Miracle-dz/UniFAR-FTUs huggingface dataset:
The Combination of Rifampin plus Moxifloxacin Is Synergistic for Suppression of Resistance but Antagonistic for Cell Kill of Mycobacterium tuberculosis as Determined in a Hollow-Fiber Infection Model

ABSTRACT Moxifloxacin is under development for expanded use against Mycobacterium tuberculosis. Rifampin is a mainstay of therapy. We examined the interaction of moxifloxacin plus rifampin for log-phase and nonreplicating persister (NRP) organisms. For this evaluation, we employed our hollow-fiber infection model, in which organisms are exposed to clinically relevant drug concentration-time profiles and the impact on bacterial cell kill and resistant subpopulation amplification is determined. In log phase, resistance emergence was observed in all monotherapy regimens and in no combination therapy regimen. No difference was seen in time to a 3-log reduction in the bacterial burden; there was a significant difference in time to resistance emergence (P = 0.0006). In the NRP experiment, no resistance emergence was seen. There was a significant difference between the monotherapy and combination therapy regimens in time to a 3-log reduction in the bacterial burden (P = 0.042). The combination is efficacious for suppressing resistant organisms but is antagonistic for cell kill. IMPORTANCE M. tuberculosis infects one-third of the world’s population. Multiresistant organisms have become more frequent, threatening our ability to provide adequate chemotherapy. Moxifloxacin has been seen as an important new agent with the potential to supplant isoniazid or add to the rifampin/isoniazid combination. M. tuberculosis also exists in different physiological states, including the NRP phenotype. We examined the moxifloxacin/rifampin combination in a new in vitro system to allow judgment of how moxifloxacin would interact with rifampin and allow its performance in clinical trials to be placed into perspective. Importantly, the combination suppressed resistance emergence, but at the price of slightly slowing bacterial cell kill. This new combination is a welcome addition to the physician’s armamentarium. M. tuberculosis infects one-third of the world’s population. Multiresistant organisms have become more frequent, threatening our ability to provide adequate chemotherapy. Moxifloxacin has been seen as an important new agent with the potential to supplant isoniazid or add to the rifampin/isoniazid combination. M. tuberculosis also exists in different physiological states, including the nonreplicating persister phenotype. We examined the moxifloxacin/rifampin combination in a new in vitro system to allow judgment of how moxifloxacin would interact with rifampin and allow its performance in clinical trials to be placed into perspective. Importantly, the combination suppressed resistance emergence, but at the price of slightly slowing bacterial cell kill. This new combination is a welcome addition to the physician’s armamentarium.
CGHcall: Calling aberrations for array CGH tumor proﬁles.

1 Overview CGHcall allows users to make an objective and e ective classi cation of their aCGH data into copy number states (loss, normal, gain or ampli cation). This document provides an overview on the usage of the CGHcall package. For more detailed information on the algorithm and assumptions we refer to the article (van de Wiel et al., 2007) and its supplementary material. As example data we attached the rst ve samples of the Wilting dataset (Wilting et al., 2006). After ltering and selecting only the autosomal 4709 datapoints remained.
Regular tree languages definable in FO and in FOmod

We consider regular languages of labeled trees. We give an effective characterization of the regular languages over such trees that are definable in first-order logic in the language of labeled graphs. These languages are the analog on trees of the “locally threshold testable” languages on strings. We show that this characterization yields a decision procedure for determining whether a regular tree language is first-order definable: The procedure is polynomial time in the minimal automaton presenting the regular language. We also provide an algorithm for deciding whether a regular language is definable in first-order logic supplemented with modular quantifiers.
THE ROUND IDEAL COMPLETION VIA SOBRIFICATION

In this paper we consider an important order completion, the rounded-ideal completion, that has arisen in the modern theory of continuous domains. We show that it can be alternately viewed as a special case of a more general topo­ logical method of completion, namely taking the sobrification of a topological space. A number of important special caSes and examples are in­ cluded.
Development of an Approach for Analyzing Supply Chain Complexity

Supply chains are faced with a rising complexity of products, structures, and processes. Because of the strong link between a supply chain’s complexity and its efficiency the supply chain complexity management becomes a major challenge of today’s business management. A two dimensional driver concept is introduced and explained to comprehend the major causes of a supply chains’ complexity. To map the effects of the drivers and to understand the different dimensions of complexity, a general complexity model is introduced. A supply chain complexity analysis approach is presented, to evaluate the initial situation and to provide the necessary information for deriving the right actions and strategies for the management of complexity within a supply chain.
Efficient Routing from Multiple Sources to Multiple sinks in Wireless Sensor Networks

The multi hop routing in wireless sensor networks (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful or even devastating attacks against the routing protocols, including sinkhole attacks, wormhole attacks, and Sybil attacks. The situation is further aggravated by mobile and harsh network conditions. Traditional cryptographic techniques or efforts at developing trust-aware routing protocols do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multi hop routing, we have designed and implemented TARF, a robust trust-aware routing framework for dynamic WSNs. Without tight time synchronization or known geographic information, TARF provides trustworthy and energy-efficient route. Most importantly, TARF proves effective against those harmful attacks developed out of identity deception; the resilience of TARF is verified through extensive evaluation with both simulation and empirical experiments on large-scale WSNs under various scenarios including mobile and RFshielding network conditions. Further, we have implemented a low-overhead TARF module in Tiny OS; as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. Based on TARF, we also demonstrated a proof-of-concept mobile target detection application that functions well against an antidetection mechanism.
Increased Synaptic Sprouting in Response to Estrogen via an Apolipoprotein E-Dependent Mechanism: Implications for Alzheimer’s Disease

Estrogen replacement therapy appears to delay the onset of Alzheimer’s disease (AD), but the mechanisms for this action are incompletely known. We show how the enhancement of synaptic sprouting by estradiol (E2) in response to an entorhinal cortex (EC) lesion model of AD may operate via an apolipoprotein E (apoE)-dependent mechanism. In wild-type (WT) mice, ovariectomy decreased commissural/associational sprouting to the inner molecular layer of the dentate gyrus, with synaptophysin (SYN) as a marker. E2 replacement returned SYN in the inner layer to levels of EC-lesioned, ovary-bearing controls and increased the area of compensatory synaptogenesis in the outer molecular layer. In EC-lesioned apoE-knock-out (KO) mice, however, E2 did not enhance sprouting. We also examined apoJ (clusterin) mRNA, which is implicated in AD by its presence in senile plaques, its transport of Aβ across the blood–brain barrier, and its induction by neurodegenerative lesioning. ApoJ mRNA levels were increased by E2 replacement in EC-lesioned WT mice but not in apoE-KO mice. These data suggest a mechanism for the protective effects of estrogens on AD and provide a link between two important risk factors in the etiology of AD, the apoE ε4 genotype and an estrogen-deficient state. This is also the first evidence that SYN, a presynaptic protein involved in neurotransmitter release, is regulated by E2 in the adult brain, and that apoE is necessary for the induction of apoJ mRNA by E2 in brain injury.
Closed loop controlled solar fed post regulated push-pull converter

A solar fed push-pull converter employing post regulation method with soft commutated switches is discussed in the paper. Incorporating an inductor in series with the source the converter operates as a current fed one. The post regulation is carried out with an auxiliary current transformer. The post regulation technique utilizes the Transformer Turns Ratio Regulator concept which adds or subtracts voltage to the output of the push-pull converter. A boost converter is incorporated at the secondary side of the transformer and a current is fed to the input of the converter. The amount of current fed is controlled by the regulator circuit which handles only a percentage of the total output power. The power handling capacity of the load is enhanced with an improvement in efficiency and regulation. The size and weight of the converter is reduced by suitably selecting higher switching frequencies. In order to reduce the switching losses, zero voltage and zero current switching (ZVZCS) have been employed. The remarkable feature of the paper presented is that the soft switching is not affected by load variations. This is discussed in detail with resonant waveforms, output waveforms and efficiency curves.
Stabilizers of Ergodic Actions of Lattices and Commensurators

We prove that any ergodic measure-preserving action of an irreducible lattice in a semisimple group, with finite center and each simple factor having rank at least two, either has finite orbits or has finite stabilizers. The same dichotomy holds for many commensurators of such lattices. The above are derived from more general results on groups with the Howe-Moore property and property $(T)$. We prove similar results for commensurators in such groups and for irreducible lattices (and commensurators) in products of at least two such groups, at least one of which is totally disconnected.
Towards a catalog of Object-Oriented Software Maintainability metrics

A high number of metrics have been used to measure Object-Oriented Software Maintainability (OOSM). However, there is no comprehensive and useful catalog showing which metrics are more appropriated for adoption in OOSM assessment in both, academic and industrial environments. In a previous work we performed a systematic mapping study to identify maintainability metrics resulting in 570 OOSM metrics found. We classified those metrics in 15 domain categories to help us on the catalog building process. This categorization will be the basement of our inclusion/exclusion criteria when we select which metrics will compose a catalog. Using the proposed categorization we believe that we can select the most relevant and/or popular OOSM metrics. In this position paper we discuss a range of options of OOSM metrics categorization, making the OOSM metrics catalog building process accurate and reliable. Such options include how to evaluate them by the academic and practitioner points of view. We also expect that such discussion during the workshop can help us to identify other options to both propose a more useful catalog and to perform its evaluation.
Diversity-dependence brings molecular phylogenies closer to agreement with the fossil record

The branching times of molecular phylogenies allow us to infer speciation and extinction dynamics even when fossils are absent. Troublingly, phylogenetic approaches usually return estimates of zero extinction, conflicting with fossil evidence. Phylogenies and fossils do agree, however, that there are often limits to diversity. Here, we present a general approach to evaluate the likelihood of a phylogeny under a model that accommodates diversity-dependence and extinction. We find, by likelihood maximization, that extinction is estimated most precisely if the rate of increase in the number of lineages in the phylogeny saturates towards the present or first decreases and then increases. We demonstrate the utility and limits of our approach by applying it to the phylogenies for two cases where a fossil record exists (Cetacea and Cenozoic macroperforate planktonic foraminifera) and to three radiations lacking fossil evidence (Dendroica, Plethodon and Heliconius). We propose that the diversity-dependence model with extinction be used as the standard model for macro-evolutionary dynamics because of its biological realism and flexibility.
Where will the oncoming vehicle be the next second?

A new image based approach for fast and robust tracking of vehicles from a moving platform is presented. Position, orientation, and the full motion state including velocity, acceleration, and yaw rate of a detected vehicle are estimated from a tracked 3D point cloud. This point cloud is computed by analyzing image sequences in both space and time, i.e. by fusion of stereo vision and tracked optical flow vectors. Starting from an automated initial vehicle hypothesis, the tracking is performed by means of Extended Kalman Filter. The filter combines the knowledge of where a point in the rigid point cloud has moved within a given time interval, with the dynamic model of a vehicle. The proposed system is applied to predict the driving path of other traffic participants and runs currently at 25 Hz (VGA images) on our demonstrator vehicle UTA.
Explicitly Modelling Model Debugging Environments

Programmers spend a large portion of their time debugging the code they write. This is supported by a variety of debugging techniques such as pause/resume, the setting of breakpoints, stepping over functions, etc. Today, modelling and simulation become increasingly important enablers in the development of complex, reactive, often real-time, software-intensive systems, as they allow rapid prototyping and early validation of designs. Simulation models, though at a higher level of abstraction than code, can however still contain bugs. There is hence a need for model-level debuggers, that are adapted to the semantics of the modelling formalism(s) used, and can properly deal with the timed nature of many of these models. This paper presents a method for constructing model debugging environments for deterministic, operational formalisms. In order to manage the inherent complexity, the timed, reactive behaviour of the debugger is modelled explicitly. The feasibility of the approach is demonstrated by constructing a visual debugging environment for Causal-Block Diagrams.
Augmented Reality Cues and Elderly Driver Hazard Perception

Objective: The aim of this study was to evaluate the effectiveness of augmented reality (AR) cues in improving driving safety among elderly drivers who are at increased crash risk because of cognitive impairments. Background: Cognitively challenging driving environments pose a particular crash risk for elderly drivers. AR cuing is a promising technology to mitigate risk by directing driver attention to roadway hazards. We investigate whether AR cues improve or interfere with hazard perception in elderly drivers with age-related cognitive decline. Method: A total of 20 elderly (M = 73 years, SD = 5) licensed drivers with a range of cognitive abilities measured by a speed-of-processing (SOP) composite participated in a 1-hr drive in an interactive, fixed-base driving simulator. Each participant drove through six straight, 6-mile-long, rural roadway scenarios following a lead vehicle. AR cues directed attention to potential roadside hazards in three of the scenarios, and the other three were uncued (baseline) drives. Effects of AR cuing were evaluated with respect to (a) detection of hazardous target objects, (b) interference with detecting nonhazardous secondary objects, and (c) impairment in maintaining safe distance behind a lead vehicle. Results: AR cuing improved the detection of hazardous target objects of low visibility. AR cues did not interfere with detection of nonhazardous secondary objects and did not impair ability to maintain safe distance behind a lead vehicle. SOP capacity did not moderate those effects. Conclusion: AR cues show promise for improving elderly driver safety by increasing hazard detection likelihood without interfering with other driving tasks, such as maintaining safe headway.
Training and Unions

[The authors] develop a model of firm-financed general training where unions, by way of making long term wage contracts enforceable, create an incentive for firms to train their workers. [The authors'] model allows for the co-existence of a unionised and a non-unionised sector and for worker heterogeneity, leading to worker selection into the two sectors. In equilibrium, firms are indifferent between being unionised and non-unionised. The co-existence of a unionised and non-unionised sector leads to a welfare improvement. The model is compatible with the implications for selection of workers of an asymmetric information model. It has, in addition, implications for selection and training intensity conditional on sector. [The authors'] empirical test uses individual and firm data on the German apprenticeship system. The evidence provides strong support for [this] model.
Database System Extensions for Decision Support: the AXL Approach

Research on database-centric data mining is seeking to improve the e ectiveness of database systems in decision support applications. Di erent solutions are now used for di erent problems, including (i) SQL extensions for more complex OLAP queries, (ii) new datablades for special data types such as time-series, and (iii) architectural extensions to support data mining functions. Here, we proposed a uni ed solution for all these problems; the solution is based on User-De ned Aggregates (UDAs) expressed in an SQL-like language called AXL. In this paper, we discuss the architecture and implementation of the AXL prototype and its use and performance in expressing data mining functions and complex OLAP queries.
Model Uncertainty in Discrete Event Systems

Earlier work concerning control of discrete event systems usually assumed that a correct model of the system to be controlled was available. A goal of this work is to provide an algorithm for determining the correct model from a set of models. The result of the algorithm is a finite language that can be used to test for the correct model or notification that the remaining models cannot be controllably distinguished. We use the finite state machine model with controllable and uncontrollable events presented by Ramadge and Wonham.
Mobile Advertising Using Customer Movement Patterns

Rapid improvements in the precision of mobile technologies make it possible for advertisers to go beyond using the real-time static location and contextual information about consumers. In this study, we propose a new mobile advertising strategy that leverages full information on consumers’ offline movement trajectories from different mobility dimensions. To analyze the effectiveness of this new trajectory-based mobile advertising strategy, we design a large-scale randomized field experiment in a large shopping mall that examines the redemption rates of mobile coupons. Our experiment results are validated based on 83,370 unique user responses for a 14-day period in June 2014. We find that trajectory-based mobile advertising can lead to higher redemption probability, faster redemption behavior, and higher transaction amount from customers compared to other kinds of advertising, all of which facilitate higher revenues for the focal store as well as the overall shopping mall. Interestingly, however trajectory-based mobile advertising becomes significantly less effective in boosting the revenues of the shopping mall during the weekend. This finding suggests that customers are likely to be in an “exploratory” shopping mode during the weekend and are likely to engage in “impulsive purchases. ” However, closely targeted mobile advertising can have the inadvertent impact of reducing impulse purchase behavior suggesting that marketers need to be careful when implementing mobile advertising strategies. Finally, trajectory-based mobile advertising is especially effective in attracting high-income consumers, suggesting the potential of mobile advertising in approaching high-end customers to achieve better customer lifetime value. On a broader note, our work can be viewed as a first step to study the digitization of individual offline behavior and how it can be linked to a better understanding individual preferences and decision-making.
Variable stiffness actuator for soft robotics using dielectric elastomer and low-melting-point alloy

A novel variable stiffness actuator composed of a dielectric elastomer actuator (DEA) and a low-melting-point-alloy (LMPA) embedded silicone substrate is demonstrated. The device which we call variable stiffness dielectric elastomer actuator (VSDEA) enables functional soft robots with a simplified structure, where the DEA generates a bending actuation and the LMPA provides controllable stiffness between soft and rigid states by Joule heating. The entire structure of VSDEA is made of soft silicones with an elastic modulus of less than 1 MPa providing a high compliance when the LMPA is active. The device has the dimension of 40 mm length × 10 mm width × 1 mm thickness, with mass of ~1 g. We characterize VSDEA in terms of the actuation stroke angle, the blocked force, and the reaction force against a forced displacement. The results show the controllable actuation angle and the blocked force up to 23.7 ° and 2.4 mN in the soft state, and 0.6 ° and 2.1 mN in the rigid state. Compared to an actuator without the LMPA, VSDEA exhibits ~90× higher rigidity. We develop a VSDEA gripper where the mass of active parts is ~2 g, which is able to successfully hold an object mass of 11 g, exhibiting the high performance of the actuator.
Distributed data association in smart camera networks using belief propagation

One of the fundamental requirements for visual surveillance with smart camera networks is the correct association of camera's observations with the tracks of objects under tracking. Most of the current systems work in a centralized manner in that the observations on all cameras need to be transmitted to a central server where some data association algorithm is running. Recently some works have been shown for distributed data association based solely on appearance observation. However, how to perform distributed association inference using both appearance and spatio-temporal information is still unclear. In this article, we present a novel method for estimating the posterior distribution of the label of each observation, indicating which of the objects it comes from, based on belief propagation between neighboring cameras. We develop distributed forward and backward inference algorithms for online and offline application, respectively, and further extend the algorithms to the case of unreliable detection. We also incorporate the proposed inference algorithms into distributed EM framework to simultaneously solve the problem of data association and appearance model learning in a completely distributed manner. The proposed method is verified on artificial data and on real world observations collected by a camera networks in an office building.