a high clustering coefficient, high density, and low diameter.
Statistical models of asset returns

This major collection presents a careful selection of the most important published articles in the field of financial econometrics. Starting with a review of the philosophical background, the collection covers such topics as the random walk hypothesis, long-memory processes, asset pricing, arbitrage pricing theory, variance bounds tests, term structure models, market microstructure, Bayesian methods and other statistical tools. Andrew Lo - one of the world's leading financial economists - has written an authoritative introduction, which offers a comprehensive overview of the subject and complements his selection.
Off-center collisions in AdS 5 with applications to multiplicity estimates in heavy-ion collisions

We study the trapped surface produced by an off-center collision of light-like, point-sourced shock waves in anti-de Sitter space. We find an analytic expression for the shape of the trapped surface in the limit where the energy of the shock waves is large and the impact parameter is not too large. We use the area of the trapped surface to estimate a lower bound on the entropy produced in the collision. We compare our results to particle multiplicity measurements in heavy-ion collisions as interpreted through the Glauber model. In an attempt to roughly simulate the effects of asymptotic freedom and confinement in quantum chromodynamics, we also consider the effects of slicing off parts of anti-de Sitter space.
Energetics of a hydrogen bond (charged and neutral) and of a cation-pi interaction in apoflavodoxin.

Anabaena apoflavodoxin contains a single histidine residue (H34) that interacts with two aromatic residues (F7 and Y47). The histidine and phenylalanine rings are almost coplanar and they can establish a cation-pi interaction when the histidine is protonated. The histidine and tyrosine side-chains are engaged in a hydrogen bond, which is their only contact. We analyse the energetics of these interactions using p Ka-shift analysis, double-mutant cycle analysis at two pH values, and X-ray crystallography. The H/F interaction is very weak when the histidine is neutral, but it is strengthened by 0.5 kcal mol-1on histidine protonation. Supporting this fact, the histidine p Kain a F7L mutant is 0.4 pH units lower than in wild-type. The strength of the H/Y hydrogen bond is 0.7 kcal mol-1when the histidine is charged, and it becomes stronger (1.3 kcal mol-1) when the histidine is neutral. This is consistent with our observation that the (H34)Nepsilon2-OH(Y47) distance is slightly shorter in the apoflavodoxin structure at pH 9.0 than in the previously reported structure at pH 6.0. It is also consistent with a histidine p Kavalue 0.6 pH units higher in a Y47F mutant than in the wild-type protein. We suggest that the higher stability of the neutral hydrogen bond could be due to a higher desolvation penalty of the charged hydrogen bond that would offset its more favourable enthalpy of formation. The relationship between hydrogen bond strength and the contribution of hydrogen bonds to protein stability is discussed.
Hands-free speech recognition using a filtered clean corpus and incremental HMM adaptation

A challenging scenario is addressed in which a hands-free speech recognizer operates in a noisy office environment with incremental model adaptation functionalities. The use of a single far microphone as well as that of a microphone array input are investigated. In a previous work it was shown that the acoustic mismatch, remaining after the application of microphone array processing, can be further reduced by conditioning hidden Markov models to operating acoustic conditions. Conditioned HMMs are models trained using the filtered version of a clean corpus, which is speech material better representing noisy real environments. Afterwards, conditioned models are used as initial models for unsupervised incremental adaptation. Experimental results of connected digit recognition show that models trained with filtered clean speech allows to obtain better recognition performance than models trained with clean speech. Furthermore, results show a significant performance increase when incremental adaptation is applied, even after recognition of few utterances.
E L I Z a Beth Laderman and Wayne Passmore

In this paper, we investigate whether elimination of the savings association charter might reduce lending to “non traditional” (e.g., low-income) mortgage borrowers. We present a theoretical model of lender portfolio choice, in which nontraditional lenders have some market power and traditional lenders are price-takers in the mortgage market. The comparative statics indicate differences be tween nontraditional and traditional lenders in terms of their asset allocation responses to changes in borrower in come and house prices. Empirical tests indicate the ab sence of such differences between savings associations and commercial banks, suggesting that elimination of the savings association charter would not impair lending to nontraditional mortgage borrowers. During the past several years, Congress has debated eliminating the federal savings and loan (S&L) industry by merging the federal S&L charter into the commercial bank charter.1 As the number of savings associations has declined sharply over the past decade (from 2,961 savings banks and savings and loans with either national or state charters in 1986 to 1,997 at the end of 1997), the elimination of the federal S&L charter might seem to be simply one more step in financial consolidation. Some critics of the plan, however, point out that the initial policy goal of chartering a separate set of depository institutions was to create institutions with a special commitment to a particular type of lending, and, in the case of savings associations, the goal was to have a set of institutions with a special commitment to the housing market. In spite of the rapid growth of mortgage securitization and the prevalence of commercial and mortgage banks in mortgage lending, they argue that a depository institution with a special commitment to mortgage lending still is needed. According to these critics, commercial and mortgage banks are “cream-skimmers” who make easy real estate loans, but who do not develop the relationships with unusual or nontraditional borrowers, that are required to lend successfully to these borrowers or institutions. A corollary to this view is that commercial banks provide only conforming mortgages that can be sold in the secondary mortgage market, while savings associations make “hard” mortgages that often must be held in the institution’s portfolio. As illustrated later, these types of institutions may behave differently in their asset allocation in response to changes in borrower income or house prices. Such differences may provide tests of whether or not special borrowers are served by these institutions.2 Is Mo r t g a ge Lending by Savings Associations Sp e c i a l ?
The Persistence of Innovation in Government

Sandford Borins addresses the enduring significance of innovation in government as practiced by public servants, analyzed by scholars, discussed by media, documented by awards, and experienced by the public. In The Persistence of Innovation in Government , he maps the changing landscape of American public sector innovation in the twenty-first century, largely by addressing three key questions: Who innovates? When, why, and how do they do it? What are the persistent obstacles and the proven methods for overcoming them? Probing both the process and the content of innovation in the public sector, Borins identifies major shifts and important continuities. His examination of public innovation combines several elements: his analysis of the Harvard Kennedy School's Innovations in American Government Awards program; significant new research on government performance; and a fresh look at the findings of his earlier, highly praised book Innovating with Integrity: How Local Heroes Are Transforming American Government . He also offers a thematic survey of the field's burgeoning literature, with a particular focus on international comparison.
Association between Markers of Fatty Liver Disease and Impaired Glucose Regulation in Men and Women from the General Population: The KORA-F4-Study

Objective To investigate whether the elevated liver enzymes gamma-glutamyltransferase (GGT), glutamate-pyruvate transaminase (GPT), glutamate-oxalacetate transaminase (GOT) and alkaline phosphatase (AP) and non-alcoholic fatty liver disease (NAFLD) respectively are independently associated with pre-diabetic states, namely impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) or known and newly diagnosed diabetes (NDD), in men and women from the general German population. Methods The study was based on 3009 subjects (1556 females, 1453 males) aged 32 to 81 years who participated in the KORA-F4-Study in 2006/2008 in Augsburg, Southern Germany. All non-diabetic participants underwent an oral glucose tolerance test to assess disturbances in glucose metabolism. NAFLD was estimated by liver enzyme concentrations and the Bedogni Fatty Liver Index (FLI). Results 229 participants (7.6%) reported known diabetes, 106 had NDD (3.5%), 107 (3.6%) had IFG, 309 (10.3%) had IGT, 69 (2.3%) were affected with both metabolic disorders (IFG/IGT) and 74 (2.5%) could not be classified. GGT and GPT were significantly elevated in persons with pre-diabetes and diabetes (GGT in diabetic persons OR = 1.76, [1.47–2.09], in IFG OR = 1.79 [1.50–2.13], GPT in diabetic persons OR = 1.51, [1.30–1.74], in NDD OR = 1.77 [1.52–2.06]), GOT and AP only inconsistently in some pre-diabetes groups. The effects were sharpened in models using an increase of two or three out of three enzymes as an estimate of fatty liver and especially in models using the FLI. Overall frequency of NAFLD applying the index was 39.8% (women: 27.3% and men: 53.2%). In participants with fatty liver disease, the OR for NDD adjusted for sex and age was 8.48 [5.13–14.00], 6.70 [3.74–12.01] for combined IFG and IGT and 4.78 [3.47–6.59] for known diabetes respectively. Conclusions Elevated GGT and GPT–values as well as estimates of fatty liver disease are significantly associated with pre-diabetes and diabetes and thus very useful first indicators of a disturbed glucose metabolism.
Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data

Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilitating the successful diagnosis and treatment of cancer. While there are quite a number of research works which perform tumor clustering, few of them considers how to incorporate fuzzy theory together with an optimization process into a consensus clustering framework to improve the performance of clustering analysis. In this paper, we first propose a random double clustering based cluster ensemble framework (RDCCE) to perform tumor clustering based on gene expression data. Specifically, RDCCE generates a set of representative features using a randomly selected clustering algorithm in the ensemble, and then assigns samples to their corresponding clusters based on the grouping results. In addition, we also introduce the random double clustering based fuzzy cluster ensemble framework (RDCFCE), which is designed to improve the performance of RDCCE by integrating the newly proposed fuzzy extension model into the ensemble framework. RDCFCE adopts the normalized cut algorithm as the consensus function to summarize the fuzzy matrices generated by the fuzzy extension models, partition the consensus matrix, and obtain the final result. Finally, adaptive RDCFCE (A-RDCFCE) is proposed to optimize RDCFCE and improve the performance of RDCFCE further by adopting a self-evolutionary process (SEPP) for the parameter set. Experiments on real cancer gene expression profiles indicate that RDCFCE and A-RDCFCE works well on these data sets, and outperform most of the state-of-the-art tumor clustering algorithms.
Effects of attackers and attacks on availability requirement in vehicular network: A survey

Availability is one of the key security requirements in vehicular network. The purpose of vehicular network is to serve the user with its potential applications, but this purpose is to fulfill only when networks are available to the end users. Due to open nature of wireless medium, the attackers can affect the vehicular environment. In this paper, we are providing a survey on the attackers and all possible attacks on the availability requirement of vehicular network. The main aim of this study is to describe the threat levels of all possible attacks on the availability. It has been investigated that each level has its own priorities. Threats levels and its priorities will be useful to understand the behavior of attackers and attacks in the vehicular network.
Finite Element Discretization Error Analysis of a General Interfacial Stress Functional

The finite element discretization of a variable interfacial stress tensor ${\sigma}^{\Gamma}(x)$ is considered; variable interfacial tension is included as a special case. Interfacial stress, for example, occurs in two-phase flow problems. In the weak formulation, the interfacial stress gives rise to a functional which is supported on the interface $\Gamma$. A finite element discretization of this functional is presented and analyzed. The discretization admits almost independent meshes for the approximation of the interface and the approximation of the flow variables. The main result is an $\mathcal{O}(h^{k+1/2})$-error-bound for the interfacial stress functional in a natural norm if the discrete interface is an $\mathcal{O}(h^{k+1})$-approximation of $\Gamma$. The bound is shown to be sharp in numerical experiments.