Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulated Atmospheric N Deposition Alters Fungal Community Composition and Suppresses Ligninolytic Gene Expression in a Northern Hardwood Forest

High levels of atmospheric nitrogen (N) deposition may result in greater terrestrial carbon (C) storage. In a northern hardwood ecosystem, exposure to over a decade of simulated N deposition increased C storage in soil by slowing litter decay rates, rather than increasing detrital inputs. To understand the mechanisms underlying this response, we focused on the saprotrophic fungal community residing in the forest floor and employed molecular genetic approaches to determine if the slower decomposition rates resulted from down-regulation of the transcription of key lignocellulolytic genes, by a change in fungal community composition, or by a combination of the two mechanisms. Our results indicate that across four Acer-dominated forest stands spanning a 500-km transect, community-scale expression of the cellulolytic gene cbhI under elevated N deposition did not differ significantly from that under ambient levels of N deposition. In contrast, expression of the ligninolytic gene lcc was significantly down-regulated by a factor of 2–4 fold relative to its expression under ambient N deposition. Fungal community composition was examined at the most southerly of the four sites, in which consistently lower levels of cbhI and lcc gene expression were observed over a two-year period. We recovered 19 basidiomycete and 28 ascomycete rDNA 28S operational taxonomic units; Athelia, Sistotrema, Ceratobasidium and Ceratosebacina taxa dominated the basidiomycete assemblage, and Leotiomycetes dominated the ascomycetes. Simulated N deposition increased the proportion of basidiomycete sequences recovered from forest floor, whereas the proportion of ascomycetes in the community was significantly lower under elevated N deposition. Our results suggest that chronic atmospheric N deposition may lower decomposition rates through a combination of reduced expression of ligninolytic genes such as lcc, and compositional changes in the fungal community.
Evaluation of a Mouse Model of Necrotic Granuloma Formation Using C3HeB/FeJ Mice for Testing of Drugs against Mycobacterium tuberculosis

ABSTRACT Persistence of Mycobacterium tuberculosis remains a significant challenge for the effective treatment of tuberculosis in humans. In animals that develop necrotic lung lesions following infection with M. tuberculosis, drug-tolerant bacilli are present and persist in an extracellular microenvironment within the necrotic cores. In this study, we examined the efficacy of drug treatment in C3HeB/FeJ (Kramnik) mice that develop lesions with liquefactive necrosis, in comparison to BALB/c mice that develop nonnecrotic lesions following aerosol challenge. To accomplish this, Kramnik and BALB/c mice were infected by aerosol with M. tuberculosis and treated for 7 to 8 weeks with monotherapy using drugs with different modes of action. The efficacy of drug therapy was quantified by enumeration of bacterial load. The progression of disease and location and distribution of bacilli within lesions were visualized using various staining techniques. In the late stages of infection, Kramnik mice developed fibrous encapsulated lung lesions with central liquefactive necrosis containing abundant extracellular bacilli, whereas BALB/c mice formed nonnecrotic lesions with primarily intracellular bacilli. Necrotic lesions in Kramnik mice showed evidence of hypoxia by pimonidazole staining. Kramnik mice were significantly more refractory to drug therapy, especially for pyrazinamide. Metronidazole showed no bactericidal activity in either model. There were significantly higher numbers of drug-resistant colonies isolated from the Kramnik mice compared to BALB/c mice. These results suggest that the Kramnik mouse model will be a valuable model to test antituberculosis drugs, especially against bacilli that persist within necrotic lesions.
An Approach for Sentiment Classification of Music

In recent years, the music recommendation systems and dynamic generation of playlists have become extremely promising research areas. Thanks to the widespread use of the Internet, users can store a consistent set of music data and use them in the everyday context thanks to portable music players. The problem of modern music recommendation systems is how to process this large amount of data and extract meaningful content descriptors. The aim of this paper is to compare different approaches to decode the content within the mood of a song and to propose a new set of features to be considered for classification.
Online face detection and user authentication

The ability to verify automatically and with great accuracy the identity of a person has become crucial in everyday life. Biometrics is an emerging topic in the field of signal processing. Our research on biometrics aims at developing a complete framework useful to control access. This technical demo shows the latest image processing techniques for face detection developed at France Telecom and for face recognition developed at Eurécom. Using only one computer and one standard webcam, our biometric system detects the user face and the recognition algorithm uses this image to enable the access to a resource, a service or a location.
The impact of delirium on clinical outcomes in mechanically ventilated surgical and trauma patients

Objective:Previously, delirium has been identified as an independent risk factor for mortality in critically ill medical patients. We undertook this study to examine the relationships among medication usage, delirium, and clinical outcomes in a critically ill surgical/trauma population. Design:Prospective, multicentered, observational study. Setting:Two surgical intensive care units in level 1 trauma centers. Patients:One hundred thirty-four consecutive surgical adult patients requiring mechanical ventilation (MV) for greater than 24 hours. Interventions:Daily delirium assessment with the Confusion Assessment Method-Intensive Care Unit tool, outcomes assessment, and prospective data collection. Measurement and Main Results:Of the 134 patients who met inclusion criteria, 84 patients (63%) developed delirium at some point during their intensive care unit (ICU) stay. Delirium was associated with more MV days (9.1 vs. 4.9 days, p < 0.01), longer ICU stay (12.2 vs. 7.4 days, p < 0.01), longer hospital stay (20.6 vs. 14.7 days, p < 0.01). Additionally, greater cumulative lorazepam dose (p = 0.012), and higher cumulative fentanyl dose (p = 0.035) were administered in the delirium group. Conclusions:Delirium in the surgical/trauma ICU cohort is independently associated with more days requiring MV, longer ICU length of stay, and longer hospital length of stay. Additionally, greater amounts of lorazepam and fentanyl were administered to patients with delirium.
Simulation and Analysis of Impact of Buffering of Voice Calls in Integrated Voice and Data Communication System

Queuing theory and Markov chain analysis plays vital role in analyzing real-life problems. It is applied to wired network, wireless network and mobile communication to analyze the packet traffic in packet switched network. In this simulation and analysis, integrated communication system such as voice and data is simulated with different queue size for voice calls with different arrival and service rate and its results are analyzed to study the impact of buffering of voice and data calls for the proposed integrated wired network using Queuing theory and Markov chain analysis. We also propose to optimize the system characteristics in an attempt to provide better Quality of Service (QoS) for systems with integrated voice and data calls. The proposed models have two traffic flow namely voice calls (real-time traffic like audio) and data calls (data traffic like FTP). A single channel is assigned for voice and data calls. The incoming voice and data calls are queued when the channel is busy. Voice calls are delay-sensitive therefore priority is assigned to Constant Bit Rate (CBR) traffic voice request. For such systems, it is important to analyze the impact of buffering the voice calls as well as data calls for various mean arrival rates and mean service times for voice and data call requests. The impact of buffering the voice calls with different queue size, mean arrival rates and service rate are analyzed. These results of dedicated integrated voice and data communication system can be used for simulating any type of wired network. The minimum buffer or jitter required for both the traffic is calculated using Packet Delivery Fraction (PDF).
Measuring individual responses to aggression-triggering events: Development of the Situational Triggers of Aggressive Responses (STAR) scale

This paper presents the development of the Situational Triggers of Aggressive Responses (STAR) scale: a self-report instrument examining individual differences in the type of events and antecedents that make people feel aggressive. In Study 1 (N = 145), participants recorded recently occurring incidents that had generated feelings of aggression in them and recorded their affect at the time of the event using the Positive and Negative Affectivity Scale. The results showed that aggression-triggering events provoked positive as well as negative affect in the sample. In Study 2 (N = 849), a 23-item scale was generated based on the events recorded during Study 1. The scale comprised two sub-scales: Frustrations and Provocations, which showed good internal reliability and good factor congruency between male and female participants' factor structures. Studies 3 (N = 241) and 4 (N = 219) demonstrated the convergent reliability of the STAR scale with measures of trait aggression [Buss and Perry, 1992] and trait narcissism [Raskin and Terry, 1988] with self-concept clarity [Campbell, Trapnell, Heine et al., 1996]. Again, the STAR scale showed good internal reliability. There were no effects of sex on STAR scale scores across Studies 3 and 4. It is suggested, therefore, that sex differences may become more salient when examining aggressive behavior, rather than aggressive feelings. Aggr. Behav. 32:1–12, 2006. © 2006 Wiley-Liss, Inc.
Integrating vision-based motion planning with defeasible decision making for the Khepera robot

Intelligent mobile robots need the ability to combine autonomous navigation with high-level reasoning. This paper integrates a defeasible decision making technique and vision-based motion planning. The problem faced comprises a scenario where a Khepera 2 robot has to perform removal tasks of different size objects. This problem can be conceptually divided in two stages: (a) to decide the objects transportation order, and (b) to plan and control the robot motion. The decision making task is carried out using the facilities provided by the cognitive layer of the Khe-DeLP framework, while the motion planning is performed using a smooth shortest path control generated from visual information.
Correlation Between Epstein-Barr Virus Membrane Antigen and Three Large Cell Surface Glycoproteins

A correlation between Epstein-Barr virus membrane antigen (MA) and three surface glycoproteins has been established on the basis of radio-immunoprecipitation and immunoabsorption experiments. For radio-immunoprecipitation, Epstein-Barr virus-infected cells were radiolabeled either with neuraminidase-galactose oxidase tritiated borohydride, a procedure highly specific for surface glycoproteins, or with a general tritiated amino acid mixture. Intact cells were incubated with MA(−) or MA(+) human sera, washed free of unbound immunoglobulins, and then lysed with Nonidet P-40. The antigen-antibody complexes were bound to protein A-Sepharose and after elution with sodium dodecyl sulfate were analyzed by acrylamide gel electrophoresis in sodium dodecyl sulfate. MA(+) sera specifically precipitated three glycoproteins with molecular weights of 236,000, 212,000, and 141,000 from B95-8 cells induced with 12-O-tetradecanoylphorbal-13-acetate (TPA) and from Raji cells superinfected with P3HR-1 virus. These glycoproteins were not detected on Epstein-Barr virus-negative Ramos cells treated with TPA or on B95-8 cells treated simultaneously with TPA and phosphonoacetic acid. Soybean lectin-Sepharose bound all three glycoproteins, and lectin-Sepharose-bound glycoproteins from TPA-induced P95-8 cells absorbed MA-specific antibody from MA(+) human sera. The data strongly suggest that either all three glycoproteins have MA determinants or they are part of a complex in which one or more of the components constitute the reactive antigen.
Robust L1 Principal Component Analysis and Its Bayesian Variational Inference

We introduce a robust probabilistic L1-PCA model in which the conventional gaussian distribution for the noise in the observed data was replaced by the Laplacian distribution (or L1 distribution). Due to the heavy tail characteristics of the L1 distribution, the proposed model is supposed to be more robust against data outliers. In this letter, we demonstrate how a variational approximation scheme enables effective inference of key parameters in the probabilistic L1-PCA model. As the L1 density can be expanded as a superposition of infinite number of gaussian densities, we express the L1-PCA model as a marginalized model over the superpositions. By doing so, a tractable Bayesian inference can be achieved based on the variational expectation-maximization-type algorithm.
Quasi-geostrophic projection of rotating shallow-water equations

With a new unifying model for layered rotating shallow-water (RSW) and quasi-geostrophic (QG) equations, this paper sheds light on the relation between these two sets of equations. We propose here a new formulation of the quasi-geostrophic equations as a projection of the rotating shallow-water equations. This QG formulation uses the same prognostic variables as RSW, namely velocity and layer thickness, restoring the proximity of these two sets of equations. It allows direct access to the ageostrophic velocities hidden in geostrophic velocities resolved by the QG equations. It opens the path of studying the difference between QG and RSW using the same underlying numerical discretization. We illustrate this new possibility on a vortex shear instability and a double-gyre configuration.
VAET: A Visual Analytics Approach for E-Transactions Time-Series

Previous studies on E-transaction time-series have mainly focused on finding temporal trends of transaction behavior. Interesting transactions that are time-stamped and situation-relevant may easily be obscured in a large amount of information. This paper proposes a visual analytics system, Visual Analysis of E-transaction Time-Series (VAET), that allows the analysts to interactively explore large transaction datasets for insights about time-varying transactions. With a set of analyst-determined training samples, VAET automatically estimates the saliency of each transaction in a large time-series using a probabilistic decision tree learner. It provides an effective time-of-saliency (TOS) map where the analysts can explore a large number of transactions at different time granularities. Interesting transactions are further encoded with KnotLines, a compact visual representation that captures both the temporal variations and the contextual connection of transactions. The analysts can thus explore, select, and investigate knotlines of interest. A case study and user study with a real E-transactions dataset (26 million records) demonstrate the effectiveness of VAET.
Negotiation in distributed artificial intelligence: drawing from human experience

Distributed artificial intelligence and cooperative problem solving deal with agents who allocate resources, make joint decisions and develop plans. Negotiation may be important for interacting agents who make sequential decisions. We discuss the use of negotiation in conflict resolution in distributed AI and select those elements of human negotiations that can help artificial agents better to resolve conflicts. Problem evolution, a basic aspect of negotiation, can be represented using the restructurable modelling method of developing decision support systems. Restructurable modelling is implemented in the knowledge-based generic decision analysis and simulation system Negoplan. Experiments show that Negoplan can effectively help resolve individual and group conflicts in negotiation. <<ETX>>
Interactive effects of levels of individualism–collectivism on cooperation: A meta-analysis

Summary We examined the interactive effects of levels of individualism–collectivism (I–C) on cooperation at work by meta-analytically combining results obtained from 201 studies, representing 225 independent samples. I–C was operationalized at the individual, organizational, and societal levels of analyses. Cooperation was conceptualized at both individual and group levels of analysis. Both cooperative behavior and performance were included as outcomes. The correlation between individual-level I–C and cooperation/performance was stronger in collectivistic as opposed to individualistic societies. Similarly, the correlation between organizational-level I–C and cooperation was stronger in collectivistic societies. Results also indicated that individual-level and organizational-level I–C, but not societal-level I–C, were moderately related to study outcomes. Examination of other potential moderators indicated that neither study setting, I–C dimensionality, nor performance measurement type (objective vs subjective measures) altered these relations. However, a conceptual match between I–C and cooperation was a moderator such that effect sizes were generally larger when I–C and outcomes were both measured at the same level of analysis. Overall, our results indicate that I–C is both theoretically and empirically distinct across the various levels of analyses and that it may be a better predictor of outcomes in collectivistic as opposed to individualistic societies. Copyright © 2013 John Wiley & Sons, Ltd.
Integrity Attacks on Real-Time Pricing in Electric Power Grids

Modern information and communication technologies used by electric power grids are subject to cyber-security threats. This article studies the impact of integrity attacks on real-time pricing (RTP), an emerging feature of advanced power grids that can improve system efficiency. Recent studies have shown that RTP creates a closed loop formed by the mutually dependent real-time price signals and price-taking demand. Such a closed loop can be exploited by an adversary whose objective is to destabilize the pricing system. Specifically, small malicious modifications to the price signals can be iteratively amplified by the closed loop, causing highly volatile prices, fluctuating power demand, and increased system operating cost. This article adopts a control-theoretic approach to deriving the fundamental conditions of RTP stability under basic demand, supply, and RTP models that characterize the essential behaviors of consumers, suppliers, and system operators, as well as two broad classes of integrity attacks, namely, the scaling and delay attacks. We show that, under an approximated linear time-invariant formulation, the RTP system is at risk of being destabilized only if the adversary can compromise the price signals advertised to consumers, by either reducing their values in the scaling attack or providing old prices to over half of all consumers in the delay attack. The results provide useful guidelines for system operators to analyze the impact of various attack parameters on system stability so that they may take adequate measures to secure RTP systems.
Model-based configuration of VPNs

The design of suitable configurations for virtual private networks (VPNs) is usually difficult and error-prone. The abstract objectives of design are given by high level policies representing various requirements and the designers are often faced with conflicting requirements. Moreover, it is difficult to find a suitable mapping of high level policies to those low level network configurations which correctly and completely implement the abstract objectives. We apply the approach of model-based management where the system itself as well as the management objectives are represented by graphical object instance diagrams. A combination of tool and libraries supports their interactive construction and automated analysis. The implementation of the approach focuses on VPNs which are based on the Linux IPsec software FreeS/WAN.
Technology Corner: Analysing E-mail Headers For Forensic Investigation

Electronic Mail (E-Mail), which is one of the most widely used applications of Internet, has become a global communication infrastructure service. Â However, security loopholes in it enable cybercriminals to misuse it by forging its headers or by sending it anonymously for illegitimate purposes, leading to e-mail forgeries. E-mail messages include transit handling envelope and trace information in the form of structured fields which are not stripped after messages are delivered, leaving a detailed record of e-mail transactions. Â A detailed header analysis can be used to map the networks traversed by messages, including information on the messaging software and patching policies of clients and gateways, etc. Cyber forensic e-mail analysis is employed to collect credible evidence to bring criminals to justice. This paper projects the need for e-mail forensic investigation and lists various methods and tools used for its realization. A detailed header analysis of a multiple tactic spoofed e-mail message is carried out in this paper. It also discusses various possibilities for detection of spoofed headers and identification of its originator. Further, difficulties that may be faced by investigators during forensic investigation of an e-mail message have been discussed along with their possible solutions.
On Device Driver Architectures for Virtual Reality Toolkits

One major goal for the development of virtual reality (VR) toolkits is to provide interfaces for novel input or output hardware to support multimodal interaction. The research community has produced several implementations that feature a large variety of device interfaces and abstractions. As a lesson learned from existing approaches, we sum up the requirements for the design of a driver layer that is the basis for a multimodal input and output system in this paper. We derive a general model for driver architectures based on these requirements. This model can be used for reasoning about different implementations of available architectures. As the flow of data through the system is of interest, we take a closer look at common patterns of data processing. Finally, we discuss a number of openly accessible driver architectures currently used for VR development.
Metabolic surgery: an evolution through bariatric animal models

Metabolic surgery was developed through the application and experience gained from bariatric or weight loss procedures. Much of our knowledge from the procedures comes from the study of animal models, where they have revealed anatomic feasibility, systemic physiological elements and cellular metabolic effects. The first generation of operation included the jejunoileal bypass and partial ileal bypass that led to the development of the current procedures including Roux‐en‐Y gastric bypass, biliopancreatic diversion, adjustable gastric banding and sleeve gastrectomy. These operations carry significant metabolic benefits and can reduce the risk of diabetes, heart disease and cancer. Further insights from these animal models can reveal genetic, molecular and systemic effects that can enhance and develop the next generation of metabolic operations.